Landform classification based on landform geospatial structure-a case study on Loess Plateau of China

作     者：Siwei Lin Jing Xie Jiayin Deng Meng Qi Nan Chen 

作者机构：Key Laboratory of Spatial Data Mining & Information SharingMinistry of EducationFuzhou UniversityFuzhouPeople’s Republic of China The Academy of Digital China (Fujian)Fuzhou UniversityFuzhouPeople’s Republic of China State Key Laboratory of Resources and Environmental Information SystemInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of SciencesBeijingPeople’s Republic of China 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2022年第15卷第1期

页      面：1125-1148页

核心收录：

学科分类：07[理学] 0705[理学-地理学] 070501[理学-自然地理学] 

基　　金：supported by the National Natural Science Foundation of China[grant numbers 41771423 41491339 41771423 41491339 41930102 and 41601408 41771423 41930102 41601408 and 41491339] 

主　　题：DEM landform classification geomorphological mapping watershed geospatial structure complex network 

摘      要：Landform classification,which is a key topic of geography,is of great significance to a wide range of fields including human construction,geological structure research,environmental governance,*** studies of landform classification generally paid attention to the topographic or texture information,whilst the watershed spatial structure has not been *** study developed a new landform classification method based on watershed geospatial *** abstracting the landform into the internal and marginal structure,we adopted the gully weighted complex network(GWCN)and watershed boundary profile(WBP)to simulate the watershed geospatial *** various indices to quantitatively depict the watershed geospatial structure,we conducted the landform classification on the Northern Shaanxi of Loess Plateau with a watershed-based strategy and established the classification *** classified landform distribution has significant spatial aggregation and clear regional *** accuracy reached 89%and the kappa coefficient reached 0.87%.Besides,the proposed method has a positive response to some similar and complex *** general,the present study first utilized the watershed geospatial structure to conduct landform classification and is an efficient landform classification method with well accuracy and universality,offering additional insights for landform classification and mapping.