{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T08:25:15Z","timestamp":1770971115927,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T00:00:00Z","timestamp":1535673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"This research was funded by the GDAS\u2019 Special Project of Science and Technology Development (2017GDASCX-0804), the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06D336), the National Natural Science Foundation of China (41271454),","award":["This research was funded by the GDAS\u2019 Special Project of Science and Technology Development (2017GDASCX-0804), the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06D336), the National Natural Science Foundation of China (41271454),"],"award-info":[{"award-number":["This research was funded by the GDAS\u2019 Special Project of Science and Technology Development (2017GDASCX-0804), the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06D336), the National Natural Science Foundation of China (41271454),"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study explores the performance of Sentinel-2A Multispectral Instrument (MSI) imagery for extracting urban impervious surface using a modified linear spectral mixture analysis (MLSMA) method. Sentinel-2A MSI provided 10 m red, green, blue, and near-infrared spectral bands, and 20 m shortwave infrared spectral bands, which were used to extract impervious surfaces. We aimed to extract urban impervious surfaces at a spatial resolution of 10 m in the main urban area of Guangzhou, China. In MLSMA, a built-up image was first extracted from the normalized difference built-up index (NDBI) using the Otsu\u2019s method; the high-albedo, low-albedo, vegetation, and soil fractions were then estimated using conventional linear spectral mixture analysis (LSMA). The LSMA results were post-processed to extract high-precision impervious surface, vegetation, and soil fractions by integrating the built-up image and the normalized difference vegetation index (NDVI). The performance of MLSMA was evaluated using Landsat 8 Operational Land Imager (OLI) imagery. Experimental results revealed that MLSMA can extract the high-precision impervious surface fraction at 10 m with Sentinel-2A imagery. The 10 m impervious surface map of Sentinel-2A is capable of recovering more detail than the 30 m map of Landsat 8. In the Sentinel-2A impervious surface map, continuous roads and the boundaries of buildings in urban environments were clearly identified.<\/jats:p>","DOI":"10.3390\/s18092873","type":"journal-article","created":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T10:57:52Z","timestamp":1535713072000},"page":"2873","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linear Spectral Mixture Analysis"],"prefix":"10.3390","volume":"18","author":[{"given":"Rudong","family":"Xu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6330-7948","authenticated-orcid":false,"given":"Jianhui","family":"Xu","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Geography, Guangzhou 510070, China"},{"name":"Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, China"},{"name":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xu, J., Zhao, Y., Zhong, K., Ruan, H., and Liu, X. 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