Joshua J. Picotte Dr. Kevin Robertson
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1 Validation of National Burn Severity Mapping Project Techniques Within the Apalachicola National Forest Joshua J. Picotte Dr. Kevin Robertson
2 Project Overview Background Project Questions Results Problems Conclusions
3 Background-Burn Burn Severity and Joint Fires Science Program (JFSP) Burn Severity-ecosystem ecosystem change and dl landscape change System developed in 1996 by Carl lk Key and dn Nate Benson Started in the Western United dst States t Initial Fires Assessed-1994 Glacier National Park Fires Needs more work in East JFSP was formed in 1998 to provide support for fuel and fire management programs Key and Benson 1995 Key and Benson 1995
4 Background-Composite Burn Index (CBI) and Normalized Burn Ratio (NBR) NBR-Remote Remote sensing of fb burn severity Landsat bands R 4 and R 7 NBR = (R 4 -R 7 )/ (R 4 +R 7 ) dnbr=nbr prefire-nbr postfire CBI-Ground measure of burn severity 30 m plot CBI should validate NBR values
5 Background-deltaNormalized deltanormalized Burn Ratio (dnbr) dnbr: Change in reflectance between pre-fire (1 year pre-fire) and post-fire NBR values dnbr=nbrd prefire -NBR postfire 30m 30m 30m Weighted dnbr = Average of plot center and corners (N=5) Severity Unburned Low Low-Moderate Moderate-High High dnbr
6 Background-Composite Burn Index (CBI) Burn Index: Unburned 3-Severe Burn Five Strata 4-5 Ratings Factors Averaged CBI Score Average of Five Strata
7 Background-Apalachicola National Forest (ANF) Gulf of Mexico 2006 Dormant dnbr Unburned Low Severity Low-Moderate Severity Moderate-High Severity High Severity ² 0 6,858 13,716 27,432 Meters
8 Background-Habitats Within ANF A. Sandhill Pineland Turkey Oak Wiregrass Bracken Fern Long-Leaf Leaf Pine B. Flatwood Pineland Palmetto Long-Leaf/Slash Leaf/Slash Pine C. Depression Swamp Cypress Titi Pond Pine A. B. C.
9 Project Questions 1. Does this system adequately describe burn severity with the South East ecosystems? 2. How long after a fire can burn perimeters be remotely sensed? 3. Are there differences in the effectiveness of using CBI and dnbr to categorize burn severity in the three community types of the ANF? 4. What are the appropriate ranges dnbr for given burn severity categories? 5. What problems arise in assessing burn severity?
10 Results-Sandhill Burn Severity ² Meters Severity Acres Unburned Area 15 Low Low-Moderate Moderate-High Percent Fire 10 High Total Total Burned dnbr
11 Results-Flatwood Burn Severity 0 8,001 16,002 32,004 Meters ² Wet Flatwoods, Initial Assessment Severity Acres 12 Unburned Low Low-Moderate Moderate-High High Total Total Burned Percent Fire Area dnbr
12 Results-Correlation Between CBI 2.5 Overall and dnbr 2.5 Sandhill 2 2 CBI CBI dnbr Weighted dnbr Weighted Flatwoods R 2 P>Fr CBI Overall Sandhills Flatwoods < dnbr Weighted
13 Results-Correlations between CBI and dnbr Within Substrates Substrates Vegetation < 1m 1m < Vegetation < 5m Subcanopy Trees Upper Canopy Trees Overall R P>Fr <0.001 < Sandhills Flatwoods R 2 P>Fr R 2 P>Fr Substrates Substrates Vegetation < 1m Vegetation < 1m <.001 1m < Vegetation < 5m m < Vegetation < 5m <.001 Subcanopy Trees Subcanopy Trees <.001 Upper Canopy Trees Upper Canopy Trees <.001
14 Burn Severity Change Detection- Water ² Meters ² Meters 2006 Dormant dnbr Unburned Low Severity Low-Moderate Severity Moderate-High Severity High Severity Lakes and Ponds Actual Pond Boundary
15 Problematic detection of Low Burn Severity A Dormant dnbr Unburned Low Severity Low-Moderate Severity Moderate-High Severity High Severity! 30m Plots B. C. Plot CBI dnbr A B. C ² ,020 Meters
16 Conclusions Successful in high fire frequency communities Extrapolation to other communities within the East Useful system for burn monitoring i Sense perimeter months following the burn Season of remote-sensing (dnbr) may be limited Useful in assessing the success of burn management plans
17 Acknowledgements Nate Benson Jason Drake Leigh Lentile Caroline Noble Joe Noble Don Ohlen Kathy Marois David Printiss Greg Titus Eugene Watkins
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