{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T09:48:26Z","timestamp":1768816106241,"version":"3.49.0"},"reference-count":71,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T00:00:00Z","timestamp":1696982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2021YFC3001405"],"award-info":[{"award-number":["2021YFC3001405"]}]},{"name":"National Key R&amp;D Program of China","award":["U2240203"],"award-info":[{"award-number":["U2240203"]}]},{"name":"Key Program of National Natural Science Foundation of China","award":["2021YFC3001405"],"award-info":[{"award-number":["2021YFC3001405"]}]},{"name":"Key Program of National Natural Science Foundation of China","award":["U2240203"],"award-info":[{"award-number":["U2240203"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban waterlogging is a natural disaster that occurs in developed cities globally and has inevitably become severe due to urbanization, densification, and climate change. The digital elevation model (DEM) is an important component of urban waterlogging risk prediction. However, previous studies generally focused on optimizing hydrological models, and there is a potential improvement in DEM by fusing remote sensing data and hydrological data. To improve the DEM accuracy of urban roads and densely built-up areas, a multisource data fusion approach (MDF-UNet) was proposed. Firstly, Fuzhou city was taken as an example, and the satellite remote sensing images, drainage network, land use, and DEM data of the study area were collected. Secondly, the U-Net model was used to identify buildings using remote sensing images. Subsequently, a multisource data fusion (MDF) method was adopted to reconstruct DEM by fusing the buildings identification results, land use, and drainage network data. Then, a coupled one-dimensional (1D) conduit drainage and two-dimensional (2D) hydrodynamic model was constructed and validated. Finally, the simulation results of the MDF-UNet approach were compared with the raw DEM data, inverse distance weighting (IDW), and MDF. The results indicated that the proposed approach greatly improved the simulation accuracy of waterlogging points by 29%, 53%, and 12% compared with the raw DEM, IDW, and MDF. Moreover, the MDF-UNet method had the smallest median value error of 0.08 m in the inundation depth simulation. The proposed method demonstrates that the credibility of the waterlogging model and simulation accuracy in roads and densely built-up areas is significantly improved, providing a reliable basis for urban waterlogging prevention and management.<\/jats:p>","DOI":"10.3390\/rs15204915","type":"journal-article","created":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T08:18:57Z","timestamp":1697012337000},"page":"4915","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Improving the Accuracy of Urban Waterlogging Simulation: A Novel Computer Vision-Based Digital Elevation Model Refinement Approach for Roads and Densely Built-Up Areas"],"prefix":"10.3390","volume":"15","author":[{"given":"Qiu","family":"Yang","sequence":"first","affiliation":[{"name":"College of the Environment & Ecology, Xiamen University, Xiamen 361104, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haocheng","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Lei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyu","family":"Feng","sequence":"additional","affiliation":[{"name":"North China Municipal Engineering Design and Research Institute Co., Ltd., Beijing 100176, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangyang","family":"Zuo","sequence":"additional","affiliation":[{"name":"School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101248","DOI":"10.1016\/j.ejrh.2022.101248","article-title":"Prediction and early warning method of inundation process at waterlogging points based on Bayesian model average and data-driven","volume":"44","author":"Zhou","year":"2022","journal-title":"J. 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