1 Importing Data

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

Reading layer `study_area' from data source 
  `C:\gailteh\IS415-GAA\In-class_Ex\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="data",
                  layer="stores") %>%
  st_transform(crs=3829)

Reading layer `stores' from data source 
  `C:\gailteh\IS415-GAA\In-class_Ex\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

##Visualising sf layers

tmap_mode("view")
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))

tmap_mode("plot")

2 Local Colocation Quotients (LCLQ)

nb <- include_self(
  st_knn(st_geometry(stores), 6))

wt <- st_kernel_weights(nb,
                        stores,
                        "gaussian")

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)

LCLQ_Stores <- cbind(stores, LCLQ)

tmap_mode("view")
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))