{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:46:38Z","timestamp":1772822798990,"version":"3.50.1"},"reference-count":119,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T00:00:00Z","timestamp":1632960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771423, 41491339, 41930102, and 41601408"],"award-info":[{"award-number":["41771423, 41491339, 41930102, and 41601408"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landform recognition is one of the most significant aspects of geomorphology research, which is the essential tool for landform classification and understanding geomorphological processes. Watershed object-based landform recognition is a new spot in the field of landform recognition. However, in the relevant studies, the quantitative description of the watershed generally focused on the overall terrain features of the watershed, which ignored the spatial structure and topological relationship, and internal mechanism of the watershed. For the first time, we proposed an effective landform recognition method from the perspective of the watershed spatial structure, which is separated from the previous studies that invariably used terrain indices or texture derivatives. The slope spectrum method was used herein to solve the uncertainty issue of the determination on the watershed area. Complex network and P\u2013N terrain, which are two effective methodologies to describe the spatial structure and topological relationship of the watershed, were adopted to simulate the spatial structure of the watershed. Then, 13 quantitative indices were, respectively, derived from two kinds of watershed spatial structures. With an advanced machine learning algorithm (LightGBM), experiment results showed that the proposed method showed good comprehensive performances. The overall accuracy achieved 91.67% and the Kappa coefficient achieved 0.90. By comparing with the landform recognition using terrain indices or texture derivatives, it showed better performance and robustness. It was noted that, in terms of loess ridge and loess hill, the proposed method can achieve higher accuracy, which may indicate that the proposed method is more effective than the previous methods in alleviating the confusion of the landforms whose morphologies are complex and similar. In addition, the LightGBM is more suitable for the proposed method, since the comprehensive manifestation of their combination is better than other machine learning methods by contrast. Overall, the proposed method is out of the previous landform recognition method and provided new insights for the field of landform recognition; experiments show the new method is an effective and valuable landform recognition method with great potential as well as being more suitable for watershed object-based landform recognition.<\/jats:p>","DOI":"10.3390\/rs13193926","type":"journal-article","created":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T21:26:20Z","timestamp":1633728380000},"page":"3926","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Automatic Landform Recognition from the Perspective of Watershed Spatial Structure Based on Digital Elevation Models"],"prefix":"10.3390","volume":"13","author":[{"given":"Siwei","family":"Lin","sequence":"first","affiliation":[{"name":"Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350116, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}]},{"given":"Nan","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350116, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}]},{"given":"Zhuowen","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350116, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1007\/s41324-018-0209-8","article-title":"A review of landform classification methods","volume":"26","author":"Mokarram","year":"2018","journal-title":"Spat. Inf. Res."},{"key":"ref_2","first-page":"558","article-title":"Landform classification in raster geo-images","volume":"Volume 3287","author":"Sanfeliu","year":"2004","journal-title":"Progress in Pattern Recognition, Image Analysis and Applications"},{"key":"ref_3","first-page":"16","article-title":"Review of automatic classification methods for geomorphic morphological types","volume":"33","author":"Wang","year":"2017","journal-title":"Geogr. Geo Inf. Sci."},{"key":"ref_4","first-page":"15","article-title":"Geomorphometry-Automatic Landform Classification","volume":"36","year":"2018","journal-title":"J. Geogr. Cograf. Derg."