Use of airborne radar images for digital mapping of soil attributes under the Amazon rainforest: a case study in Solimões Formation
Digital soil mapping, machine learning, radar remote sensing
Ana Carolinda de S. Ferreira's qualification avaliation, focusing on data modeling, digital soil mapping and remote sensing using Radar image. Coordinated by Marco Baccis Ceddia, and members; Helena Saraiva Koenow Pinheiro, Mauro Antônio Homem Antunes and Waldir de Carvalho Júnior Oliveira.
The research project assumes that it is possible to generate spatial variability maps of soil attributes from the use of data mining techniques and covariates derived from remote sensors such as radar images. The using Radar images as covariates in prediction models can improve and assist in estimating soil attributes under the Amazon rainforest. The global is to evaluate the potential of the addition of radar imaging derivatives in carbon stock prediction, soil texture and soil type identification under Amazon Forest, Solimões Formation.