{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T15:52:48Z","timestamp":1776613968100,"version":"3.51.2"},"reference-count":50,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:00:00Z","timestamp":1731715200000},"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":["62171347"],"award-info":[{"award-number":["62171347"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2024SLKJ-16"],"award-info":[{"award-number":["2024SLKJ-16"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["SMDZ-2023CX-14"],"award-info":[{"award-number":["SMDZ-2023CX-14"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shaanxi Provincial Water Conservancy Fund Project","award":["62171347"],"award-info":[{"award-number":["62171347"]}]},{"name":"Shaanxi Provincial Water Conservancy Fund Project","award":["2024SLKJ-16"],"award-info":[{"award-number":["2024SLKJ-16"]}]},{"name":"Shaanxi Provincial Water Conservancy Fund Project","award":["SMDZ-2023CX-14"],"award-info":[{"award-number":["SMDZ-2023CX-14"]}]},{"name":"research project of Shaanxi Coal Geology Group Co., Ltd.","award":["62171347"],"award-info":[{"award-number":["62171347"]}]},{"name":"research project of Shaanxi Coal Geology Group Co., Ltd.","award":["2024SLKJ-16"],"award-info":[{"award-number":["2024SLKJ-16"]}]},{"name":"research project of Shaanxi Coal Geology Group Co., Ltd.","award":["SMDZ-2023CX-14"],"award-info":[{"award-number":["SMDZ-2023CX-14"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Automated water body (WB) extraction is one of the hot research topics in the field of remote sensing image processing. To address the challenges of over-extraction and incomplete extraction in complex water scenes, we propose an encoder\u2013decoder architecture semantic segmentation network for high-precision extraction of WBs called EDWNet. We integrate the Cross-layer Feature Fusion (CFF) module to solve difficulties in segmentation of WB edges, utilizing the Global Attention Mechanism (GAM) module to reduce information diffusion, and combining with the Deep Attention Module (DAM) module to enhance the model\u2019s global perception ability and refine WB features. Additionally, an auxiliary head is incorporated to optimize the model\u2019s learning process. In addition, we analyze the feature importance of bands 2 to 7 in Landsat 8 OLI images, constructing a band combination (RGB 763) suitable for algorithm\u2019s WB extraction. When we compare EDWNet with various other semantic segmentation networks, the results on the test dataset show that EDWNet has the highest accuracy. EDWNet is applied to accurately extract WBs in the Weihe River basin from 2013 to 2021, and we quantitatively analyzed the area changes of the WBs during this period and their causes. The results show that EDWNet is suitable for WB extraction in complex scenes and demonstrates great potential in long time-series and large-scale WB extraction.<\/jats:p>","DOI":"10.3390\/rs16224275","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T06:06:54Z","timestamp":1731996414000},"page":"4275","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["EDWNet: A Novel Encoder\u2013Decoder Architecture Network for Water Body Extraction from Optical Images"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6491-3108","authenticated-orcid":false,"given":"Tianyi","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Wenbo","family":"Ji","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0047-8955","authenticated-orcid":false,"given":"Weibin","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Chenhao","family":"Qin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Tianhao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Ocean and Earth Sciences, Xiamen University, Xiamen 361101, China"}]},{"given":"Yi","family":"Ren","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Yuan","family":"Fang","sequence":"additional","affiliation":[{"name":"Shaanxi Water Development Ecological Technology R&D Co., Ltd., Xi\u2019an 710068, China"}]},{"given":"Zhixiong","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an 710021, China"}]},{"given":"Licheng","family":"Jiao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111998","DOI":"10.1016\/j.rse.2020.111998","article-title":"Anthropogenic transformation of Yangtze Plain freshwater lakes: Patterns, drivers and impacts","volume":"248","author":"Hou","year":"2020","journal-title":"Remote Sens. 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