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Proceedings Paper

Estimating above-ground biomass using lidar remote sensing
Author(s): Kevin S. Lim; Paul Treitz; Ian Morrison; Ken Baldwin
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Paper Abstract

Previous forest research using time-of-flight lidar suggests that there exists some quantile of the distribution of laser canopy heights that could provide an estimate of various forest biophysical properties. The results presented here not only support this theory, but also extend it by suggesting that a quantile of the distribution of all laser heights could provide estimates of aboveground biomass for forests with similar stand structure. Tolerant northern hardwood forests, composed predominantly of mature sugar maple (Acer saccharum Marsh.) and yellow birch (Betula alleghaniensis Britton), were surveyed using an ALTM 1225 (Optech Inc.) in August 2000. Field data for 49 circular plots, each 400 m2 in area, were collected in July 2000. Using site-specific allometric equations, total aboveground biomass and biomass components (i.e., stem wood, stem bark, live branches, and foliage) were derived for each plot. Three laser height metrics were derived from the lidar data: (i) maximum laser height; (ii) mean laser height; and (iii) mean laser height calculated from lidar returns filtered based on a threshold applied to the intensity return data LhIR). LhIR was identified as the best predictor of total aboveground biomass (R2 = 0.85) and biomass components (R2 between 0.84 to 0.85) when all plot types were considered.

Paper Details

Date Published: 17 March 2003
PDF: 8 pages
Proc. SPIE 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV, (17 March 2003); doi: 10.1117/12.462409
Show Author Affiliations
Kevin S. Lim, Queen's Univ. (United States)
Paul Treitz, Queen's Univ. (United States)
Ian Morrison, Canadian Forest Service (Canada)
Ken Baldwin, Canadian Forest Service (Canada)

Published in SPIE Proceedings Vol. 4879:
Remote Sensing for Agriculture, Ecosystems, and Hydrology IV
Manfred Owe; Guido D'Urso; Leonidas Toulios, Editor(s)

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