{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T09:40:57Z","timestamp":1770457257416,"version":"3.49.0"},"reference-count":21,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T00:00:00Z","timestamp":1592179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"East China University of Technology","award":["DHBK2019003 (110\/1410000537)"],"award-info":[{"award-number":["DHBK2019003 (110\/1410000537)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Since the launch of the Landsat-8 (L8) Operational Land Imager (OLI) on 11 February 2013, there has been a continuous effort to produce reliable ocean color products by taking the advantages of its medium spatial resolution (30 m) and higher Signal to Noise Ratio (SNR). A Provisional Aquatic Reflectance product for the L8 OLI (L8PAR) has been recently released to the public to explore its potential for ocean color applications. This study used a six-year data record of L8 for development of a regionally tuned algorithm (RTA20) for estimating Chlorophyll-a (Chl-a) concentrations around the complex coastal environment of Hong Kong, and is the first to report the usability of the L8PAR product for coastal areas. Furthermore, this study validated three previously developed algorithms, namely RTA16, RTA17 and RTA19, and two ocean color algorithms (OC2 and OC3) modified for L8 OLI by NASA\u2019s Ocean Color group. Results indicate that the newly released L8PAR product has a high potential for estimating the coastal water Chl-a concentrations with higher detail and higher accuracy than previously. The RTA20 algorithm developed in this study outperformed the previous algorithms (RTA16, RTA17, RTA19, OC2 and OC3), e.g., with lower values for Root Mean Square Error (RMSE; 0.92 mg\/m3), bias (\u22120.26 mg\/m3) and mean ratio (1.29). Although inferior to the RTA20, the OC2 algorithm also performed well in terms of Pearson\u2019s correlation coefficient (r; 0.84), slope (6.87) and intercept (\u22128.44) while for RTA20 the values for r, slope and intercept were 0.96, 0.77 and 0.27, respectively. This preliminary evaluation reveals that the OC2 algorithm can be used as an operational algorithm for L8 Chl-a product generation for global coastal areas while RTA20 can be used as a regional algorithm for the routine monitoring of Chl-a concentrations around the coastal areas of Hong Kong or for coastal areas with similar water quality elsewhere in the world.<\/jats:p>","DOI":"10.3390\/rs12121938","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T12:16:57Z","timestamp":1592223417000},"page":"1938","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["First Experiences with the Landsat-8 Aquatic Reflectance Product: Evaluation of the Regional and Ocean Color Algorithms in a Coastal Environment"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7631-1599","authenticated-orcid":false,"given":"Majid","family":"Nazeer","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1022-3999","authenticated-orcid":false,"given":"Muhammad","family":"Bilal","sequence":"additional","affiliation":[{"name":"School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Janet Elizabeth","family":"Nichol","sequence":"additional","affiliation":[{"name":"Department of Geography, School of Global Studies, University of Sussex, Brighton BN19RH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6362-9840","authenticated-orcid":false,"given":"Weicheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3225-7452","authenticated-orcid":false,"given":"Mohammad M. M.","family":"Alsahli","sequence":"additional","affiliation":[{"name":"Department of Geography, College of Social Sciences, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3795-9832","authenticated-orcid":false,"given":"Muhammad Imran","family":"Shahzad","sequence":"additional","affiliation":[{"name":"Earth &amp; Atmospheric Remote Sensing Lab (EARL), Department of Meteorology, COMSATS University Islamabad, Islamabad 45550, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bijoy Krishna","family":"Gayen","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, West Bengal 721102, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.rse.2005.07.001","article-title":"An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation","volume":"98","author":"Werdell","year":"2005","journal-title":"Remote Sens. 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