five

"FireRisk-Multi: A Dynamic Multimodal Fusion Framework with Geographic Feature-Driven Weighting for High-Precision Wildfire Risk "

收藏
DataCite Commons2025-06-30 更新2026-05-03 收录
下载链接:
https://ieee-dataport.org/documents/firerisk-multi-dynamic-multimodal-fusion-framework-geographic-feature-driven-weighting
下载链接
链接失效反馈
官方服务:
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:
IEEE DataPort
创建时间:
2025-06-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作