{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T15:34:40Z","timestamp":1760369680593,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,21]],"date-time":"2021-01-21T00:00:00Z","timestamp":1611187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Nos. 61661043, 61971246, and 61631011"],"award-info":[{"award-number":["Nos. 61661043, 61971246, and 61631011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Equipment Pre-research Foundation of China","award":["Nos. JZX7Y20190253040901 and JZX7Y20190253041401"],"award-info":[{"award-number":["Nos. JZX7Y20190253040901 and JZX7Y20190253041401"]}]},{"name":"the Science and Technology Innovation Guidance Project of Inner Mongolia Autonomous Region","award":["Nos. KCBJ2017 and KCBJ2018014"],"award-info":[{"award-number":["Nos. KCBJ2017 and KCBJ2018014"]}]},{"name":"the National Science and Technology Major Project","award":["Nos.2018YFC1505502 and 55320190431"],"award-info":[{"award-number":["Nos.2018YFC1505502 and 55320190431"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.<\/jats:p>","DOI":"10.3390\/rs13030355","type":"journal-article","created":{"date-parts":[[2021,1,21]],"date-time":"2021-01-21T02:36:05Z","timestamp":1611196565000},"page":"355","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A Novel Unsupervised Classification Method for Sandy Land Using Fully Polarimetric SAR Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9071-9470","authenticated-orcid":false,"given":"Weixian","family":"Tan","sequence":"first","affiliation":[{"name":"College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China"},{"name":"Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China"}]},{"given":"Borong","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China"},{"name":"Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China"}]},{"given":"Chenyu","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China"},{"name":"Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7720-1183","authenticated-orcid":false,"given":"Pingping","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China"},{"name":"Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8045-8817","authenticated-orcid":false,"given":"Wei","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China"},{"name":"Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3263-8768","authenticated-orcid":false,"given":"Wen","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1093\/jpe\/rtw005","article-title":"Satellite remote sensing of grasslands: From observation to management","volume":"6","author":"Ali","year":"2016","journal-title":"J. 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