Skip to Main Content
Field validation of Burned Area Reflectance Classification (BARC) products for post fire assessmentAuthor(s): Andrew T. Hudak; Peter R. Robichaud; Jeffery B. Evans; Jess Clark; Keith Lannom; Penelope Morgan; Carter Stone
Source: In: Greer, Jerry Dean, ed. Remote sensing for field users; proceedings of the tenth Forest Service remote sensing applications conference; 2004 April 5–9; Salt Lake City, UT. Bethesda, MD: American Society of Photogrammetry and Remote Sensing. CD-ROM.
Publication Series: Paper (invited, offered, keynote)
Station: Rocky Mountain Research Station
PDF: Download Publication (535.87 KB)
DescriptionThe USFS Remote Sensing Applications Center (RSAC) and the USGS EROS Data Center (EDC) produce Burned Area Reflectance Classification (BARC) maps for use by Burned Area Emergency Rehabilitation (BAER) teams in rapid response to wildfires. BAER teams desire maps indicative of soil burn severity, but photosynthetic and nonphotosynthetic vegetation also influences the spectral properties of post-fire imagery. Our objective was to assess burn severity both remotely and on the ground at six 2003 wildfires. We analyzed fire-effects data from 34 field sites located across the full range of burn severities observed at the Black Mountain Two, Cooney Ridge, Robert, and Wedge Canyon wildfires in western Montana and the Old and Simi wildfires in southern California. We generated Normalized Burn Ratio (NBR), delta Normalized Burn Ratio (dNBR), and Normalized Difference Vegetation Index (NDVI) indices from Landsat 5, SPOT 4, ASTER, MASTER and MODIS imagery. Pearson correlations between the 44 image and 79 field variables having an absolute value greater than 0.5 were judged meaningful and tabulated in overstory, understory, surface cover, and soil infiltration categories. Vegetation variables produced a higher proportion of meaningful correlations than did surface cover variables, and soil infiltration variables the lowest proportion of meaningful correlations. Soil properties had little measurable influence on NBR, dNBR or NDVI, particularly in low and moderate severity burn areas where unconsumed vegetation occludes background reflectance. BAER teams should consider BARC products much more indicative of post-fire vegetation condition than soil condition. Image acquisition date, in relation to time of field data collection and time since fire, appears to be more important than type of imagery or index used. We recommend preserving the raw NBR or dNBR values in an archived map product to enable remote monitoring of post-fire vegetation recovery. We further recommend that BAER teams rely on the continuous BARC-Adjustable (BARC-A) product (and assign their own severity thresholds as needed) more than the classified BARC product, which oversimplifies highly heterogeneous burn severity characteristics on the ground.
- You may send email to firstname.lastname@example.org to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationHudak, Andrew T.; Robichaud, Peter R.; Evans, Jeffery B.; Clark, Jess; Lannom, Keith; Morgan, Penelope; Stone, Carter. 2004. Field validation of Burned Area Reflectance Classification (BARC) products for post fire assessment. In: Greer, Jerry Dean, ed. Remote sensing for field users; proceedings of the tenth Forest Service remote sensing applications conference; 2004 April 5–9; Salt Lake City, UT. Bethesda, MD: American Society of Photogrammetry and Remote Sensing. CD-ROM.
Keywordswildfires, maps, vegetation, soil, burn severity, Moderate Resolution Imaging Spectroradiometer (MODIS), Burned Area Emergency Rehabilitation (BAER), Burned Area Reflectance Classification (BARC), Normalized Difference Vegetation Index (NDVI)
- The relationship of multispectral satellite imagery to immediate fire effects
- Sensitivity of Landsat image-derived burn severity indices to immediate post-fire effects
- Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+data.
XML: View XML