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1080\/13658810802467969","article-title":"Morphometric characterisation of landform from DEMs","volume":"24","author":"Wang","year":"2010","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.geomorph.2010.09.029","article-title":"Geomorphometry and landform mapping: What is a landform?","volume":"137","author":"Evans","year":"2012","journal-title":"Geomorphology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.geomorph.2012.11.005","article-title":"Geomorphons\u2014A pattern recognition approach to classification and mapping of landforms","volume":"182","author":"Jasiewicz","year":"2013","journal-title":"Geomorphology"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2266","DOI":"10.1002\/esp.1659","article-title":"Residual relief separation: Digital elevation model enhancement for geomorphological mapping","volume":"33","author":"Hiller","year":"2008","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.geomorph.2006.04.013","article-title":"Automated classification of landform elements using object-based image analysis","volume":"81","author":"Blaschke","year":"2006","journal-title":"Geomorphology"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.isprsjprs.2019.09.018","article-title":"Multi-modal deep learning for landform recognition","volume":"158","author":"Du","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1007\/s11442-021-1853-9","article-title":"Geomorphology-oriented digital terrain analysis: Progress and perspectives","volume":"31","author":"Xiong","year":"2021","journal-title":"J. Geogr. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/S0165-0114(99)00011-1","article-title":"High-resolution landform classification using fuzzy k-means","volume":"113","author":"Burrough","year":"2000","journal-title":"Fuzzy Sets Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1007\/s11629-016-4320-9","article-title":"Automatic recognition of loess landforms using Random Forest method","volume":"14","author":"Zhao","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1002\/esp.3290160105","article-title":"Automated recognition of valley heads from digital elevation models","volume":"16","author":"Tribe","year":"1991","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.geomorph.2011.06.027","article-title":"Geospatial technologies and digital geomorphological mapping: Concepts, issues and research","volume":"137","author":"Bishop","year":"2012","journal-title":"J. Geomorphol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1111\/j.1467-8306.1964.tb00470.x","article-title":"Analysis of properties in land form geography: An application to broad-scale land form mapping","volume":"54","author":"Hammond","year":"1964","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/S0165-0114(99)00014-7","article-title":"A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic","volume":"113","author":"MacMillan","year":"2000","journal-title":"Fuzzy Sets Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.1016\/j.cageo.2011.04.001","article-title":"An object-oriented approach to automated landform mapping: A case study of drumlins","volume":"37","author":"Saha","year":"2011","journal-title":"Comput. Geosci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/B978-0-444-53446-0.00008-2","article-title":"Digital Mapping: Visualisation, interpretation and quantification of landforms","volume":"Volume 15","author":"Smith","year":"2011","journal-title":"Developments in Earth Surface Processes"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Stepinski, T.F., Ghosh, S., and Vilalta, R. (2006, January 7\u201310). Automatic recognition of landforms on Mars using terrain segmentation and classification. Proceedings of the International Conference on Discovery Science, Barcelona, Spain.","DOI":"10.1007\/11893318_26"},{"key":"ref_21","first-page":"103","article-title":"Landform recognition in granite mountains in East Asia (Seoraksan, Republic of Korea, and Huangshan and Sanqingshan, China)\u2014A contribution of geomorphology to the UNESCO World Heritage","volume":"37","author":"Woo","year":"2018","journal-title":"Quaest. Geogr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"105230","DOI":"10.1016\/j.enggeo.2019.105230","article-title":"Geomorphology-and geophysics-based recognition of stages of deep-seated slope deformation (Sudetes, SW Poland)","volume":"260","author":"Kasprzak","year":"2019","journal-title":"Eng. Geol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Yang, X., Tang, G., Meng, X., and Xiong, L. (2019). Classification of Karst Fenglin and Fengcong Landform Units Based on Spatial Relations of Terrain Feature Points from DEMs. Remote Sens., 11.","DOI":"10.3390\/rs11161950"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"107045","DOI":"10.1016\/j.geomorph.2020.107045","article-title":"Deep learning-based approach for landform classification from integrated data sources of digital elevation model and imagery","volume":"354","author":"Li","year":"2020","journal-title":"Geomorphology"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhou, X., Xie, X., Xue, Y., Xue, B., Qin, K., and Dai, W. (2020). Bag of Geomorphological Words: A Framework for Integrating Terrain Features and Semantics to Support Landform Object Recognition from High-Resolution Digital Elevation Models. