Estimating the Surface Fuel Load of the Plant Physiognomy of the Cerrado Grassland Using Landsat 8 OLI Products.pdf

Micael Moreira Santos 1,*, Antonio Carlos Batista 1, Eduardo Henrique Rezende 2, Allan Deyvid Pereira Da Silva 2, Jader Nunes Cachoeira 2, Gil Rodrigues Dos Santos 3, Daniela Biondi 1 and Marcos Giongo Abstract: Techniques and tools meant to aid fire management activities in the Cerrado, such as accurately determining the fuel load and composition spatially and temporally, are pretty scarce. The need to obtain fuel information for more efficient management in a considerably heterogeneous, biodiverse, and fire-dependent environment requires a constant search for improved remote sensing techniques for determining fuel characteristics. This study presents the following objectives: (1) to assess the use of data from Landsat 8 OLI images to estimate the fine surface fuel load of the Cerrado during the dry season by adjusting multiple linear regression equations, (2) to estimate the fuel load through random forest and k-nearest neighbor (k-NN) algorithms in comparison to regression analyses, and (3) to evaluate t

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