Improvement of an oak canopy model extracted from digital photogrammetry

Abstract

Digital surface models (DSMs) automatically derived with digital photogrammetric systems are useful in land surface change monitoring, including forest growth monitoring. However, they cannot be applied directly to forest canopy change analysis with high accuracy due to the inevitable deficiencies in existing commercial digital photogrammetry packages. In a hardwood rangeland monitoring study, we found that the oak tree and woodland canopy boundaries were not well determined using several digital photogrammetry packages available to us. There was a noticeable discrepancy between the true crown closure and that determined by subtracting the DSM and the corresponding DEM that excludes tree heights. In this paper, we present a correction method for improvement at the erroneous canopy boundary locations in the DSM using shadow and boundary information extracted from imagery. The method is designed for correcting errors for broadleaf tree canopies. Aerial photographs taken over oak woodland hills were tested. Using manual photogrammetric measurements as the reference, we found that most of the points (88.3 percent) on the canopy boundaries were displaced by greater than 1 meter with a conventional digital photogrammetric package. After the proposed algorithms were applied, greater than 98.6 percent of the points on canopy boundaries were found to be within 1 meter of their reference positions. 78.4 percent of the reference points had greater than 2 meters elevation errors with the conventional package while greater than 85.6 percent of those points were found to be within 2 meters of the reference after the proposed algorithms were applied.