Geospatial phenomena such as forest fires, spread of disease, crime hot spots, earthquakes, and environmental pollution are usually observed by equipment such as satellites or by individual agencies such as the US Census, US Geological Service, and other agencies. The goal of geospatial process modeling is to fit a statistical model for the geospatial phenomenon of interest to observational data that are recorded either at a fixed set of geographical entities (such as sensor locations or census tracts) or at a random collection of observed events (such as earthquake locations, tree locations, and so on). In either of these geospatial process modeling situations, you often make many modeling decisions that can involve several assumptions. This workshop will show you how to use SAS® procedures for geospatial analysis to perform geospatial process modeling. It will also discuss facilities such as diagnostics and tests that enable you to make informed modeling decisions. This course is intended for a broad audience who are interested in geospatial analysis. Familiarity with geospatial data and experience with SAS procedures are recommended but not necessary.