UAV photography in forest fire sites

We propose a GCP-free photography workflow for post-wildfire surveys in mountainous regions, where the implementation of ground control points (GCPs) is not feasible for rapid surveys. The workflow integrates three sets of imagery : close-range in-forest images acquired using an AI-assisted UAV (Skydio 2+), forest-edge and open-area images obtained with a UAV equipped with network RTK GNSS (Mavic 3E), and bridging images collected to ensure overlap between the in-forest and open-area scenes. These three datasets are processed within a single Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline to propagate georeferencing to the in-forest imagery. Georeferenced imaging of post-wildfire conditions facilitates subsequent AI-based analyses and provides a contemporaneous record of site conditions. We estimate that the proposed workflow has the potential to reduce on-site fieldwork time from 2 hours and 31 minutes to 56 minutes, achieving a 62.9% reduction.

Authors

Publication Details

Journal
Journal of the Japan society of photogrammetry and remote sensing
Published
2026-05-10
DOI
https://doi.org/10.4287/jsprs.65.69
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.00
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article

UAV photography in forest fire sites

Mitsuharu Shimokawa, Taku KITABAYASHI, Takanobu Nagao, Satoko Hattori-Nagao et al.
Journal of the Japan society of photogrammetry and remote sensing
3D Surveying and Cultural Heritage
article

UAV photography in forest fire sites

Mitsuharu Shimokawa, Taku KITABAYASHI, Takanobu Nagao, Satoko Hattori-Nagao, Zhiqian ZHU, Ryohei HOMMA
article en

Abstract

We propose a GCP-free photography workflow for post-wildfire surveys in mountainous regions, where the implementation of ground control points (GCPs) is not feasible for rapid surveys. The workflow integrates three sets of imagery : close-range in-forest images acquired using an AI-assisted UAV (Skydio 2+), forest-edge and open-area images obtained with a UAV equipped with network RTK GNSS (Mavic 3E), and bridging images collected to ensure overlap between the in-forest and open-area scenes. These three datasets are processed within a single Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline to propagate georeferencing to the in-forest imagery. Georeferenced imaging of post-wildfire conditions facilitates subsequent AI-based analyses and provides a contemporaneous record of site conditions. We estimate that the proposed workflow has the potential to reduce on-site fieldwork time from 2 hours and 31 minutes to 56 minutes, achieving a 62.9% reduction.

Journal of the Japan society of photogrammetry and remote sensingVol. 65(2)
Climate action
Openalex Percentile: Top 4%
3D Surveying and Cultural Heritage
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UAV photography in forest fire sites — Mitsuharu Shimokawa, Taku KITABAYASHI, et al. · Journal of the Japan society of photogrammetry and remote sensing (2026) | TGRS Research Map | TGRS