Land Cover and Land Use Change Analysis
Land Use Change and Water Resources in the Imperial-Mexicali Valley
Water both drives and is impacted by land cover change in arid regions. This project aims to map land cover change on the US-Mexico border and to document the major drivers of those changes through mixed methods approaches that integrate remote sensing, quantitative survey data, and qualitative interviews with growers on both sides of the US-Mexico border. This project is supported in part through the NOAA CREST program Leave geography site. Principal Investigator: Trent Biggs
- GEOG 572: Land Use Analysis
- GEOG 591: Remote Sensing of Environment
- GEOG 591L: Remote Sensing of Environment Laboratory
- GEOG 592: Intermediate Remote Sensing of Environment
- GEOG 592L: Intermediate Remote Sensing of Environment Laboratory
- GEOG 780: Seminar in Techniques of Spatial Analysis
Theoretical and practical approaches to land use management. Current and relevant techniques and policies at local, state and federal levels, aimed toward providing healthy and environmentally sound communities that provide positive benefits to society and the economy. Field trips may be arranged.
Acquiring and interpreting remotely sensed data of environment. Electromagnetic radiation processes, aerial and satellite imaging systems and imagery. Geographic analysis of selected human, terrestrial, and marine processes and resources.
Practical exercises, introductory processing, visual interpretation and mapping of remotely sensed imagery.
Digital image processing. Thermal infrared and microwave imaging systems and image interpretation principles. Geographic analysis of selected human, terrestrial, oceanographic, and atmospheric processes and resources.
Digital image processing, visual interpretation, mapping of thermal infrared, and microwave imagery.
Spatial analytic techniques from image processing, remote sensing, geographic information systems, cartography or quantitative methods. May be repeated with new content. See Class Schedule for specific content.