notebook/PANGEO-Sentinel-Intake-SA-OZLocation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "\n",
    "import intake\n",
    "import satsearch\n",
    "from satsearch import Search\n",
    "\n",
    "import ast\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "\n",
    "import geopandas as gpd\n",
    "import rasterio\n",
    "import rioxarray\n",
    "\n",
    "import dask\n",
    "from dask.diagnostics import ProgressBar\n",
    "#import dask.distributed\n",
    "\n",
    "#import geoviews as gv\n",
    "#import hvplot.pandas\n",
    "from ipywidgets import interact\n",
    "from IPython.display import display, Image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = dict(GDAL_DISABLE_READDIR_ON_OPEN='EMPTY_DIR', \n",
    "           AWS_NO_SIGN_REQUEST='YES',\n",
    "           GDAL_MAX_RAW_BLOCK_CACHE_SIZE='250000000',\n",
    "           GDAL_SWATH_SIZE='250000000',\n",
    "           VSI_CURL_CACHE_SIZE='250000000')\n",
    "os.environ.update(env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "bbox = [35.48, -3.24, 35.58, -3.14] # (min lon, min lat, max lon, max lat)\n",
    "bbox = [129.0000000000000000,-39.0000000000000000, 141.0000000000000000,-26.0000000000000000]\n",
    "bbox = [138.54207373854032 - 0.01, -34.934374426311145 - 0.01, 138.54207373854032 + 0.01, -34.934374426311145 + 0.01]\n",
    "#bbox = [138.54207373854032 - 0.5, -34.934374426311145 - 0.5, 138.54207373854032 + 0.5, -34.934374426311145 + 0.5]\n",
    "\n",
    "dates = '2017-01-01/2020-12-31'\n",
    "\n",
    "URL='https://earth-search.aws.element84.com/v0'\n",
    "results = satsearch.Search.search(url=URL,\n",
    "                                  collections=['sentinel-s2-l2a-cogs'], # note collection='sentinel-s2-l2a-cogs' doesn't work\n",
    "                                  datetime=dates,\n",
    "                                  bbox=bbox,   \n",
    "                                  #property=[\"eo:cloud_cover<1\"],\n",
    "                                  #query={'eo:cloud_cover': {'lt': 1}},\n",
    "                                  query={'eo:cloud_cover': {'eq': 0}, 'platform':{'eq': 'sentinel-2a'}},\n",
    "                                  sort=['<datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40 items\n"
     ]
    }
   ],
   "source": [
    "print('%s items' % results.found())\n",
    "items = results.items()\n",
    "# Save this locally for use later\n",
    "#items.save('my-s2-l2a-cogs-sa-cloudcover1.json')\n",
    "items.save('my-s2-l2a-cogs-sa-cloudcover0OZLocation.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "catalog = intake.open_stac_item_collection(results.items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "#gf = gpd.read_file('my-s2-l2a-cogs-sa-cloudcover1.geojson')\n",
    "gf2 = gpd.read_file('my-s2-l2a-cogs-sa-cloudcover0OZLocation.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>datetime</th>\n",
       "      <th>platform</th>\n",
       "      <th>constellation</th>\n",
       "      <th>gsd</th>\n",
       "      <th>view:off_nadir</th>\n",
       "      <th>proj:epsg</th>\n",
       "      <th>sentinel:utm_zone</th>\n",
       "      <th>sentinel:latitude_band</th>\n",
       "      <th>sentinel:grid_square</th>\n",
       "      <th>sentinel:sequence</th>\n",
       "      <th>sentinel:product_id</th>\n",
       "      <th>sentinel:data_coverage</th>\n",
       "      <th>eo:cloud_cover</th>\n",
       "      <th>sentinel:valid_cloud_cover</th>\n",
       "      <th>created</th>\n",
       "      <th>updated</th>\n",
       "      <th>data_coverage</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S2A_54HTG_20201220_0_L2A</td>\n",
       "      <td>2020-12-20T00:56:43+00:00</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
       "      <td>10</td>\n",
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       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20201220T004701_N0214_R102_T54HTG_2...</td>\n",
       "      <td>99.80</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020-12-20T06:18:58.775002+00:00</td>\n",
       "      <td>2020-12-20T06:18:58.775002+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((138.87370 -35.31256, 137.70126 -35.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2A_54HTG_20201130_0_L2A</td>\n",
       "      <td>2020-11-30T00:56:45+00:00</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20201130T004711_N0214_R102_T54HTG_2...</td>\n",
       "      <td>99.84</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020-11-30T07:13:47.674000+00:00</td>\n",
       "      <td>2020-11-30T07:13:47.674000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((138.87711 -35.31261, 137.70126 -35.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S2A_54HTG_20201117_0_L2A</td>\n",
       "      <td>2020-11-17T00:46:52+00:00</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20201117T003711_N0214_R059_T54HTG_2...</td>\n",
       "      <td>61.38</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020-11-17T05:53:27.379000+00:00</td>\n",
       "      <td>2020-11-17T05:53:27.379000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((138.90758 -35.31315, 138.02743 -35.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S2A_54HTG_20200829_0_L2A</td>\n",
       "      <td>2020-08-29T00:46:54+00:00</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20200829T003711_N0214_R059_T54HTG_2...</td>\n",
       "      <td>61.31</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>2020-08-29T06:53:02.125000+00:00</td>\n",
       "      <td>2020-08-29T06:53:02.125000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((138.90758 -35.31315, 138.02787 -35.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S2A_54HTG_20200819_0_L2A</td>\n",
       "      <td>2020-08-19T00:46:54+00:00</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20200819T003711_N0214_R059_T54HTG_2...</td>\n",
       "      <td>61.32</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>2020-08-20T00:25:47.097000+00:00</td>\n",
       "      <td>2020-08-20T00:25:47.097000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((138.90758 -35.31315, 138.02765 -35.2...</td>\n",
       "    </tr>\n",
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       "</div>"
      ],
      "text/plain": [
       "                         id                   datetime     platform  \\\n",
       "0  S2A_54HTG_20201220_0_L2A  2020-12-20T00:56:43+00:00  sentinel-2a   \n",
       "1  S2A_54HTG_20201130_0_L2A  2020-11-30T00:56:45+00:00  sentinel-2a   \n",
       "2  S2A_54HTG_20201117_0_L2A  2020-11-17T00:46:52+00:00  sentinel-2a   \n",
       "3  S2A_54HTG_20200829_0_L2A  2020-08-29T00:46:54+00:00  sentinel-2a   \n",
       "4  S2A_54HTG_20200819_0_L2A  2020-08-19T00:46:54+00:00  sentinel-2a   \n",
       "\n",
       "  constellation  gsd  view:off_nadir  proj:epsg  sentinel:utm_zone  \\\n",
       "0    sentinel-2   10               0      32754                 54   \n",
       "1    sentinel-2   10               0      32754                 54   \n",
       "2    sentinel-2   10               0      32754                 54   \n",
       "3    sentinel-2   10               0      32754                 54   \n",
       "4    sentinel-2   10               0      32754                 54   \n",
       "\n",
       "  sentinel:latitude_band sentinel:grid_square sentinel:sequence  \\\n",
       "0                      H                   TG                 0   \n",
       "1                      H                   TG                 0   \n",
       "2                      H                   TG                 0   \n",
       "3                      H                   TG                 0   \n",
       "4                      H                   TG                 0   \n",
       "\n",
       "                                 sentinel:product_id  sentinel:data_coverage  \\\n",
       "0  S2A_MSIL2A_20201220T004701_N0214_R102_T54HTG_2...                   99.80   \n",
       "1  S2A_MSIL2A_20201130T004711_N0214_R102_T54HTG_2...                   99.84   \n",
       "2  S2A_MSIL2A_20201117T003711_N0214_R059_T54HTG_2...                   61.38   \n",
       "3  S2A_MSIL2A_20200829T003711_N0214_R059_T54HTG_2...                   61.31   \n",
       "4  S2A_MSIL2A_20200819T003711_N0214_R059_T54HTG_2...                   61.32   \n",
       "\n",
       "   eo:cloud_cover  sentinel:valid_cloud_cover  \\\n",
       "0               0                        True   \n",
       "1               0                        True   \n",
       "2               0                        True   \n",
       "3               0                       False   \n",
       "4               0                       False   \n",
       "\n",
       "                            created                           updated  \\\n",
       "0  2020-12-20T06:18:58.775002+00:00  2020-12-20T06:18:58.775002+00:00   \n",
       "1  2020-11-30T07:13:47.674000+00:00  2020-11-30T07:13:47.674000+00:00   \n",
       "2  2020-11-17T05:53:27.379000+00:00  2020-11-17T05:53:27.379000+00:00   \n",
       "3  2020-08-29T06:53:02.125000+00:00  2020-08-29T06:53:02.125000+00:00   \n",
       "4  2020-08-20T00:25:47.097000+00:00  2020-08-20T00:25:47.097000+00:00   \n",
       "\n",
       "   data_coverage                                           geometry  \n",
       "0            NaN  POLYGON ((138.87370 -35.31256, 137.70126 -35.2...  \n",
       "1            NaN  POLYGON ((138.87711 -35.31261, 137.70126 -35.2...  \n",
       "2            NaN  POLYGON ((138.90758 -35.31315, 138.02743 -35.2...  \n",
       "3            NaN  POLYGON ((138.90758 -35.31315, 138.02787 -35.2...  \n",
       "4            NaN  POLYGON ((138.90758 -35.31315, 138.02765 -35.2...  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gf2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "item = catalog['S2A_54HTG_20201220_0_L2A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": "S2A_54HTG_20201220_0_L2A:\n  args:\n    stac_obj: !!python/object:satstac.item.Item\n      _assets_by_common_name: null\n      _collection: !!python/object:satstac.collection.Collection\n        _data:\n          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n          extent:\n            spatial:\n              bbox:\n              - - -180\n                - -90\n                - 180\n                - 90\n            temporal:\n              interval:\n              - - '2015-06-27T10:25:31.456000Z'\n                - null\n          id: sentinel-s2-l2a-cogs\n          item_assets:\n            AOT:\n              roles:\n              - data\n              title: Aerosol Optical Thickness (AOT)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B01:\n              eo:bands:\n              - center_wavelength: 0.4439\n                common_name: coastal\n                full_width_half_max: 0.027\n                name: B01\n              gsd: 60\n              roles:\n              - data\n              title: Band 1 (coastal)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B02:\n              eo:bands:\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - data\n              title: Band 2 (blue)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B03:\n              eo:bands:\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              gsd: 10\n              roles:\n              - data\n              title: Band 3 (green)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B04:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              gsd: 10\n              roles:\n              - data\n              title: Band 4 (red)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B05:\n              eo:bands:\n              - center_wavelength: 0.7039\n                full_width_half_max: 0.019\n                name: B05\n              gsd: 20\n              roles:\n              - data\n              title: Band 5\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B06:\n              eo:bands:\n              - center_wavelength: 0.7402\n                full_width_half_max: 0.018\n                name: B06\n              gsd: 20\n              roles:\n              - data\n              title: Band 6\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B07:\n              eo:bands:\n              - center_wavelength: 0.7825\n                full_width_half_max: 0.028\n                name: B07\n              gsd: 20\n              roles:\n              - data\n              title: Band 7\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B08:\n              eo:bands:\n              - center_wavelength: 0.8351\n                common_name: nir\n                full_width_half_max: 0.145\n                name: B08\n              gsd: 10\n              roles:\n              - data\n              title: Band 8 (nir)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B09:\n              eo:bands:\n              - center_wavelength: 0.945\n                full_width_half_max: 0.026\n                name: B09\n              gsd: 60\n              roles:\n              - data\n              title: Band 9\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B11:\n              eo:bands:\n              - center_wavelength: 1.6137\n                common_name: swir16\n                full_width_half_max: 0.143\n                name: B11\n              gsd: 20\n              roles:\n              - data\n              title: Band 11 (swir16)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B12:\n              eo:bands:\n              - center_wavelength: 2.22024\n                common_name: swir22\n                full_width_half_max: 0.242\n                name: B12\n              gsd: 20\n              roles:\n              - data\n              title: Band 12 (swir22)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B8A:\n              eo:bands:\n              - center_wavelength: 0.8648\n                full_width_half_max: 0.033\n                name: B8A\n              gsd: 20\n              roles:\n              - data\n              title: Band 8A\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            SCL:\n              roles:\n              - data\n              title: Scene Classification Map (SCL)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            WVP:\n              roles:\n              - data\n              title: Water Vapour (WVP)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            info:\n              roles:\n              - metadata\n              title: Original JSON metadata\n              type: application/json\n            metadata:\n              roles:\n              - metadata\n              title: Original XML metadata\n              type: application/xml\n            overview:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            thumbnail:\n              roles:\n              - thumbnail\n              title: Thumbnail\n              type: image/png\n            visual:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n          keywords:\n          - sentinel\n          - earth observation\n          - esa\n          license: proprietary\n          links:\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n            rel: self\n          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n            rel: license\n          - href: https://github.com/stac-utils/stac-sentinel\n            rel: about\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: parent\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: root\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n            rel: items\n          providers:\n          - name: ESA\n            roles:\n            - producer\n            url: https://earth.esa.int/web/guest/home\n          - name: Sinergise\n            roles:\n            - processor\n            url: https://registry.opendata.aws/sentinel-2/\n          - name: AWS\n            roles:\n            - host\n            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n          - name: Element 84\n            roles:\n            - processor\n            url: https://element84.com\n          stac_extensions:\n          - item-assets\n          stac_version: 1.0.0-beta.2\n          summaries:\n            constellation:\n            - sentinel-2\n            gsd:\n            - 10\n            instruments:\n            - msi\n            platform:\n            - sentinel-2a\n            - sentinel-2b\n            view:off_nadir:\n            - 0\n          title: Sentinel 2 L2A COGs\n        filename: null\n      _data:\n        assets:\n          AOT:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/AOT.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 199980\n            - 0\n            - -60\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Aerosol Optical Thickness (AOT)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B01:\n            eo:bands:\n            - center_wavelength: 0.4439\n              common_name: coastal\n              full_width_half_max: 0.027\n              name: B01\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B01.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 199980\n            - 0\n            - -60\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 1 (coastal)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B02:\n            eo:bands:\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 2 (blue)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B03:\n            eo:bands:\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 3 (green)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B04:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B04.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 4 (red)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B05:\n            eo:bands:\n            - center_wavelength: 0.7039\n              full_width_half_max: 0.019\n              name: B05\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B05.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 5\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B06:\n            eo:bands:\n            - center_wavelength: 0.7402\n              full_width_half_max: 0.018\n              name: B06\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B06.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 6\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B07:\n            eo:bands:\n            - center_wavelength: 0.7825\n              full_width_half_max: 0.028\n              name: B07\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B07.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 7\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B08:\n            eo:bands:\n            - center_wavelength: 0.8351\n              common_name: nir\n              full_width_half_max: 0.145\n              name: B08\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B08.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8 (nir)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B09:\n            eo:bands:\n            - center_wavelength: 0.945\n              full_width_half_max: 0.026\n              name: B09\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B09.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 199980\n            - 0\n            - -60\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 9\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B11:\n            eo:bands:\n            - center_wavelength: 1.6137\n              common_name: swir16\n              full_width_half_max: 0.143\n              name: B11\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B11.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 11 (swir16)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B12:\n            eo:bands:\n            - center_wavelength: 2.22024\n              common_name: swir22\n              full_width_half_max: 0.242\n              name: B12\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B12.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 12 (swir22)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B8A:\n            eo:bands:\n            - center_wavelength: 0.8648\n              full_width_half_max: 0.033\n              name: B8A\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B8A.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8A\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          SCL:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/SCL.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 199980\n            - 0\n            - -20\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Scene Classification Map (SCL)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          WVP:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/WVP.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Water Vapour (WVP)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          info:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/tileInfo.json\n            roles:\n            - metadata\n            title: Original JSON metadata\n            type: application/json\n          metadata:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/metadata.xml\n            roles:\n            - metadata\n            title: Original XML metadata\n            type: application/xml\n          overview:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/L2A_PVI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 343\n            - 343\n            proj:transform:\n            - 320\n            - 0\n            - 199980\n            - 0\n            - -320\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          thumbnail:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l1c/tiles/54/H/TG/2020/12/20/0/preview.jpg\n            plots:\n              thumbnail:\n                bands: channel\n                data_aspect: 1\n                flip_yaxis: true\n                kind: rgb\n                x: x\n                xaxis: false\n                y: y\n                yaxis: false\n            roles:\n            - thumbnail\n            title: Thumbnail\n            type: image/png\n          visual:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/TCI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 199980\n            - 0\n            - -10\n            - 6200020\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n        bbox:\n        - 137.70126049728088\n        - -35.31255500628786\n        - 138.93245744899494\n        - -34.29773472288293\n        collection: sentinel-s2-l2a-cogs\n        geometry:\n          coordinates:\n          - - - 138.87369694502937\n              - -35.31255500628786\n            - - 137.70126049728088\n              - -35.28623966911122\n            - - 137.74043510840517\n              - -34.29773472288293\n            - - 138.93245744899494\n              - -34.323673927816266\n            - - 138.91111312652103\n              - -35.17541174420406\n            - - 138.87369694502937\n              - -35.31255500628786\n          type: Polygon\n        id: S2A_54HTG_20201220_0_L2A\n        links:\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2A_54HTG_20201220_0_L2A\n          rel: self\n        - href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/S2A_54HTG_20201220_0_L2A.json\n          rel: canonical\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-54-H-TG-2020-12-20-0\n          rel: via-cirrus\n          title: sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-54-H-TG-2020-12-20-0\n        - href: https://cirrus-v0-data-1qm7gekzjucbq.s3.us-west-2.amazonaws.com/sentinel-s2-l2a/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/S2A_54HTG_20201220_0_L2A.json\n          rel: derived_from\n          title: Source STAC Item\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a/workflow-cog-archive/S2A_54HTG_20201220_0_L2A\n          rel: via-cirrus\n          title: sentinel-s2-l2a/workflow-cog-archive/S2A_54HTG_20201220_0_L2A\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: parent\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: collection\n        - href: https://earth-search.aws.element84.com/v0/\n          rel: root\n        properties:\n          constellation: sentinel-2\n          created: '2020-12-20T06:18:58.775Z'\n          datetime: '2020-12-20T00:56:43Z'\n          eo:cloud_cover: 0\n          gsd: 10\n          instruments:\n          - msi\n          platform: sentinel-2a\n          proj:epsg: 32754\n          sentinel:data_coverage: 99.8\n          sentinel:grid_square: TG\n          sentinel:latitude_band: H\n          sentinel:product_id: S2A_MSIL2A_20201220T004701_N0214_R102_T54HTG_20201220T032547\n          sentinel:sequence: '0'\n          sentinel:utm_zone: 54\n          sentinel:valid_cloud_cover: true\n          updated: '2020-12-20T06:18:58.775Z'\n          view:off_nadir: 0\n        stac_extensions:\n        - eo\n        - view\n        - proj\n        stac_version: 1.0.0-beta.2\n        type: Feature\n      filename: null\n  description: ''\n  driver: intake_stac.catalog.StacItem\n  metadata:\n    catalog_dir: ''\n",
