Abstract
Investigators discuss new findings in artificial intelligence. According to news originating from London, Canada, by NewsRx correspondents, research stated, “In many regions of the world, tornadoes travel through forested areas with low population densities, making downed trees the only observable damage indicator.” The news editors obtained a quote from the research from Western University: “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 highresolution 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 this is labor-intensive, often taking several days or weeks. To solve this, this paper describes a machine learning and image processing-based model that automatically extracts fallen trees from large-scale aerial imagery, assesses their fall directions, and produces an area-averaged treefall vector map with minimal initial human interaction.”
NETL
NSTL