GEOG 586
Geographic Information Analysis

Project 3, Part B: Understanding patterns using Point Pattern Analysis (PPA)

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Background

In project 3B, you will use some of the point pattern analysis tools available in the R package spatstat to investigate some point patterns of crime in St. Louis, Missouri. You will be building on what you started in Lesson 2.

Project Resources

For Project 3B, make sure that following packages are installed in RStudio: spatstat and sf. To add any new libraries (e.g., sf), use the Packages - Install package(s)... menu option as before. If the package is installed but not loaded, use the library(package_name) command to load the package.

The data you need for Project 3B are available in Canvas for download. If you have any difficulty downloading, please contact me. The data archive includes:

  • Crime data files for St Louis: crimeStLouis20132014b.csv, crimeStLouis20132014b_agg.csv 
  • Boundary of St Louis (shapefile): stl_boundary_ll.shp
  • Projected data: stl20132014sube.shp (crime points), stl_boundary.shp (St. Louis boundary file). Note that these files are projected into the Missouri State Plane Coordinate System east zone.

Summary of Project 3B Deliverables

For Project 3B, the items you are required to submit in your report are as follows:

  • First, create density maps of the homicide data, experimenting with the kernel density bandwidth, and provide a commentary discussing the most suitable bandwidth choice for this analysis visualization method and how you made that selection.
  • Second, perform a point pattern analysis on any two of the available crime datasets (DUI, arson, or homicide). It would be beneficial if you would choose crimes with contrasting patterns. For your analysis, you should choose whatever methods discussed in this lesson seem the most useful, and present your findings in the form of maps, graphs, and accompanying commentary.

As you work your way through the R code keep the following ideas in mind:

  • What were your overall findings about crime in your study area?
  • Where did crimes take place? Was there a particular spatial distribution associated with each of the crimes? Did they take place in a particular part of the city?
  • Did the different crimes you assessed cluster in different parts of the study area or did they occur in the same parts of the city?
  • What additional types of analysis would be useful?