Point Patterns I
Content for Monday, October 13, 2025
Point patterns, where the only data are the location of a set of points (and potentially a few attributes of the points), are among the simplest (in terms of data structure) and ubiquitous (in terms of their frequency in the real world) spatial data we will encounter. That said, statistical analysis of point patterns remains an area of rapid methodological development which continues to inform many areas of spatial statistical development.
Resources
Bigger Picture
Chapter 11: Point Pattern Analysis in Manuel Gimond’s Introduction to GIS and Spatial Analysis
bookdownproject provides a nice (and free) introduction to some of these introductory point process methods.Rings, circles, and null-models for point pattern analysis in ecology by (Wiegand and A. Moloney 2004) provides an introduction to metrics for spatial clustering with applications in ecology.
Ecological information from spatial patterns of plants: insights from point process theory by (Law et al. 2009) provides a “plants-eye view” linkage between the sorts of the data ecologists often collect and the (somewhat esoteric) math of point patterns. Don’t get intimidated by the math here, just try to get an intuition for how the density and distance metrics relate to theories of spatial processes.
Spatial Point Pattern Analysis and Its Application in Geographical Epidemiology by (Gatrell et al. 1996) provides a broad overview of point patterns and processes along with some extensions and critiques based on the nature of epidemiological data. Some important points here for anyone thinking about a process that might be considered “contagious” (or spreading).
Technical Details
Chapters 17 and 18 on Spatial Point Processes and the
spatstatpackage in Paula Moraga’s book Spatial Statistics for Data Science: Theory and Practice with R.Chapter 11 in (Pebesma and Bivand 2023) illustrates the interaction between the
sfpackage andspatstatpackage for point pattern analysis.
Objectives
By the end of today, you should be able to:
Define first, and second order effects in point patterns
Simulate point patterns in
spatstatCompare quadrat counts to kernel density estimates for describing point patterns
Slides
The slides for today’s lesson are available online as an HTML file. Use the buttons below to open the slides either as an interactive website or as a static PDF (for printing or storing for later). You can also click in the slides below and navigate through them with your left and right arrow keys.