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Assessing uncertainty and demonstrating potential for estimating fire rate of spread at landscape scales based on time sequential airborne thermal infrared imaging

ORCID Icon, , , , , & ORCID Icon show all
Pages 4876-4897
Received 20 Oct 2018
Accepted 14 Jan 2019
Published online: 17 Feb 2019


An important property of wildfire behaviour is rate of spread (ROS). The objectives of this study are to evaluate the uncertainty of landscape-scale ROS estimates derived from repetitive airborne thermal infrared (ATIR) georeferenced imagery and the utility of such estimates for understanding fire behaviour and controls on spread rates. Time-sequential ATIR image data were collected for the Cedar, Detwiler, and Rey Fires, which burned in California during summers of 2016 and 2017. We analyse error, uncertainty, and precision of ROS estimates associated with co-location accuracy, delineation of active fire front positions, and generation of fire spread vectors. The major sources of uncertainty influencing accuracy of ROS estimates are co-registration accuracy of sequential image pairs and procedures for delineating active fire front locations and spread vectors between them; none of these were found to be substantial. Median ROS estimates are 11 m min−1 for the Cedar Fire and 8 m min−1 for the Detwiler Fire, both of which burned through mixed shrub and tree areas of the Sierra Nevada foothills and were estimated for downslope spread events. Of the three study fires, the fastest spread rates (average spread of 25 m min−1 with maximum of 39 m min−1) are estimated for the Rey Fire, which burned on variable directional slopes through chaparral shrubland vegetation.


ATIR image acquisition and pre-processing was conducted by Michaela Truman and David Maxwell of Kolob Canyon Air Services, Cedar City, UT. Lloyd (Pete) Coulter assisted with evaluation of image co-registration accuracy. Referees provided valuable recommendations for improving this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information


This research was funded by US National Science Foundation, Division of Social, Behavioural and Economic Research, Geography and Spatial Sciences program [grant no. G00011220]; and Directorate for Social, Behavioral and Economic Sciences.

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