In-class Exercise 4

Getting started

pacman::p_load(maptools, sf, raster, spatstat, tmap)

Things to learn from this code chunk.

Importing spatial data

childcare_sf <- st_read("data/Geospatial/child-care-services-geojson.geojson") %>% 
  st_transform(crs = 3414)

Reading layer `child-care-services-geojson' from data source 
  `C:\Users\kwekm\Desktop\SMU Year 3 Semester 2\IS415 Geospatial Analytics and Applications\KMRCrazyDuck\IS415-KMR\In-class_Ex\Data\Geospatial\child-care-services-geojson.geojson' 
  using driver `GeoJSON'
Simple feature collection with 1545 features and 2 fields
Geometry type: POINT
Dimension:     XYZ
Bounding box:  xmin: 103.6824 ymin: 1.248403 xmax: 103.9897 ymax: 1.462134
z_range:       zmin: 0 zmax: 0
Geodetic CRS:  WGS 84

sg_sf <- st_read(dsn = "data/Geospatial", layer="CostalOutline")

Reading layer `CostalOutline' from data source 
  `C:\Users\kwekm\Desktop\SMU Year 3 Semester 2\IS415 Geospatial Analytics and Applications\KMRCrazyDuck\IS415-KMR\In-class_Ex\Data\Geospatial' 
  using driver `ESRI Shapefile'
Simple feature collection with 60 features and 4 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 2663.926 ymin: 16357.98 xmax: 56047.79 ymax: 50244.03
Projected CRS: SVY21

mpsz_sf <- st_read(dsn = "data/Geospatial", 
                layer = "MP14_SUBZONE_WEB_PL")

Reading layer `MP14_SUBZONE_WEB_PL' from data source 
  `C:\Users\kwekm\Desktop\SMU Year 3 Semester 2\IS415 Geospatial Analytics and Applications\KMRCrazyDuck\IS415-KMR\In-class_Ex\Data\Geospatial' 
  using driver `ESRI Shapefile'
Simple feature collection with 323 features and 15 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 2667.538 ymin: 15748.72 xmax: 56396.44 ymax: 50256.33
Projected CRS: SVY21

tmap_mode('view')
tm_shape(childcare_sf)+
  tm_dots()

tmap_mode('view')
tm_shape(childcare_sf)+
  tm_dots(alph =0.5,
          size =0.01) +
  tm_view(set.zoom.limits = c(11,14))

tmap_mode('plot')

childcare <- as_Spatial(childcare_sf)
mpsz <- as_Spatial(mpsz_sf)
sg <- as_Spatial(sg_sf)

4.5.2 Converting the Spatial* class into generic sp format

childcare_sp <- as(childcare, "SpatialPoints")
sg_sp <- as(sg, "SpatialPolygons")

4.5.3 Converting the generic sp format into spatstat’s ppp format

childcare_ppp <- as(childcare_sp, "ppp")
childcare_ppp

Planar point pattern: 1545 points
window: rectangle = [11203.01, 45404.24] x [25667.6, 49300.88] units

plot(childcare_ppp)