SOJAMAPS: ORBITAL REMOTE SENSORS AND PHENOLOGY-BASED ALGORITHM USING THE GOOGLE EARTH ENGINE PLATFORM

Soybean is the main crop of the Brazilian agribusiness. The near-real-time monitoring of this crop is important in the production estimate, identification of the progress, and location of the crops. This study aimed to estimate and map soybean areas in almost real time using temporal series multispectral images and vegetation indices (near-infrared and red) in the Google Earth Engine system in MT, Brazil. A multitemporal algorithm of the PVI Index of MODIS, OLI, and MSI images of the 2016/2017 agricultural year was created from the identification of soybean areas using the PCEI Index. The use of the MODIS images for the monitoring of soybean areas using the Google Earth Engine platform was a viable and promising automated alternative for large-scale soybean area estimates.