{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T18:48:48Z","timestamp":1775760528293,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,12]],"date-time":"2017-06-12T00:00:00Z","timestamp":1497225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["61379032"],"award-info":[{"award-number":["61379032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science Foundation of Key Laboratory in Software Engineering of Yunnan Province","award":["2017SE205"],"award-info":[{"award-number":["2017SE205"]}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201504490008"],"award-info":[{"award-number":["201504490008"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study conducts an exploratory evaluation of the performance of the newly available Sentinel-2A Multispectral Instrument (MSI) imagery for mapping water bodies using the image sharpening approach. Sentinel-2 MSI provides spectral bands with different resolutions, including RGB and Near-Infra-Red (NIR) bands in 10 m and Short-Wavelength InfraRed (SWIR) bands in 20 m, which are closely related to surface water information. It is necessary to define a pan-like band for the Sentinel-2 image sharpening process because of the replacement of the panchromatic band by four high-resolution multi-spectral bands (10 m). This study, which aimed at urban surface water extraction, utilised the Normalised Difference Water Index (NDWI) at 10 m resolution as a high-resolution image to sharpen the 20 m SWIR bands. Then, object-level Modified NDWI (MNDWI) mapping and minimum valley bottom adjustment threshold were applied to extract water maps. The proposed method was compared with the conventional most related band- (between the visible spectrum\/NIR and SWIR bands) based and principal component analysis first component-based sharpening. Results show that the proposed NDWI-based MNDWI image exhibits higher separability and is more effective for both classification-level and boundary-level final water maps than traditional approaches.<\/jats:p>","DOI":"10.3390\/rs9060596","type":"journal-article","created":{"date-parts":[[2017,6,12]],"date-time":"2017-06-12T10:27:59Z","timestamp":1497263279000},"page":"596","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":281,"title":["Mapping of Urban Surface Water Bodies from Sentinel-2 MSI Imagery at 10 m Resolution via NDWI-Based Image Sharpening"],"prefix":"10.3390","volume":"9","author":[{"given":"Xiucheng","family":"Yang","sequence":"first","affiliation":[{"name":"ICube Laboratory, University of Strasbourg, 67081 Strasbourg, France"}]},{"given":"Shanshan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Earth & Space Sciences, Peking University, Beijing 100080, China"}]},{"given":"Xuebin","family":"Qin","sequence":"additional","affiliation":[{"name":"Depart of Computing Science, University of Alberta, Edmonton, T6G 2R3, Canada"}]},{"given":"Na","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Software, Yunnan University, Kunming 650091, China"}]},{"given":"Ligang","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Software & Microelectronucs, Peking University, Beijing 100080, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1109\/JSTARS.2012.2189099","article-title":"Automatic detection of rivers in high-resolution SAR data","volume":"5","author":"Klemenjak","year":"2012","journal-title":"IEEE J. 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