      "text/plain": [
       "S2A_54HTG_20201220_0_L2A:\n",
       "  args:\n",
       "    stac_obj: !!python/object:satstac.item.Item\n",
       "      _assets_by_common_name: null\n",
       "      _collection: !!python/object:satstac.collection.Collection\n",
       "        _data:\n",
       "          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n",
       "            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n",
       "          extent:\n",
       "            spatial:\n",
       "              bbox:\n",
       "              - - -180\n",
       "                - -90\n",
       "                - 180\n",
       "                - 90\n",
       "            temporal:\n",
       "              interval:\n",
       "              - - '2015-06-27T10:25:31.456000Z'\n",
       "                - null\n",
       "          id: sentinel-s2-l2a-cogs\n",
       "          item_assets:\n",
       "            AOT:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Aerosol Optical Thickness (AOT)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B01:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4439\n",
       "                common_name: coastal\n",
       "                full_width_half_max: 0.027\n",
       "                name: B01\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 1 (coastal)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B02:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 2 (blue)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B03:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 3 (green)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B04:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 4 (red)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B05:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7039\n",
       "                full_width_half_max: 0.019\n",
       "                name: B05\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 5\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B06:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7402\n",
       "                full_width_half_max: 0.018\n",
       "                name: B06\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 6\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B07:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7825\n",
       "                full_width_half_max: 0.028\n",
       "                name: B07\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 7\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B08:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8351\n",
       "                common_name: nir\n",
       "                full_width_half_max: 0.145\n",
       "                name: B08\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8 (nir)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B09:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.945\n",
       "                full_width_half_max: 0.026\n",
       "                name: B09\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 9\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B11:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 1.6137\n",
       "                common_name: swir16\n",
       "                full_width_half_max: 0.143\n",
       "                name: B11\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 11 (swir16)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B12:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 2.22024\n",
       "                common_name: swir22\n",
       "                full_width_half_max: 0.242\n",
       "                name: B12\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 12 (swir22)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B8A:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8648\n",
       "                full_width_half_max: 0.033\n",
       "                name: B8A\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8A\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            SCL:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Scene Classification Map (SCL)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            WVP:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Water Vapour (WVP)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            info:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original JSON metadata\n",
       "              type: application/json\n",
       "            metadata:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original XML metadata\n",
       "              type: application/xml\n",
       "            overview:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            thumbnail:\n",
       "              roles:\n",
       "              - thumbnail\n",
       "              title: Thumbnail\n",
       "              type: image/png\n",
       "            visual:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          keywords:\n",
       "          - sentinel\n",
       "          - earth observation\n",
       "          - esa\n",
       "          license: proprietary\n",
       "          links:\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "            rel: self\n",
       "          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n",
       "            rel: license\n",
       "          - href: https://github.com/stac-utils/stac-sentinel\n",
       "            rel: about\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: parent\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: root\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n",
       "            rel: items\n",
       "          providers:\n",
       "          - name: ESA\n",
       "            roles:\n",
       "            - producer\n",
       "            url: https://earth.esa.int/web/guest/home\n",
       "          - name: Sinergise\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://registry.opendata.aws/sentinel-2/\n",
       "          - name: AWS\n",
       "            roles:\n",
       "            - host\n",
       "            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n",
       "          - name: Element 84\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://element84.com\n",
       "          stac_extensions:\n",
       "          - item-assets\n",
       "          stac_version: 1.0.0-beta.2\n",
       "          summaries:\n",
       "            constellation:\n",
       "            - sentinel-2\n",
       "            gsd:\n",
       "            - 10\n",
       "            instruments:\n",
       "            - msi\n",
       "            platform:\n",
       "            - sentinel-2a\n",
       "            - sentinel-2b\n",
       "            view:off_nadir:\n",
       "            - 0\n",
       "          title: Sentinel 2 L2A COGs\n",
       "        filename: null\n",
       "      _data:\n",
       "        assets:\n",
       "          AOT:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/AOT.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Aerosol Optical Thickness (AOT)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B01:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.4439\n",
       "              common_name: coastal\n",
       "              full_width_half_max: 0.027\n",
       "              name: B01\n",
       "            gsd: 60\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B01.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 1 (coastal)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B02:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.4966\n",
       "              common_name: blue\n",
       "              full_width_half_max: 0.098\n",
       "              name: B02\n",
       "            gsd: 10\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 10980\n",
       "            - 10980\n",
       "            proj:transform:\n",
       "            - 10\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -10\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 2 (blue)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B03:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.56\n",
       "              common_name: green\n",
       "              full_width_half_max: 0.045\n",
       "              name: B03\n",
       "            gsd: 10\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 10980\n",
       "            - 10980\n",
       "            proj:transform:\n",
       "            - 10\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -10\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 3 (green)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B04:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.6645\n",
       "              common_name: red\n",
       "              full_width_half_max: 0.038\n",
       "              name: B04\n",
       "            gsd: 10\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B04.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 10980\n",
       "            - 10980\n",
       "            proj:transform:\n",
       "            - 10\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -10\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 4 (red)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B05:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.7039\n",
       "              full_width_half_max: 0.019\n",
       "              name: B05\n",
       "            gsd: 20\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B05.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 5490\n",
       "            - 5490\n",
       "            proj:transform:\n",
       "            - 20\n",
       "            - 0\n",
       "            - 199980\n",
       "            - 0\n",
       "            - -20\n",
       "            - 6200020\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 5\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B06:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.7402\n",
       "              full_width_half_max: 0.018\n",
       "              name: B06\n",
       "            gsd: 20\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B06.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
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       "          SCL:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/SCL.tif\n",
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       "                dynamic: true\n",
       "                frame_width: 500\n",
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       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          WVP:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/WVP.tif\n",
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       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          thumbnail:\n",
       "            href: https://roda.sentinel-hub.com/sentinel-s2-l1c/tiles/54/H/TG/2020/12/20/0/preview.jpg\n",
       "            plots:\n",
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       "                bands: channel\n",
       "                data_aspect: 1\n",
       "                flip_yaxis: true\n",
       "                kind: rgb\n",
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       "            roles:\n",
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       "            title: Thumbnail\n",
       "            type: image/png\n",
       "          visual:\n",
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       "            plots:\n",
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       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
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       "            - overview\n",
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       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "        bbox:\n",
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       "        - -35.31255500628786\n",
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       "        - -34.29773472288293\n",
       "        collection: sentinel-s2-l2a-cogs\n",
       "        geometry:\n",
       "          coordinates:\n",
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       "          type: Polygon\n",
       "        id: S2A_54HTG_20201220_0_L2A\n",
       "        links:\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2A_54HTG_20201220_0_L2A\n",
       "          rel: self\n",
       "        - href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/S2A_54HTG_20201220_0_L2A.json\n",
       "          rel: canonical\n",
       "          type: application/json\n",
       "        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-54-H-TG-2020-12-20-0\n",
       "          rel: via-cirrus\n",
       "          title: sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-54-H-TG-2020-12-20-0\n",
       "        - href: https://cirrus-v0-data-1qm7gekzjucbq.s3.us-west-2.amazonaws.com/sentinel-s2-l2a/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/S2A_54HTG_20201220_0_L2A.json\n",
       "          rel: derived_from\n",
       "          title: Source STAC Item\n",
       "          type: application/json\n",
       "        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a/workflow-cog-archive/S2A_54HTG_20201220_0_L2A\n",
       "          rel: via-cirrus\n",
       "          title: sentinel-s2-l2a/workflow-cog-archive/S2A_54HTG_20201220_0_L2A\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: parent\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: collection\n",
       "        - href: https://earth-search.aws.element84.com/v0/\n",
       "          rel: root\n",
       "        properties:\n",
       "          constellation: sentinel-2\n",
       "          created: '2020-12-20T06:18:58.775Z'\n",
       "          datetime: '2020-12-20T00:56:43Z'\n",
       "          eo:cloud_cover: 0\n",
       "          gsd: 10\n",
       "          instruments:\n",
       "          - msi\n",
       "          platform: sentinel-2a\n",
       "          proj:epsg: 32754\n",
       "          sentinel:data_coverage: 99.8\n",
       "          sentinel:grid_square: TG\n",
       "          sentinel:latitude_band: H\n",
       "          sentinel:product_id: S2A_MSIL2A_20201220T004701_N0214_R102_T54HTG_20201220T032547\n",
       "          sentinel:sequence: '0'\n",
       "          sentinel:utm_zone: 54\n",
       "          sentinel:valid_cloud_cover: true\n",
       "          updated: '2020-12-20T06:18:58.775Z'\n",
       "          view:off_nadir: 0\n",
       "        stac_extensions:\n",
       "        - eo\n",
       "        - view\n",
       "        - proj\n",
       "        stac_version: 1.0.0-beta.2\n",
       "        type: Feature\n",
       "      filename: null\n",
       "  description: ''\n",
       "  driver: intake_stac.catalog.StacItem\n",
       "  metadata:\n",
       "    catalog_dir: ''\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "S2A_54HTG_20201220_0_L2A"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "item"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": "info:\n  args:\n    urlpath: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/tileInfo.json\n  description: Original JSON metadata\n  driver: intake.source.textfiles.TextFilesSource\n  metadata:\n    catalog_dir: ''\n    href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/tileInfo.json\n    roles:\n    - metadata\n    title: Original JSON metadata\n    type: application/json\n",
      "text/plain": [
       "info:\n",
       "  args:\n",
       "    urlpath: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/tileInfo.json\n",
       "  description: Original JSON metadata\n",
       "  driver: intake.source.textfiles.TextFilesSource\n",
       "  metadata:\n",
       "    catalog_dir: ''\n",
       "    href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/54/H/TG/2020/12/20/0/tileInfo.json\n",
       "    roles:\n",
       "    - metadata\n",
       "    title: Original JSON metadata\n",
       "    type: application/json\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "info"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "item['overview']\n",
    "item['metadata']\n",
    "item['info']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "thumbnail\n",
      "overview\n",
      "info\n",
      "metadata\n",
      "visual\n",
      "B01\n",
      "B02\n",
      "B03\n",
      "B04\n",
      "B05\n",
      "B06\n",
      "B07\n",
      "B08\n",
      "B8A\n",
      "B09\n",
      "B11\n",
      "B12\n",
      "AOT\n",
      "WVP\n",
      "SCL\n"
     ]
    }
   ],
   "source": [
    "for x in list(item):  #catalog version\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "S2A_54HTG_20201220_0_L2A"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_STAC_items(url, collection, dates, bbox):\n",
    "    results = Search.search(url=url,\n",
    "                        collections=[collection], \n",
    "                        datetime=dates,\n",
    "                        bbox=bbox,    \n",
    "                        query={'eo:cloud_cover': {'eq': 0}, 'platform':{'eq': 'sentinel-2a'}},\n",
    "                        sortby=['-properties.datetime'])\n",
    "\n",
    "    items = results.items()\n",
    "    print(f'Found {len(items)} Items')\n",
    "    \n",
    "    return intake.open_stac_item_collection(items)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from satsearch import Search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 40 Items\n"
     ]
    }
   ],
   "source": [
    "URL2='https://earth-search.aws.element84.com/v0'\n",
    "collection2 = 'sentinel-s2-l2a-cogs' # sentinel-2 w/ atmospheric corrections\n",
    "from satsearch import Search\n",
    "items_s2 = get_STAC_items(URL2, collection2, dates, bbox)\n",
    "\n",
    "#query={'eo:cloud_cover': {'eq': 0}, 'platform':{'eq': 'sentinel-2a'}},\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rscott\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\pyproj\\crs\\crs.py:53: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  return _prepare_from_string(\" \".join(pjargs))\n"
     ]
    }
   ],
   "source": [
    "gf2function = items_s2.to_geopandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>datetime</th>\n",
       "      <th>platform</th>\n",
       "      <th>constellation</th>\n",
       "      <th>instruments</th>\n",
       "      <th>gsd</th>\n",
       "      <th>view:off_nadir</th>\n",
       "      <th>proj:epsg</th>\n",
       "      <th>sentinel:utm_zone</th>\n",
       "      <th>sentinel:latitude_band</th>\n",
       "      <th>sentinel:grid_square</th>\n",
       "      <th>sentinel:sequence</th>\n",
       "      <th>sentinel:product_id</th>\n",
       "      <th>sentinel:data_coverage</th>\n",
       "      <th>eo:cloud_cover</th>\n",
       "      <th>sentinel:valid_cloud_cover</th>\n",
       "      <th>created</th>\n",
       "      <th>updated</th>\n",
       "      <th>data_coverage</th>\n",
       "    </tr>\n",
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       "      <td>POLYGON ((138.87711 -35.31261, 137.70126 -35.2...</td>\n",
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       "      <td>[msi]</td>\n",
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       "      <td>32754</td>\n",
       "      <td>54</td>\n",
       "      <td>H</td>\n",
       "      <td>TG</td>\n",
       "      <td>0</td>\n",
       "      <td>S2A_MSIL2A_20201117T003711_N0214_R059_T54HTG_2...</td>\n",
       "      <td>61.38</td>\n",
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       "      <td>True</td>\n",
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       "      <th>3</th>\n",
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       "      <td>2020-08-29T00:46:54Z</td>\n",
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       "      <th>4</th>\n",
       "      <td>POLYGON ((138.90758 -35.31315, 138.02765 -35.2...</td>\n",
       "      <td>2020-08-19T00:46:54Z</td>\n",
       "      <td>sentinel-2a</td>\n",
       "      <td>sentinel-2</td>\n",
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       "                                            geometry              datetime  \\\n",
       "0  POLYGON ((138.87370 -35.31256, 137.70126 -35.2...  2020-12-20T00:56:43Z   \n",
       "1  POLYGON ((138.87711 -35.31261, 137.70126 -35.2...  2020-11-30T00:56:45Z   \n",
       "2  POLYGON ((138.90758 -35.31315, 138.02743 -35.2...  2020-11-17T00:46:52Z   \n",
       "3  POLYGON ((138.90758 -35.31315, 138.02787 -35.2...  2020-08-29T00:46:54Z   \n",
       "4  POLYGON ((138.90758 -35.31315, 138.02765 -35.2...  2020-08-19T00:46:54Z   \n",
       "\n",
       "      platform constellation instruments  gsd  view:off_nadir  proj:epsg  \\\n",
       "0  sentinel-2a    sentinel-2       [msi]   10               0      32754   \n",
       "1  sentinel-2a    sentinel-2       [msi]   10               0      32754   \n",
       "2  sentinel-2a    sentinel-2       [msi]   10               0      32754   \n",
       "3  sentinel-2a    sentinel-2       [msi]   10               0      32754   \n",
       "4  sentinel-2a    sentinel-2       [msi]   10               0      32754   \n",
       "\n",
       "   sentinel:utm_zone sentinel:latitude_band sentinel:grid_square  \\\n",
       "0                 54                      H                   TG   \n",
       "1                 54                      H                   TG   \n",
       "2                 54                      H                   TG   \n",
       "3                 54                      H                   TG   \n",
       "4                 54                      H                   TG   \n",
       "\n",
       "  sentinel:sequence                                sentinel:product_id  \\\n",
       "0                 0  S2A_MSIL2A_20201220T004701_N0214_R102_T54HTG_2...   \n",
       "1                 0  S2A_MSIL2A_20201130T004711_N0214_R102_T54HTG_2...   \n",
       "2                 0  S2A_MSIL2A_20201117T003711_N0214_R059_T54HTG_2...   \n",
       "3                 0  S2A_MSIL2A_20200829T003711_N0214_R059_T54HTG_2...   \n",
       "4                 0  S2A_MSIL2A_20200819T003711_N0214_R059_T54HTG_2...   \n",
       "\n",
       "   sentinel:data_coverage  eo:cloud_cover  sentinel:valid_cloud_cover  \\\n",
       "0                   99.80               0                        True   \n",
       "1                   99.84               0                        True   \n",
       "2                   61.38               0                        True   \n",
       "3                   61.31               0                       False   \n",
       "4                   61.32               0                       False   \n",
       "\n",
       "                    created                   updated  data_coverage  \n",
       "0  2020-12-20T06:18:58.775Z  2020-12-20T06:18:58.775Z            NaN  \n",
