{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:19:56Z","timestamp":1760059196503,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T00:00:00Z","timestamp":1748563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Nagasaki University Global Human Resource Development Scholarship","award":["JPMJSP2172"],"award-info":[{"award-number":["JPMJSP2172"]}]},{"name":"JST SPRING, Japan","award":["JPMJSP2172"],"award-info":[{"award-number":["JPMJSP2172"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Rapid acquisition of 3D reconstruction models of landslides is crucial for post-disaster emergency response and rescue operations. This study explores the application potential of Neural Radiance Fields (NeRF) technology for rapid post-disaster site modeling and performs a comparative analysis with traditional photogrammetry methods. Taking a landslide induced by heavy rainfall in Sasebo City, Japan, as a case study, this research utilizes drone-acquired video imagery data and employs two different 3D reconstruction techniques to create digital models of the landslide area. Visual realism and point cloud detail were compared. The results indicate that the high-capacity NeRF model (NeRF 24G) approaches or even surpasses traditional photogrammetry in visual realism under certain scenarios; however, the generated point clouds are inferior in terms of detail compared to those produced by traditional photogrammetry. Nevertheless, NeRF significantly reduces the modeling time. NeRF 6G can generate a point cloud of engineering-useful accuracy in only 45 min, providing a 3D overview of the disaster site to support emergency response efforts. In the future, integrating the advantages of both methods could enable rapid and precise post-disaster 3D reconstruction.<\/jats:p>","DOI":"10.3390\/ijgi14060218","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T05:09:12Z","timestamp":1748840952000},"page":"218","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan"],"prefix":"10.3390","volume":"14","author":[{"given":"Jinge","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan"},{"name":"School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Yan","family":"Du","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Urban Underground Space Engineering, University of Science and Technology Beijing, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4020-5989","authenticated-orcid":false,"given":"Yujing","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan"}]},{"given":"Sunhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan"},{"name":"School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Hongbin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan"}]},{"given":"Dongqi","family":"Shang","sequence":"additional","affiliation":[{"name":"Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106504","DOI":"10.1016\/j.enggeo.2021.106504","article-title":"The World\u2019s Second-Largest, Recorded Landslide Event: Lessons Learnt from the Landslides Triggered during and after the 2018 Mw 7.5 Papua New Guinea Earthquake","volume":"297","author":"Hill","year":"2022","journal-title":"Eng. 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