{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T21:11:37Z","timestamp":1783285897002,"version":"3.54.6"},"reference-count":45,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2019YFE0127700"],"award-info":[{"award-number":["2019YFE0127700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2019YFC1520800"],"award-info":[{"award-number":["2019YFC1520800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Building height is important information in disaster management and damage assessment. It is also a key parameter in studies such as population modeling and urbanization. Relatively few studies have been conducted on extracting building height in rural areas using imagery from China\u2019s Gaofen-7 satellite (GF-7). In this study, we developed a method combining photogrammetry and deep learning to extract building height using GF-7 data in the rural area of Pingquan in northern China. The deep learning model DELaMa was proposed for digital surface model (DSM) editing based on the Large Mask Inpainting (LaMa) architecture. It not only preserves topographic details but also reasonably predicts the topography inside the building mask. The percentile value of the normalized digital surface model (nDSM) in the building footprint was taken as the building height. The extracted building heights in the study area are highly consistent with the reference building heights measured from the ICESat-2 LiDAR point cloud, with an R2 of 0.83, an MAE of 1.81 m and an RMSE of 2.13 m for all validation buildings. Overall, the proposed method in this paper helps to promote the use of satellite data in large-scale building height surveys, especially in rural areas.<\/jats:p>","DOI":"10.3390\/s24186076","type":"journal-article","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T04:31:23Z","timestamp":1726806683000},"page":"6076","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Method for Extracting High-Resolution Building Height Information in Rural Areas Using GF-7 Data"],"prefix":"10.3390","volume":"24","author":[{"given":"Mingbo","family":"Liu","sequence":"first","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kailong","family":"Hu","sequence":"additional","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changjun","family":"Gu","sequence":"additional","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengyue","family":"Jin","sequence":"additional","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Chen","sequence":"additional","affiliation":[{"name":"National Disaster Reduction Center of China, Ministry of Emergency Management of the People\u2019s Republic of China, Beijing 100124, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3388","DOI":"10.1007\/s11629-022-7491-6","article-title":"Failure Criteria of Unreinforced Masonry Walls of Rural Buildings under the Impact of Flash Floods in Mountainous Regions","volume":"19","author":"Si","year":"2022","journal-title":"J. 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