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Classification of Land Use and Land Cover in the Brazilian Amazon using Fuzzy Multilayer Perceptrons

Author

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  • Toni Pimentel

    (Instituto Nacional de Pesquisas Espaciais, São José dos Campos, Brazil)

  • Fernando M. Ramos

    (Instituto Nacional de Pesquisas Espaciais, São José dos Campos, Brazil)

  • Sandra Sandri

    (Instituto Nacional de Pesquisas Espaciais, São José dos Campos, Brazil)

Abstract

Here the authors propose the use of Fuzzy Multilayer Perceptrons for classification of land use and land cover patterns in the Brazilian Amazon, using time series of vegetation index, taken from NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. In addition to the traditional Multilayer Perceptron (MLP), three fuzzy implementations were investigated. These methods were applied to a study area of approximately 10.5 km2 on the east of the state of Mato Grosso in the Brazilian Amazon. For validation purposes, the authors compared the best implementation results with the ones given for the same region by the TerraClass 2010 project. The authors observed that our fuzzy MLP correctly classified 81% of the pixels analyzed.

Suggested Citation

  • Toni Pimentel & Fernando M. Ramos & Sandra Sandri, 2015. "Classification of Land Use and Land Cover in the Brazilian Amazon using Fuzzy Multilayer Perceptrons," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 5(1), pages 57-71, January.
    • Handle: RePEc:igg:jncr00:v:5:y:2015:i:1:p:57-71
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