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A VIIRS direct broadcast algorithm for rapid response mapping of wildfire burned area in the western United States

Posted date: December 17, 2018
Publication Year: 
2018
Authors: Urbanski, Shawn P.Nordgren, Bryce L.; Albury, Carl; Schwert, Brenna; Peterson, David; Quayle, Brad; Hao, Wei Min M.
Publication Series: 
Scientific Journal (JRNL)
Source: Remote Sensing of Environment. 219: 271-283.

Abstract

We present a direct broadcast (DB) rapid response burned area mapping algorithm for Visible Infrared Imaging Radiometer Suite (VIIRS) data that combines products driven by the spectral signal of fire-affected areas from both emissive and reflective spectral bands. The algorithm processes VIIRS infrared M-bands (750 m) using spectral ratios of the top of atmosphere reflectance from a single satellite scene to identify pixels exhibiting surface properties consistent with burn scars. Next, this collection of candidate burn scar pixels is screened using a contextual filter based on VIIRS I-band (375 m) active fire detections (AFD) which removes erroneously classified pixels and provides burn scar detections (BSD). The AFD and BSD are then resampled to a 375m grid and reported jointly as VIIRS burned area (VBA). The accuracy of the VBA was assessed for 390 wildfires (11-114,500 ha in size) in the western United States. The spatial accuracy was assessed by comparison with a validation dataset of Monitoring Trends in Burn Severity (MTBS) burned area and incident fire perimeter polygons. The VBA temporal accuracy was evaluated using a time series of daily fire perimeter polygons derived from high resolution airborne infrared imagery. The algorithm's burned area mapping accuracy is 59%. The algorithm detected 60% of burned area on the initial day of burning and 73% within 24 h.

Citation

Urbanski, Shawn; Nordgren, Bryce; Albury, Carl; Schwert, Brenna; Peterson, David; Quayle, Brad; Hao, Wei Min. 2018. A VIIRS direct broadcast algorithm for rapid response mapping of wildfire burned area in the western United States. Remote Sensing of Environment. 219: 271-283.