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9110620"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Janu\u0161ait\u0117, R., Jukna, L., Jarmalavi\u010dius, D., Pupienis, D., and \u017dilinskas, G. (2021). A Novel GIS-Based Approach for Automated Detection of Nearshore Sandbar Morphological Characteristics in Optical Satellite Imagery. Remote Sens., 13.","DOI":"10.3390\/rs13112233"},{"key":"ref_27","first-page":"523","article-title":"Drainage basin object-based method for regional-scale landform classification: A case study of loess area in China","volume":"39","author":"Xiong","year":"2018","journal-title":"Phys. Geogr."},{"key":"ref_28","first-page":"452","article-title":"Study on loess landform classification based on random forest","volume":"22","author":"Cao","year":"2020","journal-title":"J. Geo Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/j.jas.2011.11.001","article-title":"Object-based landform delineation and classification from DEMs for archaeological predictive mapping","volume":"39","author":"Verhagen","year":"2012","journal-title":"J. Archaeol. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.geomorph.2011.03.003","article-title":"Object representations at multiple scales from digital elevation models","volume":"129","author":"Eisank","year":"2011","journal-title":"Geomorphology"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.isprsjprs.2013.09.014","article-title":"Geographic object-based image analysis\u2013towards a new paradigm","volume":"87","author":"Blaschke","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1080\/15481603.2018.1426092","article-title":"Geographic object-based image analysis (GEOBIA): Emerging trends and future opportunities","volume":"55","author":"Chen","year":"2018","journal-title":"GIScience Remote. Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1029\/TR038i006p00913","article-title":"Quantitative analysis of watershed geomorphology","volume":"38","author":"Strahler","year":"1957","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1080\/13658816.2012.756882","article-title":"A cellular automata model for simulating the evolution of positive\u2013negative terrains in a small loess watershed","volume":"27","author":"Cao","year":"2013","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/S0301-4797(05)80003-9","article-title":"Applied land classification for surface water quality management: II. Land process classification","volume":"31","author":"Huang","year":"1990","journal-title":"J. Environ. Manag."},{"key":"ref_37","first-page":"1592","article-title":"Study on the classification of typical loess geomorphology facing sub-basin units","volume":"36","author":"Wang","year":"2019","journal-title":"Arid Zone Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1257","DOI":"10.1111\/j.1752-1688.2004.tb01584.x","article-title":"Watershed classification using canonical correspondence analysis and clustering techniques: A cautionary note 1","volume":"40","author":"Caratti","year":"2004","journal-title":"J. Am. Water Resour. Assoc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Monteiro, F.C., and Campilho, A. (2008, January 8\u201311). Watershed framework to region-based image segmentation. Proceedings of the 2008 19th International Conference on Pattern Recognition, Tampa, FL, USA.","DOI":"10.1109\/ICPR.2008.4761587"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1016\/j.scitotenv.2018.07.269","article-title":"Quantification of subsurface hydrologic connectivity in four headwater catchments using graph theory","volume":"646","author":"Zuecco","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_41","first-page":"546","article-title":"Accuracy improvement of graph-cut image segmentation by using watershed","volume":"341","author":"Rong","year":"2012","journal-title":"Adv. Mater. Res."},{"key":"ref_42","first-page":"2070013","article-title":"Applications of graph theory","volume":"7","author":"Pirzada","year":"2007","journal-title":"J. Korean Soc. Ind. Appl. Math."