Identification of tree species from high-resolution satellite imagery by using crown parameters

This paper is a contribution to develop crown shape parameters-based individual tree species identification in spaceborne high resolution imagery. However, crown measurements with spaceborne image data have remained more difficult than on aerial photographs since trees show more structural detail at higher resolutions. This recognized problem led to the initiation of the research to determine if high resolution satellite image data could be used to identify single tree species. The proposed feature analysis by using shape parameters and the selected texture parameters-the mean, variance and angular second moment(ASM) were tested and compared for single tree species delineation and identification. As expected, initial studies have shown that the crown shape parameters and the canopy texture parameters provided a differentiating method between coniferous trees and broad-leaved trees from QuickBird imagery.

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