intensity-analysis-diagrams.ipynb

{
 "cells": [
  {
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   "id": "0df923a5-1bd0-46df-b231-f5a187ceb5c2",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Intensity analysis diagrams\n",
    "In Python.\n",
    "- **Input**: The three intensity analysis levels data files: \"IIA.csv\" (Interval level), \"CIA.csv\" (Category level), \"TIA.csv\" (Transition level). \n",
    "- **Output**: Plots for the three intensity analysis levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2bcf3d86-9eb6-42bb-95c7-edadd5cb6e09",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import plotly.graph_objects as go\n",
    "import plotly\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import font_manager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6ff38c0-7e7a-408a-b153-c5b23957273b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "xticks_font = font_manager.FontProperties(family='serif')\n",
    "\n",
    "colors = {'Extremely Low': 'yellow',\n",
    "          'Low' : \"#ffa500\",\n",
    "          'Moderate' : \"brown\",\n",
    "          'High' : \"#90ee90\",\n",
    "          'Very High' : \"green\",}\n",
    "categories = ['Extremely Low', 'Low', 'Moderate', 'High', 'Very High']\n",
    "nb_categories = len(categories)\n",
    "\n",
    "year_format=[]\n",
    "length_inteval = 4\n",
    "start_year = 2002\n",
    "end_year = 2022\n",
    "nb_intervals = int((end_year - start_year) / length_inteval)\n",
    "for i in range(nb_intervals):\n",
    "    year_format.append(f\"{start_year+i*length_inteval}\\n{start_year+(i+1)*length_inteval}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46fada08-c712-4d2f-aee3-6b578048f326",
   "metadata": {},
   "source": [
    "## Interval-level Intensity Analysis\n",
    "Displays change for each interval:\n",
    "- **Time interval change size (km²):** For each time interval, the total area (in km²) of change is displayed.\n",
    "- **Annual change intensity (%):** For each interval, the sum of element changes is devided by the total number of elements (element = pixel or km²). The obtained result is then devided by 2 in order to obtain the annual change intensity.\n",
    "- **Uniform change across intervals:** The vertical black line. Represents the intensities mean. Below it, the change in the interval is considered as slow. Above it, it is considered as fast. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c69de51b-dce9-4878-a9ba-b75dde133953",
   "metadata": {
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   "outputs": [],
   "source": [
    "#Reading the IIA data\n",
    "filename = 'IIA.csv'\n",
    "with open(filename) as f:\n",
    "    reader = csv.reader(f)\n",
    "    data = []\n",
    "    for r in reader:\n",
    "        data.append(r)\n",
    "    \n",
    "change=[]\n",
    "intensity=[]\n",
    "\n",
    "for i in range(nb_intervals):\n",
    "    change.append(float(data[i+1][1])*0.0009)\n",
    "    intensity.append(float(data[i+1][2]))\n",
    "uniform = float(data[1][3])\n",
    "\n",
    "# Set the figure size\n",
    "plt.rcParams[\"figure.figsize\"] = [12, 3]\n",
    "\n",
    "# Array for horizontal bar's position\n",
    "ind = np.array(range(nb_intervals))\n",
    "\n",
    "# Bar's width\n",
    "width = 0.3\n",
    "\n",
    "fig, axs = plt.subplots(1, 2)\n",
    "\n",
    "# Annual change\n",
    "axs[0].barh(ind,change,width,color='grey',edgecolor='black')\n",
    "axs[0].set(yticks=ind, yticklabels=[])\n",
    "for tick in axs[0].get_xticklabels():\n",
    "    tick.set_fontproperties(xticks_font)\n",
    "axs[0].invert_xaxis()\n",
    "axs[0].tick_params(\n",
    "    axis='y',          # changes apply to the y-axis\n",
    "    which='both',      # both major and minor ticks are affected\n",
    "    left=False,        # ticks along the bottom edge are off\n",
    "    labelbottom=False)  \n",
    "axs[0].set_xticks(ticks=np.arange(0, 180000, step=40000),\n",
