Abstract
Abstract. 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 applica - tions. 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 R2 = 0.01 - 0.28, while our algorithm performed showed a stronger correlation coefficient (R2 = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.
Highlights
Over the past few decades wildfires have received significant attention because of the wide range of ecological, economic, social, and political values at stake
The first phase aims to detect ‘potentially burned’ pixels while keeping a low commission error; these pixels become ‘seed patches’ and are input to a region growing image segmentation algorithm to delineate the perimeter of the fire affected area, decreasing omission errors in this process
The influence of climate change on wildfires on this type of biome is difficult to predict; some authors have suggested that an increase of wildfires is very likely to occur directly, due to an increase in climate variability and as a consequence of warmer weather (IPCC 1996, WG II, Chapter 2), and indirectly because fires may reduce local precipitation because fire-emitted aerosols increase in the number of cloud condensation nuclei, producing smaller cloud droplets that are less likely to fall as rain (IPCC 1996, WG II, Chapter 1)
Summary
Over the past few decades wildfires have received significant attention because of the wide range of ecological, economic, social, and political values at stake Their impacts rely heavily on the intensity, frequency and spatial distribution, which in turn are influenced in complex ways by several natural and anthropic factors. This paper investigates whether global fire products can cater for the provision of accurate data and information on wildfires (or bushfires) over small areas, and/or complex spatial patterns that are common to semiarid ecosystems To this end we developed and tested a novel algorithm for automatic delimitation of burned areas at regional or local scale, using the semi-arid Monte ecosystems of Argentina as pilot study area, and compared its performance with selected MODIS-and SPOT VEGETATION-derived global fire products
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