Publication Date
7-31-2026
Document Type
Article
Publication Title
International Journal of Wildland Fire
Volume
35
Issue
8
DOI
10.1071/WF25235
Abstract
Background: Wildfires profoundly impact ecosystems and human health, making them a critical research focus. Drone-mounted Thermal Infrared (TIR) sensors are widely used for active fire monitoring due to their ability to penetrate smoke and capture real-time fire dynamics. Aims: This study addresses the challenges of georeferencing TIR data accurately, caused by limited fire anatomy modeling, imprecise georeferencing, the coarse resolution of TIR imagery and the dynamic nature of fire behavior. Methods: We collected a one-hour TIR dataset capturing a fast-moving controlled fire in a California canyon, US, alongside auxiliary data of multispectral and in situ meteorological observations. We developed an enhanced georeferencing method for TIR keyframes that accounts for different stages of fire development, integrating the fire anatomy, topography and fire behavior. The approach optimized accuracy with strategic tie point allocation, TIR temperature preprocessing, fire spread theory and raster transformation tailored to topography. Key results: The approach produced a customized dataset of 106 georeferenced TIR images for a one-hour active fire event across fire development. Conclusions: The method delivered precise geographic locations for TIR imagery of fast-moving fire, enabling reliable integration with auxiliary data. Implications: This approach supports advanced fire behavior analysis when combined with fuel maps, topography, and meteorological datasets.
Funding Number
2230778
Funding Sponsor
National Science Foundation
Keywords
California, drone remote sensing, fire behavior, maritime chaparral, orthomosaics, prescribed fire, thermal infrared, uncrewed aerial vehicles
Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Department
Biological Sciences; Urban and Regional Planning; Meteorology and Climate Science
Recommended Citation
Xiangyu Ren, Bo Yang, Alexander I. Filkov, Katherine M. Wilkin, C. David Benterou, Owen Hussey, and Craig B. Clements. "Integrating Georeferencing and Fire Anatomy Modeling in Canyon Fire Experiments Using Thermal Uav Remote Sensing" International Journal of Wildland Fire (2026). https://doi.org/10.1071/WF25235