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    Author(s): Robert C. Parker; Patrick A. Glass
    Date: 2004
    Source: Gen. Tech. Rep. SRS–71. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 103-107
    Publication Series: Miscellaneous Publication
    PDF: Download Publication  (168 KB)


    LiDAR data (0.5 and 1 m postings) were used in a double-sample forest inventory on the Lee Experimental Forest, Louisiana. Phase 2 plots were established with DGPS. Tree d.b.h. (> 4.5 inches) and two sample heights were measured on every 10 th plot of the Phase 1 sample. Volume was computed for natural and planted pine and mixed hardwood species. LiDAR trees were selected with new algorithms and focal filter procedures and height computed as the z-difference between interpolated canopy and DEM surfaces. LiDAR-derived heights were regressed against ground estimates. D.b.h.-height and LiDAR ground-height models were used to predicted d.b.h. from adjusted Lidar height and compute ground and LiDAR estimates of basal area and cubic volume. Phase 2 LiDAR estimates in mixed stands were computed by randomly assigning heights to species classes using a Monte Carlo simulation. Regression coefficients for Phase 2 estimates of square foot and cubic foot volume were computed for combined species product classes. Regression estimates for low-and high-density LiDAR combined volume were partitioned by species-product distribution of Phase 2 volume. There was no statistical difference between low- and high-density LiDAR estimates on the adjusted mean volume estimate (sampling errors of 10.41 percent and 11.75 percent).

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    Parker, Robert C.; Glass, Patrick A. 2004. Preliminary Results of Double-Sample Forest Inventory of Pine and Mixed Stands with High- and Low-Density LiDAR. Gen. Tech. Rep. SRS–71. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 103-107

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