Abstract
The agricultural sector is subject to adversities arising from weather events, incidence of pests, fires and market variations, therefore, it is extremely important to adopt rural insurance for an adequate management of agricultural activities. However, the existence of market failures inhibits the development and expansion of this market, especially in Brazil. In this context, the main goal of this article is to propose an innovative methodology that combines machine learning algorithms with optical and radar satellite images for forecasting agricultural losses, thus allowing for the reduction of informational asymmetries in the Brazilian market.
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