{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T08:28:54Z","timestamp":1768033734522,"version":"3.49.0"},"reference-count":66,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T00:00:00Z","timestamp":1598572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Project funded by China Postdoctoral Science Foundation","award":["2019M662478"],"award-info":[{"award-number":["2019M662478"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurately quantifying spatiotemporal changes in surface water is essential for water resources management, nevertheless, the dynamics of Poyang Lake surface water areas with high spatiotemporal resolution, as well as its responses to climate change, still face considerable uncertainties. Using the time series of Sentinel-1 images with 6- or 12-day intervals, the Sentinel-1 water index (SWI), and SWI-based water extraction model (SWIM) from 2015 to 2020 were used to document and study the short-term characteristics of southwest Poyang Lake surface water. The results showed that the overall accuracy of surface water area was satisfactory with an average of 91.92%, and the surface water area ranged from 129.06 km2 on 2 March 2017 to 1042.57 km2 on 17 July 2016, with significant intra- and inter-month variability. Within the 6-day interval, the maximum change of lake area was 233.42 km2 (i.e., increasing from 474.70 km2 up to 708.12 km2). We found that the correlation coefficient between the water area and the 45-day accumulated precipitation reached to 0.75 (p &lt; 0.001). Moreover, a prediction model was built to predict the water area based on climate records. These results highlight the significance of high spatiotemporal resolution mapping for surface water in the erratic southwest Poyang Lake under a changing climate. The automated water extraction algorithm proposed in this study has potential applications in delineating surface water dynamics at broad geographic scales.<\/jats:p>","DOI":"10.3390\/s20174872","type":"journal-article","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T09:17:08Z","timestamp":1598606228000},"page":"4872","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations"],"prefix":"10.3390","volume":"20","author":[{"given":"Haifeng","family":"Tian","sequence":"first","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education\/College of Environment and Planning, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geography, The Ohio State University, Columbus, OH 43210, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Pei","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6962-8838","authenticated-orcid":false,"given":"Yaochen","family":"Qin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education\/College of Environment and Planning, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education\/College of Environment and Planning, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjiu","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education\/College of Environment and Planning, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3220","DOI":"10.1016\/j.rse.2011.07.006","article-title":"Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China","volume":"115","author":"Dronova","year":"2011","journal-title":"Remote Sens. 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