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Mapping the Risk of Burning in the Brazilian Amazon with the Use of Logistic Regression and Fuzzy Inference
Authors:Camil Wadih Salame  Joaquim Carlos Barbosa Queiroz  Gilberto de Miranda Rocha  Mario Miguel Amin
Institution:(1) Department of Statistics (ICEN), Federal University of Para, Brazil, 66075-110 Belem, Para, Brazil;(2) Environment Nucleus (NUMA), Federal University of Para, Brazil, 66075-110 Belem, Para, Brazil;(3) Nucleus for Amazon Research (NAEA), Federal University of Para, Brazil, 66075-110 Belem, Para, Brazil
Abstract:Through the PRODESDIGITAL Project, the National Institute for Space Research (INPE) has been mapping vegetal coverage in the Brazilian Legal Amazon using Landsat satellite images. INPE not only identifies deforested areas but also releases a daily map of burning areas. Burning is frequently used as the cheapest way to deforest, to clear areas for farming and to increase the soil’s fertility in a short period of time. In many instances, these fires get out of control and end up accidentally invading areas of forest exploited by the lumber industry, agricultural plantations and pastures. However, the deforestation and burning area maps alone are insufficient for monitoring and control on a regional scale. It is necessary to know in an analytical way how actions (deforestation and burnings) that characterize human occupation are occurring in a region. In this research, two methods are used that allow the inclusion of co-variation in the estimation of variables of interest: logistic regression, which is a statistical method that considers a categorical or discrete response variable and discrete and/or continuous co-variation; and fuzzy logic, which makes use of artificial intelligence methods to incorporate into computational models information based on the knowledge or experience of a specialist. In both methods, the response variable may be related to the probability of occurrence of the environmental variable under study.
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