Examining landscape-scale fuel and terrain controls of wildfire spread rates using repetitive Airborne Thermal Infrared (ATIR) imagery

The objectives of this study are to evaluate landscape-scale fuel and terrain controls on fire rate of spread (ROS) estimates derived from repetitive airborne thermal infrared (ATIR) imagery sequences collected during the 2017 Thomas and Detwiler extreme wildfire events in California. Environmental covariate data were derived from prefire National Agriculture Imagery Program (NAIP) orthoimagery and USGS digital elevation models (DEMs). Active fronts and spread vectors of the expanding fires were delineated from ATIR imagery. Then, statistical relationships between fire spread rates and landscape covariates were analyzed using bivariate and multivariate regression. Directional slope is found to be the most statistically significant covariate with ROS for the five fire imagery sequences that were analyzed and its relationship with ROS is best characterized as an exponential growth function (adj. R-2 max = 0.548, min = 0.075). Imaged-derived fuel covariates alone are statistically weak predictors of ROS (adj. R-2 max = 0.363, min = 0.002) but, when included in multivariate models, increased ROS predictability and variance explanation (+14%) compared to models with directional slope alone.

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Author Schag, G. M.
Stow, D. A.
Riggan, P. J.
Tissell, R. G.
Coen, Janice L.
Publisher UCAR/NCAR - Library
Publication Date 2021-02-03T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-11T19:09:49.286002
Metadata Record Identifier edu.ucar.opensky::articles:24280
Metadata Language eng; USA
Suggested Citation Schag, G. M., Stow, D. A., Riggan, P. J., Tissell, R. G., Coen, Janice L.. (2021). Examining landscape-scale fuel and terrain controls of wildfire spread rates using repetitive Airborne Thermal Infrared (ATIR) imagery. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d74b34pk. Accessed 18 August 2025.

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