{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T22:18:35Z","timestamp":1776982715812,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T00:00:00Z","timestamp":1496275200000},"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":["No. 41501469"],"award-info":[{"award-number":["No. 41501469"]}],"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>The retrieval of impervious surface information is a hot topic in remote sensing. However, researches on impervious surface retrieval from hyperspectral remote sensing imagery are rare. This paper illustrates a case study of information extraction from urban impervious surfaces based on hyperspectral remote sensing imagery that is intended to improve the image spectral resolution of impermeable materials. Fuzhou, Guangzhou, and Hangzhou were selected as test areas and EO-1 Hyperion images were used as data sources. The impervious surface features were retrieved from remote sensing images using linear spectral mixture analysis. A stepwise discriminant analysis was performed to select feature bands for impervious surface retrieval. A standard deviation analysis, correlation analysis, and principal component analysis were then carried out for each of those up to 158 valid Hyperion spectral bands. Eleven feature bands were selected using the stepwise discriminant analysis and a new image called Hyperion\u2019 was formed. The impervious surface was then retrieved from Hyperion\u2019. The results indicate that the extraction accuracy and coverage accuracy are high in all three test areas. Tests of eleven feature band combinations selected in different areas show very good representations of the band combinations in impervious surface retrieval, and can thus be used as optimal band combinations for impervious surface retrieval.<\/jats:p>","DOI":"10.3390\/rs9060550","type":"journal-article","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T10:36:36Z","timestamp":1496313396000},"page":"550","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Impervious Surface Information Extraction Based on Hyperspectral Remote Sensing Imagery"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3286-2428","authenticated-orcid":false,"given":"Fei","family":"Tang","sequence":"first","affiliation":[{"name":"Island Research Center, State Oceanic Administration, Pingtan 350400, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7158-466X","authenticated-orcid":false,"given":"Hanqiu","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Environment and Resources, Fuzhou University, Fuzhou 350116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S0034-4257(03)00082-8","article-title":"Effects of urbanization on the aquatic fauna of the Line Creek watershed, Atlanta\u2014A satellite perspective","volume":"86","author":"Gillies","year":"2003","journal-title":"Remote Sens. 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