{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T11:37:16Z","timestamp":1777894636875,"version":"3.51.4"},"reference-count":67,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T00:00:00Z","timestamp":1699401600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Fundamental Resources Investigation Program","award":["2022FY100100"],"award-info":[{"award-number":["2022FY100100"]}]},{"name":"Science and Technology Fundamental Resources Investigation Program","award":["2020YFC1807102"],"award-info":[{"award-number":["2020YFC1807102"]}]},{"name":"Science and Technology Fundamental Resources Investigation Program","award":["XDA20050103"],"award-info":[{"award-number":["XDA20050103"]}]},{"name":"National Key Research and Development Program of China","award":["2022FY100100"],"award-info":[{"award-number":["2022FY100100"]}]},{"name":"National Key Research and Development Program of China","award":["2020YFC1807102"],"award-info":[{"award-number":["2020YFC1807102"]}]},{"name":"National Key Research and Development Program of China","award":["XDA20050103"],"award-info":[{"award-number":["XDA20050103"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022FY100100"],"award-info":[{"award-number":["2022FY100100"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2020YFC1807102"],"award-info":[{"award-number":["2020YFC1807102"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA20050103"],"award-info":[{"award-number":["XDA20050103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As an environmental parameter, the chlorophyll-a concentration (Chl-a) is essential for monitoring water quality and managing the marine ecosystem. However, current mainstream Chl-a inversion algorithms have limited accuracy and poor spatial and temporal generalization in Case II waters. In this study, we constructed a quantitative model for retrieving the spatial and temporal distribution of Chl-a in the Bohai\u2013Yellow Sea area using Geostationary Ocean Color Imager (GOCI) spectral remote sensing reflectance (Rrs\u03bb) products. Firstly, the GOCI\u00a0Rrs\u03bb\u00a0correction model based on measured spectral data was proposed and evaluated. Then, the feature variables of the band combinations with the highest correlation with Chl-a were selected. Subsequently, Chl-a inversion models were developed using three empirical ocean color algorithms (OC4, OC5, and YOC) and four machine learning methods: BP neural network (BPNN), random forest (RF), AdaBoost, and support vector regression (SVR). The retrieval results showed that the machine learning methods were much more accurate than the empirical algorithms and that the RF model retrieved Chl-a with the best performance and the highest prediction accuracy, with a determination coefficient R2 of 0.916, a root mean square error (RMSE) of 0.212 mg\u00b7m\u22123, and a mean absolute percentage error (MAPE) of 14.27%. Finally, the Chl-a distribution in the Bohai\u2013Yellow Sea using the selected RF model was derived and analyzed. Spatially, Chl-a was high in the Bohai Sea, including in Laizhou Bay, Bohai Bay, and Liaodong Bay, with a value higher than 4 mg\u00b7m\u22123. Chl-a in the Bohai Strait and northern Yellow Sea was relatively low, with a value of less than 3 mg\u00b7m\u22123. Temporally, the inversion results showed that Chl-a was considerably higher in winter and spring compared to autumn and summer. Diurnal variation retrieval effectively demonstrated GOCI\u2019s potential as a capable tool for monitoring intraday changes in chlorophyll-a concentrations.<\/jats:p>","DOI":"10.3390\/rs15225285","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T07:02:05Z","timestamp":1699426925000},"page":"5285","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Quantitative Retrieval of Chlorophyll-a Concentrations in the Bohai\u2013Yellow Sea Using GOCI Surface Reflectance Products"],"prefix":"10.3390","volume":"15","author":[{"given":"Jiru","family":"Wang","sequence":"first","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7069-1044","authenticated-orcid":false,"given":"Jiakui","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3875-0459","authenticated-orcid":false,"given":"Wuhua","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7850-1062","authenticated-orcid":false,"given":"Yanjiao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1002\/etc.3220","article-title":"Are harmful algal blooms becoming the greatest inland water quality threat to public health and aquatic ecosystems?","volume":"35","author":"Brooks","year":"2016","journal-title":"Environ. 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