{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:54:19Z","timestamp":1780602859932,"version":"3.54.1"},"reference-count":50,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T00:00:00Z","timestamp":1680048000000},"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":["41901055"],"award-info":[{"award-number":["41901055"]}],"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>The accurate monitoring of long-term spatial and temporal changes in open-surface water bodies offers important guidance for water resource security and management. In the middle and lower reaches of the Yangtze River, the monitoring of water body changes is especially critical due to the dense population and drastic climate change. Due to the complexity of the physical environment in which the water bodies are located, the advantages and disadvantages of various water body detection rules can vary in large-scale areas. In this paper, we use Landsat 5\/7\/8 data to extract the area of water bodies in the study area and analyze their spatial and temporal trends from 1984 to 2020 using the Google Earth Engine (GEE) platform. We propose an improved water body extraction rule based on an existing multi-indicator water body algorithm that combines impervious surface data and digital elevation model data. In this study, the performance of the improved algorithm was cross-validated using seven other water body indicator algorithms, and the results showed the following: (1) the rule accurately retained information about the water body while minimizing the interference of shadows on the extracted water body. (2) On the annual scale from 1984 to 2020, the open-surface water body dataset extracted using this improved rule showed that the turning point for the area of each water body type was 2011, with an overall decreasing trend in area before 2011 and an increasing trend in area after 2011, with the exception of special years, such as 1998. (3) The driving mechanism analysis showed that, overall, precipitation was positively correlated with the water body area and temperature was negatively correlated with the water body area. Additionally, human activities can have an impact on surface water dynamics. The key influencing factors are diverse for each water body type; it was found that seasonal water bodies were correlated with precipitation and paddy fields and permanent water bodies were correlated with temperature and urban construction. The accurate monitoring of the spatial and temporal dynamics of open-surface water performed in this study can shed light on the sustainable development of water resources and the environment.<\/jats:p>","DOI":"10.3390\/rs15071816","type":"journal-article","created":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T03:32:25Z","timestamp":1680060745000},"page":"1816","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Long-Term Changes in Water Body Area Dynamic and Driving Factors in the Middle-Lower Yangtze Plain Based on Multi-Source Remote Sensing Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5837-1503","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongfen","family":"Teng","sequence":"additional","affiliation":[{"name":"School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liu","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Geography, Planning and Spatial Sciences, University of Tasmania, Hobart, TAS 7005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingyu","family":"Han","sequence":"additional","affiliation":[{"name":"School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1126\/science.1257890","article-title":"Coping with the curse of freshwater variability","volume":"346","author":"Hall","year":"2014","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3471","DOI":"10.1038\/s41467-020-17103-w","article-title":"Gainers and losers of surface and terrestrial water resources in China during 1989\u20132016","volume":"11","author":"Wang","year":"2020","journal-title":"Nat. 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