Modeling Relationships among 217 Fires Using Remote Sensing of Burn Severity in Southern Pine Forests

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dc.rights.license Attribution 4.0 International (CC BY 4.0) en_US
dc.contributor.author Staudhammer, Christina Lynn
dc.contributor.author Malone, Sparkle L.
dc.contributor.author Kobziar, Leda N.
dc.contributor.author Abd-Elrahman, Amr
dc.coverage.spatial Southern States en_US
dc.coverage.spatial United States en_US
dc.date.accessioned 2018-11-20T18:52:28Z
dc.date.available 2018-11-20T18:52:28Z
dc.date.issued 2011-09-07
dc.identifier.citation Malone, S., Kobziar, L., Staudhammer, C., Abd-Elrahman, A. (2011): Modeling Relationships among 217 Fires Using Remote Sensing of Burn Severity in Southern Pine Forests. Remote Sensing, 3(9). DOI: https://doi.org/10.3390/rs3092005 en_US
dc.identifier.uri http://ir.ua.edu/handle/123456789/4973
dc.description.abstract Pine flatwoods forests in the southeastern US have experienced severe wildfires over the past few decades, often attributed to fuel load build-up. These forest communities are fire dependent and require regular burning for ecosystem maintenance and health. Although prescribed fire has been used to reduce wildfire risk and maintain ecosystem integrity, managers are still working to reintroduce fire to long unburned areas. Common perception holds that reintroduction of fire in long unburned forests will produce severe fire effects, resulting in a reluctance to prescribe fire without first using expensive mechanical fuels reduction techniques. To inform prioritization and timing of future fire use, we apply remote sensing analysis to examine the set of conditions most likely to result in high burn severity effects, in relation to vegetation, years since the previous fire, and historical fire frequency. We analyze Landsat imagery-based differenced Normalized Burn Ratios (dNBR) to model the relationships between previous and future burn severity to better predict areas of potential high severity. Our results show that remote sensing techniques are useful for modeling the relationship between elevated risk of high burn severity and the amount of time between fires, the type of fire (wildfire or prescribed burn), and the historical frequency of fires in pine flatwoods forests. en_US
dc.format.mimetype application/pdf en_US
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject burn severity en_US
dc.subject remote sensing en_US
dc.subject differenced normalized burn ratios en_US
dc.subject fire frequency en_US
dc.subject pine flatwoods forest en_US
dc.subject fire model en_US
dc.subject wildfire en_US
dc.subject prescribed fire en_US
dc.title Modeling Relationships among 217 Fires Using Remote Sensing of Burn Severity in Southern Pine Forests en_US
dc.type text en_US


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Attribution 4.0 International (CC BY 4.0) Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)

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