Abstract
The objective of this project is to develop sugarcane yield prediction systems in regions of São Paulo state, based on the main drivers of crop production (soil, climate and sugarcane variety) and data from remote sensing using machine learning techniques. Remote sensing and agrometeorological data will be used to compare two methods of sugarcane yield estimation in regional scale: i) agr…