Date of Award:

5-2010

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Environment and Society

Committee Chair(s)

R. Douglas Ramsey

Committee

R. Douglas Ramsey

Committee

Mark W. Brunson

Committee

Michael R. Kuhns

Abstract

This research developed an ArcGIS Python model that extracts polygons from aerial imagery and assigns each polygon a vegetation type based on a modified set of landcover classes from the Southwest Regional Gap Analysis Project. The model showed an ability to generate polygons that accurately represent vegetation community boundaries across a large landscape. The model is for use by the Utah Division of Forestry, Fire, and State Lands to assist in the preparation of forest management plans. The model was judged useful because it was easy to use, it met a designated 50% threshold of useable polygons, and it met a designated 50% threshold of vegetation class assignment accuracy.

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