Prediction and Modeling of Forest Fires in the Pantanal

Abstract Uncontrolled fire points and forest fires in the Pantanal cause great damage to local flora and fauna. The prediction of these events is of paramount importance as it may mitigate or even avoid disasters in the Pantanal ecosystem. Given that fire prevention should be constant, the identification of fire foci is essential for immediate intervention. The objective of this study was to evaluate the forest fires in the Pantanal of Mato Grosso do Sul associated with the meteorological variables and to perform a forecast modeling. The environmental variables involved in the process were provided by the database of the Center for Weather Forecasting and Climate Studies of the National Institute for Space Research (INPE) and from the meteorological database for teaching and research of the National Institute of Meteorology (INMET). A close relationship was observed between the meteorological variables temperature, relative humidity and solar radiation and the occurrence of foci and the resulting correlations were satisfactory for the application of forecasting models. The Multiple Linear Regression technique presented fit of 41% and the Integrated Self-Regressive Analysis of Moving Average technique, 66.5%, and a general performance of 68.4%, thus making the latter the most recommended methodology for forecasting.