{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T12:27:00Z","timestamp":1774355220973,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002367","name":"Strategic Priority Research Program Project of the Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["XDA23040100"],"award-info":[{"award-number":["XDA23040100"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002367","name":"Strategic Priority Research Program Project of the Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["JSZRHYKJ202002"],"award-info":[{"award-number":["JSZRHYKJ202002"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Jiangsu Natural Resources Development Special Project","award":["XDA23040100"],"award-info":[{"award-number":["XDA23040100"]}]},{"name":"Jiangsu Natural Resources Development Special Project","award":["JSZRHYKJ202002"],"award-info":[{"award-number":["JSZRHYKJ202002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Total phosphorus (TP) and total nitrogen (TN) reflect the state of eutrophication. However, traditional point-based water quality monitoring methods are time-consuming and labor-intensive, and insufficient to estimate and assess water quality at a large scale. In this paper, we constructed machine learning models for TP and TN inversion using measured data and satellite imagery band reflectance, and verified it by in situ data. Atmospheric correction was performed on the Landsat Top of Atmosphere (TOP) data by removing the effect of the adjacency effect and correcting differences between Landsat sensors. Then, using the established model, the TP and TN patterns in Dongting Lake with a spatial resolution of 30 m from 1996 to 2021 were derived for the first time. The annual and monthly spatio-temporal variation characteristics of TP and TN in Dongting Lake were investigated in details, and the influences of hydrometeorological elements on water quality variations were analyzed. The results show that the established empirical model can accurately estimate TP with coefficient (R2) \u2265 0.70, root mean square error (RMSE) \u2264 0.057 mg\/L, mean relative error (MRE) \u2264 0.23 and TN with R2 \u2265 0.73, RMSE \u2264 0.48 mg\/L and MRE \u2264 0.20. From 1996 to 2021, TP in Dongting Lake showed a downward trend and TN showed an upward trend, while the summer value was much higher than the other seasons. Furthermore, the influencing factors on TP and TN variations were investigated and discussed. Between 1996 and 2003, the main contributors to the change of water quality in Dongting Lake were external inputs such as water level and flow. The significant changes in water quantity and sediment characteristics following the operation of the Three Gorges Dam (TGD) in 2003 also had an impact on the water quality in Dongting Lake.<\/jats:p>","DOI":"10.3390\/rs14225648","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T02:07:48Z","timestamp":1668046068000},"page":"5648","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Total Phosphorus and Nitrogen Dynamics and Influencing Factors in Dongting Lake Using Landsat Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9429-6305","authenticated-orcid":false,"given":"Yuanyuan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5108-4828","authenticated-orcid":false,"given":"Shuanggen","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China"},{"name":"School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9933-0725","authenticated-orcid":false,"given":"Ning","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Jiarui","family":"Zhao","sequence":"additional","affiliation":[{"name":"Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China"}]},{"given":"Hongwei","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Environmental Science and Engineering\/Sino-Canada Joint R&D Centre for Water and Environmental Safety, Nankai University, Tianjin 300457, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5996-9268","authenticated-orcid":false,"given":"Petri","family":"Pellikka","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Geography, University of Helsinki, FI-00014 Helsinki, Finland"},{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1680\/jwama.19.00026","article-title":"Annual variation characteristics of eutrophication in Dongting Lake, China","volume":"173","author":"Xue","year":"2020","journal-title":"Proc. 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