Fire severity estimation from space: a comparison of active and passive sensors and their synergy for different forest types
M. A. Tanase A C , R. Kennedy B and C. Aponte A
+ Author Affiliations
- Author Affiliations
A School of Ecosystem and Forest Sciences, University of Melbourne, 500 Yarra Boulevard, Richmond, Vic. 3121, Australia.
B College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-5503, USA.
C Corresponding author. Email: mihai.tanase@tma.ro
International Journal of Wildland Fire 24(8) 1062-1075 https://doi.org/10.1071/WF15059
Submitted: 26 November 2014 Accepted: 30 June 2015 Published: 31 August 2015
Abstract
Monitoring fire effects at landscape level is viable from remote sensing platforms providing repeatable and consistent measurements. Previous studies have estimated fire severity using optical and synthetic aperture radar (SAR) sensors, but to our knowledge, none have compared their effectiveness. Our study carried out such a comparison by using change detection indices computed from pre- and post-fire Landsat and L-band space-borne SAR datasets to estimate fire severity for seven fires located on three continents. Such indices were related to field-estimated fire severity through empirical models, and their estimation accuracy was compared. Empirical models based on the joint use of optical and radar indices were also evaluated. The results showed that optic-based indices provided more accurate fire severity estimates. On average, overall accuracy increased from 61% (SAR) to 76% (optical) for high-biomass forests. For low-biomass forests (i.e. aboveground biomass levels below the L-band saturation point), radar indices provided comparable results; overall accuracy was only slightly lower when compared with optical indices (69% vs 73%). The joint use of optical and radar indices decreased the estimation error and reduced misclassification of unburned forest by 9% for eucalypt and 3% for coniferous forests.
Additional keywords: accuracy assessment, ALOS PALSAR, CBI, L-band, Landsat, radar, radar-optical synergy.
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