Monetising the savings of remotely sensed data and information in Burn Area Emergency Response (BAER) wildfire assessment
Richard Bernknopf
A G , Yusuke Kuwayama B , Reily Gibson B , Jessica Blakely B , Bethany Mabee B , T. J. Clifford C , Brad Quayle D , Justin Epting D , Terry Hardy E and David Goodrich F
A Department of Economics, University of New Mexico, 1915 Roma Avenue, NE 1019, Albuquerque, NM 87131, USA.
B Resources for the Future, 1616 P Street NW, Suite 600, Washington, DC 20036, USA.
C Bruneau Field Office, Bureau of Land Management, US Department of the Interior, 3948 Development Avenue, Boise, ID 83705, USA.
D Geospatial Technology and Applications Center, Forest Service, US Department of Agriculture, 2222 West 2300 South, Salt Lake City, UT 84119, USA.
E Supervisor’s Office, Boise National Forest, Forest Service, US Department of Agriculture, 1249 S. Vinnell Way, Suite 200, Boise, ID 83709, USA.
F Southwest Watershed Research Center, Agricultural Research Service, US Department of Agriculture, 2000 East Allen Road, Tucson, AZ 85719, USA.
G Corresponding author. Email: rbern@unm.edu
International Journal of Wildland Fire 30(1) 18-29 https://doi.org/10.1071/WF19209
Submitted: 20 December 2019 Accepted: 13 September 2020 Published: 22 October 2020
Abstract
We used a value of information approach to demonstrate the cost-effectiveness of using satellite imagery as part of the Burn Area Emergency Response (BAER), a US federal program that identifies imminent post-wildfire threats to human life and safety, property and critical natural or cultural resources. We compared the costs associated with producing a Burn Area Reflectance Classification map and implementing a BAER when imagery from satellites (either Landsat or a commercial satellite) was available to when the response team relied on information collected solely by aerial reconnaissance. The case study included two evaluations with and without Burn Area Reflectance Classification products: (a) savings of up to US$51 000 for the Elk Complex wildfire incident request and (b) savings of a multi-incident map production program. Landsat is the most cost-effective way to input burn severity information into the BAER program, with savings of up to US$35 million over a 5-year period.
Keywords: cost effectiveness, fire economics, fire severity, policy, remote sensing.
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