The Characterization of a Forest Cover through Shape and Texture Parameters from Quickbird Imagery

Tree crown information on the amount of forest cover using high resolution images improves estimation of forest biomass which is needed for assessing carbon stocks both at the stand and plot-level. This paper is a contribution to develop crown discrimination of coniferous species, Pinus densiflora and Pinus Koraiensis, from QuickBird imagery. The proposed feature analysis derived from shape parameters and first and second-order statistical texture features of the same test area were compared for the two species separation and delineation. As expected, initial studies have shown that the form factor parameter provided the successful differentiating method between the pine species within the compartment for single crown identification from spaceborne high resolution imagery, even though the roundness parameter was used as segment based feature extraction. Another result revealed that the selected texture parameters - the mean, variance, angular second moment(ASM) - in the infrared band image could produce good subset combination of texture features for representing detailed tree crown outline.