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Quantifying the impact of cloud obscuration on remote sensing of active fires in the Brazilian Amazon

Wilfrid Schroeder, University of Maryland, schroeder@hermes.geog.umd.edu (Presenting)

Vegetation fires continue to play a significant role in land and atmospheric processes globally. Their occurrence is particularly important in tropical regions where human activity is still heavily based on the use of fires for land use management and land cover change. Correct quantification of fire events is needed primarily for understanding the dynamics of land use and land cover change, as well as for providing information for modeling of emission estimates from biomass combustion. A major factor influencing fire numbers derived from remotely sensed data is the effect caused by cloud obscuration. Current methods used to compensate satellite active fire detection numbers to account for fires missed due to cloud obscuration tend to rely on the assumption that fires occur with the same frequency under cloud covered areas as they do in the open. The simplicity of this assumption will often cause an overestimation of fire omission due to clouds, especially in areas where fires are unevenly distributed in space. Here I present an alternative approach that uses physical (precipitation) and social (fire use history) information to more precisely quantify the potential omission error associated with the cloud obscuration affecting satellite active fire detection products. The proposed approach is applied to a geostationary satellite fire data set, in order to characterize the cloud effect on fire detection over the entire diurnal cycle. The analyses are focused on the Brazilian Amazon basin where intense fire activity and frequent cloud cover are prevalent.

Science Theme:  LC (Land Use and Land Cover Change)

Presentation Type:  Poster

Abstract ID: 75

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