AUTOMATED MAPPING OF BURNED AREAS IN SEMI-ARID ECOSYSTEMS USING MODIS TIME-SERIES IMAGERY

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Standard satellite burned area and active fire products derived from the 500-m MODIS and SPOT are avail able to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applications. Consequently, we propose a novel algorithm for automated identification and mapping of burned areas at regional scale in semi-arid shrublands. The algorithm uses a set of the Normalized Burned Ratio Index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. The correlation between the size of burnt areas detected by the global fire products and independently-derived Landsat reference data ranged from R-2 = 0.01 - 0.28, while our algorithm performed showed a stronger correlation coefficient (R-2 = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.