Packages

library(sf)
library(tidyverse)
library(mapview)

Data

NC counties

nc <- st_read(system.file("shape/nc.shp", package = "sf"), quiet = T)

NC gamelands

download.file("https://opendata.arcgis.com/datasets/e5ddff9b96204c6181be7c022e61d946_0.zip?outSR=%7B%22latestWkid%22%3A32119%2C%22wkid%22%3A32119%7D",
              destfile = "data/Gamelands.zip")
unzip("data/Gamelands.zip", exdir = "data/")
nc_gamelands <- st_read("data/679190a9-3cfb-4be4-9a1e-255188fd3f6e202044-1-707iid.5jdc8.shp", quiet = T)

Exercise 1

Problem

Create a map that includes NC county boundaries, Game Lands, and hazardous waste sites. Data for the hazardous waste sites is available at https://www.nconemap.gov/datasets/hazardous-waste-sites

This data set represents the location of sites within North Carolina that are regulated by the hazardous waste portions of the Resource Conservation and Recovery Act (RCRA).

Solution

Let’s get the data.

download.file("https://opendata.arcgis.com/datasets/84ff6d8f569f4bb0965bfa906aa06e6d_2.zip?outSR=%7B%22latestWkid%22%3A32119%2C%22wkid%22%3A32119%7D",
              destfile = "data/waste.zip")
unzip("data/waste.zip", exdir = "data/")
waste <- st_read("data/Hazardous_Waste_Sites.shp", quiet = T)

Next, we’ll put everything on the same coordinate reference system.

st_crs(nc)
#> Coordinate Reference System:
#>   EPSG: 4267 
#>   proj4string: "+proj=longlat +datum=NAD27 +no_defs"
st_crs(nc_gamelands)
#> Coordinate Reference System:
#>   EPSG: 32119 
#>   proj4string: "+proj=lcc +lat_1=36.16666666666666 +lat_2=34.33333333333334 +lat_0=33.75 +lon_0=-79 +x_0=609601.22 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"
st_crs(waste)
#> Coordinate Reference System:
#>   EPSG: 32119 
#>   proj4string: "+proj=lcc +lat_1=36.16666666666666 +lat_2=34.33333333333334 +lat_0=33.75 +lon_0=-79 +x_0=609601.22 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"
nc <- st_transform(nc, st_crs(nc_gamelands))

Create three layers using mapview().

nc_mapview <- mapview(nc, alpha.regions = .2, alpha = .9,
                  label = nc[, "NAME", drop = T], popup = NULL,
                  layer.name = "NC Counties")
nc_gamelands_mapview <- mapview(nc_gamelands, col.regions = "#ff6700",
        label = round(nc_gamelands[, "SUM_ACRES", drop = T], 2),
        layer.name = "NC Gamelands")
nc_waste_mapview <- mapview(waste, col.regions = "#65ff00",
                            alpha = .3,
                            popup = NULL,
                            alpha.regions = .3,
                            label = waste[, "SITE_NAME", drop = T],
                            layer.name = "NC Waste Sites")
mapviewOptions(legend.pos = "bottomright")
nc_mapview + nc_gamelands_mapview + nc_waste_mapview

Exercise 2

Problem

Create a plot of North Carolina’s Game Lands and all the waste sites within 100 meters of a Game Land area. Try two of the three plot functions.

Solution

From Exercise 1, we have both layers on the same coordinate reference system.

close_waste_lgl <- st_is_within_distance(waste, nc_gamelands, 
                                         dist = 100, sparse = F)
close_waste <- waste %>% 
  filter(apply(close_waste_lgl, 1, sum) > 0)

Using mapview()

nc_gamelands_mapview <- mapview(nc_gamelands, col.regions = "#ff6700",
        label = nc_gamelands$GML_HAB,
        layer.name = "NC Gamelands")

nc_waste_mapview <- mapview(close_waste, col.regions = "#65ff00",
                            alpha = .3,
                            alpha.regions = .3,
                            label = waste[, "SITE_NAME", drop = T],
                            layer.name = "NC Waste Sites")

nc_gamelands_mapview + nc_waste_mapview

Using ggplot()

ggplot(nc) +
  geom_sf(alpha = .3) +
  geom_sf(data = close_waste, color = "#65ff00", size = 3) +
  geom_sf(data = nc_gamelands, fill = "#ff6700", alpha = .5) +
  theme_bw()