An accuracy assessment of the MTBS burned area product for shrub–steppe fires in the northern Great Basin, United States
Aaron M. Sparks A , Luigi Boschetti A , Alistair M. S. Smith A B , Wade T. Tinkham A , Karen O. Lannom A and Beth A. Newingham A
+ Author Affiliations
- Author Affiliations
A Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, ID 83844-1133, USA.
B Corresponding author. Email: alistair@uidaho.edu
International Journal of Wildland Fire 24(1) 70-78 https://doi.org/10.1071/WF14131
Submitted: 25 July 2014 Accepted: 28 August 2014 Published: 26 November 2014
Abstract
Although fire is a common disturbance in shrub–steppe, few studies have specifically tested burned area mapping accuracy in these semiarid to arid environments. We conducted a preliminary assessment of the accuracy of the Monitoring Trends in Burn Severity (MTBS) burned area product on four shrub–steppe fires that exhibited varying degrees of within-fire patch heterogeneity. Independent burned area perimeters were derived through visual interpretation and were used to cross-compare the MTBS burned area perimeters with classifications produced using set thresholds on the Relativised differenced Normalised Burn Index (RdNBR), Mid-infrared Burn Index (MIRBI) and Char Soil Index (CSI). Overall, CSI provided the most consistent accuracies (96.3–98.6%), with only small commission errors (1.5–4.4%). MIRBI also had relatively high accuracies (92.2–97.9%) and small commission errors (2.1–10.8%). The MTBS burned area product had higher commission errors (4.3–15.5%), primarily due to inclusion of unburned islands and fingers within the fire perimeter. The RdNBR burned area maps exhibited lower accuracies (92.9–96.0%). However, the different indices when constrained by the MTBS perimeter provided variable results, with CSI providing the highest and least variable accuracies (97.4–99.1%). Studies seeking to use MTBS perimeters to analyse trends in burned area should apply spectral indices to constrain the final burned area maps. The present paper replaces a former paper of the same title (http://dx.doi.org/10.1071/WF13206), which was withdrawn owing to errors discovered in data analysis after the paper was accepted for publication.
Additional keywords: CSI, dNBR, MIRBI, RdNBR, remote sensing.
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