1 Getting Started

1.1 Installing and Loading Packages

Firstly, the code below will check if pacman has been installed. If it has not been installed, R will download and install it, before activating it for use during this session.

if (!require('pacman', character.only = T)){
  install.packages('pacman')
}

Loading required package: pacman

library('pacman')

Next, pacman assists us by helping us load R packages that we require, sf, tidyverse and tmap.

pacman::p_load(tidyverse, tmap, sf, sfdep)

1.2 Importing Data

studyArea <- st_read(dsn = "In-Class_Ex05/data", layer = "study_area") %>%
  st_transform(crs = 3829)

Reading layer `study_area' from data source 
  `C:\renjie-teo\IS415-GAA\exercises\In-Class_Ex05\data' using driver `ESRI Shapefile'
Simple feature collection with 7 features and 7 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 121.4836 ymin: 25.00776 xmax: 121.592 ymax: 25.09288
Geodetic CRS:  TWD97

stores <- st_read(dsn = "In-Class_Ex05/data", layer = "stores") %>%
  st_transform(crs = 3829)

Reading layer `stores' from data source 
  `C:\renjie-teo\IS415-GAA\exercises\In-Class_Ex05\data' using driver `ESRI Shapefile'
Simple feature collection with 1409 features and 4 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 121.4902 ymin: 25.01257 xmax: 121.5874 ymax: 25.08557
Geodetic CRS:  TWD97

1.3 Visualising SF Layers

tmap_mode("view")

tmap mode set to interactive viewing

tm_shape(studyArea) +
  tm_polygons() +
tm_shape(stores) +
  tm_dots(col = "Name",
          size = 0.01,
          border.col = "black",
          border.lwd = 0.5) +
tm_view(set.zoom.limits = c(12,16))

Note

The polygon layers should always be above the dots. The geospatial layers are rendered in sequence, hence if polygons are rendered after the dots (ie. dots are ontop of the polygon code), the dots might be coverd by the polygon line/fill.

2 Local Colocation Quotients (LCLQ)

nb <- include_self(
  st_knn(st_geometry(stores), 6))
wt <- st_kernel_weights(nb, stores, "gaussian")

Warning in spdep::knearneigh(pnts, k): knearneigh: identical points found

Warning in spdep::knearneigh(pnts, k): knearneigh: kd_tree not available for
identical points

The variable nb stores the values of its neighbours. The number 6 defines 6 points including itself and 5 other neighbours.

The variable wt will balance weights according to distance to centre point. The further points will get lower weights.

FamilyMart <- stores %>%
  filter(Name == "Family Mart")
A <- FamilyMart$Name

SevenEleven <- stores %>%
  filter(Name == "7-Eleven")
B <- SevenEleven$Name

LCLQ <- local_colocation(A, B, nb, wt, 49) #49 = 50 simulations and immediately see p value

LCLQ_stores <- cbind(stores, LCLQ)

tmap_mode("view")

tmap mode set to interactive viewing

tmap_mode("view")

tmap mode set to interactive viewing

tm_shape(studyArea) +
  tm_polygons() +
tm_shape(LCLQ_stores) +
  tm_dots(col = "X7.Eleven",
          size = 0.01,
          border.col = "black",
          border.lwd = 0.5) +
tm_view(set.zoom.limits = c(12,16))