Point Pattern Analysis
Content for Monday, October 17, 2022
Much of the development in statistical techniques for spatial data is rooted in the analysis of point processes. This is, perhaps, unsurprising given that the the point is the simplest of our different data models and the least ambiguous to reference spatially. Although points may be a “simpler” geometry, the analyses associated with them are far from simple. Today’s lecture is only the briefest of introductions to point pattern analysis, but hopefully will get you comfortable with the ideas and terminology behind more advanced analyses.
Resources
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.
Improving the usability of spatial point process methodology: an interdisciplinary dialogue between statistics and ecology by Janine Illian (a major contributor to modern point pattern analyses) and David Burslem (a Scottish plant ecologist) (Illian and Burslem 2017) is a fairly modern take on the challenges associated with point process modeling in ecology.
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.
Objectives
By the end of today you should be able to:
Define a point process and their utility for ecological applications
Define first and second-order Complete Spatial Randomness
Use several common functions to explore point patterns
Leverage point patterns to interpolate missing data
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.
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