{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:18:46Z","timestamp":1780636726686,"version":"3.54.1"},"reference-count":49,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T00:00:00Z","timestamp":1650499200000},"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>Algal blooms frequently occur in numerous lakes in China, risking human health and the environment. In contrast, aquatic vegetation contributes to water purification. Due to the similar spectral characteristics shared by algal and aquatic vegetation, both are hardly distinguishable in remote sensing imaging, especially in turbid water bodies. To address this challenge, this study constructed a method to effectively extract algal blooms and aquatic vegetation from the turbid water bodies using Sentinel 2 images with high spatial resolution. Our results showed that the accuracy of the extraction of vegetation information could reach 96.1%. Since this method combined the vegetation extraction results from multiple indices, it effectively tackled the mis-extraction when only the Floating Algae Index (FAI) or the Normalized Difference Vegetation Index (NDVI) is used in water with high turbidity. By combining the image time series information with the natural phenological characteristics of the aquatic vegetation and algal blooms, an improved Vegetation Presence Frequency (VPF) was developed. It effectively distinguished algal blooms and aquatic vegetation without actual measurement data. Based on the above method and process, the information of algal blooms and aquatic vegetation was sufficiently distinguished in five typical lakes in China (Lake Hulun, Lake Hongze, Lake Chaohu, Lake Taihu, and Lake Dianchi), and the spatial distribution was reasonably mapped. The overall identification accuracy of aquatic vegetation and algal blooms using the improved VPF ranged 71.8\u201384.3%. The spatial transferability test of the method in the independent lakes with the various optical properties indicated the prospects of its application in other turbid water bodies. This study should provide strong methodological and theoretical support for future monitoring of algal blooms in turbid water bodies with vigorous aquatic vegetation, especially in the absence of actual measurement data. This should have practical relevance for water environment management and governance departments.<\/jats:p>","DOI":"10.3390\/rs14091988","type":"journal-article","created":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T00:45:21Z","timestamp":1650761121000},"page":"1988","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Distinguishing Algal Blooms from Aquatic Vegetation in Chinese Lakes Using Sentinel 2 Image"],"prefix":"10.3390","volume":"14","author":[{"given":"Jing","family":"Pu","sequence":"first","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"College of Geographical Sciences, Changchun Normal University, Changchun 130032, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9996-2450","authenticated-orcid":false,"given":"Kaishan","family":"Song","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunfeng","family":"Lv","sequence":"additional","affiliation":[{"name":"College of Geographical Sciences, Changchun Normal University, Changchun 130032, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ge","family":"Liu","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chong","family":"Fang","sequence":"additional","affiliation":[{"name":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junbin","family":"Hou","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8801-5324","authenticated-orcid":false,"given":"Zhidan","family":"Wen","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,21]]},"reference":[{"key":"ref_1","unstructured":"Jeppesen, E., Sondergaard, M., Jensen, J.P., Kanstrup, E., and Petersen, B. (1996, January 16\u201320). Macrophytes and turbidity in brackish lakes with special emphasis on the role of top-down control. Proceedings of the Workshop on the Structuring Role of Submerged Macrophytes in Lakes, Freshwater Ctr, Silkeborg, Denmark."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/0169-5347(93)90254-M","article-title":"Alternative Equilibria in Shallow Lakes","volume":"8","author":"Scheffer","year":"1993","journal-title":"Trends Ecol. Evol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1007\/BF02804901","article-title":"Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences","volume":"25","author":"Anderson","year":"2002","journal-title":"Estuaries"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.hal.2015.07.009","article-title":"Harmful algal blooms and climate change: Learning from the past and present to forecast the future","volume":"49","author":"Wells","year":"2015","journal-title":"Harmful Algae"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.hal.2015.12.007","article-title":"A review of the global ecology, genomics, and biogeography of the toxic cyanobacterium, Microcystis spp","volume":"54","author":"Harke","year":"2016","journal-title":"Harmful Algae"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1038\/s41586-019-1648-7","article-title":"Widespread