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Object-Based Segmentation And Classification Of One Meter Imagery For Use In Forest Management Plans, W. Kevin Wells
Object-Based Segmentation And Classification Of One Meter Imagery For Use In Forest Management Plans, W. Kevin Wells
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
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 …
Modeling Bark Beetle Outbreak And Fire Interactions In Western U.S. Forests And The Invasion Potential Of An Invasive Puerto Rican Frog In Hawaii Using Remote Sensing Data, Simon A. Bisrat
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
I used Moderate-Resolution Imaging Spectroradiometer (MODIS) imagery to answer two ecological questions. In the first project, I investigated the interactions between bark beetle-caused tree mortality and fire occurrence in western U.S. forests. I used remotely sensed fire data detected by MODIS satellite and bark beetle-caused tree mortality data. I tested the hypothesis that there is an increased probability of fire incidence in bark beetle-damaged forests compared to healthy forests using conditional probability modeling across the national forests of the western U.S. regardless of forest type. My results did not show a consistent pattern (increase or decrease of conditional probability of …