Assessing the susceptibility of semiarid rangelands to wildfires using Terra MODIS and Landsat Thematic Mapper data
Fang Chen A B , Keith T. Weber A , Jamey Anderson A and Bhushan Gokhal A
+ Author Affiliations
- Author Affiliations
A GIS Training and Research Center, Idaho State University, 921 S 8th Avenue, Stop 8104, Pocatello, ID 83209-8104, USA.
B Corresponding author. Email address: chenfang@isu.edu
International Journal of Wildland Fire 20(5) 690-701 https://doi.org/10.1071/WF10001
Submitted: 5 January 2010 Accepted: 28 November 2010 Published: 8 August 2011
Abstract
In order to monitor wildfires at broad spatial scales and with frequent periodicity, satellite remote sensing techniques have been used in many studies. Rangeland susceptibility to wildfires closely relates to accumulated fuel load. The normalised difference vegetation index (NDVI) and fraction of photosynthetically active radiation (fPAR) are key variables used by many ecological models to estimate biomass and vegetation productivity. Subsequently, both NDVI and fPAR data have become an indirect means of deriving fuel load information. For these reasons, NDVI and fPAR, derived from the Moderate Resolution Imaging Spectroradiometer on-board Terra and Landsat Thematic Mapper imagery, were used to represent prefire vegetation changes in fuel load preceding the Millennial and Crystal Fires of 2000 and 2006 in the rangelands of south-east Idaho respectively. NDVI and fPAR change maps were calculated between active growth and late-summer senescence periods and compared with precipitation, temperature, forage biomass and percentage ground cover data. The results indicate that NDVI and fPAR value changes 2 years before the fire were greater than those 1 year before fire as an abundance of grasses existed 2 years before each wildfire based on field forage biomass sampling. NDVI and fPAR have direct implication for the assessment of prefire vegetation change. Therefore, rangeland susceptibility to wildfire may be estimated using NDVI and fPAR change analysis. Furthermore, fPAR change data may be included as an input source for early fire warning models, and may increase the accuracy and efficiency of fire and fuel load management in semiarid rangelands.
Additional keywords: biomass burning, fPAR, fuel loads, Idaho, NDVI, remote sensing.
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