In-Class Exercise 5: Advanced Spatial Point Patterns Analysis: Local Co-Location Quotient

Published

February 6, 2023

Modified

March 17, 2023

Getting Started

Importing Module

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

Importing Data

studyArea <- st_read(dsn="data",
                     layer="study_area") %>%
  st_transform(crs = 3829)
Reading layer `study_area' from data source 
  `C:\Users\la935\Desktop\IS415 - GAA\IS415 - GAA (New)\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:\Users\la935\Desktop\IS415 - GAA\IS415 - GAA (New)\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 The 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))

Local Colocation Quotients (LCLQ)

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

#Use even number to avoid 50/50 results
wt <- st_kernel_weights(nb,
                        stores,
                        "gaussian",
                        adaptive = TRUE)

#Higher the weight, the nearer the point
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)

#Running 50 simulation
LCLQ_stores <- cbind(stores, LCLQ)

#cbind only works when the table structure is not changed (aka filter)
tmap_mode("view")
tm_shape(studyArea) +
  tm_polygons() +
tm_shape(LCLQ_stores) +
  tm_dots(col = "X7.Eleven", size=0.01) +
  tm_view(set.zoom.limits = c(12,14))