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

BURN SEVERITY AND BURNING EFFICIENCY ESTIMATION USING
SIMULATION MODELS AND GEOCBI
A. De Santis 1 , G.P. Asner 2 , P.J. Vaughan 3 , D. Knapp 2
1 Ingenieria y Servicios Aeroespaciales, SA (INSA), Systems & Earth Observation Department,
Madrid, Spain, angela.de.santis@insa.org
2 Stanford University, Department of Global Ecology, Stanford (CA)
gpa@stanford.edu; deknapp@stanford.edu
3 Laboratorio de Espectro-radiometria y Teledetección Ambiental. CCHS-CSIC
Madrid, Spain, patrick.vaughan@cchs.csic.es
Abstract: Uncertainties in burning efficiency (BE) estimates can lead to
high errors in fire emission quantification, due to the spatial variability of
fuel consumption within the burned area. Burn severity (BS) can be used
to improve the BE assessment. Therefore, in this study, a burn severity map
of two large fires in California was obtained by inverting a simulation model
and using a post-fire Landsat TM image. Estimated BS were validated
against field measurements, obtaining a high correlation (r 2 =0.85) and low
errors (Root Mean Square Error, RMSE = 0.14). The BS map obtained was
then used to adjust BE reference values per vegetation type found in the
area before the fire. The adjusted burning efficiency (BEadj) was compared
to the burned biomass, which was estimated by subtracting NDVI from preand
post-fire images. Results showed a high correlation for hardwoods
(r 2 =0.72) and grasslands (r 2 =0.69) and medium correlation (r 2 ~0.5) for
conifers and shrubs. In general for all vegetation types, BEadj perform better
(r 2 =0.4 - 0.72) than literature BE (r 2