    "                  labels=np.arange(0, 180000, step=40000),font=\"serif\")\n",
    "axs[0].set_facecolor(\"white\")\n",
    "axs[0].grid(axis='x',color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "axs[0].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "axs[0].set_title(f\"Time interval change size (km²)\",fontsize = 12,font=\"serif\") \n",
    "    \n",
    "# Annual change intensity\n",
    "axs[1].barh(ind, intensity, width, color='gray', edgecolor='black')\n",
    "        \n",
    "for tick in axs[1].get_xticklabels():\n",
    "    tick.set_fontproperties(xticks_font)\n",
    "axs[1].set(yticks=ind)\n",
    "axs[1].set_yticklabels(np.array(year_format),fontsize=12,font=\"serif\")    \n",
    "axs[1].tick_params(\n",
    "    axis='y',          # changes apply to the y-axis\n",
    "    which='both',      # both major and minor ticks are affected\n",
    "    left=False,        # ticks along the bottom edge are off\n",
    "    labelbottom=False)  \n",
    "        \n",
    "axs[1].set_facecolor(\"white\")\n",
    "axs[1].grid(axis='x',color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "axs[1].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "\n",
    "axs[1].set_title(f\"Annual change intensity (%)\",fontsize = 12,font=\"serif\")\n",
    "    \n",
    "#Uniform category intensity lines\n",
    "point1 = [uniform,0 - width/2]\n",
    "point2 = [point1[0], point1[1] + nb_intervals-1 + width ]\n",
    "x_values = [point1[0], point2[0]]\n",
    "y_values = [point1[1], point2[1]]\n",
    "axs[1].plot(x_values, y_values, \"black\", linestyle=\"-\")\n",
    "axs[1].text(point1[0] - 0.014 ,  point2[1], \"slow\",fontsize = 8,font=\"serif\")\n",
    "axs[1].text(point1[0] + 0.003 ,  point2[1], \"fast\",fontsize = 8,font=\"serif\")\n",
    "\n",
    "# Save the plot (dimension shoukd be adapted)\n",
    "# plt.rcParams.update({'font.size': 12})\n",
    "# plt.savefig(\"iia.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "916644a8-f2fc-4fd7-8481-19de54e2201d",
   "metadata": {},
   "source": [
    "## Category-level Intensity Analysis :\n",
    "Displays gain and loss for each category in each interval :\n",
    "- **Annual change size (km²):** For each time interval, the area (in km²) of gain and loss are displayed for each category. The obtained numbers are divided by 2 in order to obtain annual changes.\n",
    "- **Annual change intensity (%):** For each interval, the number of gain and loss elements for a category are devided by the number of elements for this catogory in the interval starting year (element = pixel or km²). The obtained result is then devided by 2 in order to have the annual change intensity by category.\n",
    "- **Uniform category intensity:** The black vertical line. Represents the annual change intensity for the interval. Below it, the gain or loss change is considered as dormant. Above it, it is considered as active. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27311308-9502-4458-a706-d50b2aed8521",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Reading the CIA data\n",
    "filename = 'CIA.csv'\n",
    "with open(filename) as f:\n",
    "    reader = csv.reader(f)\n",
    "    data = []\n",
    "    for r in reader:\n",
    "        data.append(r)\n",
    "    \n",
    "gross_loss=[[] for _ in range(nb_intervals)]\n",
    "gross_gain=[[] for _ in range(nb_intervals)]\n",
    "intensity_loss=[[] for _ in range(nb_intervals)]\n",
    "intensity_gain=[[] for _ in range(nb_intervals)]\n",
    "uniform=[]\n",
    "\n",
    "for i in range(nb_intervals):\n",
    "    for c in range(nb_categories):\n",
    "        gross_loss[c].append(float(data[2+i*8+c][1])*0.0009)\n",
    "        gross_gain[c].append(float(data[2+i*8+c][2])*0.0009)\n",
    "        intensity_loss[c].append(float(data[2+i*8+c][3]))\n",
    "        intensity_gain[c].append(float(data[2+i*8+c][4]))\n",
    "    uniform.append(float(data[2+i*8+c][5]))\n",
    "\n",
    "labels = []\n",
