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Remote Sens. 2011, 3(11), 2403-2419; doi:10.3390/rs3112403
Article

Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data

1,2
, 2,*  and 2
Received: 20 September 2011; in revised form: 18 October 2011 / Accepted: 18 October 2011 / Published: 11 November 2011
(This article belongs to the Special Issue Advances in Remote Sensing of Wildland Fires)
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Abstract: Wildland fires are a yearly recurring phenomenon in many terrestrial ecosystems. Accurate fire severity estimates are of paramount importance for modeling fire-induced trace gas emissions and rehabilitating post-fire landscapes. We used high spatial and high spectral resolution MODIS/ASTER (MASTER) airborne simulator data acquired over four 2007 southern California burns to evaluate the effectiveness of 19 different spectral indices, including the widely used Normalized Burn Ratio (NBR), for assessing fire severity in southern California chaparral. Ordinal logistic regression was used to assess the goodness-of-fit between the spectral index values and ordinal field data of severity. The NBR and three indices in which the NBR is enhanced with surface temperature or emissivity data revealed the best performance. Our findings support the operational use of the NBR in chaparral ecosystems by Burned Area Emergency Rehabilitation (BAER) projects, and demonstrate the potential of combining optical and thermal data for assessing fire severity. Additional testing in more burns, other ecoregions and different vegetation types is required to fully understand how (thermally enhanced) spectral indices relate to fire severity.
Keywords: fire severity; burn severity; Normalized Burn Ratio; emissivity; surface temperature; southern California; chaparral; MASTER fire severity; burn severity; Normalized Burn Ratio; emissivity; surface temperature; southern California; chaparral; MASTER
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Harris, S.; Veraverbeke, S.; Hook, S. Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data. Remote Sens. 2011, 3, 2403-2419.

AMA Style

Harris S, Veraverbeke S, Hook S. Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data. Remote Sensing. 2011; 3(11):2403-2419.

Chicago/Turabian Style

Harris, Sarah; Veraverbeke, Sander; Hook, Simon. 2011. "Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data." Remote Sens. 3, no. 11: 2403-2419.


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