{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T15:27:41Z","timestamp":1775834861647,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,11]],"date-time":"2017-08-11T00:00:00Z","timestamp":1502409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring the dynamic characteristics of the diffuse attenuation coefficient (Kd(490)) on the basis of the high temporal-resolution satellite data is critical for regulating the ecological environment of lake. By measuring the in-situ Kd(490) and the remote-sensing reflectance, a semi-analytical algorithm for Kd(490) was developed to determine the short-term variation of Kd(490). From 2006 to 2014, the data about 412 samples (among which 60 were used as match-up points, 282 for calibrating dataset and the remaining 70 for validating dataset) were gathered from nine expeditions to calibrate and validate the aforesaid semi-analytical algorithm. The root mean square percentage error (RMSP) and the mean absolute relative error (MAPE) of validation datasets were respectively 27.44% and 22.60 \u00b1 15.57%, while that of the match-up datasets were respectively 34.29% and 27.57 \u00b1 20.56%. These percentages indicate that the semi-analytical algorithm and Geostationary Ocean Color Imager (GOCI) data are applicable to obtain the short-term variation of Kd(490) in the turbid shallow inland waters. The short-term GOCI-observed Kd(490) shows a significant seasonal and spatial variation and a similar distribution to the matching Moderate Resolution Imaging Spectroradiometer (MODIS) which derived Kd(490). A comparative analysis on wind (observed by buoys) and GOCI-derived Kd(490) suggests that wind is a primary driving factor of Kd(490) variation, but the lacustrine morphometry affects the wind force that is contributing to Kd(490) variation.<\/jats:p>","DOI":"10.3390\/rs9080825","type":"journal-article","created":{"date-parts":[[2017,8,11]],"date-time":"2017-08-11T10:07:40Z","timestamp":1502446060000},"page":"825","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9833-5663","authenticated-orcid":false,"given":"Changchun","family":"Huang","sequence":"first","affiliation":[{"name":"School of Geography Science, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210023, China"},{"name":"Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6120-5806","authenticated-orcid":false,"given":"Ling","family":"Yao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"350","DOI":"10.4319\/lo.1984.29.2.0350","article-title":"Dependence of relationship between inherent and apparent optical properties of water on solar altitude","volume":"29","author":"Kirk","year":"1984","journal-title":"Limnol. 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