A per-segment approach to improving Aspen mapping from high-resolution remote sensing imagery

Abstract

Aspen (Populus tremuloides) stands on Winter Ridge in central Oregon were mapped from remote sensing imagery utilizing a per-segment approach. A 1-meter color infrared (CIR) image was segmented based on its hue and saturation values to generate aspen "candidates," which were then classified to show aspen coverage according to the mean values of multiresolution texture and spectral reflectance within the segments. With three broad categories for aspen distribution, overall accuracy was 88 percent, with K-hat statistics of 82 percent. The classification method holds promise for more detailed mapping of aspen from fine-resolution satellite imagery.