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Prediction of Burned Areas Using the Random Forest Classifier in the Minas Gerais State

2020; UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; Volume: 27; Issue: 3 Linguagem: Inglês

10.1590/2179-8087.011518

ISSN

2179-8087

Autores

Eliana Elizabet dos Santos, Nathalie Cruz Sena, Diego Balestrin, Elpı́dio Inácio Fernandes Filho, Liovando Marciano da Costa, Leiliane Bozzi Zeferino,

Tópico(s)

Environmental and biological studies

Resumo

Fire behavior prediction models can assist environmental agencies with fire prevention and control. This study aimed to adjust a fire prediction model for the state of Minas Gerais, Brazil. Using the R program and hotspots provided by the National Institute for Space Research (INPE) for 2010, prediction of the probability of fires through the Random Forest algorithm was conducted using the Bootstrapping method. The model generated a prediction map with global kappa value of 0.65. External validation was performed with hotspots in 2015. Results showed that 58% of the hotspots are in areas with ignition probability > 50%, being 24% of them in areas with 25-50% probability, and 17% in areas with < 25% probability. These results were considered satisfactory, demonstrating that the model is suitable for predicting fires.

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