Remote sensing data has been widely used for vegetation analysis. From the study of spectral variations in plants using remote sensing techniques, it is possible to obtain key information about the state of the vegetation. Vegetation indices are dimensionless radiometric measurements used to model the biophysical parameters of vegetation. These VIs are used to extract information such as green vegetation activity, leaf area index, percentage of green cover, chlorophyll content, green biomass, and absorbed photosynthetically active radiation.

The occurrence of diseases in plants has been causing major losses for pulp-producing companies in Brazil. Plant diseases can be evaluated by direct methods, where the estimation of the amount of disease is made directly from the symptoms, or by indirect methods, where the amount of disease is estimated by the pathogen population. Among the direct methods are the estimation of incidence and severity parameters and remote sensing techniques (Maffia et al., 2007). In studies of plant diseases, remote sensing, besides being used for quantification, can also serve to detect infected plants and/or areas attacked by phytopathogens.

The diversity of remote sensors in orbit and the development of digital image processing techniques have completely changed the way we evaluate diseases in large plantations. Plants infected by phytopathogens are not always perceptible to the human eye; however, they can be diagnosed using sensors that reveal changes in the spectral behavior of the plant. Remote sensing eliminates the need to collect and analyze laboratory samples, allowing for precise and reliable surveys in a short period of time and at a fraction of the cost of traditional methods. Orbital image processing can detect and monitor these occurrences, contributing to better productivity, regardless of the size of the area in question.