Next Article in Journal
Object-Based Image Analysis of Downed Logs in Disturbed Forested Landscapes Using Lidar
Next Article in Special Issue
Burned Area Mapping in Greece Using SPOT-4 HRVIR Images and Object-Based Image Analysis
Previous Article in Journal
Tracking Environmental Compliance and Remediation Trajectories Using Image-Based Anomaly Detection Methodologies
Previous Article in Special Issue
Modeling Relationships among 217 Fires Using Remote Sensing of Burn Severity in Southern Pine Forests
Article Menu

Article Versions

Export Article

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

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

1
School of Geography and Environmental Science, Monash University, Melbourne, VIC 3800, Australia
2
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
*
Author to whom correspondence should be addressed.
Received: 20 September 2011 / Revised: 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)
View Full-Text   |   Download PDF [1021 KB, uploaded 19 June 2014]   |  

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. View Full-Text
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 (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top