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《Science of Surveying and Mapping》 2017-01
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An algorithm for gridded the DEM filling depressions for large river basins

LIU Yonghe;HU Yonghong;LI Yanli;School of Resources and Environment,Henan Polytechnic University;Key Laboratory of Digital Earth,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences;  
Currently there are a variety of commonly used algorithms for filling depressions and removing planar cells in extracting digital river networks from the digital elevation models(DEM)data.For the extraction for flat and large river basins,conventional depression-filling algorithm is still difficult to ensure the complete extraction of river networks.This paper proposes a method based on an existing algorithm,which takes the idea of gradual inundating the cells and using apriority queue.By modifying this algorithm,the inundating orders of all cells are exported to a matrix.Then the flow directions and accumulated flow directions are calculated from this matrix instead of the original DEM.For testing the algorithm,small scale and middle scale DEM with high resolution,the comparatively low-resolution DEM covering large river basins such as Yellow River basin and Yangtze River basin,the results show that the proposed method can extract complete river networks,but other algorithms have produced intermittent and erroneous river networks for large river basins.This indicates the proposed method is very robust,and it overcomes the shortcomings of the existing algorithms for depression filling of DEM data on large river basins.
【Fund】: 国家自然科学基金项目(41105074 41275108);; 河南理工大学博士研究基金项目(B2011-038);; 中国科学院数字地球重点实验室开放基金项目(2011LDE010)
【CateGory Index】: P208
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