    "for c in categories:\n",
    "    labels.append(f\"{c} Loss\")\n",
    "    labels.append(f\"{c} Gain\")\n",
    "\n",
    "# Set the figure size\n",
    "plt.rcParams[\"figure.figsize\"] = [12, 4]\n",
    "#plt.rcParams[\"figure.autolayout\"] = True\n",
    "\n",
    "# Array for horizontal bar's position\n",
    "ind = np.array(range(nb_intervals))\n",
    "\n",
    "# Bar's width\n",
    "width = 0.08\n",
    "\n",
    "fig, axs = plt.subplots(1, 2)\n",
    "\n",
    "l = []\n",
    "\n",
    "# Annual change area by category\n",
    "for c in range(nb_categories):\n",
    "    l.append(axs[0].barh(ind + width*(2*c), gross_loss[c], width, color=colors[categories[c]], hatch=\"//\",edgecolor='black')[0])\n",
    "    l.append(axs[0].barh(ind + width*(2*c+1), gross_gain[c], width, color=colors[categories[c]],edgecolor='black')[0])\n",
    "        \n",
    "    # Set Y-axis ticks and ticklabels\n",
    "    axs[0].set(yticks=ind+width*4.5, yticklabels=[])\n",
    "    for tick in axs[0].get_xticklabels():\n",
    "        tick.set_fontproperties(xticks_font)\n",
    "    axs[0].set_xticks(ticks=np.arange(0, 23000, step=5000),labels=np.arange(0, 23000, step=5000),font=\"serif\")\n",
    "\n",
    "    axs[0].tick_params(\n",
    "        axis='y',          # changes apply to the y-axis\n",
    "        which='both',      # both major and minor ticks are affected\n",
    "        left=False,        # ticks along the bottom edge are off\n",
    "        labelbottom=False)  \n",
    "    \n",
    "    axs[0].invert_xaxis()\n",
    "    \n",
    "    axs[0].set_facecolor(\"white\")\n",
    "    axs[0].grid(axis='x',color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    axs[0].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    \n",
    "    axs[0].set_title(f\"Annual change size (km²)\",fontsize = 12,font=\"serif\")\n",
    "    \n",
    "# Annual change intensity\n",
    "for c in range(5):\n",
    "    axs[1].barh(ind + width*(2*c), intensity_loss[c], width, color=colors[categories[c]], hatch=\"//\",edgecolor='black')\n",
    "    axs[1].barh(ind + width*(2*c+1), intensity_gain[c], width, color=colors[categories[c]],edgecolor='black')\n",
    "        \n",
    "    for tick in axs[1].get_xticklabels():\n",
    "        tick.set_fontproperties(xticks_font)\n",
    "    axs[1].set(yticks=ind+width*4.5)\n",
    "    axs[1].set_yticklabels(np.array(year_format),fontsize=12,font=\"serif\")    \n",
    "    axs[1].tick_params(\n",
    "        axis='y',          # changes apply to the y-axis\n",
    "        which='both',      # both major and minor ticks are affected\n",
    "        left=False,        # ticks along the bottom edge are off\n",
    "        labelbottom=False)  \n",
    "        \n",
    "    axs[1].set_facecolor(\"white\")\n",
    "    axs[1].grid(axis='x',color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    axs[1].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "\n",
    "    axs[1].set_title(f\"Annual change intensity (%)\",fontsize = 12,font=\"serif\")\n",
    "    \n",
    "#Uniform category intensity lines\n",
    "for i in range(nb_intervals):\n",
    "    point1 = [uniform[i], -0.5*width + ind[i] ]\n",
    "    point2 = [point1[0], point1[1] + 10*width ]\n",
    "    x_values = [point1[0], point2[0]]\n",
    "    y_values = [point1[1], point2[1]]\n",
    "    axs[1].plot(x_values, y_values, \"black\", linestyle=\"-\")\n",
    "    axs[1].text(point1[0] - 0.03 ,  point1[1] + width * 10 + 0.01, \"dormant\",fontsize = 8,font=\"serif\")\n",
    "    axs[1].text(point1[0] + 0.003 ,  point1[1] + width * 10 + 0.01, \"active\",fontsize = 8,font=\"serif\")\n",
    "\n",
    "fig.legend(l, labels, loc='upper center', bbox_to_anchor=(0.51,1.1), ncol=5, prop={\"family\":\"Serif\",\"size\":8})\n",
    "\n",
    "# Save the plot (dimension shoukd be adapted)\n",
    "# plt.rcParams.update({'font.size': 12})\n",
    "# plt.savefig(\"cia.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09e4d089-8c93-4a10-a2ba-aabbc76f5d0e",
