The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 119–124, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-119-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 119–124, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-119-2020

  05 Nov 2020

05 Nov 2020

COMPARISON BETWEEN DIFFERENT VERSIONS OF INPE'S FIRE RISK MODEL FOR THE BRAZILIAN BIOMES

G. Martins, J. Nogueira, A. Setzer, and F. Morelli G. Martins et al.
  • Satellite Division and Environmental Systems, Center for Weather Forecast and Climate Studies (CPTEC), National Institute for Space Research (INPE), Sao Jose dos Campos, Brazil

Keywords: fire regime, Brazilian biomes, INPE, meteorological data, MapBiomas, IGBP

Abstract. Fires are intrinsic disturbances in ecosystems functioning and structure in fire-prone biomes. In recent decades there has been an increase in the number of fire events in Brazilian biomes, especially due to misuse of fire in the land use and deforestation. The spatial and temporal pattern fire risk is a important way to understanding the seasonality and intensity of fire in different climate and fuel conditions. However, consistent long-term assessment at biome level is only possible with the support of remote sensing and modeling information. Thus, the objective of this work was to evaluate the fire risk patterns for the Brazilian biomes in the last years (2015–2018), using the new version of INPE’s fire risk (FR, v2). Regarding the temporal and spatial FR patterns by this new version from FR model, we evaluated that elevation and latitude correction factors, as well as the meteorological and land cover datasets with finer spatial scales can be contributed to adjust better the fire season vulnerability, notably in the less prone-biomes, such as Mata Atlantica, Pampa and Pantanal. However, there is still a need for adjustment to match the spatial active fire distribution, considering a biomass (fuel) map and the vegetation water status indicators. These improvements help to inform with more accuracy the most fire prone areas to define the strategies and decisions for fire combat and management.