{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:35:12Z","timestamp":1760150112552,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T00:00:00Z","timestamp":1698019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["42022054","XDA23090303","2022YFS0543","2022YFG0140"],"award-info":[{"award-number":["42022054","XDA23090303","2022YFS0543","2022YFG0140"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of CAS","award":["42022054","XDA23090303","2022YFS0543","2022YFG0140"],"award-info":[{"award-number":["42022054","XDA23090303","2022YFS0543","2022YFG0140"]}]},{"name":"Sichuan Science and Technology Program","award":["42022054","XDA23090303","2022YFS0543","2022YFG0140"],"award-info":[{"award-number":["42022054","XDA23090303","2022YFS0543","2022YFG0140"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The efficiency and accuracy of grid-based computational fluid dynamics methods are strongly dependent on the chosen cell size. The computational time increases exponentially with decreasing cell size. Therefore, a grid coarsing technology without apparent precision loss is essential for various numerical modeling methods. In this article, a physical adaption neural network (PANN) is proposed to optimize coarse grid representation from a fine grid. A new convolutional neural network is constructed to achieve a significant reduction in computational cost while maintaining a relatively accurate solution. An application to numerical modeling of dynamic processes in landslides is firstly carried out, and better results are obtained compared to the baseline method. More applications in various flood scenarios in mountainous areas are then analyzed. It is demonstrated that the proposed PANN downscaling method outperforms other currently widely used downscaling methods. The code is publicly available and can be applied broadly. Computing by PANN is hundreds of times more efficient, meaning that it is significant for the numerical modeling of various complicated Earth-surface flows and their applications.<\/jats:p>","DOI":"10.3390\/rs15205075","type":"journal-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T10:32:24Z","timestamp":1698057144000},"page":"5075","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A PANN-Based Grid Downscaling Technology and Its Application in Landslide and Flood Modeling"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9091-3185","authenticated-orcid":false,"given":"Binlan","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Key Laboratory of Mountain Hazards and Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4456-8485","authenticated-orcid":false,"given":"Chaojun","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mountain Hazards and Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6172-4753","authenticated-orcid":false,"given":"Dongpo","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Fulei","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mountain Hazards and Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0906-7290","authenticated-orcid":false,"given":"Qingsong","family":"Xu","sequence":"additional","affiliation":[{"name":"Data Science in Earth Observation, Technical University of Munich, 80333 Munich, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Blazek, J. 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