{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T04:42:58Z","timestamp":1780461778837,"version":"3.54.1"},"reference-count":24,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T00:00:00Z","timestamp":1667001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["2017YFE0119600"],"award-info":[{"award-number":["2017YFE0119600"]}]},{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["51874306"],"award-info":[{"award-number":["51874306"]}]},{"name":"National Key Research and Development Program of China","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"National Key Research and Development Program of China","award":["2017YFE0119600"],"award-info":[{"award-number":["2017YFE0119600"]}]},{"name":"National Key Research and Development Program of China","award":["51874306"],"award-info":[{"award-number":["51874306"]}]},{"name":"Natural Science Foundation of China","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"Natural Science Foundation of China","award":["2017YFE0119600"],"award-info":[{"award-number":["2017YFE0119600"]}]},{"name":"Natural Science Foundation of China","award":["51874306"],"award-info":[{"award-number":["51874306"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mastering urban change information is of great importance and significance in practical areas such as urban development planning, land management, and vegetation cover. At present, high-resolution remote sensing images and deep learning techniques have been widely used in the detection of urban information changes. However, most of the existing change detection networks are Siamese networks based on encoder\u2013decoder architectures, which tend to ignore the pixel-to-pixel relationships and affect the change detection results. To solve this problem, we introduced a generative adversarial network (GAN). The change detection network based on the encoder\u2013decoder architecture was used as the generator of the GAN, and the Jensen-Shannon(JS) scatter in the GAN model was replaced by the Wasserstein distance. An urban scene change detection dataset named XI\u2019AN-CDD was produced to verify the effectiveness of the algorithm. Compared with the baseline model of the change detection network, our generator outperformed it significantly and had higher feature integrity. When the GAN was added, the detected feature integrity was better, and the F1-score increased by 4.4%.<\/jats:p>","DOI":"10.3390\/rs14215448","type":"journal-article","created":{"date-parts":[[2022,10,30]],"date-time":"2022-10-30T09:01:42Z","timestamp":1667120502000},"page":"5448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Use of GAN to Help Networks to Detect Urban Change Accurately"],"prefix":"10.3390","volume":"14","author":[{"given":"Chenyang","family":"He","sequence":"first","affiliation":[{"name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China"},{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7883-9506","authenticated-orcid":false,"given":"Yindi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China"},{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihong","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1007\/s10661-015-4295-y","article-title":"Urban development change detection based on Multi-Temporal Satellite Images as a fast tracking approach\u2014A case study of Ahwaz County, southwestern Iran","volume":"187","author":"Malmir","year":"2015","journal-title":"Environ. 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