global increase in intense lake phytoplankton blooms since the 1980s","volume":"574","author":"Ho","year":"2019","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/s00248-012-0159-y","article-title":"Harmful Cyanobacterial Blooms: Causes, Consequences, and Controls","volume":"65","author":"Paerl","year":"2013","journal-title":"Microb. Ecol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1007\/s10295-003-0074-9","article-title":"Harmful algal blooms: Causes, impacts and detection","volume":"30","author":"Sellner","year":"2003","journal-title":"J. Ind. Microbiol. Biotechnol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.4319\/lo.2010.55.5.2025","article-title":"Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data","volume":"55","author":"Wynne","year":"2010","journal-title":"Limnol. Oceanogr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"215","DOI":"10.18307\/2009.0209","article-title":"Identification of algae-bloom and aquatic macrophytes in Lake Taihu from in-situ measured spectra data","volume":"21","author":"Junsheng","year":"2009","journal-title":"Lake Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2014.04.031","article-title":"Distinguishing surface cyanobacterial blooms and aquatic macrophytes using Landsat\/TM and ETM plus shortwave infrared bands","volume":"157","author":"Oyama","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"10295","DOI":"10.3390\/rs70810295","article-title":"Mapping Aquatic Vegetation in a Large, Shallow Eutrophic Lake: A Frequency-Based Approach Using Multiple Years of MODIS Data","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Liang, Q., Zhang, Y., Ma, R., Loiselle, S., Li, J., and Hu, M. (2017). A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu. Remote Sens., 9.","DOI":"10.3390\/rs9020133"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/JSTARS.2017.2757006","article-title":"Distinguishing Cyanobacterial Bloom from Floating Leaf Vegetation in Lake Taihu Based on Medium-Resolution Imaging Spectrometer (MERIS) Data","volume":"11","author":"Zhu","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"12437","DOI":"10.3390\/s120912437","article-title":"A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates","volume":"12","author":"Jiang","year":"2012","journal-title":"Sensors"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1080\/01431160500444806","article-title":"Integration of environmental variables with satellite images in regional scale vegetation classification","volume":"27","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.rse.2005.11.007","article-title":"Fuzzy learning vector quantization for hyperspectral coastal vegetation classification","volume":"100","author":"Filippi","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2138","DOI":"10.1016\/j.jenvman.2007.06.022","article-title":"Identification and mapping of submerged plants in a shallow lake using quickbird satellite data","volume":"90","author":"Dogan","year":"2009","journal-title":"J. Environ. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7442","DOI":"10.3390\/rs6087442","article-title":"A New Method for Modifying Thresholds in the Classification of Tree Models for Mapping Aquatic Vegetation in Taihu Lake with Satellite Images","volume":"6","author":"Luo","year":"2014","journal-title":"Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3988","DOI":"10.3390\/s8063988","article-title":"Detecting aquatic vegetation changes in Taihu Lake, China using multi-temporal satellite imagery","volume":"8","author":"Ma","year":"2008","journal-title":"Sensors"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"40326","DOI":"10.1038\/srep40326","article-title":"Long-term MODIS observations of cyanobacterial dynamics in Lake Taihu: Responses to nutrient enrichment and meteorological factors","volume":"7","author":"Shi","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Feng, L., Hou, X., Liu, J., and Zheng, C. (2020). Unrealistic phytoplankton bloom trends in global lakes derived from Landsat measurements. Nature.","DOI":"10.31223\/OSF.IO\/2WXNT"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hu, C., Lee, Z., Ma, R., Yu, K., Li, D., and Shang, S. (2010). Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China. J. Geophys. Res. Ocean., 115.","DOI":"10.1029\/2009JC005511"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2048","DOI":"10.1016\/j.rse.2010.04.011","article-title":"Remote detection of Trichodesmium blooms in optically complex coastal waters: Examples with MODIS full-spectral data","volume":"114","author":"Hu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"117455","DOI":"10.1016\/j.envpol.2021.117455","article-title":"Effects of air quality and vegetation on algal bloom early warning systems in large lakes in the middle-lower Yangtze River basin","volume":"285","author":"Zhang","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1016\/j.rse.2009.05.012","article-title":"A novel ocean color index to detect floating algae in the global oceans","volume":"113","author":"Hu","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1071\/MF9950295","article-title":"Mechanisms, Measurement and Importance of Sediment Resuspension in Lakes","volume":"46","author":"Bloesch","year":"1995","journal-title":"Mar. Freshw. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2015.02.029","article-title":"Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250 m MODIS-Aqua data","volume":"164","author":"Shi","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01431161.2020.1829154","article-title":"Long-term remote sensing of total suspended matter using Landsat series sensors in Hulun Lake, China","volume":"42","author":"Wang","year":"2021","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1364\/JOSA.64.001107","article-title":"Optical properties of water in the near infrared","volume":"64","author":"Palmer","year":"1974","journal-title":"JOSA"},{"key":"ref_32","unstructured":"Hoffer, R.M. (1978). Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data. Remote Sensing: The Quantitative Approach, McGraw-Hill."},{"key":"ref_33","first-page":"154","article-title":"Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information","volume":"57","author":"Luo","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_34","unstructured":"Wang, N. (2012). A Comparative Study of the Ecosystem Structure and Aquatic Evolution of Lakes in the Great Lakes Region of China. [Master\u2019s Thesis, Nanjing University]."},{"key":"ref_35","first-page":"108","article-title":"Remote Sensing of Harmful Algal Blooms Variability for Lake Hulun Using Adjusted FM (AFAI) Algorithm","volume":"34","author":"Fang","year":"2019","journal-title":"J. Environ. Inform."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"073589","DOI":"10.1117\/1.JRS.7.073589","article-title":"Changes in vegetative coverage of the Hongze Lake national wetland nature reserve: A decade-long assessment using MODIS medium-resolution data","volume":"7","author":"Yu","year":"2013","journal-title":"J. Appl. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Ruan, R.Z., and Zhang, L. (2010, January 23\u201325). Changes of Hongze Lake Wetlands in the Past Three Decades. Proceedings of the 6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM), Chengdu, China.","DOI":"10.1109\/WICOM.2010.5601034"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"10523","DOI":"10.3390\/rs70810523","article-title":"Fourteen-Year Record (2000\u20132013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ma, J.Y., Jin, S.G., Li, J., He, Y., and Shang, W. (2021). Spatio-Temporal Variations and Driving Forces of Harmful Algal Blooms in Chaohu Lake: A Multi-Source Remote Sensing Approach. Remote Sens., 13.","DOI":"10.3390\/rs13030427"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1021\/acs.est.8b06887","article-title":"Phenology of Phytoplankton Blooms in a Trophic Lake Observed from Long-Term MODIS Data","volume":"53","author":"Shi","year":"2019","journal-title":"Environ. Sci. Technol."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zhang, T., Hu, H., Ma, X., and Zhang, Y. (2020). Long-Term Spatiotemporal Variation and Environmental Driving Forces Analyses of Algal Blooms in Taihu Lake Based on Multi-Source Satellite and Land Observations. Water, 12.","DOI":"10.3390\/w12041035"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1511","DOI":"10.1016\/j.jglr.2020.08.024","article-title":"Variations in water level, area and volume of Hongze Lake, China from 2003 to 2018","volume":"46","author":"Cai","year":"2020","journal-title":"J. Great Lakes Res."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Jing, Y., Zhang, Y., Hu, M., Chu, Q., and Ma, R. (2019). MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China. Remote Sens., 11.","DOI":"10.3390\/rs11212582"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2929","DOI":"10.1021\/acs.est.0c06480","article-title":"Climatic versus Anthropogenic Controls of Decadal Trends (1983\u20132017) in Algal Blooms in Lakes and Reservoirs across China","volume":"55","author":"Song","year":"2021","journal-title":"Environ. Sci. Technol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.jglr.2014.04.007","article-title":"Submerged macrophyte communities and the controlling factors in large, shallow Lake Taihu (China): Sediment distribution and water depth","volume":"40","author":"Dong","year":"2014","journal-title":"J. Great Lakes Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"108146","DOI":"10.1016\/j.agrformet.2020.108146","article-title":"Attribution of climate and human activities to vegetation change in China using machine learning techniques","volume":"294","author":"Shi","year":"2020","journal-title":"Agric. For. Meteorol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the normalized difference water index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/1988\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:58:08Z","timestamp":1760137088000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/1988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,21]]},"references-count":49,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["rs14091988"],"URL":"https:\/\/doi.org\/10.3390\/rs14091988","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,21]]}}}