       "1  2020-11-30T07:13:47.674Z  2020-11-30T07:13:47.674Z            NaN  \n",
       "2  2020-11-17T05:53:27.379Z  2020-11-17T05:53:27.379Z            NaN  \n",
       "3  2020-08-29T06:53:02.125Z  2020-08-29T06:53:02.125Z            NaN  \n",
       "4  2020-08-20T00:25:47.097Z  2020-08-20T00:25:47.097Z            NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gf2function.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in items_s2:\n",
    "    junk = items_s2[x]\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'blue'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "junk['B02'].metadata['eo:bands'][0]['common_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": "B03:\n  args:\n    chunks: {}\n    urlpath: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n  description: Band 3 (green)\n  driver: intake_xarray.raster.RasterIOSource\n  metadata:\n    catalog_dir: ''\n    eo:bands:\n    - center_wavelength: 0.56\n      common_name: green\n      full_width_half_max: 0.045\n      name: B03\n    gsd: 10\n    href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n    plots:\n      geotiff:\n        cmap: viridis\n        data_aspect: 1\n        dynamic: true\n        frame_width: 500\n        kind: image\n        rasterize: true\n        x: x\n        y: y\n    proj:shape:\n    - 10980\n    - 10980\n    proj:transform:\n    - 10\n    - 0\n    - 199980\n    - 0\n    - -10\n    - 6200020\n    - 0\n    - 0\n    - 1\n    roles:\n    - data\n    title: Band 3 (green)\n    type: image/tiff; application=geotiff; profile=cloud-optimized\n",
      "text/plain": [
       "B03:\n",
       "  args:\n",
       "    chunks: {}\n",
       "    urlpath: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n",
       "  description: Band 3 (green)\n",
       "  driver: intake_xarray.raster.RasterIOSource\n",
       "  metadata:\n",
       "    catalog_dir: ''\n",
       "    eo:bands:\n",
       "    - center_wavelength: 0.56\n",
       "      common_name: green\n",
       "      full_width_half_max: 0.045\n",
       "      name: B03\n",
       "    gsd: 10\n",
       "    href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif\n",
       "    plots:\n",
       "      geotiff:\n",
       "        cmap: viridis\n",
       "        data_aspect: 1\n",
       "        dynamic: true\n",
       "        frame_width: 500\n",
       "        kind: image\n",
       "        rasterize: true\n",
       "        x: x\n",
       "        y: y\n",
       "    proj:shape:\n",
       "    - 10980\n",
       "    - 10980\n",
       "    proj:transform:\n",
       "    - 10\n",
       "    - 0\n",
       "    - 199980\n",
       "    - 0\n",
       "    - -10\n",
       "    - 6200020\n",
       "    - 0\n",
       "    - 0\n",
       "    - 1\n",
       "    roles:\n",
       "    - data\n",
       "    title: Band 3 (green)\n",
       "    type: image/tiff; application=geotiff; profile=cloud-optimized\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "B03"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "junk['B03']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "da2 = junk['B02'].to_dask()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 1, y: 10980, x: 10980)&gt;\n",
       "dask.array&lt;open_rasterio-ce94d0bc56811550c67f0001959dc7ad&lt;this-array&gt;, shape=(1, 10980, 10980), dtype=uint16, chunksize=(1, 10980, 10980), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * band     (band) int32 1\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 10980</li><li><span class='xr-has-index'>x</span>: 10980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-946ff16d-528b-4413-a06c-d0080f4f3499' class='xr-array-in' type='checkbox' checked><label for='section-946ff16d-528b-4413-a06c-d0080f4f3499' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 10980, 10980), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 241.12 MB </td> <td> 241.12 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (1, 10980, 10980) </td> <td> (1, 10980, 10980) </td></tr>\n",
       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> uint16 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"194\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"120\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,134.9485979497544 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"134\" x2=\"144\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"84.948598\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >10980</text>\n",
       "  <text x=\"164.948598\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,74.948598)\">10980</text>\n",
       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">1</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-681cc421-5e6d-4ce9-9d71-9e24b0c1b344' class='xr-section-summary-in' type='checkbox'  checked><label for='section-681cc421-5e6d-4ce9-9d71-9e24b0c1b344' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-a16a303e-dd4f-4492-b1dd-5544a4f016f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a16a303e-dd4f-4492-b1dd-5544a4f016f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0fb6a56-2061-4876-bd70-009f2e90481b' class='xr-var-data-in' type='checkbox'><label for='data-c0fb6a56-2061-4876-bd70-009f2e90481b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-fb11d005-8907-44be-864c-3e7172bb3c15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb11d005-8907-44be-864c-3e7172bb3c15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3202034-1d64-49b0-b58d-cff6d0034a10' class='xr-var-data-in' type='checkbox'><label for='data-e3202034-1d64-49b0-b58d-cff6d0034a10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-89994a7e-0083-4e2d-bb62-2987f41f6d65' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89994a7e-0083-4e2d-bb62-2987f41f6d65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82232727-f80b-4d2a-9a14-1c573648927c' class='xr-var-data-in' type='checkbox'><label for='data-82232727-f80b-4d2a-9a14-1c573648927c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5fe3642b-f321-4947-90f2-99cf9d285708' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5fe3642b-f321-4947-90f2-99cf9d285708' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32754</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>1</dd><dt><span>nodatavals :</span></dt><dd>(0.0,)</dd><dt><span>scales :</span></dt><dd>(1.0,)</dd><dt><span>offsets :</span></dt><dd>(0.0,)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>OVR_RESAMPLING_ALG :</span></dt><dd>AVERAGE</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (band: 1, y: 10980, x: 10980)>\n",
       "dask.array<open_rasterio-ce94d0bc56811550c67f0001959dc7ad<this-array>, shape=(1, 10980, 10980), dtype=uint16, chunksize=(1, 10980, 10980), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * band     (band) int32 1\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "stackedtest = junk.stack_bands(['B02','B03'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": {
       "args": {
        "chunks": {},
        "concat_dim": "band",
        "path_as_pattern": "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/{band}.tif",
        "plots": {
         "geotiff": {
          "cmap": "viridis",
          "data_aspect": 1,
          "dynamic": true,
          "frame_width": 500,
          "kind": "image",
          "rasterize": true,
          "x": "x",
          "y": "y"
         }
        },
        "title": "B02, B03",
        "type": "image/tiff; application=geotiff; profile=cloud-optimized",
        "urlpath": [
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif"
        ]
       },
       "container": "xarray",
       "description": "B02, B03",
       "direct_access": true,
       "metadata": {
        "chunks": {},
        "concat_dim": "band",
        "path_as_pattern": "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/{band}.tif",
        "plots": {
         "geotiff": {
          "cmap": "viridis",
          "data_aspect": 1,
          "dynamic": true,
          "frame_width": 500,
          "kind": "image",
          "rasterize": true,
          "x": "x",
          "y": "y"
         }
        },
        "title": "B02, B03",
        "type": "image/tiff; application=geotiff; profile=cloud-optimized",
        "urlpath": [
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif"
        ]
       },
       "name": "B02_B03",
       "plugin": [
        "rasterio"
       ],
       "user_parameters": []
      },
      "text/plain": [
       "name: B02_B03\n",
       "container: xarray\n",
       "plugin: ['rasterio']\n",
       "description: B02, B03\n",
       "direct_access: True\n",
       "user_parameters: []\n",
       "metadata: \n",
       "  concat_dim: band\n",
       "  urlpath: ['https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif']\n",
       "  path_as_pattern: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/{band}.tif\n",
       "  type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "  title: B02, B03\n",
       "  plots: \n",
       "    geotiff: \n",
       "      kind: image\n",
       "      x: x\n",
       "      y: y\n",
       "      frame_width: 500\n",
       "      data_aspect: 1\n",
       "      rasterize: True\n",
       "      dynamic: True\n",
       "      cmap: viridis\n",
       "  chunks: \n",
       "args: \n",
       "  concat_dim: band\n",
       "  urlpath: ['https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B02.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/B03.tif']\n",
       "  path_as_pattern: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/54/H/TG/2020/12/S2A_54HTG_20201220_0_L2A/{band}.tif\n",
       "  type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "  title: B02, B03\n",
       "  plots: \n",
       "    geotiff: \n",
       "      kind: image\n",
       "      x: x\n",
       "      y: y\n",
       "      frame_width: 500\n",
       "      data_aspect: 1\n",
       "      rasterize: True\n",
       "      dynamic: True\n",
       "      cmap: viridis\n",
       "  chunks: "
      ]
     },
     "metadata": {
      "application/json": {
       "root": "B02_B03"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stackedtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[                                        ] | 0% Completed |  0.0s<Intake catalog: S2A_54HTG_20200819_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180323_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190507_1_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170308_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20181231_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190216_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180125_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20201220_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20181029_0_L2A>\n",
      "[                                        ] | 0% Completed |  0.1s<Intake catalog: S2A_54HTG_20190917_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180105_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20191024_0_L2A>\n",
      "[                                        ] | 0% Completed | 18.5s<Intake catalog: S2A_54HTG_20200102_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190301_0_L2A>\n",
      "[############                            ] | 30% Completed | 18.6s<Intake catalog: S2A_54HTG_20171226_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190709_0_L2A><Intake catalog: S2A_54HTG_20180714_0_L2A><Intake catalog: S2A_54HTG_20170318_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20201130_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170619_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200112_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180422_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20170226_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190226_0_L2A>\n",
      "[############                            ] | 30% Completed | 35.2s<Intake catalog: S2A_54HTG_20190120_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190914_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200829_0_L2A>\n",
      "[####################                    ] | 50% Completed | 35.3s<Intake catalog: S2A_54HTG_20201117_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180525_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20171226_1_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180909_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190517_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20191216_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20181118_0_L2A><Intake catalog: S2A_54HTG_20200610_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200414_0_L2A>\n",
      "\n",
      "[########################                ] | 60% Completed | 52.4s<Intake catalog: S2A_54HTG_20200723_0_L2A>\n",
      "[###########################             ] | 67% Completed | 52.5s<Intake catalog: S2A_54HTG_20171017_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200204_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170127_0_L2A>\n",
      "[########################################] | 100% Completed | 57.1s\n",
      "Wall time: 57.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# First let's construct a large dataset with all the scenes in our search so that we\n",
    "# have a time dimension\n",
    "# Loop through geopandas geodataframe (each row is a STAC ITEM)\n",
    "import dask\n",
    "\n",
    "@dask.delayed\n",
    "def stacitem_to_dataset2(item, datetimeuse):\n",
    "    print(item)\n",
    "    #stacked = catalog[item.id].stack_bands(bands)\n",
    "    #stacked = item.stack_bands(['B02','B03','B04','B05'])\n",
    "    stacked = item.stack_bands(['B02'])\n",
    "    da = stacked(chunks=dict(band=1, x=2048, y=2048)).to_dask()\n",
    "    #da = stacked(chunks=dict(band=1, x=5120, y=5120)).to_dask()\n",
    "    #da['band'] = bands # use common names\n",
    "    #da['band'] = ['blue','green','red','nir'] # use common names\n",
    "    da['band'] = ['blue'] # use common names\n",
    "    da = da.expand_dims(time=[pd.to_datetime(datetimeuse)])\n",
    "    #da = stacked(chunks=dict(band=1, x=5120, y=5120, time=-1)).to_dask()\n",
    "    ds = da.to_dataset(dim='band')\n",
    "    return ds\n",
    "\n",
    "lazy_datasets = []\n",
    "#for i,item in gf.iterrows():\n",
    "#for i,item in gf.head(1).iterrows():   \n",
    "\n",
    "for index, x in enumerate(items_s2):\n",
    "    #need to make items_s2\n",
    "    #need to get datetime from the dataframe gf2 as well\n",
    "    datetimeuse = gf2function.iloc[index]['datetime']\n",
    "    itemx = items_s2[x]\n",
    "    ds = stacitem_to_dataset2(itemx, datetimeuse)\n",
    "    lazy_datasets.append(ds)\n",
    "\n",
    "from dask.diagnostics import ProgressBar\n",
    "with ProgressBar():\n",
    "    #out = dask.compute(*lazy_datasets)\n",
    "    \n",
    "#datasets = dask.compute(*lazy_datasets).mean(dim='time')\n",
    "    datasets = dask.compute(*lazy_datasets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-12-20T00:56:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-11-30T00:56:45+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-11-17T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-08-29T00:46:54+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-08-19T00:46:54+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-07-23T00:56:50+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-06-10T00:46:55+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-04-14T00:56:44+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-02-04T00:56:36+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-01-12T00:46:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-01-02T00:46:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-12-16T00:56:39+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-10-24T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-09-17T00:56:44+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-09-14T00:46:47+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-07-09T00:56:50+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-05-17T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-05-07T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-03-01T01:01:28+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-02-26T00:57:15+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-02-16T00:46:45+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-01-20T00:56:41+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-12-31T00:56:38+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-11-18T00:46:42+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-10-29T00:37:01+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-09-09T00:37:02+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-07-14T00:47:07+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-05-25T00:47:08+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-04-22T00:37:06+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
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       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
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       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
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       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
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       "     scales:              (1.0,)\n",
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       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
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       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
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       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
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       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
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       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
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       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
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       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-02-26T00:45:47+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-01-27T00:42:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#datasets = dask.compute(*lazy_datasets)\n",
    "datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray\n",
    "len(datasets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "DS = xarray.concat(datasets, dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 40, x: 10980, y: 10980)\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "Data variables:\n",
       "    blue     (time, y, x) uint16 dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c1b8374a-8e5e-49dc-ad7f-5dfa8fac3e29' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c1b8374a-8e5e-49dc-ad7f-5dfa8fac3e29' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 40</li><li><span class='xr-has-index'>x</span>: 10980</li><li><span class='xr-has-index'>y</span>: 10980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a2ac7335-b338-4c89-a6a6-7ad01680298c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2ac7335-b338-4c89-a6a6-7ad01680298c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1608425803000000000 ... 14854777...</div><input id='attrs-470965e8-b8aa-4fb6-b16f-9ac6f03c10a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-470965e8-b8aa-4fb6-b16f-9ac6f03c10a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cb9c104-c840-4c3b-9315-6306be626249' class='xr-var-data-in' type='checkbox'><label for='data-0cb9c104-c840-4c3b-9315-6306be626249' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1608425803000000000, 1606697805000000000, 1605574012000000000,\n",
       "       1598662014000000000, 1597798014000000000, 1595465810000000000,\n",
       "       1591750015000000000, 1586825804000000000, 1580777796000000000,\n",
       "       1578790003000000000, 1577926003000000000, 1576457799000000000,\n",
       "       1571878012000000000, 1568681804000000000, 1568422007000000000,\n",
       "       1562633810000000000, 1558054012000000000, 1557190012000000000,\n",
       "       1551402088000000000, 1551142635000000000, 1550278005000000000,\n",
       "       1547945801000000000, 1546217798000000000, 1542502002000000000,\n",
       "       1540773421000000000, 1536453422000000000, 1531529227000000000,\n",
       "       1527209228000000000, 1524357426000000000, 1521765422000000000,\n",
       "       1516841792000000000, 1515113790000000000, 1514249602000000000,\n",
       "       1514249602000000000, 1508201796000000000, 1497833797000000000,\n",
       "       1489797945000000000, 1488933983000000000, 1488069947000000000,\n",
       "       1485477763000000000], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-22f5e814-942e-46ea-94ff-17d44e8aef63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22f5e814-942e-46ea-94ff-17d44e8aef63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b439dae-0b7f-4593-9ebb-ea44f6e92d34' class='xr-var-data-in' type='checkbox'><label for='data-1b439dae-0b7f-4593-9ebb-ea44f6e92d34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-ffd5c294-3513-4a2f-9751-67d9830720b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ffd5c294-3513-4a2f-9751-67d9830720b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a13663cc-6df7-4b2b-b051-9c0a4010c88a' class='xr-var-data-in' type='checkbox'><label for='data-a13663cc-6df7-4b2b-b051-9c0a4010c88a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d3cd152-b72a-4eee-ad7f-50864890ad3a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2d3cd152-b72a-4eee-ad7f-50864890ad3a' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>blue</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-70853522-d823-4d3e-b2ef-2978ad1af056' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70853522-d823-4d3e-b2ef-2978ad1af056' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e890553c-7218-4010-9b87-e090eca5effb' class='xr-var-data-in' type='checkbox'><label for='data-e890553c-7218-4010-9b87-e090eca5effb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 9.64 GB </td> <td> 8.39 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (40, 10980, 10980) </td> <td> (1, 2048, 2048) </td></tr>\n",
       "    <tr><th> Count </th><td> 5800 Tasks </td><td> 1440 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> uint16 </td><td> numpy.ndarray </td></tr>\n",
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      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 40, x: 10980, y: 10980)\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "Data variables:\n",
       "    blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#DS['blue'].quantile(0.5,dim='time')\n",
    "DS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#DSquantile = xarray.quantile(50,dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "stacked = junk.stack_bands(['B02','B03'])\n",
    "da = stacked(chunks=dict(band=1, x=2048, y=2048)).to_dask()\n",
    "#da['band'] = bands # use common names\n",
    "da['band'] = ['blue','green'] # use common names\n",
    "da = da.expand_dims(time=[pd.to_datetime(datetimeuse)])\n",
    "ds = da.to_dataset(dim='band')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dsmedian = ds.mean(dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Intake catalog: S2A_54HTG_20170127_0_L2A>\n"
     ]
    }
   ],
   "source": [
    "#dsmedian2 = ds.quantile(50,dim='time').compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (x: 10980, y: 10980)\n",
       "Coordinates:\n",
       "  * y         (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x         (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "    quantile  float64 50.0\n",
       "Data variables:\n",
       "    blue      (y, x) float64 dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;\n",