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.earscirev.2015.02.002","article-title":"Graph theory in the geosciences","volume":"143","author":"Phillips","year":"2015","journal-title":"Earth Sci. Rev."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1038\/35065725","article-title":"Exploring complex networks","volume":"410","author":"Strogatz","year":"2001","journal-title":"Nature"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.jhydrol.2008.05.022","article-title":"Applications of network analysis for adaptive management of artificial drainage systems in landscapes vulnerable to sea level rise","volume":"357","author":"Poulter","year":"2008","journal-title":"J. Hydrol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"145","DOI":"10.5194\/npg-13-145-2006","article-title":"Complex-network description of seismicity","volume":"13","author":"Abe","year":"2006","journal-title":"Nonlinear Process. Geophys."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/j.proeng.2016.01.290","article-title":"Analysis of Urban Road Traffic Network Based on Complex Network","volume":"137","author":"Tian","year":"2016","journal-title":"Procedia Eng."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.jclepro.2016.07.046","article-title":"Product transportation distance based supplier selection in sustainable supply chain network","volume":"137","author":"Yu","year":"2016","journal-title":"J. Clean. Prod."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Hossmann, T., Spyropoulos, T., and Legendre, F. (2011, January 10\u201315). A complex network analysis of human mobility. Proceedings of the 2011 IEEE Conference on Computer Communications Workshops, Shanghai, China.","DOI":"10.1109\/INFCOMW.2011.5928936"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1098\/rsif.2009.0495","article-title":"The complex network of global cargo ship movements","volume":"7","author":"Kaluza","year":"2010","journal-title":"J. Royal Soc. Interface"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1080\/01441647.2013.848955","article-title":"Complex network topology of transportation systems","volume":"33","author":"Lin","year":"2013","journal-title":"Transp. Rev."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"012039","DOI":"10.1088\/1742-6596\/1706\/1\/012039","article-title":"Application of fuzzy combined SVM & graph theory for agriculture productivity prediction","volume":"1706","author":"Prabakaran","year":"2020","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/BF00125131","article-title":"Landscape graphs: Ecological modeling with graph theory to detect configurations common to diverse landscapes","volume":"8","author":"Cantwell","year":"1993","journal-title":"Landsc. Ecol."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Wu, X., Yu, K., and Wang, X. (2011, January 10\u201315). On the growth of Internet application flows: A complex network perspective. Proceedings of the 2011 IEEE INFOCOM, Shanghai, China.","DOI":"10.1109\/INFCOM.2011.5935019"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2785","DOI":"10.1016\/j.cnsns.2013.12.026","article-title":"Propagation of computer virus both across the Internet and external computers: A complex-network approach","volume":"19","author":"Gan","year":"2014","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.geomorph.2014.12.024","article-title":"Graph theory\u2014Recent developments of its application in geomorphology","volume":"243","author":"Heckmann","year":"2015","journal-title":"Geomorphology"},{"key":"ref_57","unstructured":"Beauguitte, L., and Ducruet, C. (2011, January 1). Scale-free and small-world networks in geographical research: A critical examination. Proceedings of the 17th European Colloquium on Theoretical and Quantitative Geography, Athens, Greece."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"L10403","DOI":"10.1029\/2011GL046837","article-title":"Structure and controls of the global virtual water trade network","volume":"38","author":"Suweis","year":"2011","journal-title":"Geophys. Res. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3301","DOI":"10.5194\/hess-19-3301-2015","article-title":"Complex network theory, streamflow, and hydrometric monitoring system design","volume":"19","author":"Halverson","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"W06D07","DOI":"10.1029\/2005WR004108","article-title":"Trees, networks, and hydrology","volume":"42","author":"Rinaldo","year":"2006","journal-title":"Water Resour. Res."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1007\/s11442-010-0064-6","article-title":"Positive and negative terrains on northern Shaanxi Loess Plateau","volume":"20","author":"Zhou","year":"2010","journal-title":"J. Geogr. