{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T05:29:21Z","timestamp":1761629361151,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,16]],"date-time":"2018-08-16T00:00:00Z","timestamp":1534377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFE0107100"],"award-info":[{"award-number":["2017YFE0107100"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51774270, 41604005"],"award-info":[{"award-number":["51774270, 41604005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Enterprise Commissioned Project","award":["D010102"],"award-info":[{"award-number":["D010102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The neighborhood-based method was proposed and widely used in the change detection of synthetic aperture radar (SAR) images because the neighborhood information of SAR images is effective to reduce the negative effect of speckle noise. Nevertheless, for the neighborhood-based method, it is unreasonable to use a fixed window size for the entire image because the optimal window size of different pixels in an image is different. Hence, if you let the neighborhood-based method use a large window to significantly suppress noise, it cannot preserve the detail information such as the edge of a changed area. To overcome this drawback, we propose a spatial-temporal adaptive neighborhood-based ratio (STANR) approach for change detection in SAR images. STANR employs heterogeneity to adaptively select the spatial homogeneity neighborhood and uses the temporal adaptive strategy to determine multi-temporal neighborhood windows. Experimental results on two data sets show that STANR can both suppress the negative influence of noise and preserve edge details, and can obtain a better difference image than other state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/rs10081295","type":"journal-article","created":{"date-parts":[[2018,8,16]],"date-time":"2018-08-16T11:39:08Z","timestamp":1534419548000},"page":"1295","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Spatial-Temporal Adaptive Neighborhood-Based Ratio Approach for Change Detection in SAR Images"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2267-9205","authenticated-orcid":false,"given":"Huifu","family":"Zhuang","sequence":"first","affiliation":[{"name":"NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongdong","family":"Fan","sequence":"additional","affiliation":[{"name":"NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6621-5408","authenticated-orcid":false,"given":"Kazhong","family":"Deng","sequence":"additional","affiliation":[{"name":"NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6305-4514","authenticated-orcid":false,"given":"Guobiao","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1109\/36.843009","article-title":"Automatic analysis of the difference image for unsupervised change detection","volume":"38","author":"Bruzzone","year":"2000","journal-title":"IEEE Trans. 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