       "    green     (y, x) float64 dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3dd3f620-11e0-4f95-a3df-bc7fec5ced7e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3dd3f620-11e0-4f95-a3df-bc7fec5ced7e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 10980</li><li><span class='xr-has-index'>y</span>: 10980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-467d8125-c7b0-4ab9-b652-c3c3cf9c3c90' class='xr-section-summary-in' type='checkbox'  checked><label for='section-467d8125-c7b0-4ab9-b652-c3c3cf9c3c90' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-804a66cd-989d-437a-b407-37ccd0b02190' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-804a66cd-989d-437a-b407-37ccd0b02190' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f7996f9-99de-4a7c-a073-986af9370dac' class='xr-var-data-in' type='checkbox'><label for='data-1f7996f9-99de-4a7c-a073-986af9370dac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-0dd1b783-60ae-4620-a9c3-161c84d9544a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0dd1b783-60ae-4620-a9c3-161c84d9544a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e50942cc-6fe6-4adc-ae69-13b6768d9fa2' class='xr-var-data-in' type='checkbox'><label for='data-e50942cc-6fe6-4adc-ae69-13b6768d9fa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quantile</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>50.0</div><input id='attrs-7d93b794-490a-46b5-b691-b945d4da6adc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d93b794-490a-46b5-b691-b945d4da6adc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-308c3ffd-62ed-43bf-b1f1-aa1df3437be8' class='xr-var-data-in' type='checkbox'><label for='data-308c3ffd-62ed-43bf-b1f1-aa1df3437be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(50.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-01671ab2-eed3-4d5f-a0d8-e6e5a42df917' 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      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (x: 10980, y: 10980)\n",
       "Coordinates:\n",
       "  * y         (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x         (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "    quantile  float64 50.0\n",
       "Data variables:\n",
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       "    green     (y, x) float64 dask.array<chunksize=(2048, 2048), meta=np.ndarray>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
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    }
   ],
   "source": [
    "#dsmedian2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def median(array, dim, keep_attrs=False, skipna=False, **kwargs):\n",
    "    \"\"\" Runs a median on an dask-backed xarray.\n",
    "    \n",
    "    This function does not scale!\n",
    "    It will rechunk along the given dimension, so make sure \n",
    "    your other chunk sizes are small enough that it \n",
    "    will fit into memory.\n",
    "    \n",
    "    :param DataArray array: An xarray.DataArray wrapping a dask array\n",
    "    :param dim str: The name of the dim in array to calculate the median\n",
    "    \"\"\"\n",
    "    if type(array) is xr.Dataset:\n",
    "        return array.apply(median, dim=dim, keep_attrs=keep_attrs, **kwargs)\n",
    "    \n",
    "    if not hasattr(array.data, 'dask'):\n",
    "        return array.median(dim, keep_attrs=keep_attrs, **kwargs)\n",
    "    \n",
    "    array = array.chunk({dim:-1})\n",
    "    axis = array.dims.index(dim)\n",
    "    median_func = np.nanmedian if skipna else np.median\n",
    "    blocks = dask.array.map_blocks(median_func, array.data, dtype=array.dtype, drop_axis=axis, axis=axis, **kwargs)\n",
    "    \n",
    "    new_coords={k: v for k, v in array.coords.items() if k != dim and dim not in v.dims}\n",
    "    new_dims = tuple(d for d in array.dims if d != dim)\n",
    "    new_attrs = array.attrs if keep_attrs else None\n",
    "    \n",
    "    return xr.DataArray(blocks, coords=new_coords, dims=new_dims, attrs=new_attrs)"
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "DS['blue']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "blue_median = median(DS.blue, dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;median-8d32d5f5f58296f25583e94cf808a8aa&#x27; (y: 10980, x: 10980)&gt;\n",
       "dask.array&lt;median, shape=(10980, 10980), dtype=uint16, chunksize=(2048, 2048), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'median-8d32d5f5f58296f25583e94cf808a8aa'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 10980</li><li><span class='xr-has-index'>x</span>: 10980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4f3b3806-cde8-46fd-92a6-f15bd7d1c80b' class='xr-array-in' type='checkbox' checked><label for='section-4f3b3806-cde8-46fd-92a6-f15bd7d1c80b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
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       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 241.12 MB </td> <td> 8.39 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (10980, 10980) </td> <td> (2048, 2048) </td></tr>\n",
       "    <tr><th> Count </th><td> 5872 Tasks </td><td> 36 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> uint16 </td><td> numpy.ndarray </td></tr>\n",
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      ],
      "text/plain": [
       "<xarray.DataArray 'median-8d32d5f5f58296f25583e94cf808a8aa' (y: 10980, x: 10980)>\n",
       "dask.array<median, shape=(10980, 10980), dtype=uint16, chunksize=(2048, 2048), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blue_median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "blue_mean = DS['blue'].mean(dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "blue_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed |  1hr 24min 21.6s\n"
     ]
    }
   ],
   "source": [
    "with ProgressBar():\n",
    "\n",
    "    bluemedianNP = blue_median.compute()\n",
    "    #bluemeanNP = blue_mean.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import rioxarray\n",
    "#blue_median.rio.to_raster(\"C:/users/rscott/Downloads/blue_median.tif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;median-8d32d5f5f58296f25583e94cf808a8aa&#x27; (y: 10980, x: 10980)&gt;\n",
       "array([[  0. ,   0. ,   0. , ..., 632.5, 599. , 611.5],\n",
       "       [  0. ,   0. ,   0. , ..., 491. , 505.5, 459.5],\n",
       "       [  0. ,   0. ,   0. , ..., 582.5, 718. , 585. ],\n",
       "       ...,\n",
       "       [  0. ,   0. ,   0. , ..., 268. , 227.5, 235. ],\n",
       "       [  0. ,   0. ,   0. , ..., 262.5, 237.5, 265.5],\n",
       "       [  0. ,   0. ,   0. , ..., 268.5, 266. , 263.5]])\n",
       "Coordinates:\n",
       "  * y            (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06\n",
       "  * x            (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    grid_mapping:  spatial_ref</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'median-8d32d5f5f58296f25583e94cf808a8aa'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 10980</li><li><span class='xr-has-index'>x</span>: 10980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-47b13dd2-cacf-41f3-b097-ea205d4a8800' class='xr-array-in' type='checkbox' checked><label for='section-47b13dd2-cacf-41f3-b097-ea205d4a8800' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 266.0 280.5 289.0 268.5 266.0 263.5</span></div><div class='xr-array-data'><pre>array([[  0. ,   0. ,   0. , ..., 632.5, 599. , 611.5],\n",
       "       [  0. ,   0. ,   0. , ..., 491. , 505.5, 459.5],\n",
       "       [  0. ,   0. ,   0. , ..., 582.5, 718. , 585. ],\n",
       "       ...,\n",
       "       [  0. ,   0. ,   0. , ..., 268. , 227.5, 235. ],\n",
       "       [  0. ,   0. ,   0. , ..., 262.5, 237.5, 265.5],\n",
       "       [  0. ,   0. ,   0. , ..., 268.5, 266. , 263.5]])</pre></div></div></li><li class='xr-section-item'><input id='section-928dd28c-b60c-42b1-a53f-2fd4f4d8d1e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-928dd28c-b60c-42b1-a53f-2fd4f4d8d1e2' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-b4ae1a3a-e9b6-44d3-8851-1cc750096569' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b4ae1a3a-e9b6-44d3-8851-1cc750096569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bb96a2c-85b4-4923-971f-f01a0fc8424c' class='xr-var-data-in' type='checkbox'><label for='data-4bb96a2c-85b4-4923-971f-f01a0fc8424c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-9ddff8b4-fcc7-415a-9e62-d541c073ece0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ddff8b4-fcc7-415a-9e62-d541c073ece0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4205cf6-4b84-4fbb-bb1c-94de67f83b14' class='xr-var-data-in' type='checkbox'><label for='data-d4205cf6-4b84-4fbb-bb1c-94de67f83b14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-15c07e8c-c070-4b01-b9e5-96b13d4045e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15c07e8c-c070-4b01-b9e5-96b13d4045e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d38bca59-3641-4f47-b898-aa8480060612' class='xr-var-data-in' type='checkbox'><label for='data-d38bca59-3641-4f47-b898-aa8480060612' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 54S&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,DATUM[&quot;World Geodetic System 1984&quot;,ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 54S&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,141,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,10000000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;easting&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;northing&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],ID[&quot;EPSG&quot;,32754]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 54S</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>141.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>10000000.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 54S&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,DATUM[&quot;World Geodetic System 1984&quot;,ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 54S&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,141,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,10000000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;easting&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;northing&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],ID[&quot;EPSG&quot;,32754]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bc01ff95-a4cf-4877-8158-ca387efca3c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bc01ff95-a4cf-4877-8158-ca387efca3c8' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'median-8d32d5f5f58296f25583e94cf808a8aa' (y: 10980, x: 10980)>\n",
       "array([[  0. ,   0. ,   0. , ..., 632.5, 599. , 611.5],\n",
       "       [  0. ,   0. ,   0. , ..., 491. , 505.5, 459.5],\n",
       "       [  0. ,   0. ,   0. , ..., 582.5, 718. , 585. ],\n",
       "       ...,\n",
       "       [  0. ,   0. ,   0. , ..., 268. , 227.5, 235. ],\n",
       "       [  0. ,   0. ,   0. , ..., 262.5, 237.5, 265.5],\n",
       "       [  0. ,   0. ,   0. , ..., 268.5, 266. , 263.5]])\n",
       "Coordinates:\n",
       "  * y            (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06\n",
       "  * x            (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    grid_mapping:  spatial_ref"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#blue_median.rio.write_crs('EPSG:32754', inplace=True)\n",
    "#blue_median.rio.to_raster(\"C:/users/rscott/Downloads/blue_median20pth5.tif\")\n",
    "bluemedianNP.rio.write_crs('EPSG:32754', inplace=True)\n",
    "#bluemedianNP.rio.to_raster(\"C:/users/rscott/Downloads/blue_medianOZ.tif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;blue&#x27; (time: 40, y: 10980, x: 10980)&gt;\n",
       "dask.array&lt;concatenate, shape=(40, 10980, 10980), dtype=uint16, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'blue'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 40</li><li><span class='xr-has-index'>y</span>: 10980</li><li><span class='xr-has-index'>x</span>: 10980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-834786e3-e66c-4c73-a616-bedd0fafc686' class='xr-array-in' type='checkbox' checked><label for='section-834786e3-e66c-4c73-a616-bedd0fafc686' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 9.64 GB </td> <td> 8.39 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (40, 10980, 10980) </td> <td> (1, 2048, 2048) </td></tr>\n",
       "    <tr><th> Count </th><td> 5800 Tasks </td><td> 1440 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> uint16 </td><td> numpy.ndarray </td></tr>\n",
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       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"84.948598\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >10980</text>\n",
       "  <text x=\"164.948598\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,74.948598)\">10980</text>\n",
       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">40</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-722e3da5-db09-4945-b9d9-aed5a3cec6c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-722e3da5-db09-4945-b9d9-aed5a3cec6c6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1608425803000000000 ... 14854777...</div><input id='attrs-bb88c66f-365b-4020-b70a-ae0cd8514543' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb88c66f-365b-4020-b70a-ae0cd8514543' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b615435-b26b-4902-b941-385efa865eb0' class='xr-var-data-in' type='checkbox'><label for='data-4b615435-b26b-4902-b941-385efa865eb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1608425803000000000, 1606697805000000000, 1605574012000000000,\n",
       "       1598662014000000000, 1597798014000000000, 1595465810000000000,\n",
       "       1591750015000000000, 1586825804000000000, 1580777796000000000,\n",
       "       1578790003000000000, 1577926003000000000, 1576457799000000000,\n",
       "       1571878012000000000, 1568681804000000000, 1568422007000000000,\n",
       "       1562633810000000000, 1558054012000000000, 1557190012000000000,\n",
       "       1551402088000000000, 1551142635000000000, 1550278005000000000,\n",
       "       1547945801000000000, 1546217798000000000, 1542502002000000000,\n",
       "       1540773421000000000, 1536453422000000000, 1531529227000000000,\n",
       "       1527209228000000000, 1524357426000000000, 1521765422000000000,\n",
       "       1516841792000000000, 1515113790000000000, 1514249602000000000,\n",
       "       1514249602000000000, 1508201796000000000, 1497833797000000000,\n",
       "       1489797945000000000, 1488933983000000000, 1488069947000000000,\n",
       "       1485477763000000000], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-519db159-4229-4cb2-b88a-ccc47ca9fac3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-519db159-4229-4cb2-b88a-ccc47ca9fac3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c01d9467-5e24-4e22-b3bf-e86b2ba551b5' class='xr-var-data-in' type='checkbox'><label for='data-c01d9467-5e24-4e22-b3bf-e86b2ba551b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-3d8c4669-2deb-489b-813d-e2ef0645a915' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d8c4669-2deb-489b-813d-e2ef0645a915' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e6e7e1d-0868-4cb8-bd04-91307a66eb67' class='xr-var-data-in' type='checkbox'><label for='data-9e6e7e1d-0868-4cb8-bd04-91307a66eb67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6749b2d0-1cec-4d75-ae69-199295a74640' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6749b2d0-1cec-4d75-ae69-199295a74640' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'blue' (time: 40, y: 10980, x: 10980)>\n",
       "dask.array<concatenate, shape=(40, 10980, 10980), dtype=uint16, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DS['blue']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bluemedianNP.plot.imshow();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentinel_good = ['B02','B03','B04','B05','B06','B07','B08','B8A','B11','B12']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "junk['B02'].metadata['gsd']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "10\n",
      "10\n",
      "20\n",
      "20\n",
      "10\n",
      "20\n",
      "20\n",
      "20\n"
     ]
    }
   ],
   "source": [
    "for i in sentinel_good:\n",
    "    print(junk[i].metadata['gsd'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "sss = junk.stack_bands(sentinel_good)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": {
       "args": {
        "chunks": {},
        "concat_dim": "band",
        "path_as_pattern": "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/{band}.tif",
        "plots": {
         "geotiff": {
          "cmap": "viridis",
          "data_aspect": 1,
          "dynamic": true,
          "frame_width": 500,
          "kind": "image",
          "rasterize": true,
          "x": "x",
          "y": "y"
         }
        },
        "title": "B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12",
        "type": "image/tiff; application=geotiff; profile=cloud-optimized",
        "urlpath": [
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif"
        ]
       },
       "container": "xarray",
       "description": "B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12",
       "direct_access": true,
       "metadata": {
        "chunks": {},
        "concat_dim": "band",
        "path_as_pattern": "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/{band}.tif",
        "plots": {
         "geotiff": {
          "cmap": "viridis",
          "data_aspect": 1,
          "dynamic": true,
          "frame_width": 500,
          "kind": "image",
          "rasterize": true,
          "x": "x",
          "y": "y"
         }
        },
        "title": "B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12",
        "type": "image/tiff; application=geotiff; profile=cloud-optimized",
        "urlpath": [
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif",
         "https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif"
        ]
       },
       "name": "B02_B03_B04_B05_B06_B07_B08_B8A_B11_B12",
       "plugin": [
        "rasterio"
       ],
       "user_parameters": []
      },
      "text/plain": [
       "name: B02_B03_B04_B05_B06_B07_B08_B8A_B11_B12\n",
       "container: xarray\n",
       "plugin: ['rasterio']\n",
       "description: B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12\n",
       "direct_access: True\n",
       "user_parameters: []\n",
       "metadata: \n",
       "  concat_dim: band\n",
       "  urlpath: ['https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif']\n",
       "  path_as_pattern: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/{band}.tif\n",
       "  type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "  title: B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12\n",
       "  plots: \n",
       "    geotiff: \n",
       "      kind: image\n",
       "      x: x\n",
       "      y: y\n",
       "      frame_width: 500\n",
       "      data_aspect: 1\n",
       "      rasterize: True\n",
       "      dynamic: True\n",
       "      cmap: viridis\n",
       "  chunks: \n",
       "args: \n",
       "  concat_dim: band\n",
       "  urlpath: ['https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif', 'https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif']\n",
       "  path_as_pattern: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/{band}.tif\n",
       "  type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "  title: B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12\n",
       "  plots: \n",
       "    geotiff: \n",
       "      kind: image\n",
       "      x: x\n",
       "      y: y\n",
       "      frame_width: 500\n",
       "      data_aspect: 1\n",
       "      rasterize: True\n",
       "      dynamic: True\n",
       "      cmap: viridis\n",
       "  chunks: "
      ]
     },
     "metadata": {
      "application/json": {
       "root": "B02_B03_B04_B05_B06_B07_B08_B8A_B11_B12"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "dasss = sss(chunks=dict(band=1, x=8000, y=2048)).to_dask()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "dasss = sss(chunks=dict(band=1, x=2048, y=2048)).to_dask()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 10, y: 16470, x: 16470)&gt;\n",
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       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 10</li><li><span class='xr-has-index'>y</span>: 16470</li><li><span class='xr-has-index'>x</span>: 16470</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3e6e96ae-71ea-4f05-98d2-4f63d88b08dc' class='xr-array-in' type='checkbox' checked><label for='section-3e6e96ae-71ea-4f05-98d2-4f63d88b08dc' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 21.70 GB </td> <td> 33.55 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (10, 16470, 16470) </td> <td> (1, 2048, 2048) </td></tr>\n",
       "    <tr><th> Count </th><td> 5983 Tasks </td><td> 810 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-973c1ba3-3b52-4a13-9f71-6080fdba3908' class='xr-section-summary-in' type='checkbox'  checked><label for='section-973c1ba3-3b52-4a13-9f71-6080fdba3908' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7e+05 7e+05 ... 8.098e+05 8.098e+05</div><input id='attrs-5f428af0-bf47-4222-96af-f074c1825e41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f428af0-bf47-4222-96af-f074c1825e41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-809205cd-ad7f-4810-b963-b415bd2f957d' class='xr-var-data-in' type='checkbox'><label for='data-809205cd-ad7f-4810-b963-b415bd2f957d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([699965., 699970., 699975., ..., 809745., 809750., 809755.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.19e+06 6.19e+06 ... 6.3e+06</div><input id='attrs-2c6bcd7c-2fef-4e79-a259-9203645903e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c6bcd7c-2fef-4e79-a259-9203645903e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c2ecde2-a563-400a-9782-022239c45b3e' class='xr-var-data-in' type='checkbox'><label for='data-3c2ecde2-a563-400a-9782-022239c45b3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6190245., 6190250., 6190255., ..., 6300025., 6300030., 6300035.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;B02&#x27; &#x27;B03&#x27; &#x27;B04&#x27; ... &#x27;B11&#x27; &#x27;B12&#x27;</div><input id='attrs-4eaaa266-1cfc-4e23-bea6-f9f522a6a815' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4eaaa266-1cfc-4e23-bea6-f9f522a6a815' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1147d137-cad1-4d94-a051-7c17c30ddb9c' class='xr-var-data-in' type='checkbox'><label for='data-1147d137-cad1-4d94-a051-7c17c30ddb9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;B02&#x27;, &#x27;B03&#x27;, &#x27;B04&#x27;, &#x27;B05&#x27;, &#x27;B06&#x27;, &#x27;B07&#x27;, &#x27;B08&#x27;, &#x27;B8A&#x27;, &#x27;B11&#x27;, &#x27;B12&#x27;],\n",
       "      dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9b52b29e-8808-43bc-9da0-a076b9b185ae' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b52b29e-8808-43bc-9da0-a076b9b185ae' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 699960.0, 0.0, -10.0, 6300040.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32752</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>1</dd><dt><span>nodatavals :</span></dt><dd>(0.0,)</dd><dt><span>scales :</span></dt><dd>(1.0,)</dd><dt><span>offsets :</span></dt><dd>(0.0,)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>OVR_RESAMPLING_ALG :</span></dt><dd>AVERAGE</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (band: 10, y: 16470, x: 16470)>\n",
       "dask.array<rechunk-merge, shape=(10, 16470, 16470), dtype=float64, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * x        (x) float64 7e+05 7e+05 7e+05 ... 8.097e+05 8.098e+05 8.098e+05\n",
       "  * y        (y) float64 6.19e+06 6.19e+06 6.19e+06 ... 6.3e+06 6.3e+06 6.3e+06\n",
       "  * band     (band) <U3 'B02' 'B03' 'B04' 'B05' ... 'B08' 'B8A' 'B11' 'B12'\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 699960.0, 0.0, -10.0, 6300040.0)\n",
