自然资源遥感2026，Vol.38Issue(2)：31-40,10.DOI:10.6046/zrzyyg.2025040
基于RepFNet印度河上游流域积雪覆盖度的反演研究
RepFNet-based inversion of fractional snow cover in the upper reaches of the Indus River
摘要
Abstract
Mapping the fractional snow cover(FSC)is significant for water resource management,especially in the upper reaches of the Indus River,where water resources are highly dependent on alpine snowmelt.This study proposed a RepVGG network-based FSC inversion model,RepFNet,which used FY-4A/AGRI remote sensing data and Landsat8 OLI images for FSC feature extraction.Moreover,this model incorporated upsampling and downsampling modules,an innovative attention mechanism,and a specific loss function,thereby enabling the FSC mapping of the upper reaches of the Indus River at 2 000-m resolution.The mapping results were validated using the MODIS data.The experimental results show that the RepFNet achieved a coefficient of determination of 0.667,a root mean square error(RMSE)of 0.090,a correlation coefficient(r)of 0.890,an explained variance score(EVS)of 0.683,and a Kappa coefficient of 0.468,remarkably outperforming the classical algorithms such as random forest and U-Net.Overall,the RepFNet model demonstrates excellent performance in FSC inversion,offering a novel technical solution for high-accuracy FSC monitoring.关键词
遥感图像/积雪覆盖度/印度河上游流域/RepVGG/注意力机制Key words
remote sensing image/fractional snow cover(FSC)/upper reaches of the Indus River/RepVGG/at-tention mechanism分类
信息技术与安全科学引用本文复制引用
王婧,阚希,刘旭,张永宏,周舟,朱灵龙,宫磊..基于RepFNet印度河上游流域积雪覆盖度的反演研究[J].自然资源遥感,2026,38(2):31-40,10.基金项目
国家自然科学基金项目"青藏高原复杂地形积雪覆盖率多源卫星协同反演研究"(编号:42105143)、"基于微波亮温重建的积雪深度超分辨率反演研究"(编号:42305158)、江苏省高等学校基础科学(自然科学)研究面上项目"基于微波亮温重建的积雪深度超分辨率反演研究"(编号:23KJB170025)、无锡市"太湖之光"科技攻关(基础研究)项目"面向边云协同的城市交通状态感知与预测方法研究"(编号:K20231021)和江苏省研究生科研与实践创新计划项目"青藏高原积雪覆盖度多卫星协调反演研究"(编号:SJCX24_0482)共同资助. （编号:42105143）
