PrintAdding the R packages that will be needed for the analysis
Double-check that you've loaded sf and spatstat.
Set the working directory
Use Session - Set Working Directory - Choose Directory to set your working directory to the unzipped folder with the Lesson 3 data.
Reading in and Mapping The Data
The first step in any spatial analysis is to become familiar with your data. You have already completed some of this in Lesson 2 when you used a mixture of descriptive statistics and visualizations (e.g., map of crime, boxplots, bar charts, and histograms) to get a general overview of the types of crimes that were taking place in St Louis over time and where these were occurring.
In Project 3B, we will be revisiting the crime data that you saw in Lesson 2. However, for Lesson 3, the crime data and St. Louis boundary are contained within two shapefiles (stl20132014sube.shp and stl_boundary, respectively) where each shapefile is projected into the Missouri State Plane Coordinate System east zone. The methods introduced in this lesson require that the data be projected.
Why? Think about this a bit as you work through the lesson's steps.
You might find it helpful to copy the code lines into the console one-by-one so that you can see the result of each line. This will help you to better understand what each line is doing.
#Set up links to the shapefiles -- you will need to change the filepaths as appropriate on your machine #the code example presumes your data are stored in C:\Geog586_Les3_Project #crime data file_dir_gis <-"C:/Geog586_Les3_Project/gis/" gis_file <-paste(file_dir_gis,"stl20132014sube.shp", sep="") #check that R can find the file and that there are no path name problems. This should return a message of TRUE in the console. #if everything is ok, move on. If not, you might be missing a "/" in your file path or have a spelling error. file.exists(gis_file) #read in the shapefile crimes_shp_prj<-read_sf(gis_file) #study area boundary -- notice this is adding a file from the lesson 2 data. Be sure you have the right path. gis_file_2 <-paste(file_dir_gis,"stl_boundary.shp", sep="") file.exists(gis_file_2) StLouis_BND_prj <-read_sf(gis_file_2) #Set up the analysis environment by creating an analysis window from the city boundary Sbnd <-as.owin(StLouis_BND_prj) #check the shapefile will plot correctly plot(Sbnd) #add the crime events to the analysis window and attach point attributes (marks) crimes_marks <-data.frame(crimes_shp_prj) crimesppp <-ppp(crimes_shp_prj$MEAN_XCoor, crimes_shp_prj$MEAN_YCoor, window=Sbnd, marks=crimes_marks) #plot the points to the boundary as a solid red circle one-half the default plotting size points(crimesppp$x, crimesppp$y, pch = 19, cex=0.5, col = "red")
For more information on handling shapefiles with spatstat, you can consult this useful resource. This might be helpful if your term-long project involves doing point pattern statistics.