{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:50:18Z","timestamp":1760161818728,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T00:00:00Z","timestamp":1611792000000},"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":["41901372,41901072"],"award-info":[{"award-number":["41901372,41901072"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory","award":["GML2019ZD0301"],"award-info":[{"award-number":["GML2019ZD0301"]}]},{"name":"Science and Technology Program of Guangzhou","award":["202002030247"],"award-info":[{"award-number":["202002030247"]}]},{"name":"GDAS Project of Science and Technology Development","award":["2019GDASYL-0103004"],"award-info":[{"award-number":["2019GDASYL-0103004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Impervious surfaces (IS), the most common land cover in urban areas, not only provide convenience to the city, but also exert significant negative environmental impacts, thereby affecting the ecological environment carrying capacity of urban agglomerations. Most of the current research considers IS as a single land-cover type, yet this does not fully reflect the complex physical characteristics of various IS types. Therefore, limited information for urban micro-ecology and urban fine management can be provided through one IS land-cover type. This study proposed a finer IS classification scheme and mapped the detailed IS fraction in Guangzhou City, China using Landsat imagery. The IS type was divided into seven finer classes, including blue steel, cement, asphalt, other impervious surface, and other metal, brick, and plastic. Classification results demonstrate that finer IS can be well extracted from the Landsat imagery as all root mean square errors (RMSE) are less than 15%. Specially, the accuracies of asphalt, plastic, and cement are better than other finer IS types with the RMSEs of 7.99%, 8.48%, and 9.92%, respectively. Quantitative analyses illustrate that asphalt, other impervious surface, and brick are the dominant IS types in the study area with the percentages of 9.68%, 6.27%, and 4.45%, respectively, and they are mainly located in Yuexiu, Liwan, Haizhu, and Panyu districts. These results are valuable for research into urban fine management and can support the detailed analysis of urban micro-ecology.<\/jats:p>","DOI":"10.3390\/rs13030459","type":"journal-article","created":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T09:03:45Z","timestamp":1611824625000},"page":"459","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Extraction and Analysis of Finer Impervious Surface Classes in Urban Area"],"prefix":"10.3390","volume":"13","author":[{"given":"Wenyue","family":"Liao","sequence":"first","affiliation":[{"name":"College of Geographical Science, Harbin Normal University, Harbin 150025, China"},{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Yingbin","family":"Deng","sequence":"additional","affiliation":[{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9673-0638","authenticated-orcid":false,"given":"Miao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geographical Science, Harbin Normal University, Harbin 150025, China"}]},{"given":"Meiwei","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Geographical Science, Harbin Normal University, Harbin 150025, China"},{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}]},{"given":"Ji","family":"Yang","sequence":"additional","affiliation":[{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6330-7948","authenticated-orcid":false,"given":"Jianhui","family":"Xu","sequence":"additional","affiliation":[{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sun, Z., Wang, C., Guo, H., and Shang, R. 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