System for processing of airborne images of forest ecosystems using high spectral and spatial resolution data

The developed hardware and software system for the recognition of natural and man-made objects based on the airborne hyperspectral sensing implements flight tasks on selected survey routes and computational procedures for solving applied problems that occur in data processing. The basics of object recognition based on obtained images of high spectral and spatial resolution in mathematical terms of sets of sites and labels and the basics of interrelations between separate resolution elements (pixels) for selected object classes are presented. Features of energy minimization of the processed scene are depicted as a target function of the optimization of computation and regularization of the solution of the considered problems as a theoretical basis for distinguishing between classes of objects in the presence of boundaries between them. Examples of the formation of information layers of recorded spectra for selected “pure species” of pine and birch forests are cited, with the separation of illuminated and shaded pixels, which increases the accuracy of object recognition in the processing of the images.