摘要
The automatic extraction of gullies from digital elevation models(DEMs)has great application value in GIS and hydrology.Many types of algorithms have been developed to address this problem,and the well-known D8(Deterministic eight-node)algorithm has been widely applied and implemented in some commercial GIS software such as ArcGIS.However,a key parameter called flow accumulation threshold(FAT)must be determined in this process.Numerous studies focus on how to determine an optimal value for this parameter but ignore that the optimal threshold varies for different gullies,so the universality of a different optimal threshold parameter determined by different methods is poor.To address this problem,this study designs a parameter called surface concavity index(SC-index)that can describe the shape of gullies from the perspective of surface morphology.Based on this index,the positions of different gullies'heads are identified,and then the flow accumulation matrix calculated by the D8 algorithm is used as auxiliary data to extract the gully network in the research area.In this study,six small watersheds in the Loess Plateau in northern Shaanxi,China,were used as test areas to verify the validity of the proposed method in areas with various landform types.Experimental results show that gully heads in different test areas can be effectively identified by setting different SCindex thresholds that are related to the types of terrain in the test areas.Then,the entire gully network can be extracted in watersheds with the help of a D8 algorithm.The accuracy of the gully network extracted by the new method is better than the contrast method in all test areas.In test areas with a large area of flat land(e.g.,Chunhua),the difference between the total length of gullies extracted by the new method and the reference value is-2.77 km,while the corresponding value of the contrast method is 14.50 km.In test areas with large numbers of short gullies(e.g.,Jiuyuangou),the difference between the total length of gullies extracted by the new
基金
supported by Anhui Province Universities Outstanding Talented Person Support Project(No.gxyq2022097)
Major Project of Natural Science Research of Anhui Provincial Department of Education(No.KJ2021ZD0130)
“113”Industry Innovation Team of Chuzhou city in Anhui province
The guiding plan project of Chuzhou science and Technology Bureau(No.2021ZD008)
General Project of Natural Science Research of Anhui Provincial Department of Education(No.KJ2020B02)。
