Spatial Patterns of Fire Recurrence Using Remote Sensing and GIS in the Brazilian Savanna: Serra do Tombador Nature Reserve, Brazil

The Cerrado is the second largest biome in Brazil after the Amazon and is the savanna with the highest biodiversity in the world. Serra Tombador Natural Reserve (STNR) is the largest private reserve located in Goiás State, and the fourth largest in the Cerrado biome. The present study aimed to map the burnt areas and to describe the spatial patterns of fire recurrence and its interactions with the classes of land-cover that occurred in STNR and its surroundings in the period between 2001 and 2010. Several Landsat TM images acquired around the months of July, August and September, coinciding with the region’s dry season when fire events intensify, were employed to monitor burnt areas. Fire scars were mapped using the supervised Mahalanobis-distance classifier and further refined using expert visual interpretation. Burnt area patterns were described by spatial landscape metrics. The effects of fire on landscape structure were obtained by comparing results among different land-cover classes, and results summarized in terms of fire history and frequencies. During the years covered by the study, 69% of the areas analyzed had fire events. The year with the largest burnt area was 2004, followed by 2001, 2007 and 2010. Thus, the largest fire events occurred in a 3-year cycle, which is compatible with other OPEN ACCESS Remote Sens. 2014, 6 9874 areas of the Brazilian savanna. The regions with higher annual probabilities of fire recurrence occur in the buffer zone around the park. The year 2004 also had the highest number of burnt area patches (831). In contrast, the burnt area in 2007 showed the most extensive fires with low number of patches (82). The physiognomies that suffered most fires were the native savanna formations. The study also identified areas where fires are frequently recurrent, highlighting priority areas requiring special attention. Thus, the methodology adopted in this study assists in monitoring and recovery of areas affected by fire over time.