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Rapid Loss of the Sierra Nevada's Largest Trees Driven by Fire

arXiv · AI, language, vision and robotics · article · Sep 15, 2026 · UTC

Large trees disproportionately contribute to biomass storage, habitat structure, and ecosystem functioning. However, their distribution and health dynamics remain poorly quantified at a regional scale. Here, a deep learning model (U-Net-ID) and canopy height models derived from sub-meter aerial imagery from 2020 were used to delineate all individual trees with crown area $\geq$ 100 m$^2$ across the Sierra Nevada Floristic Province. The model was trained using more than 3.3 million synthetic tree crowns and achieved a median Intersection over Union (IoU) of 0.602 when validated against an indep

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Evidence & attribution

First collected: 2026-09-20T08:20:57.646Z. This is not the publication date.