Remote sensing techniques have shown very promising results in the development of more trustworthy and economically viable large-scale agricultural production measurements. The Surface Energy Balance Algorithm for Land (SEBAL) has the advantage of obtaining biophysical parameters using satellite images and few observational data. This work aimed to estimate sugarcane production using the SEBAL algorithm and Landsat 5 TM images. It was performed on sugarcane crops at the Boa Fé farm, located in Conquista, MG, Brazil. The used method showed varying performance in the sugarcane production estimates for each plot, probably due to the influences of the size of the plots and the spatial resolution of the image, and of varieties and crop planting and harvest dates. However, the results indicate the method has potential for application on large areas on which there is limited availability of meteorological data.
Sugarcane; Biomass; SEBAL; Remote Sensing