   "metadata": {},
   "source": [
    "## Transition-level Intensity Analysis:\n",
    "Displays gains of each category from every other category in each interval:\n",
    "- **Annual transition area for gain (km²):** For each time interval, the transition area (in km²) for gain of each category from each other category is displayed. The obtained numbers are divided by 2 in order to obtain annual changes.\n",
    "- **Annual transition intensity for gain (percentage):** For each interval, the number of elements transitioning to a category from another are devided by the number of elements of the second catogory at the starting year of the interval (element = pixel or km²). The obtained result is then devided by 2 in order to have the annual intensity change by transition.\n",
    "- **Uniform Transition Intensity:** The red dashed line. Reprsents the total number of elements gained by the category devided by the total number of elements of all the other categories at the starting year of the interval. A category with a change intensity below it, is considered as avoided. Otherwise, it is considered targeted.\n",
    "\n",
    "**Note**: Plot scales (same or adaptive) can be configured through the boolean variable \"same_scale\". "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe9d9bab-b6fc-4e93-b5aa-b2c66c6ea3d9",
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   "source": [
    "nb_categories_to_display = 5\n",
    "#All plots have the same scale (True). Every plot is scaled according to its max value (False).\n",
    "same_scale = True\n",
    "\n",
    "filename = 'TIA.csv'\n",
    "with open(filename) as f:\n",
    "    reader = csv.reader(f)\n",
    "    data = []\n",
    "    for r in reader:\n",
    "        data.append(r)\n",
    "\n",
    "other_categories=[[[] for _ in range(nb_categories-1)] for _ in range(nb_categories_to_display)]\n",
    "transition=[[[] for _ in range(nb_categories-1)] for _ in range(nb_categories_to_display)]\n",
    "transition_intensity=[[[] for _ in range(nb_categories-1)] for _ in range(nb_categories_to_display)]\n",
    "uniform=[[[] for _ in range(nb_categories-1)] for _ in range(nb_categories_to_display)]\n",
    "\n",
    "#main categories\n",
    "for c in range(nb_categories_to_display):\n",
    "    #intervals\n",
    "    for i in range(nb_intervals):\n",
    "        #other categories\n",
    "        for oc in range(nb_categories-1):\n",
    "            other_categories[c][oc].append(data[2+oc+i*31+c*6][0])\n",
    "            transition[c][oc].append(float(data[2+oc+i*31+c*6][1])*0.0009)            \n",
    "            transition_intensity[c][oc].append(float(data[2+oc+i*31+c*6][2]))            \n",
    "            uniform[c][oc].append(float(data[2+oc+i*31+c*6][3]))\n",
    "\n",
    "# Set the figure size\n",
    "plt.rcParams[\"figure.figsize\"] = [12, 18]\n",
    "# plt.rcParams[\"figure.autolayout\"] = True\n",
    "\n",
    "# Array for horizontal bar's position\n",
    "ind = np.array(range(nb_intervals))\n",
    "\n",
    "# Bar's width\n",
    "width = 0.2\n",
    "\n",
    "fig, axs = plt.subplots(nb_categories_to_display, 2)\n",
    "\n",
    "L = []\n",
    "\n",
    "for c in range(nb_categories_to_display):\n",
    "    for oc in range(nb_categories-1):\n",
    "        l = axs[c,0].barh(ind + width*oc, transition[c][oc], width, color=colors[other_categories[c][oc][0]],edgecolor='black')[0]\n",
    "        L.append(l)\n",
    "        \n",
    "    # Set Y-axis ticks and ticklabels\n",
    "    axs[c,0].set(yticks=ind+width*1.5, yticklabels=[])\n",
    "        \n",
    "    axs[c,0].tick_params(\n",
    "        axis='y',          # changes apply to the y-axis\n",
    "        which='both',      # both major and minor ticks are affected\n",
    "        left=False,       # ticks along the bottom edge are off\n",
    "        labelbottom=False)  \n",
    "    \n",
    "    if same_scale :\n",
