{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T01:43:55Z","timestamp":1768700635347,"version":"3.49.0"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T00:00:00Z","timestamp":1643328000000},"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":["41971381"],"award-info":[{"award-number":["41971381"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Program of Beijing Municipal Bureau of Water","award":["TAHP-2018-ZBYY-490S"],"award-info":[{"award-number":["TAHP-2018-ZBYY-490S"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Submerged aquatic vegetation (SAV) is one of the most important biological groups in shallow lakes ecosystems, and it plays a vital role in stabilizing the structure and function of water ecosystems. The study area of this research is Baiyangdian, which is a typical macrophytic lake with complex land cover types. This research aims to solve the low accuracy problem of the remote sensing extraction of SAV, which is mainly caused by water level fluctuations, differences in life-history characteristics, and mixed-pixel phenomena. Here, we developed a phenology\u2013pixel method to determine the spatial distribution of SAV and the start and end dates of its growing season by using all Sentinel-2 images collected over a year on the Google Earth Engine platform. The experimental results show the following: (1) The phenology\u2013pixel algorithm can effectively identify the maximum spatial distribution and growth period of submerged aquatic vegetation in Baiyangdian Lake throughout the year. The unique normalized difference vegetation index (NDVI) peak characteristics of Potamogeton crispus from March to May were used to effectively distinguish it from the low Phragmites australis population. Textural features based on the modified normalized difference water index (MNDWI) index effectively removed the mixed-pixel phenomenon of macrophytic lakes (such as dikes and sparse reeds). (2) A complete five-day interval NDVI time-series dataset was obtained, which removes potential noise on the temporal scale and fills in noisy observations by the harmonic analysis of time series (HANTS) method. We determined the two phenological periods of typical SAV by analyzing the intrayear variation characteristics of NDVI and MNDWI. (3) Using field-survey data for accuracy verification, the overall accuracy of our method was determined to be 94.8%, and the user\u2019s accuracy and producer\u2019s accuracy were 93.3% and 87.3%, respectively. Determining the temporal and spatial distribution of different SAV populations provides important technical support for actively promoting the maintenance and reconstruction of lake and reservoir ecosystems.<\/jats:p>","DOI":"10.3390\/rs14030640","type":"journal-article","created":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T01:43:27Z","timestamp":1643420607000},"page":"640","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Accurate Monitoring of Submerged Aquatic Vegetation in a Macrophytic Lake Using Time-Series Sentinel-2 Images"],"prefix":"10.3390","volume":"14","author":[{"given":"Shuang","family":"Liang","sequence":"first","affiliation":[{"name":"College of Resources, Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Municipal Key Lab of Resources Environment and GIS, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5760-6367","authenticated-orcid":false,"given":"Zhaoning","family":"Gong","sequence":"additional","affiliation":[{"name":"College of Resources, Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Municipal Key Lab of Resources Environment and GIS, Beijing 100048, China"}]},{"given":"Yingcong","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resources, Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Municipal Key Lab of Resources Environment and GIS, Beijing 100048, China"}]},{"given":"Jiafu","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China"}]},{"given":"Wenji","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Resources, Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Municipal Key Lab of Resources Environment and GIS, Beijing 100048, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1007\/s10452-007-9122-2","article-title":"Influence of the macrophyte Eichhornia azurea on fish assemblage of the Upper Paran\u00e1 River floodplain (Brazil)","volume":"41","author":"Agostinho","year":"2007","journal-title":"Aquat. Ecol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0304-3770(91)90038-7","article-title":"Sediment interactions with submersed macrophyte growth and community dynamics","volume":"41","author":"Barko","year":"1991","journal-title":"Aquat. Bot."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s10750-013-1800-6","article-title":"Remote sensing of phytoplankton-macrophyte coexistence in shallow hypereutrophic fluvial lakes","volume":"737","author":"Bolpagni","year":"2014","journal-title":"Hydrobiologia"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0925-8574(93)90024-A","article-title":"Nutrient removal processes in freshwater submersed macrophyte systems","volume":"2","author":"Gumbricht","year":"1993","journal-title":"Ecol. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Jeppesen, E. (1998). The Structuring Role of Submerged Macrophytes in Lakes, Springer.","DOI":"10.1007\/978-1-4612-0695-8"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1641\/0006-3568(2006)56[987:AGCFSE]2.0.CO;2","article-title":"A Global Crisis for Seagrass Ecosystems","volume":"56","author":"Orth","year":"2006","journal-title":"BioScience"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"23867","DOI":"10.1038\/srep23867","article-title":"Aquatic vegetation in response to increased eutrophication and degraded light climate in Eastern Lake Taihu: Implications for lake ecological restoration","volume":"6","author":"Zhang","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1146\/annurev.ecolsys.35.021103.105711","article-title":"Regime Shifts, Resilience, and Biodiversity in Ecosystem Management","volume":"35","author":"Folke","year":"2004","journal-title":"Annu. Rev. Ecol. Evol. