{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T12:40:15Z","timestamp":1736253615905,"version":"3.32.0"},"reference-count":61,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42101056","42101378"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Provincial Natural Science Foundation of Jiangsu of China","award":["BK20210989"]},{"name":"Jiangsu Environmental Protection and Research Funds","award":["2019003"]},{"name":"Taihu Lake Water Pollution Control Special Funds","award":["TH2018402"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Widespread harmful cyanobacterial bloom is one of the most pressing concerns in lakes and reservoirs, resulting in a lot of negative ecological consequences and threatening public health. Ocean color instruments with low spatial resolution have been used to monitor cyanobacterial bloom in large lakes; however, they cannot be applied to small water bodies well. Here, the Multi-Spectral Instrument (MSI) onboard Sentinel-2A and -2B and the Operational Landsat Imager (OLI) onboard Landsat-8 were employed to assemble the virtual constellation and to track spatial and seasonal variations in floating algae blooms from 2016 to 2020 in a small eutrophic plateau lake: Lake Xingyun in China. The floating algae index (FAI) was calculated using Rayleigh-corrected reflectance in the red, near-infrared, and short-wave infrared bands. The MSI-derived FAI had a similar pattern to the OLI-derived FAI, with a mean absolute percentage error of 19.98% and unbiased percentage difference of 17.05%. Then, an FAI threshold, 0.0693, was determined using bimodal histograms of FAI images for floating algae extraction. The floating algae had a higher occurrence in the northern region than the southern region in this lake, whilst the occurrence of floating algae in summer and autumn was higher than that in spring and winter. Such a spatial and seasonal pattern was related to the variability in air temperature, wind speed and direction, and nutrients. The climatological annual mean occurrence of floating algae from 2016 to 2020 in Lake Xingyun exhibited a significant decrease, which was related to decreases in nutrients, resulting from efficient ecological restoration by the local government. This research highlighted the application of OLI-MSI virtual constellation on monitoring floating algae in a small lake, providing a practical and theoretical reference to monitor aquatic environments in small water bodies.<\/jats:p>","DOI":"10.3390\/rs13214479","type":"journal-article","created":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T03:08:41Z","timestamp":1636427321000},"page":"4479","source":"Crossref","is-referenced-by-count":23,"title":["Sentinel-2 and Landsat-8 Observations for Harmful Algae Blooms in a Small Eutrophic Lake"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3888-1849","authenticated-orcid":false,"given":"Miao","family":"Liu","sequence":"first","affiliation":[{"name":"Jiangsu Provincial Key Laboratory of Environmental Engineering, Jiangsu Provincial Academy of Environmental Science, Nanjing 210036, China"}]},{"given":"Hong","family":"Ling","sequence":"additional","affiliation":[{"name":"Jiangsu Provincial Key Laboratory of Environmental Engineering, Jiangsu Provincial Academy of Environmental Science, Nanjing 210036, China"}]},{"given":"Dan","family":"Wu","sequence":"additional","affiliation":[{"name":"Jiangsu Provincial Key Laboratory of Environmental Engineering, Jiangsu Provincial Academy of Environmental Science, Nanjing 210036, China"}]},{"given":"Xiaomei","family":"Su","sequence":"additional","affiliation":[{"name":"Jiangsu Provincial Key Laboratory of Environmental Engineering, Jiangsu Provincial Academy of Environmental Science, Nanjing 210036, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5329-2906","authenticated-orcid":false,"given":"Zhigang","family":"Cao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/j.rse.2018.08.026","article-title":"Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index","volume":"217","author":"Wang","year":"2018","journal-title":"Remote Sens. 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