Geospatial Wildfire Mapping Using a DEM-Ray Intersection Method

Wildfires are increasing in frequency and impact, and responders need timely information on fire fronts, spot fires, and residual burning areas during suppression and damping-down operations. Thermal cameras on unmanned aerial vehicles (UAVs) reveal such phenomena, but these observations must be converted into georeferenced data before they can be shared with other responders and integrated into geographic information systems (GIS). This paper presents a DEM-Ray intersection method for geolocating fire areas detected in thermal images captured by UAVs. Image coordinates associated with the fire detections are converted into viewing-direction vectors based on the camera parameters and rotated using the orientations of the UAV and gimbal. The resulting vectors, temperature values, and UAV position are transmitted to an edge system, where rays originating from the UAV are intersected with terrain represented by digital elevation model data. This produces temperature-attributed geospatial points representing the detected fire areas on the ground. The points can be visualized and further processed in GIS applications and shared with external systems using standard geospatial formats such as GeoJSON. The proposed approach can also be used to determine the geospatial coverage of each capture, which may support coverage assessment and flight planning. Developed and demonstrated within the wildfire use case of the HiCONNECTS project, the method provides a terrain-aware approach for transforming thermal-image detections into geospatial information for operational and analytical use.

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Publication Details

Journal
Journal of Artificial Intelligence and Data Analytics
Published
2026-11-03
DOI
https://doi.org/10.67927/jaidataanalytics/2026(1)114
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
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article

Geospatial Wildfire Mapping Using a DEM-Ray Intersection Method

Markus Liuska, A. B. Sagar, Markku Hartikainen, Ossi Saukko et al.
Journal of Artificial Intelligence and Data Analytics
Fire Detection and Safety Systems
article

Geospatial Wildfire Mapping Using a DEM-Ray Intersection Method

Markus Liuska, A. B. Sagar, Markku Hartikainen, Ossi Saukko, Tero Kippola, Gurpreet Singh Kalsi, Pasi Hakasaari, Sergei Alekseev
article en

Abstract

Wildfires are increasing in frequency and impact, and responders need timely information on fire fronts, spot fires, and residual burning areas during suppression and damping-down operations. Thermal cameras on unmanned aerial vehicles (UAVs) reveal such phenomena, but these observations must be converted into georeferenced data before they can be shared with other responders and integrated into geographic information systems (GIS). This paper presents a DEM-Ray intersection method for geolocating fire areas detected in thermal images captured by UAVs. Image coordinates associated with the fire detections are converted into viewing-direction vectors based on the camera parameters and rotated using the orientations of the UAV and gimbal. The resulting vectors, temperature values, and UAV position are transmitted to an edge system, where rays originating from the UAV are intersected with terrain represented by digital elevation model data. This produces temperature-attributed geospatial points representing the detected fire areas on the ground. The points can be visualized and further processed in GIS applications and shared with external systems using standard geospatial formats such as GeoJSON. The proposed approach can also be used to determine the geospatial coverage of each capture, which may support coverage assessment and flight planning. Developed and demonstrated within the wildfire use case of the HiCONNECTS project, the method provides a terrain-aware approach for transforming thermal-image detections into geospatial information for operational and analytical use.

Journal of Artificial Intelligence and Data AnalyticsVol. 1(3)
Openalex Percentile: Top 14%
Fire Detection and Safety Systems
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