Land Use and Environmental Modeling

Planners are increasingly using spatial data and computational models to analyze existing patterns, identify and parameterize key trends and urban processes, visualize alternative futures, and evaluate development impacts. This class is a survey of methods, software, and concepts in modeling systems related to urban and environmental planning. In the first module of the course, students learn methods related to nature-urban interfaces. These models include site suitability analysis, landscape fragmentation analysis, hydrological modeling, pollution monitoring, among others. A second module introduces agent-based simulation of urban and environmental system. The final module of the course features land-use applications including supervised classification of remotely sensed data, and urban growth modeling. Students will learn basics of geo-spatial machine learning using the statistical software language R. No experience with R is required, however, basic familiarity with ArcGIS is required.