Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: Influence of spatial pattern and vegetation type

An algorithm for burned area mapping in Africa based on classification trees was developed using SPOT-VEGETATION (VGT) imagery. The derived 1 km spatial resolution burned area maps were compared with 30 m spatial resolution maps obtained with 13 Landsat ETM+ scenes, through linear regression analysis. The procedure quantifies the bias in burned area estimation present in the low spatial resolution burned area map. Good correspondence was observed for seven sites, with values of the coefficient of determination (R²) ranging from 0.787 to 0.983. Poorer agreement was observed in four sites (R² values between 0.257 and 0.417), and intermediate values of R² (0.670 and 0.613) were obtained for two sites. The observed variation in the level of agreement between the Landsat and VGT estimates of area burned results from differences in the spatial pattern and size distribution of burns in the different fire regimes encompassed by our analysis. Small and fragmented burned areas result in large underestimation at 1 km spatial resolution. When large and compact burned areas dominate the landscape, VGT estimates of burned area are accurate, although in certain situations there is some overestimation. Accuracy of VGT burned area estimates also depends on vegetation type. Results showed that in forest ecosystems VGT maps underestimate substantially the amount of burned area. The most accurate estimates were obtained for woodlands and grasslands. An overall linear regression fitted with the data from the 13 comparison sites revealed that there is a strong relationship between VGT and Landsat estimates of burned area, with a value of R² of 0.754 and a slope of 0.803. Our findings indicate that burned area mapping based on 1 km spatial resolution VGT data provides adequate regional information.     

Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain)

The Ayora region, situated about 60 km southwest of the city of Valencia/Spain, was chosen to demonstrate pathways of characterizing fire events and post-fire succession in Mediterranean ecosystems using multi-temporal satellite imagery. A corresponding time series of 6 Landsat MSS, 13 Landsat-5 TM and 1 Landsat-7 ETM + images, covering the period 1975—2000, was processed to account for geometric and radiometric distortions as well as sensor calibration. Spectral Mixture Analysis was applied to derive estimates of photosynthetic active green vegetation cover as a primary indicator.A combination of pixel-based linear trend analysis and diachronic thresholding was employed to procure a fire perimeter data base and characterize post-fire dynamics based on a temporally stratified trend analysis. The results were integrated with auxiliary information to evaluate driving factors and further interpreted in relation to field-based information on plant communities and post-fire succession patterns.Reflecting typical recovery phases with an initial establishment of grasses and herbaceous species, followed by a gradual development of a shrub layer and the subsequent colonization of tree individuals, temporal trajectories could be described by exponential functions and were related to plot-based botanical information.