{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T02:57:34Z","timestamp":1779245854386,"version":"3.51.4"},"reference-count":55,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:00:00Z","timestamp":1642723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In China, landslides are abundant, widespread, and regular, destroying villages and agriculture and sometimes posing a threat to people\u2019s lives. The question of how to rapidly detect and attain landslide data is a significant topic of research, yet traditional measurement using medium-resolution remote sensing data is problematic. Object-oriented categorization is utilized in this research to extract landside data from high-resolution GF-1 and Sentinel-2 data. Data preprocessing begins with orthophoto correction, image matching, and data fusion, followed by band enhancement, which comprises band synthesis, principal component analysis, and filtering, and finally landside extraction using an object-oriented technique. The impact of geology, lithology, rainfall, and human activities on the occurrence of landslides in the study area is explored utilizing DEM data, visualization tools, remote sensing interpretation map, and other associated data. The studies are conducted in Shuicheng County, Guizhou Province, China, with a segmentation scale of 25 pixels and 14 classification feature parameters. Following that, the landslide mass is extracted and categorization findings of nearby characteristics are acquired. Finally, the destructiveness of the landslide is determined by comparing the results of object-oriented classification before and after the landslide. With a Kappa coefficient of 0.76 and a landslide extraction accuracy of 79.8%, the overall classification accuracy is 87%. Combined with the geological structure, rock lithology, spatial location, landslide occurrence process, elevation of the study area, precipitation and the impact of human activities, the causes of the landslide are discussed and analyzed. The early warning of other unknown landslides can be obtained by analyzing the features of the aforementioned components.<\/jats:p>","DOI":"10.3390\/rs14030502","type":"journal-article","created":{"date-parts":[[2022,1,23]],"date-time":"2022-01-23T20:34:40Z","timestamp":1642970080000},"page":"502","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Extraction of Landslide Information Based on Object-Oriented Approach and Cause Analysis in Shuicheng, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Yunfei","family":"Han","sequence":"first","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongguo","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8842-3224","authenticated-orcid":false,"given":"Muhammad","family":"Yasir","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266580, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunmei","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0126-9944","authenticated-orcid":false,"given":"Shah","family":"Nazir","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Swabi, Swabi 23430, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4324-2395","authenticated-orcid":false,"given":"Md Sakaouth","family":"Hossain","sequence":"additional","affiliation":[{"name":"Department of Geological Sciences, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saleem","family":"Ullah","sequence":"additional","affiliation":[{"name":"Department of Space Science, Institute of Space Technology, Islamabad 45600, Pakistan"},{"name":"GIS & Space Applications in Geosciences (G-SAG) Lab, National Center of GIS & Space Applications (NCGSA), Institute of Space Technology, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2562-3477","authenticated-orcid":false,"given":"Sulaiman","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Swabi, Swabi 23430, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,21]]},"reference":[{"key":"ref_1","first-page":"124","article-title":"Statistics and analysis of landslide disaster data in China in recent 60 years","volume":"10","author":"Sang","year":"2013","journal-title":"Sci. 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