Abstract
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. R2 max = 0.548, min = 0.075). Imaged-derived fuel covariates alone are statistically weak predictors of ROS (adj. R2 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.
Highlights
Wildfires induce a variety of valuable ecosystem processes [1,2] but can inflict severe economic, social, and environmental losses
This study directly builds on Stow et al [63,64] by linking detailed airborne thermal infrared (ATIR) wildfire spread measurements to geospatial data representing fuel and topographic distributions derived from prefire National Agriculture Imagery Program (NAIP) orthoimagery and USGS digital elevation models (DEMs)
Through this study we demonstrated that repetitive ATIR imagery from the FireMapperTM 2.0 imaging system facilitates attainment of broader knowledge of the relationships between extreme wildfire behavior and controlling environmental factors
Summary
Wildfires induce a variety of valuable ecosystem processes [1,2] but can inflict severe economic, social, and environmental losses. Research on the mechanisms that govern wildfire spread are commonly conducted using laboratory [4,5,6,7] or outdoor fire experiments [8,9,10], where inputs may be controlled by researchers. Findings discerned from such studies have been extended to larger spatial scales using numerical models that simulate wildfire spread in various environments and conditions e.g., [11,12,13,14]
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