{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T14:26:52Z","timestamp":1768400812650,"version":"3.49.0"},"reference-count":42,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,24]],"date-time":"2019-05-24T00:00:00Z","timestamp":1558656000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2018YFC0407804"],"award-info":[{"award-number":["2018YFC0407804"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41371343"],"award-info":[{"award-number":["41371343"]}],"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>Wetland flooding is significant for the flora and fauna of wetlands. High temporal resolution remote sensing images are widely used for the timely mapping of wetland flooding but have a limitation of their relatively low spatial resolutions. In this study, a novel method based on random forests and spatial attraction models (RFSAM) was proposed to improve the accuracy of sub-pixel mapping of wetland flooding (SMWF) using remote sensing images. A random forests-based SMWF algorithm (RM-SMWF) was developed firstly, and a comprehensive complexity index of a mixed pixel was formulated. Then the RFSAM-SMWF method was developed. Landsat 8 Operational Land Imager (OLI) images of two wetlands of international importance included in the Ramsar List were used to evaluate RFSAM-SMWF against three other SMWF methods, and it consistently achieved more accurate sub-pixel mapping results in terms of visual and quantitative assessments in the two wetlands. The effects of the number of trees in random forests and the complexity threshold on the mapping accuracy of RFSAM-SMWF were also discussed. The results of this study improve the mapping accuracy of wetland flooding from medium-low spatial resolution remote sensing images and therefore benefit the environmental studies of wetlands.<\/jats:p>","DOI":"10.3390\/rs11101231","type":"journal-article","created":{"date-parts":[[2019,5,24]],"date-time":"2019-05-24T11:20:46Z","timestamp":1558696846000},"page":"1231","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Remote Sensing of Wetland Flooding at a Sub-Pixel Scale Based on Random Forests and Spatial Attraction Models"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2185-8407","authenticated-orcid":false,"given":"Linyi","family":"Li","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"given":"Yun","family":"Chen","sequence":"additional","affiliation":[{"name":"Commonwealth Scientific and Industrial Research Organisation (CSIRO) Land and Water, Canberra 2601, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4860-1679","authenticated-orcid":false,"given":"Tingbao","family":"Xu","sequence":"additional","affiliation":[{"name":"Fenner School of Environment and Society, The Australian National University, Canberra 2601, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9047-2885","authenticated-orcid":false,"given":"Kaifang","family":"Shi","sequence":"additional","affiliation":[{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"given":"Rui","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8621-4581","authenticated-orcid":false,"given":"Chang","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Northwest University, Xi\u2019an 710127, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7847-7560","authenticated-orcid":false,"given":"Binbin","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"given":"Lingkui","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11273-017-9559-6","article-title":"Flood plain wetland fisheries of India: With special reference to impact of climate change","volume":"26","author":"Sarkar","year":"2018","journal-title":"Wetl. 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