Date of Award:
Master of Science (MS)
Environment and Society
R. Douglas Ramsey
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.
Wells, W. Kevin, "Object-Based Segmentation and Classification of One Meter Imagery for Use in Forest Management Plans" (2010). All Graduate Theses and Dissertations. Paper 653.
Copyright for this work is retained by the student.