水利水电技术（中英文）2026，Vol.57Issue(3)：138-153,16.DOI:10.13928/j.cnki.wrahe.2026.03.010
融合多源遥感的缺资料河槽地形构建与验证
Construction and validation of data-scarce river channel topography using integrated multi-source remote sensing
摘要
Abstract
[Objective]Topographic data of river channels is fundamental for hydrological monitoring.However,in data-scarce regions,existing method struggle to obtain high-accuracy river channel information,which has become a key bottleneck for hydrological observation.Using a 7-km river segment upstream and downstream of the Benzilan hydrological station on the Jinsha River as the study area,this study applies an integrated multi-source remote sensing approach to construct river channel topography,aiming to provide new technical pathways and solutions for terrain modelling in complex river segments and data-scarce settings.[Methods]Based on an unmanned-aerial-vehicle-derived digital elevation model(UAV-DEM)and measured cross-sectional elevation data from the hydrological station,river channel topography within water-level fluctuation ranges from dry and flood seasons was constructed by integrating surface water elevation data from the Surface Water and Ocean Topography(SWOT)satellite and shoreline data extracted from high-resolution remote sensing imagery.Additionally,comparative analysis was conducted with the river channel topographic data(GF7-DEM)generated from GF-7 stereo imagery during the dry season.[Results]The result showed that after correction,the GF7-DEM showed improved accuracy,with RMSE reduced from 0.717 8 m to 0.601 9 m,MAE reduced from 0.561 5 m to 0.476 2 m,and STD from 0.717 5 m to 0.596 m,and R2 increased from 0.909 5 to 0.930 1,indicating enhanced representation capability for large-scale river channel morphology.(2)The multi-source remote sensing-derived DEMs-RBF-DEM,EBK-DEM,and IDW-DEM all showed good spatial consistency when compared with UAV-DEM.The RBF method showed optimal performance,achieving the lowest errors(MAE=1.063 9 m,RMSE=1.330 5 m),the least dispersion(STD=1.284 9 m),and the relatively high correlation.(3)For large-scale river channel morphology representation,the corrected GF7-DEM(RMSE=0.601 9 m,MAE=0.476 2 m,STD=0.596 m,and R2=0.930 1)outperformed the RBF-DEM(RMSE=1.330 5 m,MAE=1.063 9 m,STD=1.284 9 m,and R2=0.792 9)in both accuracy and stability.However,when GF7 data were incomplete,the RBF-DEM served as a more effective alternative for terrain reconstruction in data-scarce regions.[Conclusion]GF7-DEM demonstrates strong capability in representing river channel topography,but it has high data acquisition requirements,necessitating the use of dry-season data for DEM generation and offering limited spatial coverage.In contrast,SWOT satellite data are abundant.Together with GF7-DEM,they complement each other to form an approach for acquiring topographic data in data-scarce regions.This provides fundamental support for research applications and management in different fields,including remote sensing-based runoff monitoring,river hydrodynamic process simulation,digital twin watersheds,river habitat evolution.关键词
缺资料河段/地形构建/GF-7卫星/SWOT卫星/精度验证/水文/无人机/多源遥感Key words
data-scarce river segments/topographic construction/GF-7 satellite/SWOT satellite/accuracy validation/hydrology/unmanned aerial vehicle/multi-source remote sensing分类
建筑与水利引用本文复制引用
赵建勋,龚家国,康艳,常紫倩,李泽林,崔磊磊,王英..融合多源遥感的缺资料河槽地形构建与验证[J].水利水电技术（中英文）,2026,57(3):138-153,16.基金项目
国家自然科学基金项目(长江水科学研究联合基金)(U2240202) （长江水科学研究联合基金）
国家自然科学基金项目(52394233) （52394233）
国家重点研发计划(2018YFC0506904) （2018YFC0506904）
