Caatinga Burned Areas' Validation through a Machine Learning approach to the INPE's Burns and Forest Fires Monitoring

Authors

  • Olga Oliveira Bittencourt Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil
  • Cícero Alves dos Santos Júnior Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil
  • Pedro Lagden Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil
  • Lucas Oliveira Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil
  • Rafael Santos Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil
  • Fabiano Morelli Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil

DOI:

https://doi.org/10.37002/biodiversidadebrasileira.v9i1.1196

Keywords:

Burned areas classification, machine learning, Caatinga

Author Biography

Olga Oliveira Bittencourt, Brazilian National Institute for Space Research (INPE), São José dos Campos, Brasil

Laboratório Associado de Computação e Matemática Aplicada - LAC

References

- Instituto Nacional de Pesquisas Espaciais (INPE): Programa de monitoramento de queimadas. http://www.inpe.br/queimadas/portal, accessed: 2018-01-28.

- Júnior, C. A. S, Bittencourt, O. O., Morelli, F. and Santos, R. Classificação de áreas queimadas por Machine Learning usando dados de Sensoriamento Remoto, XIX Simpósio Brasileiro de Sensoriamento Remoto, 2019.

- DEMsAR, J. et al. Orange: Data mining toolbox in python.

Journal of Machine Learning Research, v. 14, p. 2349-2353,

Published

2019-05-15