       "    crs:                 +init=epsg:32752\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dasss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "datetime",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\miniconda3\\envs\\pangeo\\lib\\site-packages\\intake\\catalog\\base.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, item)\u001b[0m\n\u001b[0;32m    338\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 339\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m]\u001b[0m  \u001b[1;31m# triggers reload_on_change\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    340\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\envs\\pangeo\\lib\\site-packages\\intake\\catalog\\base.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    409\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 410\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    411\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'datetime'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-151-b656702b4e2e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mjunk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdatetime\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\miniconda3\\envs\\pangeo\\lib\\site-packages\\intake\\catalog\\base.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, item)\u001b[0m\n\u001b[0;32m    339\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m]\u001b[0m  \u001b[1;31m# triggers reload_on_change\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    340\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 341\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    342\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    343\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: datetime"
     ]
    }
   ],
   "source": [
    "junk.datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": "S2B_52HGH_20201231_0_L2A:\n  args:\n    stac_obj: !!python/object:satstac.item.Item\n      _assets_by_common_name: null\n      _collection: !!python/object:satstac.collection.Collection\n        _data:\n          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n          extent:\n            spatial:\n              bbox:\n              - - -180\n                - -90\n                - 180\n                - 90\n            temporal:\n              interval:\n              - - '2015-06-27T10:25:31.456000Z'\n                - null\n          id: sentinel-s2-l2a-cogs\n          item_assets:\n            AOT:\n              roles:\n              - data\n              title: Aerosol Optical Thickness (AOT)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B01:\n              eo:bands:\n              - center_wavelength: 0.4439\n                common_name: coastal\n                full_width_half_max: 0.027\n                name: B01\n              gsd: 60\n              roles:\n              - data\n              title: Band 1 (coastal)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B02:\n              eo:bands:\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - data\n              title: Band 2 (blue)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B03:\n              eo:bands:\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              gsd: 10\n              roles:\n              - data\n              title: Band 3 (green)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B04:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              gsd: 10\n              roles:\n              - data\n              title: Band 4 (red)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B05:\n              eo:bands:\n              - center_wavelength: 0.7039\n                full_width_half_max: 0.019\n                name: B05\n              gsd: 20\n              roles:\n              - data\n              title: Band 5\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B06:\n              eo:bands:\n              - center_wavelength: 0.7402\n                full_width_half_max: 0.018\n                name: B06\n              gsd: 20\n              roles:\n              - data\n              title: Band 6\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B07:\n              eo:bands:\n              - center_wavelength: 0.7825\n                full_width_half_max: 0.028\n                name: B07\n              gsd: 20\n              roles:\n              - data\n              title: Band 7\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B08:\n              eo:bands:\n              - center_wavelength: 0.8351\n                common_name: nir\n                full_width_half_max: 0.145\n                name: B08\n              gsd: 10\n              roles:\n              - data\n              title: Band 8 (nir)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B09:\n              eo:bands:\n              - center_wavelength: 0.945\n                full_width_half_max: 0.026\n                name: B09\n              gsd: 60\n              roles:\n              - data\n              title: Band 9\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B11:\n              eo:bands:\n              - center_wavelength: 1.6137\n                common_name: swir16\n                full_width_half_max: 0.143\n                name: B11\n              gsd: 20\n              roles:\n              - data\n              title: Band 11 (swir16)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B12:\n              eo:bands:\n              - center_wavelength: 2.22024\n                common_name: swir22\n                full_width_half_max: 0.242\n                name: B12\n              gsd: 20\n              roles:\n              - data\n              title: Band 12 (swir22)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B8A:\n              eo:bands:\n              - center_wavelength: 0.8648\n                full_width_half_max: 0.033\n                name: B8A\n              gsd: 20\n              roles:\n              - data\n              title: Band 8A\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            SCL:\n              roles:\n              - data\n              title: Scene Classification Map (SCL)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            WVP:\n              roles:\n              - data\n              title: Water Vapour (WVP)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            info:\n              roles:\n              - metadata\n              title: Original JSON metadata\n              type: application/json\n            metadata:\n              roles:\n              - metadata\n              title: Original XML metadata\n              type: application/xml\n            overview:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            thumbnail:\n              roles:\n              - thumbnail\n              title: Thumbnail\n              type: image/png\n            visual:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n          keywords:\n          - sentinel\n          - earth observation\n          - esa\n          license: proprietary\n          links:\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n            rel: self\n          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n            rel: license\n          - href: https://github.com/stac-utils/stac-sentinel\n            rel: about\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: parent\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: root\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n            rel: items\n          providers:\n          - name: ESA\n            roles:\n            - producer\n            url: https://earth.esa.int/web/guest/home\n          - name: Sinergise\n            roles:\n            - processor\n            url: https://registry.opendata.aws/sentinel-2/\n          - name: AWS\n            roles:\n            - host\n            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n          - name: Element 84\n            roles:\n            - processor\n            url: https://element84.com\n          stac_extensions:\n          - item-assets\n          stac_version: 1.0.0-beta.2\n          summaries:\n            constellation:\n            - sentinel-2\n            gsd:\n            - 10\n            instruments:\n            - msi\n            platform:\n            - sentinel-2a\n            - sentinel-2b\n            view:off_nadir:\n            - 0\n          title: Sentinel 2 L2A COGs\n        filename: null\n      _data:\n        assets:\n          AOT:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/AOT.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Aerosol Optical Thickness (AOT)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B01:\n            eo:bands:\n            - center_wavelength: 0.4439\n              common_name: coastal\n              full_width_half_max: 0.027\n              name: B01\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B01.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 1 (coastal)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B02:\n            eo:bands:\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 2 (blue)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B03:\n            eo:bands:\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 3 (green)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B04:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 4 (red)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B05:\n            eo:bands:\n            - center_wavelength: 0.7039\n              full_width_half_max: 0.019\n              name: B05\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 5\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B06:\n            eo:bands:\n            - center_wavelength: 0.7402\n              full_width_half_max: 0.018\n              name: B06\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 6\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B07:\n            eo:bands:\n            - center_wavelength: 0.7825\n              full_width_half_max: 0.028\n              name: B07\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 7\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B08:\n            eo:bands:\n            - center_wavelength: 0.8351\n              common_name: nir\n              full_width_half_max: 0.145\n              name: B08\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8 (nir)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B09:\n            eo:bands:\n            - center_wavelength: 0.945\n              full_width_half_max: 0.026\n              name: B09\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B09.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 9\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B11:\n            eo:bands:\n            - center_wavelength: 1.6137\n              common_name: swir16\n              full_width_half_max: 0.143\n              name: B11\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 11 (swir16)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B12:\n            eo:bands:\n            - center_wavelength: 2.22024\n              common_name: swir22\n              full_width_half_max: 0.242\n              name: B12\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 12 (swir22)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B8A:\n            eo:bands:\n            - center_wavelength: 0.8648\n              full_width_half_max: 0.033\n              name: B8A\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8A\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          SCL:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/SCL.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Scene Classification Map (SCL)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          WVP:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/WVP.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Water Vapour (WVP)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          info:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/52/H/GH/2020/12/31/0/tileInfo.json\n            roles:\n            - metadata\n            title: Original JSON metadata\n            type: application/json\n          metadata:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/52/H/GH/2020/12/31/0/metadata.xml\n            roles:\n            - metadata\n            title: Original XML metadata\n            type: application/xml\n          overview:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/L2A_PVI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 343\n            - 343\n            proj:transform:\n            - 320\n            - 0\n            - 699960\n            - 0\n            - -320\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          thumbnail:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l1c/tiles/52/H/GH/2020/12/31/0/preview.jpg\n            plots:\n              thumbnail:\n                bands: channel\n                data_aspect: 1\n                flip_yaxis: true\n                kind: rgb\n                x: x\n                xaxis: false\n                y: y\n                yaxis: false\n            roles:\n            - thumbnail\n            title: Thumbnail\n            type: image/png\n          visual:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/TCI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n        bbox:\n        - 131.9984760650785\n        - -33.4646861649747\n        - 132.3327571457415\n        - -33.39432388162574\n        collection: sentinel-s2-l2a-cogs\n        geometry:\n          coordinates:\n          - - - 132.3327571457415\n              - -33.4646861649747\n            - - 131.9984760650785\n              - -33.402787873790494\n            - - 132.33006605863437\n              - -33.39432388162574\n            - - 132.3327571457415\n              - -33.4646861649747\n          type: Polygon\n        id: S2B_52HGH_20201231_0_L2A\n        links:\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2B_52HGH_20201231_0_L2A\n          rel: self\n        - href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n          rel: canonical\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n          rel: via-cirrus\n          title: sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n        - href: https://cirrus-v0-data-1qm7gekzjucbq.s3.us-west-2.amazonaws.com/sentinel-s2-l2a/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n          rel: derived_from\n          title: Source STAC Item\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n          rel: via-cirrus\n          title: sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: parent\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: collection\n        - href: https://earth-search.aws.element84.com/v0/\n          rel: root\n        properties:\n          constellation: sentinel-2\n          created: '2020-12-31T04:58:49.199Z'\n          datetime: '2020-12-31T01:16:33Z'\n          eo:cloud_cover: 95.64\n          gsd: 10\n          instruments:\n          - msi\n          platform: sentinel-2b\n          proj:epsg: 32752\n          sentinel:data_coverage: 0.97\n          sentinel:grid_square: GH\n          sentinel:latitude_band: H\n          sentinel:product_id: S2B_MSIL2A_20201231T010729_N0214_R045_T52HGH_20201231T024641\n          sentinel:sequence: '0'\n          sentinel:utm_zone: 52\n          sentinel:valid_cloud_cover: true\n          updated: '2020-12-31T04:58:49.199Z'\n          view:off_nadir: 0\n        stac_extensions:\n        - eo\n        - view\n        - proj\n        stac_version: 1.0.0-beta.2\n        type: Feature\n      filename: null\n  description: ''\n  driver: intake_stac.catalog.StacItem\n  metadata:\n    catalog_dir: ''\n",
      "text/plain": [
       "S2B_52HGH_20201231_0_L2A:\n",
       "  args:\n",
       "    stac_obj: !!python/object:satstac.item.Item\n",
       "      _assets_by_common_name: null\n",
       "      _collection: !!python/object:satstac.collection.Collection\n",
       "        _data:\n",
       "          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n",
       "            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n",
       "          extent:\n",
       "            spatial:\n",
       "              bbox:\n",
       "              - - -180\n",
       "                - -90\n",
       "                - 180\n",
       "                - 90\n",
       "            temporal:\n",
       "              interval:\n",
       "              - - '2015-06-27T10:25:31.456000Z'\n",
       "                - null\n",
       "          id: sentinel-s2-l2a-cogs\n",
       "          item_assets:\n",
       "            AOT:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Aerosol Optical Thickness (AOT)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B01:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4439\n",
       "                common_name: coastal\n",
       "                full_width_half_max: 0.027\n",
       "                name: B01\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 1 (coastal)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B02:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 2 (blue)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B03:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 3 (green)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B04:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 4 (red)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B05:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7039\n",
       "                full_width_half_max: 0.019\n",
       "                name: B05\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 5\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B06:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7402\n",
       "                full_width_half_max: 0.018\n",
       "                name: B06\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 6\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B07:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7825\n",
       "                full_width_half_max: 0.028\n",
       "                name: B07\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 7\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B08:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8351\n",
       "                common_name: nir\n",
       "                full_width_half_max: 0.145\n",
       "                name: B08\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8 (nir)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B09:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.945\n",
       "                full_width_half_max: 0.026\n",
       "                name: B09\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 9\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B11:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 1.6137\n",
       "                common_name: swir16\n",
       "                full_width_half_max: 0.143\n",
       "                name: B11\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 11 (swir16)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B12:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 2.22024\n",
       "                common_name: swir22\n",
       "                full_width_half_max: 0.242\n",
       "                name: B12\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 12 (swir22)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B8A:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8648\n",
       "                full_width_half_max: 0.033\n",
       "                name: B8A\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8A\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            SCL:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Scene Classification Map (SCL)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            WVP:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Water Vapour (WVP)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            info:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original JSON metadata\n",
       "              type: application/json\n",
       "            metadata:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original XML metadata\n",
       "              type: application/xml\n",
       "            overview:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            thumbnail:\n",
       "              roles:\n",
       "              - thumbnail\n",
       "              title: Thumbnail\n",
       "              type: image/png\n",
       "            visual:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          keywords:\n",
       "          - sentinel\n",
       "          - earth observation\n",
       "          - esa\n",
       "          license: proprietary\n",
       "          links:\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "            rel: self\n",
       "          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n",
       "            rel: license\n",
       "          - href: https://github.com/stac-utils/stac-sentinel\n",
       "            rel: about\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: parent\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: root\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n",
       "            rel: items\n",
       "          providers:\n",
       "          - name: ESA\n",
       "            roles:\n",
       "            - producer\n",
       "            url: https://earth.esa.int/web/guest/home\n",
       "          - name: Sinergise\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://registry.opendata.aws/sentinel-2/\n",
       "          - name: AWS\n",
       "            roles:\n",
       "            - host\n",
       "            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n",
       "          - name: Element 84\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://element84.com\n",
       "          stac_extensions:\n",
       "          - item-assets\n",
       "          stac_version: 1.0.0-beta.2\n",
       "          summaries:\n",
       "            constellation:\n",
       "            - sentinel-2\n",
       "            gsd:\n",
       "            - 10\n",
       "            instruments:\n",
       "            - msi\n",
       "            platform:\n",
       "            - sentinel-2a\n",
       "            - sentinel-2b\n",
       "            view:off_nadir:\n",
       "            - 0\n",
       "          title: Sentinel 2 L2A COGs\n",
       "        filename: null\n",
       "      _data:\n",
       "        assets:\n",
       "          AOT:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/AOT.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 699960\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6300040\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Aerosol Optical Thickness (AOT)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B01:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.4439\n",
       "              common_name: coastal\n",
       "              full_width_half_max: 0.027\n",
       "              name: B01\n",
       "            gsd: 60\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B01.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 699960\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6300040\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 1 (coastal)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B02:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.4966\n",
       "              common_name: blue\n",
       "              full_width_half_max: 0.098\n",
       "              name: B02\n",
       "            gsd: 10\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 10980\n",
       "            - 10980\n",
       "            proj:transform:\n",
       "            - 10\n",
       "            - 0\n",
       "            - 699960\n",
