Download (PDF 1.02 MB): https://research.fs.usda.gov/download/treesearch/26573.pdf
Abstract
A study of forest stand canopy variable assessment using digital, airborne, multispectral imagery is presented. Variable estimation involves stem density, canopy closure, and mean crown diameter, and it is based on quantification of spatial autocorrelation among pixel digital numbers (DN) using variogram analysis and an alternative, non-parametric approach known as slope-break analysis. Variable estimation proceeds from identification of tree tops. Variable accuracy assessment is obtained via value comparison with a spatially precise set of 34 Forest Inventory and Analysis (FIA) design plots installed in five cover types common in the Midwest region. Results show that slope-break-based variable estimates are superior to those obtained using variograms. Estimated root mean square errors for the former average at the plot level were 6.5 percent for stem density, 3.5 percent for canopy closure, and 2.5 percent for mean crown diameter. These error rates are equivalent, if not superior to (lower than), those obtained via traditional forest stand cruising by experienced personnel. The approach benefits from parsimonious parameterization and is amenable to automation.
Parent Publication
Citation
Gatziolis, Demetrios. 2006. Forest Stand Canopy Structure Attribute Estimation from High Resolution Digital Airborne Imagery. In: Aguirre-Bravo, C.; Pellicane, Patrick J.; Burns, Denver P.; and Draggan, Sidney, Eds. 2006. Monitoring Science and Technology Symposium: Unifying Knowledge for Sustainability in the Western Hemisphere Proceedings RMRS-P-42CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 783-789
