Examine geographic patterns, relationships, and trends using GIS techniques and statistical methods. Spatial analysis helps solve complex spatial problems by analyzing location-based data for applications such as urban planning, environmental management, and transportation modeling.
- Fire hydrant spacing using network-based spatial analysis
- Automating geodatabase updates with Python and ArcPy
- Outdoor public art at UNM
- Industrial air releases and minority population in St. Louis County
- Spatial regression of traffic crashes in Austin
- Point pattern analysis of residential fires in Modesto
- Siting mobile library stops in rural West Virginia
- Pedestrian accessibility in Zurich
- Historic sites and urban accessibility in Boston
- Siting a raptor rehabilitation center in central New Mexico
- Interpolation of fine particulate matter across the U.S.
- South Fork post-fire burn severity assessment
- Glenn County NDVI trend and crop classification
- Comparing mapping-grade and survey-grade GNSS receivers
