Algorithms for Geospatial Intelligence Analysis
Exposes students to fundamental algorithms in geospatial intelligence and their application in methodological and substantive domains, and their implementation in computer programs and software systems. Current topics include spatial and space-time analysis, cartographic transformations, data compression and reduction, MapReduce and distributed data access, genetic algorithms, clustering and indexing algorithms, filtering algorithms, geometry and tessellation algorithms, routing algorithms, localization algorithms, and complexity and scaling. Implementation of algorithms will be explored through pseudo-code and a variety of scripting, data access, and programming languages.
Topics
- spatial and space-time analysis
- cartographic transformations
- data compression and reduction
- MapReduce and distributed data access
- genetic algorithms
- clustering and indexing algorithms
- filtering algorithms
- geometry and tessellation algorithms
- routing algorithms
- localization algorithms
- and complexity and scaling
Topics explicitly listed in official catalogue description
Prerequisites & course information
Recommended: Students taking the course must be familiar with data structures, basic GIS and RS concepts, and demonstrate basic understanding of using GIS and RS software. Restriction: Permission of BSOS-Geography department; or must be enrolled in Geographical Sciences MPS or graduate certificate program.
Sources
- Course catalogue ↗2026-2027