{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T08:00:08Z","timestamp":1773907208427,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T00:00:00Z","timestamp":1636416000000},"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":["41771029, 41771417"],"award-info":[{"award-number":["41771029, 41771417"]}],"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>Impervious surfaces are key indicators for urbanization monitoring and watershed degradation assessment over space and time. However, most empirical studies only extracted impervious surface from spatial, temporal or spectral perspectives, paying less attention to integrating multiple dimensions in acquiring continuous changes in impervious surfaces. In this study, we proposed a neighborhood-based spatio-temporal filter (NSTF) to obtain the continuous change information of impervious surfaces from multi-temporal Landsat images in the Qinhuai River Basin (QRB), Jiangsu, China from 1988\u20132017, based on the results from semi-automatic decision tree classification. Moreover, we used the expansion intensity index (EII) and the landscape extension index (LEI) to further characterize the spatio-temporal characteristics of impervious surfaces on different spatial scales. The preliminary results showed that the overall accuracies of the final classification were about 95%, with the kappa coefficients ranging between 0.9 and 0.96. The QRB underwent rapid urbanization with the percentage of the impervious surfaces increasing from 2.72% in 1988 to 25.6% in 2017. Since 2006, the center of urbanization expansion was shaped from the urban built-up areas of Nanjing and Jiangning to non-urban built-up areas of the Jiangning, Lishui, and Jurong districts. The edge expansion occupied 73% on average among the different landscape expansion types, greatly beyond outlying (12%) and infilling (15%). The window size in the NSTF has a direct impact on the subsequent analysis. Our research could provide decision-making references for future urban planning and development in the similar basins.<\/jats:p>","DOI":"10.3390\/rs13224494","type":"journal-article","created":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T21:39:07Z","timestamp":1636493947000},"page":"4494","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Spatio-Temporal Analysis of Impervious Surface Expansion in the Qinhuai River Basin, China, 1988\u20132017"],"prefix":"10.3390","volume":"13","author":[{"given":"Shanshan","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1211-1205","authenticated-orcid":false,"given":"Yingxia","family":"Pu","sequence":"additional","affiliation":[{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"},{"name":"Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}]},{"given":"Shengfeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]},{"given":"Runjie","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]},{"given":"Maohua","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,9]]},"reference":[{"key":"ref_1","first-page":"409","article-title":"Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data","volume":"21","author":"Sun","year":"2013","journal-title":"Int. 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