Quick Plot: TidyTuesday 2021 Week 45

The third of three posts revisiting old data visualization work on TidyTuesday data sets. The code and plot were initially created on November 2nd, 2021. This was an interesting and unusual TidyTuesday, exploring a book instead of a dataset. This week’s exercise was an introduction to geocomputation through the resource, Geocomputation with R. See the TidyTuesday repo for more information.

1 Setup

1.1 (Install) and Load Packages

1.2 Read in data

nz_elev = terra::rast(system.file(
  "raster/nz_elev.tif",
  package = "spDataLarge"
))

2 Create some maps

2.1 Add a fill layer to the shape of New Zealand

tm_shape(nz) +
  tm_fill()

2.2 Draw the borders

tm_shape(nz) +
  tm_borders()

2.3 Combine the fill and borders layers

tm_shape(nz) +
  tm_fill() +
  tm_borders()

2.4 Display multiple data sources on a map

1. Begin with a

map_nz = tm_shape(nz) + tm_polygons()
map_nz

2. Add elevation data

map_nz1 = map_nz +
  tm_shape(nz_elev) +
  tm_raster(col_alpha = 0.7)

3. Surround the geometry with a buffer region representing water

nz_water = st_union(nz) %>% st_buffer(22200) %>% st_cast(to = "LINESTRING")

map_nz2 = map_nz1 +
  tm_shape(nz_water) +
  tm_lines()

4. Draw dots at the 101 highest points in New Zealand

map_nz3 = map_nz2 +
  tm_shape(nz_height) +
  tm_dots()

tmap_arrange(map_nz1, map_nz2, map_nz3)