- Identify several cluster detection techniques and discuss their limitations
- Demonstrate the extension of spatial clustering to deal with clustering in space-time using the Know and Mantel tests
- Perform a cluster detection analysis to detect “hot spots” in a point pattern
- Discuss the characteristics of the various cluster detection techniques
This knowledge area embodies a variety of data driven analytics, geocomputational methods, simulation and model driven approaches designed to study complex spatial-temporal problems, develop insights into characteristics of geospatial data sets, create and test geospatial process models, and construct knowledge of the behavior of geographically-explicit and dynamic processes and their patterns.
Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been updated and expanded are in bold. Forthcoming, future topics are italicized.