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1002\/hyp.9719","article-title":"Landform-oriented flow-routing algorithm for the dual-structure loess terrain based on digital elevation models","volume":"28","author":"Xiong","year":"2014","journal-title":"Hydrol. Process."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.1007\/s11629-016-4227-5","article-title":"Quantifying spatial scale of positive and negative terrains pattern at watershed-scale: Case in soil and water conservation region on Loess Plateau","volume":"14","author":"Yang","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1007\/s11442-015-1245-0","article-title":"Slope spectrum critical area and its spatial variation in the Loess Plateau of China","volume":"25","author":"Tang","year":"2015","journal-title":"J. Geogr. Sci."},{"key":"ref_65","unstructured":"Zhou, Y. (2011). Study on Positive and Negative Topography and Spatial Differentiation of Loess Plateau Based on DEM. [Ph.D. Thesis, Nanjing Normal University]."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1130\/0016-7606(1956)67[571:QSA]2.0.CO;2","article-title":"Quantitative slope analysis","volume":"67","author":"Strahler","year":"1956","journal-title":"Geol. Soc. Am. Bull."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2637","DOI":"10.1007\/s11629-018-5000-8","article-title":"Hierarchy structure characteristics analysis for the China Loess watersheds based on gully node calibration","volume":"15","author":"Zhu","year":"2018","journal-title":"J. Mt. Sci."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1007\/s12145-020-00491-4","article-title":"Spatial variation of gully development in the loess plateau of China based on the morphological perspective","volume":"13","author":"Li","year":"2020","journal-title":"Earth Sci. Inform."},{"key":"ref_69","first-page":"192","article-title":"Extraction method for terrain feature point considering spatial feature","volume":"46","author":"Wang","year":"2021","journal-title":"Sci. Surv. Mapp."},{"key":"ref_70","first-page":"173","article-title":"Extraction of River Network in Three Gorges Reservoir Area Based on Mean Change Point Analysis","volume":"37","author":"Lai","year":"2012","journal-title":"Sci. Surv. Mapp."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2751","DOI":"10.1029\/98WR01474","article-title":"Hillslope processes, drainage density, and landscape morphology","volume":"34","author":"Tucker","year":"1998","journal-title":"Water Resour. Res."},{"key":"ref_72","unstructured":"Wang, T. (2015). A Preliminary Study on Population Characteristics of Gullies in Small Watershed of the Loess Plateau. [Doctoral Dissertation, Nanjing Normal University]."},{"key":"ref_73","first-page":"165","article-title":"Study on the influence of slope classification on surface slope spectrum","volume":"34","author":"Zhu","year":"2009","journal-title":"Sci. Surv. Mapp."},{"key":"ref_74","first-page":"1747","article-title":"Evolution of slope spectrum of construction land in China and influence of slope climbing","volume":"76","author":"Dang","year":"2021","journal-title":"Acta Geogr. Sin."},{"key":"ref_75","first-page":"172","article-title":"Study on minimum area threshold for slope statistical analysis","volume":"45","author":"Yang","year":"2020","journal-title":"Sci. Surv. Mapp."},{"key":"ref_76","first-page":"160","article-title":"Analysis of the relationship between slope spectrum information entropy and topographic factors in purple soil water erosion area in southwest China","volume":"36","author":"Zhao","year":"2020","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_77","unstructured":"Zhao, M., Tang, G., Chen, Z., and Zhu, H.C. (2002). Comparison of different slope classification systems and surface slope spectrum in loess hilly and gully region. Bull. Soil Water Conserv., 33\u201336."},{"key":"ref_78","first-page":"1109","article-title":"Watershed classification and runoff simulation in no data area based on SOM","volume":"33","author":"Yi","year":"2014","journal-title":"Progress Geogr."},{"key":"ref_79","first-page":"125","article-title":"Characteristics and spatial differentiation of slope spectrum in different types of arsenic sandstone","volume":"37","author":"Wu","year":"2021","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_80","unstructured":"Tang, G. (2015). Exploration and Practice of Digital Terrain Analysis on Loess Plateau, Science Press."},{"key":"ref_81","first-page":"539","article-title":"Uncertainty of slope spectrum information extraction based on DEM","volume":"10","author":"Wang","year":"2008","journal-title":"Geoinf. Sci."