Environmental Spatial Data Analysis

Department Numbers
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Information about events and attributes that is referenced to locations can provide special insights into social and environmental processes. By analyzing this information in ways that take advantage of the spatial dimensions, we search for spatial patterns to generate and test hypotheses about the causes and effects of these patterns. This course deals with the processing and quantitative treatment of spatial data for use in ecological and environmental analysis and assessment. The first topics of the class will address spatial data representation and visualization that make use of GIS for spatial analysis. The topics include discussion of transformation among spatial feature types, scale and resolution issues, sampling and data display. The remaining topics introduce multiple approaches to analysis of point and area data. We begin with point pattern analysis to test for patterns of points (e.g. clustering), then discuss geostatistical methods for estimation when the points represent locations of attribute measurements. We will look at a specific set of analytical tools for describing landscape patterns, derived from teh field of landscape ecology. Finally, we will look at methods for inferential analysis using area-based measurements. Assignments involve computer exercises using real social and physical environmental data. Students are to read and report on applications of the methods studied in the lectures and assignments.

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Minimum Credits: 
Maximum Credits: 
Pass/Fail or S/U optional
EAS 531 and EAS 538 or equivalent

Terms Offered

Fall Semester: 
Winter Semester: 

This course is taught every other year.