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Automated Large-Scale Tornado Treefall Detection And Directional Analysis Using Machine Learning, Daniel G. Butt, Aaron L. Jaffe, Connell S. Miller, Gregory A. Kopp, David Sills
Automated Large-Scale Tornado Treefall Detection And Directional Analysis Using Machine Learning, Daniel G. Butt, Aaron L. Jaffe, Connell S. Miller, Gregory A. Kopp, David Sills
Civil and Environmental Engineering Publications
Abstract
In many regions of the world, tornadoes travel through forested areas with low population densities, making downed trees the only observable damage indicator. Current methods in the EF scale for analyzing tree damage may not reflect the true intensity of some tornadoes. However, new methods have been developed that use the number of trees downed or treefall directions from high-resolution aerial imagery to provide an estimate of maximum wind speed. Treefall Identification and Direction Analysis (TrIDA) maps are used to identify areas of treefall damage and treefall directions along the damage path. Currently, TrIDA maps are generated manually, but …