},{"key":"ref_82","first-page":"587","article-title":"Basic regional conditions for extraction and application of slope spectrum","volume":"27","author":"Wang","year":"2007","journal-title":"Sci. Geogr. Sin."},{"key":"ref_83","first-page":"824","article-title":"Uncertainty of ground slope in loess Plateau extracted from DEM","volume":"58","author":"Tang","year":"2003","journal-title":"Acta Geogr. Sin."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1007\/s11707-015-0519-2","article-title":"Slope spectrum variation in a simulated loess watershed","volume":"10","author":"Li","year":"2016","journal-title":"Front. Earth Sci."},{"key":"ref_85","first-page":"1570","article-title":"Research progress of digital topographic analysis of regional geomorphology in China","volume":"46","author":"Tang","year":"2017","journal-title":"Acta Geod. Et Cartogr. Sin."},{"key":"ref_86","first-page":"1","article-title":"Xiong LI-yang. Research progress of digital topographic analysis on loess Plateau","volume":"33","author":"Tang","year":"2017","journal-title":"Geogr. Geo Inf. Sci."},{"key":"ref_87","first-page":"2200","article-title":"Study on slope spectrum evolution of construction land in Shenzhen in 2000 and 2015","volume":"33","author":"Peng","year":"2018","journal-title":"J. Nat. Resour."},{"key":"ref_88","first-page":"1234","article-title":"Automatic identification and analysis of slope spectrum of loess landform types","volume":"17","author":"Liu","year":"2015","journal-title":"J. Geo Inf. Sci."},{"key":"ref_89","first-page":"245","article-title":"Object-oriented land use classification in Dongjiang River Basin based on GF-1 image","volume":"34","author":"Li","year":"2018","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_90","first-page":"13","article-title":"Scale effect and spatial differentiation of slope spectrum information entropy","volume":"9","author":"Li","year":"2007","journal-title":"Geoinf. Sci."},{"key":"ref_91","first-page":"86","article-title":"Study on the relationship between information entropy of mountain slope spectrum and topographic factors of soil and water loss. Sci","volume":"44","author":"Ju","year":"2019","journal-title":"Surv. Mapp."},{"key":"ref_92","first-page":"345","article-title":"Characteristics of surface slope spectrum in the upper reaches of Shule River basin","volume":"38","author":"Chu","year":"2015","journal-title":"Arid Land Geogr."},{"key":"ref_93","first-page":"97","article-title":"Study on soil and water conservation based on slope spectrum and information entropy: A case study of three counties in Hunan Province","volume":"39","author":"Chen","year":"2016","journal-title":"Geomat. Spat. Inf."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"433","DOI":"10.5194\/esurf-2-433-2014","article-title":"Transitional relation exploration for typical loess geomorphologic types based on slope spectrum characteristics","volume":"2","author":"Zhao","year":"2014","journal-title":"Earth Surf. Dyn."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1002\/esp.3290120107","article-title":"Quantitative Analysis of Land Surface Topography","volume":"12","author":"Zevenbergen","year":"1987","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s11431-008-5002-9","article-title":"Research on the slope spectrum of the Loess Plateau","volume":"51","author":"Tang","year":"2008","journal-title":"Sci. China Ser. E Technol. Sci."},{"key":"ref_97","first-page":"44","article-title":"Review of research along loess landform gully","volume":"28","author":"Zhang","year":"2012","journal-title":"Geogr. Geo Inf. Sci."},{"key":"ref_98","first-page":"261","article-title":"Study on automatic segmentation of positive and negative terrain of loess landform based on high-resolution DEM","volume":"30","author":"Zhou","year":"2010","journal-title":"Sci. Geogr. Sin."},{"key":"ref_99","unstructured":"Zhu, H., Tang, G., Zhang, Y., Yi, H., and Li, M. (2003). Extraction of gully line in loess hilly region based on DEM. Bull. Soil Water Conserv., 43\u201345."},{"key":"ref_100","unstructured":"Tang, G., and Yang, X. (2012). ArcGIS Gis Spatial Analysis Experiment Course, Science Press. Version 2."},{"key":"ref_101","unstructured":"Lu, Z. (1991). Watershed Geomorphic System, Dalian Press."},{"key":"ref_102","first-page":"707","article-title":"Study on the classification system of 11 million digital landforms in China","volume":"11","author":"Zhou","year":"2009","journal-title":"J. Geo Inf. Sci."