    "        axs[c,0].set_xticks(ticks=np.arange(0, 18000, step=4000),labels=np.arange(0, 18000, step=4000),font=\"serif\")\n",
    "    \n",
    "    for tick in axs[c,0].get_xticklabels():\n",
    "        tick.set_fontproperties(xticks_font)\n",
    "\n",
    "    axs[c,0].invert_xaxis()\n",
    "    \n",
    "    axs[c,0].set_facecolor(\"white\")\n",
    "    axs[c,0].grid(axis='x',color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    axs[c,0].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "\n",
    "#main categories\n",
    "for c in range(nb_categories_to_display):\n",
    "    #other categories\n",
    "    for oc in range(nb_categories-1):\n",
    "        l = axs[c,1].barh(ind + width*oc, transition_intensity[c][oc], width, color=colors[other_categories[c][oc][0]],edgecolor='black')[0]\n",
    "        L.append(l)\n",
    "    \n",
    "    axs[c,1].set_facecolor(\"white\")\n",
    "    axs[c,1].grid(axis='x', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    axs[c,1].grid(axis='y', color = 'grey', linestyle = '--', linewidth = 0.5)\n",
    "    \n",
    "    # Set Y-axis ticks and ticklabels\n",
    "    axs[c,1].set(yticks=ind+width*1.5, yticklabels=np.array(year_format))\n",
    "    \n",
    "    if same_scale:\n",
    "        axs[c,1].set(xlim=[0,0.16])\n",
    "                     \n",
    "    axs[c,1].set_yticklabels(np.array(year_format),fontsize=12,font=\"serif\")\n",
    "    axs[c,1].set_xticks(ticks=np.array(np.arange(0, 0.16, step=0.03)),\n",
    "                        labels=np.array(np.arange(0, 0.16, step=0.03)),\n",
    "                        fontsize=12)\n",
    "    for tick in axs[c,1].get_xticklabels():\n",
    "        tick.set_fontproperties(xticks_font)\n",
    "    \n",
    "    axs[c,1].tick_params(\n",
    "        axis='y',          # changes apply to the y-axis\n",
    "        which='both',      # both major and minor ticks are affected\n",
    "        left=False,        # ticks along the bottom edge are off\n",
    "        labelbottom=False)  \n",
    "\n",
    "for c in range(nb_categories_to_display):\n",
    "    for i in range(nb_intervals):\n",
    "        point1 = [uniform[c][0][i], -width/2 + ind[i] ]\n",
    "        point2 = [point1[0], point1[1] + 4*width ]\n",
    "        x_values = [point1[0], point2[0]]\n",
    "        y_values = [point1[1], point2[1]]\n",
    "        axs[c,1].plot(x_values, y_values, \"black\", linestyle=\"-\")\n",
    "        point2_ax = axs[c,1].transLimits.transform(point2)\n",
    "        axs[c,1].text(point2[0]/axs[c,1].get_xlim()[1]-0.08,point2_ax[1], \"avoid\",fontsize = 8,transform=axs[c,1].transAxes,font=\"serif\",)\n",
    "        axs[c,1].text(point2[0]/axs[c,1].get_xlim()[1]+0.01,point2_ax[1], \"target\",fontsize = 8,transform=axs[c,1].transAxes,font=\"serif\",)\n",
    "        \n",
    "fig.legend((L[4],L[0],L[1],L[2],L[3]), (categories[0],categories[1],categories[2],categories[3],categories[4]), \n",
    "    loc='upper center', bbox_to_anchor=(0.5,0.94), ncol=5,fontsize = 12, prop={\"family\":\"Serif\"})\n",
    "  \n",
    "#Adjust space between subplots      \n",
    "fig.subplots_adjust(wspace=0.15)\n",
    "\n",
    "#Common titles to columns and rows\n",
    "cols = ['Annual transition size (km²)','Annual transition intensity (%)']\n",
    "pad = 0 # in points\n",
    "for ax, col in zip(axs[0], cols):\n",
    "    ax.annotate(col, xy=(0.5, 1.05), xytext=(0, pad),\n",
    "                xycoords='axes fraction', textcoords='offset points',\n",
    "                size=12, ha='center', va='baseline', font=\"serif\" )\n",
    "for ax, row in zip(axs[:,0], categories[0:nb_categories_to_display]):\n",
    "    ax.annotate(row, xy=(0, 0.5), xytext=(5, 0),\n",
    "                xycoords=ax.yaxis.label, textcoords='offset points',\n",
    "                size=12, ha='right', va='center', font=\"serif\", rotation=90)"
   ]
  }
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