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.ecolind.2015.07.029","article-title":"Applying remote sensing techniques to monitoring seasonal and interannual changes of aquatic vegetation in Taihu Lake, China","volume":"60","author":"Luo","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"116353","DOI":"10.1016\/j.watres.2020.116353","article-title":"Submerged macrophyte assessment in rivers: An automatic mapping method using Pl\u00e9iades imagery","volume":"186","author":"Espel","year":"2020","journal-title":"Water Res."},{"key":"ref_11","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_12","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.scitotenv.2018.09.216","article-title":"Long-term and inter-monthly dynamics of aquatic vegetation and its relation with environmental factors in Taihu Lake, China","volume":"651","author":"Wang","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_13","first-page":"113","article-title":"Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation","volume":"30","author":"Villa","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhao, D., Lv, M., Jiang, H., Cai, Y., and Xu, D. (2013). Spatio-Temporal Variability of Aquatic Vegetation in Taihu Lake over the Past 30 Years. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0066365"},{"key":"ref_15","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_16","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.rse.2014.04.032","article-title":"A satellite-based multi-temporal assessment of the extent of nuisance Cladophora and related submerged aquatic vegetation for the Laurentian Great Lakes","volume":"157","author":"Brooks","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"112459","DOI":"10.1016\/j.rse.2021.112459","article-title":"An automatic classification algorithm for submerged aquatic vegetation in shallow lakes using Landsat imagery","volume":"260","author":"Dai","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5684","DOI":"10.1109\/JSTARS.2021.3080692","article-title":"Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation Under Water Depth Fluctuations","volume":"14","author":"Gong","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_19","first-page":"971","article-title":"Analysis of changes of Baiyangdian wetland from 1975 to 2018 based on remote sensing","volume":"23","author":"Zhu","year":"2019","journal-title":"J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1080\/17538947.2017.1356388","article-title":"Winter wheat mapping using a random forest classifier combined with multi-temporal and multi-sensor data","volume":"11","author":"Liu","year":"2018","journal-title":"Int. J. Digit. Earth"},{"key":"ref_21","first-page":"1634","article-title":"Landscape pattern evolution and its driving factors of Baiyangdian lake-marsh wetland system","volume":"32","author":"Junhong","year":"2013","journal-title":"Geogr. Res."},{"key":"ref_22","first-page":"4780","article-title":"Landscape pattern change and the driving forces in Baiyangdian wetland from 1984 to 2014","volume":"36","author":"Zhang","year":"2016","journal-title":"Acta Ecol. Sin."},{"key":"ref_23","first-page":"549","article-title":"An Analysis of the Evolution of Baiyangdian Wetlands in Hebei Province with Artificial Recharge","volume":"39","author":"Wang","year":"2018","journal-title":"Acta Geosci. Sin."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s Optical High-Resolution Mission for GMES Operational Services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_25","first-page":"138","article-title":"Phenologies from harmonics analysis of AVHRR NDVI time series","volume":"12","author":"Lin","year":"2006","journal-title":"Trans. CSAE"},{"key":"ref_26","first-page":"620","article-title":"Changes of Green-up Day of Vegetation Growing Season Based on GIMMS 3g NDVI in Northern China in Recent 30 Years","volume":"37","author":"Li","year":"2017","journal-title":"Sci. Geogr. Sin."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"355","DOI":"10.3390\/rs1030355","article-title":"A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia","volume":"1","author":"Xiao","year":"2009","journal-title":"Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3780","DOI":"10.1109\/JSTARS.2020.3005135","article-title":"Monitoring Human-induced Surface Water Disturbance around Taihu Lake since 1984 by Time Series Landsat Images","volume":"13","author":"Meng","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, Q., Yu, R., Hao, Y., Wu, L., Zhang, W., Zhang, Q., and Bu, X. (2018). A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data. Remote Sens., 10.","DOI":"10.3390\/rs10081279"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Vahtme, E., Kutser, T., and Paavel, B. (2020). Performance and Applicability of Water Column Correction Models in Optically Complex Coastal Waters. Remote Sens., 12.","DOI":"10.3390\/rs12111861"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"111829","DOI":"10.1016\/j.rse.2020.111829","article-title":"Canopy modeling of aquatic vegetation: A geometric optical approach (AVGO)","volume":"245","author":"Zhou","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2219","DOI":"10.1016\/j.jenvman.2007.08.021","article-title":"Predictive models of turbidity and water depth in the Doana marshes using Landsat TM and ETM+ images","volume":"90","author":"Bustamante","year":"2009","journal-title":"J. Environ. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s10661-007-9855-3","article-title":"Remote sensing of aquatic vegetation: Theory and applications","volume":"140","author":"Silva","year":"2008","journal-title":"Environ. Monit. Assess."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/640\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:10:16Z","timestamp":1760134216000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/640"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,28]]},"references-count":33,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030640"],"URL":"https:\/\/doi.org\/10.3390\/rs14030640","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,28]]}}}