DEM-Based UAV Geolocation of Thermal Hotspots on Complex Terrain

Reliable geolocation of thermal hotspots, such as smoldering embers that can reignite after vegetation fire suppression, deep-seated peat fires, or underground coal seam fires, is critical to prevent fire resurgence, limit prolonged greenhouse gas emissions, and mitigate environmental and health impacts. This study develops and tests an algorithm to estimate the GPS positions of thermal hotspots detected in infrared images acquired by an unmanned aerial vehicle (UAV), designed to operate over flat and mountainous terrain. Its originality lies in a reformulated Bresenham traversal of the digital elevation model (DEM), combined with a lightweight, ray-tracing-inspired strategy that efficiently detects the intersection of the optical ray with the terrain by approximating the ray altitude at the cell level. UAV flight experiments in complex terrain were conducted, with thermal image acquisitions performed at 60 m and 120 m above ground level and simulated hotspots generated using controlled heat sources. The tests were carried out with two thermal cameras: a Zenmuse H20T mounted on a Matrice 300 UAV flown both with and without Real-Time Kinematic (RTK) positioning, and a Matrice 30T UAV without RTK. The implementation supports both real-time and post-processed operation modes. The results demonstrated robust and reliable geolocation performance, with mean positional errors consistently below 4.2 m for all the terrain configurations tested. A successful real-time operation in the test confirmed the suitability of the algorithm for time-critical intervention scenarios. Since July 2024, the post-processed version of the method has been in operational use by the Corsica fire services.