       "            - 0\n",
       "            - -10\n",
       "            - 6300040\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Band 2 (blue)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B03:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.56\n",
       "              common_name: green\n",
       "              full_width_half_max: 0.045\n",
       "              name: B03\n",
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       "          rel: via-cirrus\n",
       "          title: sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: parent\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: collection\n",
       "        - href: https://earth-search.aws.element84.com/v0/\n",
       "          rel: root\n",
       "        properties:\n",
       "          constellation: sentinel-2\n",
       "          created: '2020-12-31T04:58:49.199Z'\n",
       "          datetime: '2020-12-31T01:16:33Z'\n",
       "          eo:cloud_cover: 95.64\n",
       "          gsd: 10\n",
       "          instruments:\n",
       "          - msi\n",
       "          platform: sentinel-2b\n",
       "          proj:epsg: 32752\n",
       "          sentinel:data_coverage: 0.97\n",
       "          sentinel:grid_square: GH\n",
       "          sentinel:latitude_band: H\n",
       "          sentinel:product_id: S2B_MSIL2A_20201231T010729_N0214_R045_T52HGH_20201231T024641\n",
       "          sentinel:sequence: '0'\n",
       "          sentinel:utm_zone: 52\n",
       "          sentinel:valid_cloud_cover: true\n",
       "          updated: '2020-12-31T04:58:49.199Z'\n",
       "          view:off_nadir: 0\n",
       "        stac_extensions:\n",
       "        - eo\n",
       "        - view\n",
       "        - proj\n",
       "        stac_version: 1.0.0-beta.2\n",
       "        type: Feature\n",
       "      filename: null\n",
       "  description: ''\n",
       "  driver: intake_stac.catalog.StacItem\n",
       "  metadata:\n",
       "    catalog_dir: ''\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "S2B_52HGH_20201231_0_L2A"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "junk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "thumbnail\n",
      "overview\n",
      "info\n",
      "metadata\n",
      "visual\n",
      "B01\n",
      "B02\n",
      "B03\n",
      "B04\n",
      "B05\n",
      "B06\n",
      "B07\n",
      "B08\n",
      "B8A\n",
      "B09\n",
      "B11\n",
      "B12\n",
      "AOT\n",
      "WVP\n",
      "SCL\n"
     ]
    }
   ],
   "source": [
    "for j in junk:\n",
    "    print(j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": "S2B_52HGH_20201231_0_L2A:\n  args:\n    stac_obj: !!python/object:satstac.item.Item\n      _assets_by_common_name: null\n      _collection: !!python/object:satstac.collection.Collection\n        _data:\n          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n          extent:\n            spatial:\n              bbox:\n              - - -180\n                - -90\n                - 180\n                - 90\n            temporal:\n              interval:\n              - - '2015-06-27T10:25:31.456000Z'\n                - null\n          id: sentinel-s2-l2a-cogs\n          item_assets:\n            AOT:\n              roles:\n              - data\n              title: Aerosol Optical Thickness (AOT)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B01:\n              eo:bands:\n              - center_wavelength: 0.4439\n                common_name: coastal\n                full_width_half_max: 0.027\n                name: B01\n              gsd: 60\n              roles:\n              - data\n              title: Band 1 (coastal)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B02:\n              eo:bands:\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - data\n              title: Band 2 (blue)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B03:\n              eo:bands:\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              gsd: 10\n              roles:\n              - data\n              title: Band 3 (green)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B04:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              gsd: 10\n              roles:\n              - data\n              title: Band 4 (red)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B05:\n              eo:bands:\n              - center_wavelength: 0.7039\n                full_width_half_max: 0.019\n                name: B05\n              gsd: 20\n              roles:\n              - data\n              title: Band 5\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B06:\n              eo:bands:\n              - center_wavelength: 0.7402\n                full_width_half_max: 0.018\n                name: B06\n              gsd: 20\n              roles:\n              - data\n              title: Band 6\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B07:\n              eo:bands:\n              - center_wavelength: 0.7825\n                full_width_half_max: 0.028\n                name: B07\n              gsd: 20\n              roles:\n              - data\n              title: Band 7\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B08:\n              eo:bands:\n              - center_wavelength: 0.8351\n                common_name: nir\n                full_width_half_max: 0.145\n                name: B08\n              gsd: 10\n              roles:\n              - data\n              title: Band 8 (nir)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B09:\n              eo:bands:\n              - center_wavelength: 0.945\n                full_width_half_max: 0.026\n                name: B09\n              gsd: 60\n              roles:\n              - data\n              title: Band 9\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B11:\n              eo:bands:\n              - center_wavelength: 1.6137\n                common_name: swir16\n                full_width_half_max: 0.143\n                name: B11\n              gsd: 20\n              roles:\n              - data\n              title: Band 11 (swir16)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B12:\n              eo:bands:\n              - center_wavelength: 2.22024\n                common_name: swir22\n                full_width_half_max: 0.242\n                name: B12\n              gsd: 20\n              roles:\n              - data\n              title: Band 12 (swir22)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            B8A:\n              eo:bands:\n              - center_wavelength: 0.8648\n                full_width_half_max: 0.033\n                name: B8A\n              gsd: 20\n              roles:\n              - data\n              title: Band 8A\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            SCL:\n              roles:\n              - data\n              title: Scene Classification Map (SCL)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            WVP:\n              roles:\n              - data\n              title: Water Vapour (WVP)\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            info:\n              roles:\n              - metadata\n              title: Original JSON metadata\n              type: application/json\n            metadata:\n              roles:\n              - metadata\n              title: Original XML metadata\n              type: application/xml\n            overview:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n            thumbnail:\n              roles:\n              - thumbnail\n              title: Thumbnail\n              type: image/png\n            visual:\n              eo:bands:\n              - center_wavelength: 0.6645\n                common_name: red\n                full_width_half_max: 0.038\n                name: B04\n              - center_wavelength: 0.56\n                common_name: green\n                full_width_half_max: 0.045\n                name: B03\n              - center_wavelength: 0.4966\n                common_name: blue\n                full_width_half_max: 0.098\n                name: B02\n              gsd: 10\n              roles:\n              - overview\n              title: True color image\n              type: image/tiff; application=geotiff; profile=cloud-optimized\n          keywords:\n          - sentinel\n          - earth observation\n          - esa\n          license: proprietary\n          links:\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n            rel: self\n          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n            rel: license\n          - href: https://github.com/stac-utils/stac-sentinel\n            rel: about\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: parent\n          - href: https://earth-search.aws.element84.com/v0/\n            rel: root\n          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n            rel: items\n          providers:\n          - name: ESA\n            roles:\n            - producer\n            url: https://earth.esa.int/web/guest/home\n          - name: Sinergise\n            roles:\n            - processor\n            url: https://registry.opendata.aws/sentinel-2/\n          - name: AWS\n            roles:\n            - host\n            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n          - name: Element 84\n            roles:\n            - processor\n            url: https://element84.com\n          stac_extensions:\n          - item-assets\n          stac_version: 1.0.0-beta.2\n          summaries:\n            constellation:\n            - sentinel-2\n            gsd:\n            - 10\n            instruments:\n            - msi\n            platform:\n            - sentinel-2a\n            - sentinel-2b\n            view:off_nadir:\n            - 0\n          title: Sentinel 2 L2A COGs\n        filename: null\n      _data:\n        assets:\n          AOT:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/AOT.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Aerosol Optical Thickness (AOT)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B01:\n            eo:bands:\n            - center_wavelength: 0.4439\n              common_name: coastal\n              full_width_half_max: 0.027\n              name: B01\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B01.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 1 (coastal)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B02:\n            eo:bands:\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 2 (blue)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B03:\n            eo:bands:\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 3 (green)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B04:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B04.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 4 (red)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B05:\n            eo:bands:\n            - center_wavelength: 0.7039\n              full_width_half_max: 0.019\n              name: B05\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B05.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 5\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B06:\n            eo:bands:\n            - center_wavelength: 0.7402\n              full_width_half_max: 0.018\n              name: B06\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B06.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 6\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B07:\n            eo:bands:\n            - center_wavelength: 0.7825\n              full_width_half_max: 0.028\n              name: B07\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B07.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 7\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B08:\n            eo:bands:\n            - center_wavelength: 0.8351\n              common_name: nir\n              full_width_half_max: 0.145\n              name: B08\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B08.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8 (nir)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B09:\n            eo:bands:\n            - center_wavelength: 0.945\n              full_width_half_max: 0.026\n              name: B09\n            gsd: 60\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B09.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 1830\n            - 1830\n            proj:transform:\n            - 60\n            - 0\n            - 699960\n            - 0\n            - -60\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 9\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B11:\n            eo:bands:\n            - center_wavelength: 1.6137\n              common_name: swir16\n              full_width_half_max: 0.143\n              name: B11\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 11 (swir16)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B12:\n            eo:bands:\n            - center_wavelength: 2.22024\n              common_name: swir22\n              full_width_half_max: 0.242\n              name: B12\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B12.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 12 (swir22)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          B8A:\n            eo:bands:\n            - center_wavelength: 0.8648\n              full_width_half_max: 0.033\n              name: B8A\n            gsd: 20\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B8A.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Band 8A\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          SCL:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/SCL.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 5490\n            - 5490\n            proj:transform:\n            - 20\n            - 0\n            - 699960\n            - 0\n            - -20\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Scene Classification Map (SCL)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          WVP:\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/WVP.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - data\n            title: Water Vapour (WVP)\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          info:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/52/H/GH/2020/12/31/0/tileInfo.json\n            roles:\n            - metadata\n            title: Original JSON metadata\n            type: application/json\n          metadata:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l2a/tiles/52/H/GH/2020/12/31/0/metadata.xml\n            roles:\n            - metadata\n            title: Original XML metadata\n            type: application/xml\n          overview:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/L2A_PVI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 343\n            - 343\n            proj:transform:\n            - 320\n            - 0\n            - 699960\n            - 0\n            - -320\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n          thumbnail:\n            href: https://roda.sentinel-hub.com/sentinel-s2-l1c/tiles/52/H/GH/2020/12/31/0/preview.jpg\n            plots:\n              thumbnail:\n                bands: channel\n                data_aspect: 1\n                flip_yaxis: true\n                kind: rgb\n                x: x\n                xaxis: false\n                y: y\n                yaxis: false\n            roles:\n            - thumbnail\n            title: Thumbnail\n            type: image/png\n          visual:\n            eo:bands:\n            - center_wavelength: 0.6645\n              common_name: red\n              full_width_half_max: 0.038\n              name: B04\n            - center_wavelength: 0.56\n              common_name: green\n              full_width_half_max: 0.045\n              name: B03\n            - center_wavelength: 0.4966\n              common_name: blue\n              full_width_half_max: 0.098\n              name: B02\n            gsd: 10\n            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/TCI.tif\n            plots:\n              geotiff:\n                cmap: viridis\n                data_aspect: 1\n                dynamic: true\n                frame_width: 500\n                kind: image\n                rasterize: true\n                x: x\n                y: y\n            proj:shape:\n            - 10980\n            - 10980\n            proj:transform:\n            - 10\n            - 0\n            - 699960\n            - 0\n            - -10\n            - 6300040\n            - 0\n            - 0\n            - 1\n            roles:\n            - overview\n            title: True color image\n            type: image/tiff; application=geotiff; profile=cloud-optimized\n        bbox:\n        - 131.9984760650785\n        - -33.4646861649747\n        - 132.3327571457415\n        - -33.39432388162574\n        collection: sentinel-s2-l2a-cogs\n        geometry:\n          coordinates:\n          - - - 132.3327571457415\n              - -33.4646861649747\n            - - 131.9984760650785\n              - -33.402787873790494\n            - - 132.33006605863437\n              - -33.39432388162574\n            - - 132.3327571457415\n              - -33.4646861649747\n          type: Polygon\n        id: S2B_52HGH_20201231_0_L2A\n        links:\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2B_52HGH_20201231_0_L2A\n          rel: self\n        - href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n          rel: canonical\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n          rel: via-cirrus\n          title: sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n        - href: https://cirrus-v0-data-1qm7gekzjucbq.s3.us-west-2.amazonaws.com/sentinel-s2-l2a/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n          rel: derived_from\n          title: Source STAC Item\n          type: application/json\n        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n          rel: via-cirrus\n          title: sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: parent\n        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n          rel: collection\n        - href: https://earth-search.aws.element84.com/v0/\n          rel: root\n        properties:\n          constellation: sentinel-2\n          created: '2020-12-31T04:58:49.199Z'\n          datetime: '2020-12-31T01:16:33Z'\n          eo:cloud_cover: 95.64\n          gsd: 10\n          instruments:\n          - msi\n          platform: sentinel-2b\n          proj:epsg: 32752\n          sentinel:data_coverage: 0.97\n          sentinel:grid_square: GH\n          sentinel:latitude_band: H\n          sentinel:product_id: S2B_MSIL2A_20201231T010729_N0214_R045_T52HGH_20201231T024641\n          sentinel:sequence: '0'\n          sentinel:utm_zone: 52\n          sentinel:valid_cloud_cover: true\n          updated: '2020-12-31T04:58:49.199Z'\n          view:off_nadir: 0\n        stac_extensions:\n        - eo\n        - view\n        - proj\n        stac_version: 1.0.0-beta.2\n        type: Feature\n      filename: null\n  description: ''\n  driver: intake_stac.catalog.StacItem\n  metadata:\n    catalog_dir: ''\n",
      "text/plain": [
       "S2B_52HGH_20201231_0_L2A:\n",
       "  args:\n",
       "    stac_obj: !!python/object:satstac.item.Item\n",
       "      _assets_by_common_name: null\n",
       "      _collection: !!python/object:satstac.collection.Collection\n",
       "        _data:\n",
       "          description: Sentinel-2a and Sentinel-2b imagery, processed to Level 2A\n",
       "            (Surface Reflectance) and converted to Cloud-Optimized GeoTIFFs\n",
       "          extent:\n",
       "            spatial:\n",
       "              bbox:\n",
       "              - - -180\n",
       "                - -90\n",
       "                - 180\n",
       "                - 90\n",
       "            temporal:\n",
       "              interval:\n",
       "              - - '2015-06-27T10:25:31.456000Z'\n",
       "                - null\n",
       "          id: sentinel-s2-l2a-cogs\n",
       "          item_assets:\n",
       "            AOT:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Aerosol Optical Thickness (AOT)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B01:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4439\n",
       "                common_name: coastal\n",
       "                full_width_half_max: 0.027\n",
       "                name: B01\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 1 (coastal)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B02:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 2 (blue)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B03:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 3 (green)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B04:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 4 (red)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B05:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7039\n",
       "                full_width_half_max: 0.019\n",
       "                name: B05\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 5\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B06:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7402\n",
       "                full_width_half_max: 0.018\n",
       "                name: B06\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 6\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B07:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.7825\n",
       "                full_width_half_max: 0.028\n",
       "                name: B07\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 7\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B08:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8351\n",
       "                common_name: nir\n",
       "                full_width_half_max: 0.145\n",
       "                name: B08\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8 (nir)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B09:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.945\n",
       "                full_width_half_max: 0.026\n",
       "                name: B09\n",
       "              gsd: 60\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 9\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B11:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 1.6137\n",
       "                common_name: swir16\n",
       "                full_width_half_max: 0.143\n",
       "                name: B11\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 11 (swir16)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B12:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 2.22024\n",
       "                common_name: swir22\n",
       "                full_width_half_max: 0.242\n",
       "                name: B12\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 12 (swir22)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            B8A:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.8648\n",
       "                full_width_half_max: 0.033\n",
       "                name: B8A\n",
       "              gsd: 20\n",
       "              roles:\n",
       "              - data\n",
       "              title: Band 8A\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            SCL:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Scene Classification Map (SCL)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            WVP:\n",
       "              roles:\n",
       "              - data\n",
       "              title: Water Vapour (WVP)\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            info:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original JSON metadata\n",
       "              type: application/json\n",
       "            metadata:\n",
