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This research was aimed at providing a study of digital elevation models from Airborne Laser Scanner (ALS) data. The goal was to improve the forest monitoring, or more specifically, arboreal canopy monitoring, which contains the most elevated vegetation of the forest. It is also described as the surface above the canopy top. The region of rain forest between the states of São Paulo and Paraná in Brazil was analyzed. The proposed method employs the ALS system that provides information related to different vegetative cover bedding, to analyze it and reach to estimate for the most elevated stage. The methodology is based on differentiating the identified surfaces in the original set of data. It uses these surfaces with a raster, which was obtained from an interpolation of different sets of points from the surfaces of interest. The raster structure, unlike vector data, allows for processes linked to the digital processing of images. It enables implementation of digital filters over the data. The method helped in reducing the influence of errors during classification and achieving the theoretical surface. The results revealed a coherent relationship with anthropogenic influence such as the introduction of exotic vegetation. We concluded that arboreal vegetation could be an index of conservation for environmental registration and licensing organizations

CANOPY HEIGHT MODELS TO MONITOR AREAS UNDER DEGRADATION IN MIXED OMBROPHILE