FireRisk-Multi: A Dynamic Multimodal Fusion Framework with Geographic Feature-Driven Weighting for High-Precision Wildfire Risk
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https://ieee-dataport.org/documents/firerisk-multi-dynamic-multimodal-fusion-framework-geographic-feature-driven-weighting
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资源简介：
This study presents an integrated wildfire risk assessment framework combining multi-source geospatial data (NAIP imagery, SRTM topography, ERA5 meteorology, and MODIS NDVI) with machine learning. Our methodology features a novel weighted fusion approach for risk modeling, validated across 49 US regions. The system achieves 87% prediction accuracy with SHAP-interpretable feature importance, offering actionable insights for land management and emergency planning.
提供机构：
Qian Tang