       "              roles:\n",
       "              - metadata\n",
       "              title: Original XML metadata\n",
       "              type: application/xml\n",
       "            overview:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "            thumbnail:\n",
       "              roles:\n",
       "              - thumbnail\n",
       "              title: Thumbnail\n",
       "              type: image/png\n",
       "            visual:\n",
       "              eo:bands:\n",
       "              - center_wavelength: 0.6645\n",
       "                common_name: red\n",
       "                full_width_half_max: 0.038\n",
       "                name: B04\n",
       "              - center_wavelength: 0.56\n",
       "                common_name: green\n",
       "                full_width_half_max: 0.045\n",
       "                name: B03\n",
       "              - center_wavelength: 0.4966\n",
       "                common_name: blue\n",
       "                full_width_half_max: 0.098\n",
       "                name: B02\n",
       "              gsd: 10\n",
       "              roles:\n",
       "              - overview\n",
       "              title: True color image\n",
       "              type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          keywords:\n",
       "          - sentinel\n",
       "          - earth observation\n",
       "          - esa\n",
       "          license: proprietary\n",
       "          links:\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "            rel: self\n",
       "          - href: https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice\n",
       "            rel: license\n",
       "          - href: https://github.com/stac-utils/stac-sentinel\n",
       "            rel: about\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: parent\n",
       "          - href: https://earth-search.aws.element84.com/v0/\n",
       "            rel: root\n",
       "          - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items\n",
       "            rel: items\n",
       "          providers:\n",
       "          - name: ESA\n",
       "            roles:\n",
       "            - producer\n",
       "            url: https://earth.esa.int/web/guest/home\n",
       "          - name: Sinergise\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://registry.opendata.aws/sentinel-2/\n",
       "          - name: AWS\n",
       "            roles:\n",
       "            - host\n",
       "            url: http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/\n",
       "          - name: Element 84\n",
       "            roles:\n",
       "            - processor\n",
       "            url: https://element84.com\n",
       "          stac_extensions:\n",
       "          - item-assets\n",
       "          stac_version: 1.0.0-beta.2\n",
       "          summaries:\n",
       "            constellation:\n",
       "            - sentinel-2\n",
       "            gsd:\n",
       "            - 10\n",
       "            instruments:\n",
       "            - msi\n",
       "            platform:\n",
       "            - sentinel-2a\n",
       "            - sentinel-2b\n",
       "            view:off_nadir:\n",
       "            - 0\n",
       "          title: Sentinel 2 L2A COGs\n",
       "        filename: null\n",
       "      _data:\n",
       "        assets:\n",
       "          AOT:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/AOT.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 699960\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6300040\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
       "            roles:\n",
       "            - data\n",
       "            title: Aerosol Optical Thickness (AOT)\n",
       "            type: image/tiff; application=geotiff; profile=cloud-optimized\n",
       "          B01:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.4439\n",
       "              common_name: coastal\n",
       "              full_width_half_max: 0.027\n",
       "              name: B01\n",
       "            gsd: 60\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B01.tif\n",
       "            plots:\n",
       "              geotiff:\n",
       "                cmap: viridis\n",
       "                data_aspect: 1\n",
       "                dynamic: true\n",
       "                frame_width: 500\n",
       "                kind: image\n",
       "                rasterize: true\n",
       "                x: x\n",
       "                y: y\n",
       "            proj:shape:\n",
       "            - 1830\n",
       "            - 1830\n",
       "            proj:transform:\n",
       "            - 60\n",
       "            - 0\n",
       "            - 699960\n",
       "            - 0\n",
       "            - -60\n",
       "            - 6300040\n",
       "            - 0\n",
       "            - 0\n",
       "            - 1\n",
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       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B02.tif\n",
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       "            eo:bands:\n",
       "            - center_wavelength: 0.56\n",
       "              common_name: green\n",
       "              full_width_half_max: 0.045\n",
       "              name: B03\n",
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       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B03.tif\n",
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       "            eo:bands:\n",
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       "              common_name: red\n",
       "              full_width_half_max: 0.038\n",
       "              name: B04\n",
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       "            eo:bands:\n",
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       "            eo:bands:\n",
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       "              full_width_half_max: 0.018\n",
       "              name: B06\n",
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       "            plots:\n",
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       "            eo:bands:\n",
       "            - center_wavelength: 0.7825\n",
       "              full_width_half_max: 0.028\n",
       "              name: B07\n",
       "            gsd: 20\n",
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       "            plots:\n",
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       "          B08:\n",
       "            eo:bands:\n",
       "            - center_wavelength: 0.8351\n",
       "              common_name: nir\n",
       "              full_width_half_max: 0.145\n",
       "              name: B08\n",
       "            gsd: 10\n",
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       "            plots:\n",
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       "            eo:bands:\n",
       "            - center_wavelength: 0.945\n",
       "              full_width_half_max: 0.026\n",
       "              name: B09\n",
       "            gsd: 60\n",
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       "            plots:\n",
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       "            eo:bands:\n",
       "            - center_wavelength: 1.6137\n",
       "              common_name: swir16\n",
       "              full_width_half_max: 0.143\n",
       "              name: B11\n",
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       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/B11.tif\n",
       "            plots:\n",
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       "            - data\n",
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       "            eo:bands:\n",
       "            - center_wavelength: 2.22024\n",
       "              common_name: swir22\n",
       "              full_width_half_max: 0.242\n",
       "              name: B12\n",
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       "            - data\n",
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       "            eo:bands:\n",
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       "              full_width_half_max: 0.033\n",
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       "            - data\n",
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       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/SCL.tif\n",
       "            plots:\n",
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       "            - data\n",
       "            title: Scene Classification Map (SCL)\n",
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       "          WVP:\n",
       "            href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/WVP.tif\n",
       "            plots:\n",
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       "            - metadata\n",
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       "          type: Polygon\n",
       "        id: S2B_52HGH_20201231_0_L2A\n",
       "        links:\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2B_52HGH_20201231_0_L2A\n",
       "          rel: self\n",
       "        - href: https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n",
       "          rel: canonical\n",
       "          type: application/json\n",
       "        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n",
       "          rel: via-cirrus\n",
       "          title: sentinel-s2-l2a-aws/workflow-publish-sentinel/tiles-52-H-GH-2020-12-31-0\n",
       "        - href: https://cirrus-v0-data-1qm7gekzjucbq.s3.us-west-2.amazonaws.com/sentinel-s2-l2a/52/H/GH/2020/12/S2B_52HGH_20201231_0_L2A/S2B_52HGH_20201231_0_L2A.json\n",
       "          rel: derived_from\n",
       "          title: Source STAC Item\n",
       "          type: application/json\n",
       "        - href: https://cirrus-earth-search.aws.element84.com/v0/catid/sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n",
       "          rel: via-cirrus\n",
       "          title: sentinel-s2-l2a/workflow-cog-archive/S2B_52HGH_20201231_0_L2A\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: parent\n",
       "        - href: https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs\n",
       "          rel: collection\n",
       "        - href: https://earth-search.aws.element84.com/v0/\n",
       "          rel: root\n",
       "        properties:\n",
       "          constellation: sentinel-2\n",
       "          created: '2020-12-31T04:58:49.199Z'\n",
       "          datetime: '2020-12-31T01:16:33Z'\n",
       "          eo:cloud_cover: 95.64\n",
       "          gsd: 10\n",
       "          instruments:\n",
       "          - msi\n",
       "          platform: sentinel-2b\n",
       "          proj:epsg: 32752\n",
       "          sentinel:data_coverage: 0.97\n",
       "          sentinel:grid_square: GH\n",
       "          sentinel:latitude_band: H\n",
       "          sentinel:product_id: S2B_MSIL2A_20201231T010729_N0214_R045_T52HGH_20201231T024641\n",
       "          sentinel:sequence: '0'\n",
       "          sentinel:utm_zone: 52\n",
       "          sentinel:valid_cloud_cover: true\n",
       "          updated: '2020-12-31T04:58:49.199Z'\n",
       "          view:off_nadir: 0\n",
       "        stac_extensions:\n",
       "        - eo\n",
       "        - view\n",
       "        - proj\n",
       "        stac_version: 1.0.0-beta.2\n",
       "        type: Feature\n",
       "      filename: null\n",
       "  description: ''\n",
       "  driver: intake_stac.catalog.StacItem\n",
       "  metadata:\n",
       "    catalog_dir: ''\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "S2B_52HGH_20201231_0_L2A"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "junk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2020-12-31T01:16:33Z'"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gf2.iloc[0]['datetime']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[                                        ] | 0% Completed |  0.0s<Intake catalog: S2A_54HTG_20180125_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200829_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20191216_0_L2A><Intake catalog: S2A_54HTG_20180323_0_L2A>\n",
      "\n",
      "[                                        ] | 0% Completed |  0.2s\n",
      "<Intake catalog: S2A_54HTG_20190914_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190301_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190226_0_L2A><Intake catalog: S2A_54HTG_20170226_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190517_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20200112_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180909_0_L2A>\n",
      "[                                        ] | 0% Completed |  2.0s<Intake catalog: S2A_54HTG_20171017_0_L2A>\n",
      "[#                                       ] | 2% Completed |  3.7s<Intake catalog: S2A_54HTG_20180525_0_L2A>\n",
      "[##                                      ] | 5% Completed |  6.8s<Intake catalog: S2A_54HTG_20181118_0_L2A>\n",
      "[###                                     ] | 7% Completed | 18.3s<Intake catalog: S2A_54HTG_20191024_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190917_0_L2A><Intake catalog: S2A_54HTG_20201117_0_L2A><Intake catalog: S2A_54HTG_20190216_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20200610_0_L2A>\n",
      "\n",
      "[##########                              ] | 25% Completed | 18.4s<Intake catalog: S2A_54HTG_20171226_0_L2A><Intake catalog: S2A_54HTG_20181231_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20201220_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190709_0_L2A>\n",
      "[############                            ] | 30% Completed | 24.5s<Intake catalog: S2A_54HTG_20170619_0_L2A>\n",
      "[#############                           ] | 32% Completed | 27.4s<Intake catalog: S2A_54HTG_20200204_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190507_1_L2A>\n",
      "[###############                         ] | 37% Completed | 33.3s<Intake catalog: S2A_54HTG_20200723_0_L2A>\n",
      "[################                        ] | 40% Completed | 34.7s<Intake catalog: S2A_54HTG_20170308_0_L2A>\n",
      "[#################                       ] | 42% Completed | 41.7s<Intake catalog: S2A_54HTG_20201130_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20171226_1_L2A>\n",
      "[###################                     ] | 47% Completed | 42.8s<Intake catalog: S2A_54HTG_20180105_0_L2A>\n",
      "[#####################                   ] | 52% Completed | 42.9s<Intake catalog: S2A_54HTG_20180422_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20181029_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200102_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200819_0_L2A>\n",
      "[########################                ] | 60% Completed | 47.6s<Intake catalog: S2A_54HTG_20200414_0_L2A>\n",
      "[#########################               ] | 62% Completed | 50.8s<Intake catalog: S2A_54HTG_20170127_0_L2A>\n",
      "[##########################              ] | 65% Completed | 55.3s<Intake catalog: S2A_54HTG_20190120_0_L2A>\n",
      "[###########################             ] | 67% Completed | 56.4s<Intake catalog: S2A_54HTG_20180714_0_L2A>\n",
      "[########################################] | 100% Completed |  1min 11.5s\n",
      "Wall time: 1min 11s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# First let's construct a large dataset with all the scenes in our search so that we\n",
    "# have a time dimension\n",
    "# Loop through geopandas geodataframe (each row is a STAC ITEM)\n",
    "import dask\n",
    "\n",
    "@dask.delayed\n",
    "def stacitem_to_dataset3(item, datetimeuse):\n",
    "    print(item)\n",
    "    #stacked = catalog[item.id].stack_bands(bands)\n",
    "    stacked = item.stack_bands(['B02','B03','B04','B08'])\n",
    "    #stacked = item.stack_bands(['B02'])\n",
    "    da4 = stacked(chunks=dict(band=1, x=2048, y=2048)).to_dask()\n",
    "    #da = stacked(chunks=dict(band=1, x=5120, y=5120)).to_dask()\n",
    "    #da['band'] = bands # use common names\n",
    "    da4['band'] = ['blue','green','red','nir'] # use common names\n",
    "    #da['band'] = ['blue'] # use common names\n",
    "    da4 = da4.expand_dims(time=[pd.to_datetime(datetimeuse)])\n",
    "    #da = stacked(chunks=dict(band=1, x=5120, y=5120, time=-1)).to_dask()\n",
    "    ds4 = da4.to_dataset(dim='band')\n",
    "    return ds4\n",
    "\n",
    "lazy_datasets4 = []\n",
    "#for i,item in gf.iterrows():\n",
    "#for i,item in gf.head(1).iterrows():   \n",
    "\n",
    "for index, x in enumerate(items_s2):\n",
    "    #need to make items_s2\n",
    "    #need to get datetime from the dataframe gf2 as well\n",
    "    datetimeuse = gf2function.iloc[index]['datetime']\n",
    "    itemx = items_s2[x]\n",
    "    ds4 = stacitem_to_dataset3(itemx, datetimeuse)\n",
    "    lazy_datasets4.append(ds4)\n",
    "\n",
    "from dask.diagnostics import ProgressBar\n",
    "with ProgressBar():\n",
    "    #out = dask.compute(*lazy_datasets)\n",
    "    \n",
    "#datasets = dask.compute(*lazy_datasets).mean(dim='time')\n",
    "    datasets4 = dask.compute(*lazy_datasets4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-12-20T00:56:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-11-30T00:56:45+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-11-17T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-08-29T00:46:54+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-08-19T00:46:54+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-07-23T00:56:50+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-06-10T00:46:55+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-04-14T00:56:44+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-02-04T00:56:36+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-01-12T00:46:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2020-01-02T00:46:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-12-16T00:56:39+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-10-24T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-09-17T00:56:44+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-09-14T00:46:47+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-07-09T00:56:50+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-05-17T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-05-07T00:46:52+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-03-01T01:01:28+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-02-26T00:57:15+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-02-16T00:46:45+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2019-01-20T00:56:41+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-12-31T00:56:38+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-11-18T00:46:42+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-10-29T00:37:01+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-09-09T00:37:02+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-07-14T00:47:07+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-05-25T00:47:08+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-04-22T00:37:06+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-03-23T00:37:02+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-01-25T00:56:32+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2018-01-05T00:56:30+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-12-26T00:53:22+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-12-26T00:53:22+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-10-17T00:56:36+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-06-19T00:56:37+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-03-18T00:45:45+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-03-08T00:46:23+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
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       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
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       " Data variables:\n",
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       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE,\n",
       " <xarray.Dataset>\n",
       " Dimensions:  (time: 1, x: 10980, y: 10980)\n",
       " Coordinates:\n",
       "   * time     (time) object 2017-01-27T00:42:43+00:00\n",
       "   * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "   * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       " Data variables:\n",
       "     blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "     nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       " Attributes:\n",
       "     transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "     crs:                 +init=epsg:32754\n",
       "     res:                 (10.0, 10.0)\n",
       "     is_tiled:            1\n",
       "     nodatavals:          (0.0,)\n",
       "     scales:              (1.0,)\n",
       "     offsets:             (0.0,)\n",
       "     AREA_OR_POINT:       Area\n",
       "     OVR_RESAMPLING_ALG:  AVERAGE)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datasets4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "DS4 = xarray.concat(datasets4, dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 40, x: 10980, y: 10980)\n",
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       "Data variables:\n",
       "    blue     (time, y, x) uint16 dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
       "    green    (time, y, x) uint16 dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
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       "    nir      (time, y, x) uint16 dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7468a92a-e944-48ce-82e0-5a9fae80c905' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7468a92a-e944-48ce-82e0-5a9fae80c905' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 40</li><li><span class='xr-has-index'>x</span>: 10980</li><li><span class='xr-has-index'>y</span>: 10980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-991e501e-40f2-412e-a375-1ebcc93cb4c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-991e501e-40f2-412e-a375-1ebcc93cb4c6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1608425803000000000 ... 14854777...</div><input id='attrs-95a7c342-62d7-437f-83d0-5142b02a86cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95a7c342-62d7-437f-83d0-5142b02a86cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92408f9b-a087-4237-874e-dac7598b9337' class='xr-var-data-in' type='checkbox'><label for='data-92408f9b-a087-4237-874e-dac7598b9337' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1608425803000000000, 1606697805000000000, 1605574012000000000,\n",
       "       1598662014000000000, 1597798014000000000, 1595465810000000000,\n",
       "       1591750015000000000, 1586825804000000000, 1580777796000000000,\n",
       "       1578790003000000000, 1577926003000000000, 1576457799000000000,\n",
       "       1571878012000000000, 1568681804000000000, 1568422007000000000,\n",
       "       1562633810000000000, 1558054012000000000, 1557190012000000000,\n",
       "       1551402088000000000, 1551142635000000000, 1550278005000000000,\n",
       "       1547945801000000000, 1546217798000000000, 1542502002000000000,\n",
       "       1540773421000000000, 1536453422000000000, 1531529227000000000,\n",
       "       1527209228000000000, 1524357426000000000, 1521765422000000000,\n",
       "       1516841792000000000, 1515113790000000000, 1514249602000000000,\n",
       "       1514249602000000000, 1508201796000000000, 1497833797000000000,\n",
       "       1489797945000000000, 1488933983000000000, 1488069947000000000,\n",
