{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:13:22Z","timestamp":1775913202833,"version":"3.50.1"},"reference-count":60,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T00:00:00Z","timestamp":1657843200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42171373"],"award-info":[{"award-number":["42171373"]}]},{"name":"National Natural Science Foundation of China","award":["SKLGIE2019-M-3-1"],"award-info":[{"award-number":["SKLGIE2019-M-3-1"]}]},{"name":"National Natural Science Foundation of China","award":["GLAB2020ZR07"],"award-info":[{"award-number":["GLAB2020ZR07"]}]},{"name":"National Natural Science Foundation of China","award":["GLAB2020ZR17"],"award-info":[{"award-number":["GLAB2020ZR17"]}]},{"name":"National Natural Science Foundation of China","award":["2019CFA023"],"award-info":[{"award-number":["2019CFA023"]}]},{"name":"National Natural Science Foundation of China","award":["220100035"],"award-info":[{"award-number":["220100035"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["42171373"],"award-info":[{"award-number":["42171373"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["SKLGIE2019-M-3-1"],"award-info":[{"award-number":["SKLGIE2019-M-3-1"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["GLAB2020ZR07"],"award-info":[{"award-number":["GLAB2020ZR07"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["GLAB2020ZR17"],"award-info":[{"award-number":["GLAB2020ZR17"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["2019CFA023"],"award-info":[{"award-number":["2019CFA023"]}]},{"name":"state Key Laboratory of Geo-Information Engineering","award":["220100035"],"award-info":[{"award-number":["220100035"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["42171373"],"award-info":[{"award-number":["42171373"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["SKLGIE2019-M-3-1"],"award-info":[{"award-number":["SKLGIE2019-M-3-1"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["GLAB2020ZR07"],"award-info":[{"award-number":["GLAB2020ZR07"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["GLAB2020ZR17"],"award-info":[{"award-number":["GLAB2020ZR17"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["2019CFA023"],"award-info":[{"award-number":["2019CFA023"]}]},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education","award":["220100035"],"award-info":[{"award-number":["220100035"]}]},{"name":"Hubei Natural Science Fundation of China","award":["42171373"],"award-info":[{"award-number":["42171373"]}]},{"name":"Hubei Natural Science Fundation of China","award":["SKLGIE2019-M-3-1"],"award-info":[{"award-number":["SKLGIE2019-M-3-1"]}]},{"name":"Hubei Natural Science Fundation of China","award":["GLAB2020ZR07"],"award-info":[{"award-number":["GLAB2020ZR07"]}]},{"name":"Hubei Natural Science Fundation of China","award":["GLAB2020ZR17"],"award-info":[{"award-number":["GLAB2020ZR17"]}]},{"name":"Hubei Natural Science Fundation of China","award":["2019CFA023"],"award-info":[{"award-number":["2019CFA023"]}]},{"name":"Hubei Natural Science Fundation of China","award":["220100035"],"award-info":[{"award-number":["220100035"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["42171373"],"award-info":[{"award-number":["42171373"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["SKLGIE2019-M-3-1"],"award-info":[{"award-number":["SKLGIE2019-M-3-1"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["GLAB2020ZR07"],"award-info":[{"award-number":["GLAB2020ZR07"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["GLAB2020ZR17"],"award-info":[{"award-number":["GLAB2020ZR17"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["2019CFA023"],"award-info":[{"award-number":["2019CFA023"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["220100035"],"award-info":[{"award-number":["220100035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate bathymetric and topographical information is crucial for coastal and marine applications. In the past decades, owing to its low cost and high efficiency, satellite-derived bathymetry has been widely used to estimate the depth of shallow water in coastal areas. However, insufficient spectral bands and availability of in situ water depths limit the application of satellite-derived bathymetry. Currently, the investigation about the bathymetric potential of hyperspectral imaging is relatively insufficient based on datasets of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). In this study, Zhuhai-1 hyperspectral images and ICESat-2 datasets were utilized to perform nearshore bathymetry and explore the bathymetric capability by selecting different bands based on classical empirical models (the band ratio model and the linear band model). Furthermore, experimental results achieved at the South China Sea indicate that the combination of blue (2 and 3 band) and green (9 band) bands and the combination of red (10 and 12 band) and near-infrared (29 band) bands are most suitable to achieve nearshore bathymetry. Correspondingly, the highest accuracy of bathymetry reached root mean square error values of 0.98 m and 1.19 m for different band combinations evaluated through bathymetric results of reference water depth. The bathymetric accuracy of Zhuhai-1 image is similar with that of Sentinel-2 when employing the blue and green bands. The combination of red and near-infrared bands has a higher bathymetric accuracy for Zhuhai-1 image than that for Sentinel-2 image.<\/jats:p>","DOI":"10.3390\/rs14143406","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T01:53:22Z","timestamp":1658109202000},"page":"3406","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Investigating the Shallow-Water Bathymetric Capability of Zhuhai-1 Spaceborne Hyperspectral Images Based on ICESat-2 Data and Empirical Approaches: A Case Study in the South China Sea"],"prefix":"10.3390","volume":"14","author":[{"given":"Yuan","family":"Le","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengzhi","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifu","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"},{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongfang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"},{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lizhe","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"},{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.isprsjprs.2021.02.013","article-title":"A maximum bathymetric depth model to simulate satellite photon-counting lidar performance","volume":"174","author":"Zhang","year":"2021","journal-title":"ISPRS J. 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