::p_load(tidyverse, tmap, sf, sfdep) pacman
In-class_Ex05
Getting Started
Importing data shapefile for study area
<- st_read(dsn = "data/Geospatial",
studyArea layer = "study_area") %>%
st_transform(crs = 3829)
Reading layer `study_area' 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 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
Importing data shapefile for stores
<- st_read(dsn = "data/Geospatial",
stores layer = "stores") %>%
st_transform(crs = 3829)
Reading layer `stores' 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 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
Visualizing the sf layer
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)
<- include_self(
nb st_knn(st_geometry(stores), 6))
<- st_kernel_weights(nb,
wt
stores, "gaussian",
adaptive = TRUE)
<- stores %>%
FamilyMart filter(Name == "Family Mart")
<- FamilyMart$Name A
<- stores %>%
SevenEleven filter(Name == "7-Eleven")
<- SevenEleven$Name B
<- local_colocation(A, B, nb, wt , 49) LCLQ
<- cbind(stores, LCLQ) LCLQ_stores
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))