       "       1485477763000000000], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-500135e4-c632-4b93-941c-515d29c3bfc0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-500135e4-c632-4b93-941c-515d29c3bfc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea99352b-111c-4160-93c8-f2510ca5c771' class='xr-var-data-in' type='checkbox'><label for='data-ea99352b-111c-4160-93c8-f2510ca5c771' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200015., 6200005., 6199995., ..., 6090245., 6090235., 6090225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-3cedd443-77b6-4133-aaa2-163716a2798f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3cedd443-77b6-4133-aaa2-163716a2798f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cf3daad-5643-429d-bc6d-1222598b376d' class='xr-var-data-in' type='checkbox'><label for='data-0cf3daad-5643-429d-bc6d-1222598b376d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199985., 199995., 200005., ..., 309755., 309765., 309775.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95874e71-06b8-4f81-8281-614b6db57236' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95874e71-06b8-4f81-8281-614b6db57236' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>blue</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-4f2d2284-78a1-4628-a62b-9efd2da160dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f2d2284-78a1-4628-a62b-9efd2da160dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f96ed82f-b499-4be7-8302-0fd4a618fdde' class='xr-var-data-in' type='checkbox'><label for='data-f96ed82f-b499-4be7-8302-0fd4a618fdde' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "  <text x=\"164.948598\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,74.948598)\">10980</text>\n",
       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">40</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c36c2b65-2a17-4e75-8c4b-59902d4756ba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c36c2b65-2a17-4e75-8c4b-59902d4756ba' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32754</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>1</dd><dt><span>nodatavals :</span></dt><dd>(0.0,)</dd><dt><span>scales :</span></dt><dd>(1.0,)</dd><dt><span>offsets :</span></dt><dd>(0.0,)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>OVR_RESAMPLING_ALG :</span></dt><dd>AVERAGE</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 40, x: 10980, y: 10980)\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.098e+05 3.098e+05 3.098e+05\n",
       "Data variables:\n",
       "    blue     (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    green    (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    red      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    nir      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "Attributes:\n",
       "    transform:           (10.0, 0.0, 199980.0, 0.0, -10.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (10.0, 10.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DS4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "red_median.rio.write_crs('EPSG:32754', inplace=True)\n",
    "red_medianNP.rio.to_raster(\"C:/users/rscott/Downloads/red_medianOZ.tif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def median4(sentinelDS):\n",
    "    blue_median = median(sentinelDS.blue, dim='time')\n",
    "    green_median = median(sentinelDS.green, dim='time')\n",
    "    red_median = median(sentinelDS.red, dim='time')\n",
    "    nir_median = median(sentinelDS.nir, dim='time')\n",
    "    \n",
    "    return (blue_median, green_median, red_median, nir_median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed |  1hr 30min  9.0s\n",
      "[########################################] | 100% Completed |  1hr 27min 52.5s\n",
      "[########################################] | 100% Completed |  1hr 39min  2.3s\n",
      "[########################################] | 100% Completed |  1hr 21min 50.3s\n"
     ]
    }
   ],
   "source": [
    "blue_median, green_median, red_median, nir_median = median4(DS4)\n",
    "with ProgressBar():\n",
    "    blue_medianNP = blue_median.compute()\n",
    "    green_medianNP = green_median.compute()\n",
    "    red_medianNP = red_median.compute()\n",
    "    nir_medianNP = nir_median.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "ename": "CRSError",
     "evalue": "Invalid projection: ESPG:32754: (Internal Proj Error: proj_create: crs not found)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mCRSError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-56-98f3b65eccdd>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrasterNP\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrasters\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[0mrasterNP\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite_crs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'ESPG:32754'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      7\u001b[0m     \u001b[1;31m#rasterNP.rio.to_raster(r\"H:\\Copa de Cobre\" + \"\\\\\" + raster_files[index])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\rioxarray\\rioxarray.py\u001b[0m in \u001b[0;36mwrite_crs\u001b[1;34m(self, input_crs, grid_mapping_name, inplace)\u001b[0m\n\u001b[0;32m    461\u001b[0m         \"\"\"\n\u001b[0;32m    462\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0minput_crs\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 463\u001b[1;33m             \u001b[0mdata_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_crs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_crs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    464\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    465\u001b[0m             \u001b[0mdata_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_obj\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\rioxarray\\rioxarray.py\u001b[0m in \u001b[0;36mset_crs\u001b[1;34m(self, input_crs, inplace)\u001b[0m\n\u001b[0;32m    377\u001b[0m             \u001b[0mDataset\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mcrs\u001b[0m \u001b[0mattribute\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    378\u001b[0m         \"\"\"\n\u001b[1;32m--> 379\u001b[1;33m         \u001b[0mcrs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mCRS\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfrom_wkt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcrs_to_wkt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_crs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    380\u001b[0m         \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_obj\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    381\u001b[0m         \u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_crs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcrs\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\rioxarray\\crs.py\u001b[0m in \u001b[0;36mcrs_to_wkt\u001b[1;34m(crs_input)\u001b[0m\n\u001b[0;32m     30\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     31\u001b[0m         \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 32\u001b[1;33m     \u001b[0mcrs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mCRS\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfrom_user_input\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcrs_input\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     33\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mLooseVersion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrasterio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__gdal_version__\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0mLooseVersion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"3.0.0\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     34\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mcrs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_wkt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\pyproj\\crs\\crs.py\u001b[0m in \u001b[0;36mfrom_user_input\u001b[1;34m(value, **kwargs)\u001b[0m\n\u001b[0;32m    438\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCRS\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    439\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 440\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mCRS\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    441\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    442\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget_geod\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mOptional\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mGeod\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\pangeo\\lib\\site-packages\\pyproj\\crs\\crs.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, projparams, **kwargs)\u001b[0m\n\u001b[0;32m    294\u001b[0m             \u001b[0mprojstring\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_prepare_from_string\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\" \"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprojstring\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprojkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    295\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 296\u001b[1;33m         \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprojstring\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    297\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    298\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpyproj/_crs.pyx\u001b[0m in \u001b[0;36mpyproj._crs._CRS.__init__\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mCRSError\u001b[0m: Invalid projection: ESPG:32754: (Internal Proj Error: proj_create: crs not found)"
     ]
    }
   ],
   "source": [
    "rasters = [blue_medianNP, green_medianNP, red_medianNP, nir_medianNP]\n",
    "rasters = [green_medianNP, red_medianNP, nir_medianNP]\n",
    "raster_files = ['blue_medianOZ.tif','green_medianOZ.tif','red_medianOZ.tif','nir_medianOZ.tif']\n",
    "\n",
    "for index, rasterNP in enumerate(rasters):\n",
    "    rasterNP.rio.write_crs('ESPG:32754', inplace=True)\n",
    "    #rasterNP.rio.to_raster(r\"H:\\Copa de Cobre\" + \"\\\\\" + raster_files[index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[                                        ] | 0% Completed |  0.0s<Intake catalog: S2A_54HTG_20200204_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190120_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190517_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20191216_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170308_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190709_0_L2A>\n",
      "[                                        ] | 0% Completed |  0.1s<Intake catalog: S2A_54HTG_20190226_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170127_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200112_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170619_0_L2A><Intake catalog: S2A_54HTG_20180323_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200610_0_L2A>\n",
      "\n",
      "[                                        ] | 0% Completed |  1min 34.3s<Intake catalog: S2A_54HTG_20191024_0_L2A>\n",
      "[#                                       ] | 2% Completed |  1min 36.1s<Intake catalog: S2A_54HTG_20201117_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20181118_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20200723_0_L2A><Intake catalog: S2A_54HTG_20190914_0_L2A><Intake catalog: S2A_54HTG_20170226_0_L2A>\n",
      "\n",
      "\n",
      "[######                                  ] | 15% Completed |  1min 38.9s<Intake catalog: S2A_54HTG_20190216_0_L2A>\n",
      "[#######                                 ] | 17% Completed |  1min 42.7s<Intake catalog: S2A_54HTG_20181029_0_L2A>\n",
      "[#########                               ] | 22% Completed |  1min 48.6s<Intake catalog: S2A_54HTG_20200102_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20201220_0_L2A>\n",
      "[##########                              ] | 25% Completed |  1min 49.7s<Intake catalog: S2A_54HTG_20190917_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180909_0_L2A>\n",
      "[############                            ] | 30% Completed |  3min  9.1s<Intake catalog: S2A_54HTG_20190507_1_L2A>\n",
      "[#############                           ] | 32% Completed |  3min 10.5s<Intake catalog: S2A_54HTG_20171017_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20170318_0_L2A>\n",
      "[###############                         ] | 37% Completed |  3min 20.3s<Intake catalog: S2A_54HTG_20201130_0_L2A>\n",
      "[################                        ] | 40% Completed |  3min 24.0s<Intake catalog: S2A_54HTG_20200829_0_L2A>\n",
      "[###################                     ] | 47% Completed |  3min 24.1s<Intake catalog: S2A_54HTG_20171226_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180714_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20180125_0_L2A><Intake catalog: S2A_54HTG_20200414_0_L2A>\n",
      "\n",
      "<Intake catalog: S2A_54HTG_20181231_0_L2A>\n",
      "[#######################                 ] | 57% Completed |  3min 24.3s<Intake catalog: S2A_54HTG_20180525_0_L2A>\n",
      "[#######################                 ] | 57% Completed |  3min 39.6s<Intake catalog: S2A_54HTG_20200819_0_L2A>\n",
      "[########################                ] | 60% Completed |  4min 58.3s<Intake catalog: S2A_54HTG_20180105_0_L2A>\n",
      "[##########################              ] | 65% Completed |  4min 58.4s<Intake catalog: S2A_54HTG_20180422_0_L2A>\n",
      "<Intake catalog: S2A_54HTG_20171226_1_L2A>\n",
      "<Intake catalog: S2A_54HTG_20190301_0_L2A>\n",
      "[########################################] | 100% Completed |  5min 18.7s\n",
      "Wall time: 5min 18s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# First let's construct a large dataset with all the scenes in our search so that we\n",
    "# have a time dimension\n",
    "# Loop through geopandas geodataframe (each row is a STAC ITEM)\n",
    "import dask\n",
    "\n",
    "@dask.delayed\n",
    "def stacitem_to_dataset3(item, datetimeuse):\n",
    "    print(item)\n",
    "    #stacked = catalog[item.id].stack_bands(bands)\n",
    "    stacked = item.stack_bands(['B05','B06','B07','B8A','B11','B12'])\n",
    "    da6 = stacked(chunks=dict(band=1, x=2048, y=2048)).to_dask()\n",
    "    da6['band'] = ['B05','B06','B07','B8A','B11','B12'] # use common names\n",
    "    da6 = da6.expand_dims(time=[pd.to_datetime(datetimeuse)])\n",
    "    ds6 = da6.to_dataset(dim='band')\n",
    "    return ds6\n",
    "\n",
    "lazy_datasets6 = []\n",
    "#for i,item in gf.iterrows():\n",
    "#for i,item in gf.head(1).iterrows():   \n",
    "\n",
    "for index, x in enumerate(items_s2):\n",
    "    #need to make items_s2\n",
    "    #need to get datetime from the dataframe gf2 as well\n",
    "    datetimeuse = gf2function.iloc[index]['datetime']\n",
    "    itemx = items_s2[x]\n",
    "    ds6 = stacitem_to_dataset3(itemx, datetimeuse)\n",
    "    lazy_datasets6.append(ds6)\n",
    "\n",
    "from dask.diagnostics import ProgressBar\n",
    "with ProgressBar():\n",
    "    #out = dask.compute(*lazy_datasets)\n",
    "    \n",
    "#datasets = dask.compute(*lazy_datasets).mean(dim='time')\n",
    "    datasets6 = dask.compute(*lazy_datasets6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "def median6(sentinelDS):\n",
    "    b05_median = median(sentinelDS.B05, dim='time')\n",
    "    b06_median = median(sentinelDS.B06, dim='time')\n",
    "    b07_median = median(sentinelDS.B07, dim='time')\n",
    "    b08a_median = median(sentinelDS.B8A, dim='time')\n",
    "    b11_median = median(sentinelDS.B11, dim='time')\n",
    "    b12_median = median(sentinelDS.B12, dim='time')\n",
    "    \n",
    "    return (b05_median, b06_median, b07_median, b08a_median, b11_median, b12_median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "DS6 = xarray.concat(datasets6, dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
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       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3586109-d3f8-4732-9640-29c922b465ac' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f3586109-d3f8-4732-9640-29c922b465ac' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 40</li><li><span class='xr-has-index'>x</span>: 5490</li><li><span class='xr-has-index'>y</span>: 5490</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-90daf10f-0870-4018-be92-5e18b72a08e4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-90daf10f-0870-4018-be92-5e18b72a08e4' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1608425803000000000 ... 14854777...</div><input id='attrs-45f7f3bd-4810-44fa-a473-51b5db1a1249' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45f7f3bd-4810-44fa-a473-51b5db1a1249' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cc89880-d14c-4d39-b501-984a87a43215' class='xr-var-data-in' type='checkbox'><label for='data-1cc89880-d14c-4d39-b501-984a87a43215' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1608425803000000000, 1606697805000000000, 1605574012000000000,\n",
       "       1598662014000000000, 1597798014000000000, 1595465810000000000,\n",
       "       1591750015000000000, 1586825804000000000, 1580777796000000000,\n",
       "       1578790003000000000, 1577926003000000000, 1576457799000000000,\n",
       "       1571878012000000000, 1568681804000000000, 1568422007000000000,\n",
       "       1562633810000000000, 1558054012000000000, 1557190012000000000,\n",
       "       1551402088000000000, 1551142635000000000, 1550278005000000000,\n",
       "       1547945801000000000, 1546217798000000000, 1542502002000000000,\n",
       "       1540773421000000000, 1536453422000000000, 1531529227000000000,\n",
       "       1527209228000000000, 1524357426000000000, 1521765422000000000,\n",
       "       1516841792000000000, 1515113790000000000, 1514249602000000000,\n",
       "       1514249602000000000, 1508201796000000000, 1497833797000000000,\n",
       "       1489797945000000000, 1488933983000000000, 1488069947000000000,\n",
       "       1485477763000000000], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.2e+06 6.2e+06 ... 6.09e+06</div><input id='attrs-143b338d-4d43-40a7-a79d-df585696681b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-143b338d-4d43-40a7-a79d-df585696681b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31b6ff11-34a2-4e54-be81-ed9f14976dc7' class='xr-var-data-in' type='checkbox'><label for='data-31b6ff11-34a2-4e54-be81-ed9f14976dc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6200010., 6199990., 6199970., ..., 6090270., 6090250., 6090230.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e+05 2e+05 ... 3.098e+05 3.098e+05</div><input id='attrs-37830a4a-68a6-4cc0-9713-b3cee1699f4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37830a4a-68a6-4cc0-9713-b3cee1699f4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50ae9770-39bb-4d62-9fb1-2d7342b24d4c' class='xr-var-data-in' type='checkbox'><label for='data-50ae9770-39bb-4d62-9fb1-2d7342b24d4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([199990., 200010., 200030., ..., 309730., 309750., 309770.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-afe970cf-b7fa-468f-93af-bb009eb258b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-afe970cf-b7fa-468f-93af-bb009eb258b4' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>B05</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-d46451a1-7dfb-46f4-9774-81a8290e12a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d46451a1-7dfb-46f4-9774-81a8290e12a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f23356ea-9958-41bd-ba6d-0c604d3bd61a' class='xr-var-data-in' type='checkbox'><label for='data-f23356ea-9958-41bd-ba6d-0c604d3bd61a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
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       "<table>\n",
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       "  <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B07</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-e54a42ec-29ed-48b3-b4cb-e9db3c1549ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e54a42ec-29ed-48b3-b4cb-e9db3c1549ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-835ae498-8ac7-4a0f-8d6d-9ec636d80a87' class='xr-var-data-in' type='checkbox'><label for='data-835ae498-8ac7-4a0f-8d6d-9ec636d80a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B8A</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-845d099c-2f1b-42ac-90e5-c784b38267e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-845d099c-2f1b-42ac-90e5-c784b38267e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-095b0e96-7893-46f6-9f66-ee37b40f6be5' class='xr-var-data-in' type='checkbox'><label for='data-095b0e96-7893-46f6-9f66-ee37b40f6be5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B11</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-950d9a1d-2083-4bd4-99c5-b701c6fea29f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-950d9a1d-2083-4bd4-99c5-b701c6fea29f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee5b7b47-2f5c-4dfa-bbe4-7bc79f953fdf' class='xr-var-data-in' type='checkbox'><label for='data-ee5b7b47-2f5c-4dfa-bbe4-7bc79f953fdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 40, x: 5490, y: 5490)\n",
       "Coordinates:\n",
       "  * time     (time) object 1608425803000000000 ... 1485477763000000000\n",
       "  * y        (y) float64 6.2e+06 6.2e+06 6.2e+06 ... 6.09e+06 6.09e+06 6.09e+06\n",
       "  * x        (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05\n",
       "Data variables:\n",
       "    B05      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    B06      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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       "    B8A      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    B11      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "    B12      (time, y, x) uint16 dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
       "Attributes:\n",
       "    transform:           (20.0, 0.0, 199980.0, 0.0, -20.0, 6200020.0)\n",
       "    crs:                 +init=epsg:32754\n",
       "    res:                 (20.0, 20.0)\n",
       "    is_tiled:            1\n",
       "    nodatavals:          (0.0,)\n",
       "    scales:              (1.0,)\n",
       "    offsets:             (0.0,)\n",
       "    AREA_OR_POINT:       Area\n",
       "    OVR_RESAMPLING_ALG:  AVERAGE"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DS6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 18min 44.7s\n",
      "[########################################] | 100% Completed | 19min 35.5s\n",
      "[########################################] | 100% Completed | 19min 44.7s\n",
      "[########################################] | 100% Completed | 19min 47.2s\n",
      "[########################################] | 100% Completed | 20min 45.8s\n",
      "[########################################] | 100% Completed | 19min 41.6s\n"
     ]
    }
   ],
   "source": [
    "b05_median, b06_median, b07_median, b08a_median, b11_median, b12_median = median6(DS6)\n",
    "with ProgressBar():\n",
    "    b05_medianNP = b05_median.compute()\n",
    "    b06_medianNP = b06_median.compute()\n",
    "    b07_medianNP = b07_median.compute()\n",
    "    b08a_medianNP = b08a_median.compute()\n",
    "    b11_medianNP = b11_median.compute()\n",
    "    b12_medianNP = b12_median.compute()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "rasters6 = [b05_medianNP, b06_medianNP, b07_medianNP, b08a_medianNP, b11_medianNP, b12_medianNP]\n",
    "raster_files6 = ['b05_medianOZ.tif','b06_medianOZ.tif','b07_medianOZ.tif','b8a_medianOZ.tif','b11_medianOZ.tif','b12_medianOZ.tif']\n",
    "\n",
    "import rasterio\n",
    "import rioxarray\n",
    "\n",
    "for index, rasterNP in enumerate(rasters6):\n",
    "    #rasterNP.rio.write_crs('ESPG:32754', inplace=True)\n",
    "    rasterNP.rio.to_raster(r\"H:\\Copa de Cobre\" + \"\\\\\" + raster_files6[index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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