Abstract
New approaches to the processing of airborne hyperspectral images are implemented in order to develop emerging applications based on high-performance computing resources. The focus is on solving the problem of recognizing forest vegetation of different species composition and age based on high spectral and spatial resolution airborne sensing data. Examples of the formation of information layers of recorded spectra for “pure species” of pine and birch forests are given with the selection of illuminated and shaded pixels, which increases the accuracy of recognition of objects in the processing of these images.
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