Um modelo de rede neural para estimar a produtividade de milho a partir de imagens de satélite

Abstract

The soy moratorium has been an important instrument aimed at reducing deforestation in the Amazon biome. However, the existence of illegal deforestation of forests grows proportionally with the numbers of embargoed lands. Since in the moratorium there are some loopholes that have been exploited by producers linked to deforestation and practices such as grain laundering, which makes it difficult for analysts and control agencies to identify the real productivity of a property. This work proposes a model of artificial neural networks, called Deep Yield Prediction (DYP), capable of decoding the information learned using convolutional neural networks (CNN) in corn crop yield predictions, in a way that helps in the identification of how much a property will produce. Therefore collaborating to break the cycle of grain laundering and illegal deforestation in the Amazon biome.