Automated estimation of localized forest volume from large-scale aerial photographs and ancillary cartographic information in a boreal forest

The development of an automated method for obtaining locally reliable estim ates of forest volume is demonstrated for a mixed-species boreal forest of the Lac St. Jean region of Quebec. The method relies on the ability of an a lgorithm based on local maxima to identify individual stems from a scanned aerial photograph under the assumption that the points of maximum light ref lectance will be the highest points on individual trees. This information i s linked via regression analysis to mean heights of dominant and co-dominan t trees and ground-based forest inventory data to provide a statistical rel ationship with forest volume. It was demonstrated that, by using the method , the local uncertainty of volume estimates could be decreased by 61% relat ive to standard forest inventory procedures. The method is not applicable t o young or disturbed stands. The greatest difficulty with the method is tha t sample plots used for validation must be locatable with absolute accuracy on the scanned aerial photographs-something that is likely to be problemat ic in many forest conditions.