},{"key":"ref_103","first-page":"7","article-title":"Extraction and analysis of gully nodes based on geomorphological structures and catchment characteristics: A case study in the Loess Plateau of north Shaanxi province","volume":"23","author":"Zhu","year":"2012","journal-title":"Adv. Water Sci."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Tricot, C. (1995). Curves and Fractal Dimension, Springer.","DOI":"10.1007\/978-1-4612-4170-6"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"4150","DOI":"10.1021\/acs.jcim.9b00633","article-title":"LightGBM: An effective and scalable algorithm for prediction of chemical toxicity\u2013application to the Tox21 and mutagenicity data sets","volume":"59","author":"Zhang","year":"2019","journal-title":"J. Chem. Inf. modeling"},{"key":"ref_106","first-page":"6","article-title":"Comparison between XGBoost, LightGBM and CatBoost using a home credit dataset","volume":"13","year":"2019","journal-title":"Int. J. Comput. Inf. Eng."},{"key":"ref_107","first-page":"2003","article-title":"Simulation and effectiveness evaluation of network warfare based on LightGBM algorithm","volume":"40","author":"Chen","year":"2020","journal-title":"J. Comput. Appl."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Wang, D., Zhang, Y., and Zhao, Y. (2017, January 18). LightGBM: An effective miRNA classification method in breast cancer patients. Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics, Budapest, Hungary.","DOI":"10.1145\/3155077.3155079"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1502","DOI":"10.12928\/telkomnika.v14i4.3956","article-title":"SVM parameter optimization using grid search and genetic algorithm to improve classification performance","volume":"14","author":"Syarif","year":"2016","journal-title":"Telkomnika"},{"key":"ref_110","first-page":"77","article-title":"Fitting segmented regression models by grid search","volume":"29","author":"Lerman","year":"1980","journal-title":"J. R. Stat. Soc. Ser. C"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1162\/089976698300017197","article-title":"Approximate statistical tests for comparing supervised classification learning algorithms","volume":"10","author":"Dietterich","year":"1998","journal-title":"Neural Comput."},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Mei, Z., Xiang, F., and Zhen-hui, L. (2018, January 1). Short-term traffic flow prediction based on combination model of xgboost-lightgbm. Proceedings of the 2018 International Conference on Sensor Networks and Signal Processing (SNSP), Xi\u2019an, China.","DOI":"10.1109\/SNSP.2018.00069"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.elerap.2018.08.002","article-title":"Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning","volume":"31","author":"Ma","year":"2018","journal-title":"Electron. Commer. Res. Appl."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"67531R","DOI":"10.1117\/12.761894","article-title":"Quantitative analysis and spatial distribution of slope spectrum: A case study in the Loess Plateau in north Shaanxi province","volume":"6753","author":"Li","year":"2007","journal-title":"Geoinformatics 2007 Geospat. Inf. Sci."},{"key":"ref_115","unstructured":"Zhang, L. (2013). Study on Spatial Pattern of Loess Landform Based on Core Topographic Factor Analysis. [Master\u2019s Thesis, Nanjing Normal University]."},{"key":"ref_116","unstructured":"Zhang, W. (2011). Study on the Watershed Profile Spectrum of Loess Plateau in Northern Shaanxi Based on DEM. [Master\u2019s Thesis, Nanjing Normal University]."},{"key":"ref_117","unstructured":"Zhu, S. (2013). Study on the Elevation Integral Pedigree of Loess Plateau Watershed Area Based on DEM. [Ph.D. Thesis, Nanjing Normal University]."},{"key":"ref_118","unstructured":"Guth, P.L. (1999, January 1). Quantifying and visualizing terrain fabric from Digital Elevation Models. Proceedings of the Geocomputacion 99: Proceedings of the 4th International Conference of GeoComputacion, Fredericksburg, VA, USA."},{"key":"ref_119","doi-asserted-by":"crossref","unstructured":"Sivakumar, B., Puente, C.E., and Maskey, M.L. (2018). Complex Networks and Hydrologic Applications. Advances in Nonlinear Geosciences, Springer.","DOI":"10.1007\/978-3-319-58895-7_26"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/19\/3926\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:08:02Z","timestamp":1760166482000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/19\/3926"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,30]]},"references-count":119,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["rs13193926"],"URL":"https:\/\/doi.org\/10.3390\/rs13193926","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,30]]}}}