{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T14:57:42Z","timestamp":1775228262501,"version":"3.50.1"},"reference-count":108,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T00:00:00Z","timestamp":1604448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Project of China","award":["No. 2016YFC0500203"],"award-info":[{"award-number":["No. 2016YFC0500203"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 41571427"],"award-info":[{"award-number":["No. 41571427"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Significant water quality changes have been observed in the Dongting Lake region due to environmental changes and the strong influence of human activities. To protect and manage Dongting Lake, the long-term dynamics of the water surface and algal bloom areas were systematically analyzed and quantified for the first time based on 17 years of Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The traditional methods (index-based threshold algorithms) were optimized by a dynamic learning neural network (DL-NN) to extract and identify the water surface area and algal bloom area while reducing the extraction complexity and improving the extraction accuracy. The extraction accuracy exceeded 94.5% for the water and algal bloom areas, and the analysis showed decreases in the algal bloom and water surface areas from 2001\u20132017. Additionally, the variations in the water surface and algal bloom areas are greatly affected by human activities and climatic factors. The results of these analyses can help us better monitor human contamination in Dongting Lake and take measures to control the water quality during certain periods, which is crucial for future management. Moreover, the traditional methods optimized by the DL-NN used in this study can be extended to other inland lakes to assess and monitor long-term temporal and spatial variations in algal bloom areas and can also be used to acquire baseline information for future assessments of the water quality of lakes.<\/jats:p>","DOI":"10.3390\/rs12213622","type":"journal-article","created":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T00:00:37Z","timestamp":1604534437000},"page":"3622","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6816-7104","authenticated-orcid":false,"given":"Mengmeng","family":"Cao","sequence":"first","affiliation":[{"name":"Hulunbeir Grassland Ecosystem Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1288-8428","authenticated-orcid":false,"given":"Kebiao","family":"Mao","sequence":"additional","affiliation":[{"name":"Hulunbeir Grassland Ecosystem Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"},{"name":"School of Physics and Electronic-Engineerring, Ningxia University, Ningchuan 750021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyi","family":"Shen","sequence":"additional","affiliation":[{"name":"Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1744-8974","authenticated-orcid":false,"given":"Tongren","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yibo","family":"Yan","sequence":"additional","affiliation":[{"name":"Hulunbeir Grassland Ecosystem Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijin","family":"Yuan","sequence":"additional","affiliation":[{"name":"Hulunbeir Grassland Ecosystem Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2016.12.006","article-title":"Fifteen-year monitoring of the turbidity dynamics in large lakes and reservoirs in the middle and lower basin of the Yangtze River, China","volume":"190","author":"Hou","year":"2017","journal-title":"Remote Sens. 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