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map-detection-data.R
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map-detection-data.R
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################################################################################
# Create maps to visualize camera trap data
# C McIntyre
# 2022-07-07
################################################################################
# relies on the dh from the sagw-leca-2017 code
# just playing around and learning how to make maps in R
library(sf) # for working with simple features
library(tmap) # for mapping spatial data
library(leaflet) # Another package for mapping spatial data
library(dplyr)
naive <- as.data.frame(dh) %>%
mutate(V1 = ifelse(is.na(V1),0,V1)) %>% # set V1 = 0 for single NA
mutate(Pct_Present = (V1 + V2 + V3 + V4 + V5)/5) %>%
mutate(Present = ifelse(Pct_Present>0,1,0))
# naive occupancy = 0.417 (25 sites out of 60 had at least one detection)
naive_sf <- st_as_sf(naive %>%
tibble::rownames_to_column(., "loc") %>%
left_join(., locs_park, by = "loc"),
coords=c("long","lat"), crs=4326)
# I was struggling with the maps and so was trying different ways of making the simple features
naive_present <- naive %>%
filter(Present==1) %>%
tibble::rownames_to_column(., "loc") %>%
left_join(., locs_park, by = "loc")
naive_present_sf <- st_as_sf(naive_present,
coords=c("long","lat"), crs=4326)
naive_sf_absent <- naive_sf %>% filter(Present ==0 | is.na(Present))
# Try to make an interactive map
# Load park tiles
# code below modified from NPS IMD Intro to R Training: https://katemmiller.github.io/IMD_R_Training_Intro/
NPSbasic = 'https://atlas-stg.geoplatform.gov/styles/v1/atlas-user/ck58pyquo009v01p99xebegr9/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYXRsYXMtdXNlciIsImEiOiJjazFmdGx2bjQwMDAwMG5wZmYwbmJwbmE2In0.lWXK2UexpXuyVitesLdwUg'
NPSimagery = 'https://atlas-stg.geoplatform.gov/styles/v1/atlas-user/ck72fwp2642dv07o7tbqinvz4/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYXRsYXMtdXNlciIsImEiOiJjazFmdGx2bjQwMDAwMG5wZmYwbmJwbmE2In0.lWXK2UexpXuyVitesLdwUg'
NPSslate = 'https://atlas-stg.geoplatform.gov/styles/v1/atlas-user/ck5cpvc2e0avf01p9zaw4co8o/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYXRsYXMtdXNlciIsImEiOiJjazFmdGx2bjQwMDAwMG5wZmYwbmJwbmE2In0.lWXK2UexpXuyVitesLdwUg'
NPSlight = 'https://atlas-stg.geoplatform.gov/styles/v1/atlas-user/ck5cpia2u0auf01p9vbugvcpv/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYXRsYXMtdXNlciIsImEiOiJjazFmdGx2bjQwMDAwMG5wZmYwbmJwbmE2In0.lWXK2UexpXuyVitesLdwUg'
naive_map_lf <-
leaflet() %>%
setView(lng = -111.166, lat = 32.298, zoom = 13) %>%
# parktiles
addTiles(group = 'Map',
urlTemplate = NPSbasic) %>%
addTiles(group = 'Imagery',
urlTemplate = NPSimagery) %>%
addTiles(group = 'Light',
urlTemplate = NPSlight) %>%
addTiles(group = 'Slate',
urlTemplate = NPSslate) %>%
addLayersControl(map = .,
baseGroups = c('Map', 'Imagery', 'Light', 'Slate'),
options = layersControlOptions(collapsed = T)) %>%
# points
addCircleMarkers(data = naive_present_sf,
lng = st_coordinates(naive_present_sf)[,1],
lat = st_coordinates(naive_present_sf)[,2],
fillColor = '#56B4E9',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_absent,
lng = st_coordinates(naive_sf_absent)[,1],
lat = st_coordinates(naive_sf_absent)[,2],
fillColor = '#99999',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
# scale bar and settings
addScaleBar(position = 'bottomright') %>%
scaleBarOptions(maxWidth = 10, metric = TRUE)
naive_map_lf
# make map by percent weeks with detection
naive_sf_0 <- naive_sf %>% filter(Pct_Present ==0)
naive_sf_20 <- naive_sf %>% filter(Pct_Present ==0.2)
naive_sf_40 <- naive_sf %>% filter(Pct_Present ==0.4)
naive_sf_60 <- naive_sf %>% filter(Pct_Present ==0.6)
naive_sf_80 <- naive_sf %>% filter(Pct_Present ==0.8)
naive_sf_100 <- naive_sf %>% filter(Pct_Present ==1)
naive_map_pct <-
leaflet() %>%
setView(lng = -111.166, lat = 32.298, zoom = 12) %>%
# parktiles
addTiles(group = 'Map',
urlTemplate = NPSbasic) %>%
addTiles(group = 'Imagery',
urlTemplate = NPSimagery) %>%
addTiles(group = 'Light',
urlTemplate = NPSlight) %>%
addTiles(group = 'Slate',
urlTemplate = NPSslate) %>%
addLayersControl(map = .,
baseGroups = c('Map', 'Imagery', 'Light', 'Slate'),
options = layersControlOptions(collapsed = T)) %>%
# points
addCircleMarkers(data = naive_sf_0,
lng = st_coordinates(naive_sf_0)[,1],
lat = st_coordinates(naive_sf_0)[,2],
fillColor = '#FFFFFF',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_20,
lng = st_coordinates(naive_sf_20)[,1],
lat = st_coordinates(naive_sf_20)[,2],
fillColor = '#d5d2db',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_40,
lng = st_coordinates(naive_sf_40)[,1],
lat = st_coordinates(naive_sf_40)[,2],
fillColor = '#aba5b7',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_60,
lng = st_coordinates(naive_sf_60)[,1],
lat = st_coordinates(naive_sf_60)[,2],
fillColor = '#827893',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_80,
lng = st_coordinates(naive_sf_80)[,1],
lat = st_coordinates(naive_sf_80)[,2],
fillColor = '#584b6f',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
addCircleMarkers(data = naive_sf_100,
lng = st_coordinates(naive_sf_100)[,1],
lat = st_coordinates(naive_sf_100)[,2],
fillColor = '#2e1e4b',
radius = 4,
stroke = FALSE, # turn off outline
fillOpacity = 1) %>%
# scale bar and settings
addScaleBar(position = 'bottomright') %>%
scaleBarOptions(maxWidth = 10, metric = TRUE)
naive_map_pct