7th Workshop on Forest Fire Management - EARSeL, European ...

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II - VALIDATION OF RS PRODUCTS FOR FIRE MANAGEMENT
2 - Materials and methods
The analyses were carried out on AST07 surface reflectance in the VIS/NIR
with a resolution of 15 m and SWIR wavelengths with a spatial resolution
of 30 m. Three sets of ASTER data acquired over southern Italy in different
sites were used:
• Four scenes (08/17/02 - 06/10/03 - 06/24/03 - 08/11/03) to perform
SIs separability analysis by selecting pixels for burn (~1200) and unburn
classes (~800) (Stroppiana et al., 2009).
• Four scenes (20/07/01 - 08/09/01 - 05/09/03 - 14/09/04) to train the
algorithm by selecting 15,000 pixels of burn by photo-interpretation.
• One scene (28/07/2003) to assess method performance.
2.1 - SI selection and separability analysis
The analysis was conducted on five different Spectral Indices commonly
used for fire monitoring, see table, using images of the first data set. We
also included the NIR ASTER band 3 that is very sensitive to the damage
caused to vegetation by fire.
Index Formula
NBR Normalized Burn Ratio (ρNIR - ρSWIR 8 ) /(ρNIR - ρSWIR 8 )
BAI Burned Area Index [(0.1 - ρRED) 2 +(0.6 - ρNIR) 2 ] -1
MIBI Mid-Infrared Burn Index 10ρSWIR 5 - 9.5ρSWIR 4 + 2
CSI Char Soil Index ρNIR/ρSWIR 8
SAVI Soil-Adjusted Veg. Index (ρNIR - ρRED)(1.5)/(ρNIR + ρRED + 0.5)
ρRED, ρNIR, ρSWIR 4 , ρSWIR 5 , and ρSWIR 8 is the reflectance in ASTER bands 2, 3, 4, 5, and 8, respectively
Table 1 - Spectral indices used in this study.
Separability (S) (Kaufman and Remer, 1994) between burns and other surfaces
was computed using the formula S = |µ i,b - µ i,u |/(σ i,b + σ i,u ) where µ i,b
and σ i,b are the mean and standard deviation of burned areas and µ i,u and
σ i,u are the mean and standard deviation of unburned surfaces, respectively.
2.2 - Fuzzy functions definition and mapping method
In the adopted partially data-driven approach (Robinson, 2003) the histograms
of the values of each SI for the burn training pixels (data set 2)
were interpolated with a sigmoid curve. These functions map SI values into
the [0,1] domain where the higher likelihood of burn provides a score closer
to 1. The membership degrees of the indices are then combined into a