Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery

Uncertainties in burning efficiency (BE) estimates can lead to large errors in fire emission quantification (from 23% to 46%). One of the main causes of these errors is the spatial variability of fuel consumption within burned areas. This paper studies whether burn severity (BS) maps can be used to improve BE assessment. A burn severity map of two large fires in California was obtained by inverting a simulation model constrained by post-fire observations from Landsat TM imagery. Model output values of BS were validated against field measurements, obtaining a high correlation (R2 = 0.85) and low errors (Root Mean Square Error, RMSE = 0.14) throughout a wide range of BS levels. 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 vegetation indices from pre- and post-fire images. Results showed a high correlation for conifers (R2 = 0.75) and hardwoods (R2 = 0.73), and a moderate correlation (R2 ∼ 0.5) for shrubs and grasslands. In general, for all vegetation types BEadj performed better (R2 = 0.4–0.75) than literature-based BE (R2 < 0.0001). This study demonstrates: (i) the consistency of the simulation model inversion for BS estimation in temperate ecosystems, and (ii) the improvement of BE estimation when the spatial variability of the combustion was quantified in terms of BS.