Near real time yield estimation for sugarcane in Brazil combining remote sensing and official statistical data

Besides energy concerns, the cultivation of sugarcane in Brazil plays an important role in the development of its agriculture, economy, and environment. However, there is no research on a broad operational yield monitoring system for sugarcane in Brazil based on remote sensing technologies. This paper aims at proposing a method to fill this gap. Five municipalities located in the west corner of São Paulo State, Brazil, were used to run and test a new method, which estimates the yield based on a combination of remote sensing and official historical data without using crop masks. Using data from 2003 to 2012, results stated that sugarcane yield estimates from January to March using remote sensing data tends to match strongly with the official yield, with the benefit of being known before the harvest season. Although we only tested five municipalities, we do expect that the proposed method might be applicable to wider regions as well as to other crops.