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Volume 14
Issue 6
10.3390/ijgi14060218
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan

by
Jinge Zhang
1,2,
Yan Du
3,
Yujing Jiang
1,*,
Sunhao Zhang
1,2,
Hongbin Chen
1 and
Dongqi Shang
1
1
Department of Integrated Science and Technology, Nagasaki University, Nagasaki 852-8521, Japan
2
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
3
Beijing Key Laboratory of Urban Underground Space Engineering, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2025, 14(6), 218; https://doi.org/10.3390/ijgi14060218 (registering DOI)
Submission received: 10 March 2025 / Revised: 14 May 2025 / Accepted: 29 May 2025 / Published: 30 May 2025
(This article belongs to the Topic Geotechnics for Hazard Mitigation)
Versions Notes

Abstract

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.
Keywords: photogrammetry; neural radiance fields; landslide; 3D reconstruction photogrammetry; neural radiance fields; landslide; 3D reconstruction

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MDPI and ACS Style

Zhang, J.; Du, Y.; Jiang, Y.; Zhang, S.; Chen, H.; Shang, D. Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan. ISPRS Int. J. Geo-Inf. 2025, 14, 218. https://doi.org/10.3390/ijgi14060218

AMA Style

Zhang J, Du Y, Jiang Y, Zhang S, Chen H, Shang D. Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan. ISPRS International Journal of Geo-Information. 2025; 14(6):218. https://doi.org/10.3390/ijgi14060218

Chicago/Turabian Style

Zhang, Jinge, Yan Du, Yujing Jiang, Sunhao Zhang, Hongbin Chen, and Dongqi Shang. 2025. "Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan" ISPRS International Journal of Geo-Information 14, no. 6: 218. https://doi.org/10.3390/ijgi14060218

APA Style

Zhang, J., Du, Y., Jiang, Y., Zhang, S., Chen, H., & Shang, D. (2025). Exploring the Application of NeRF in Enhancing Post-Disaster Response: A Case Study of the Sasebo Landslide in Japan. ISPRS International Journal of Geo-Information, 14(6), 218. https://doi.org/10.3390/ijgi14060218

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