4.7 Article

Measuring forest structure and biomass in New England forest stands using Echidna ground-based lidar

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 115, Issue 11, Pages 2965-2974

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2010.03.019

Keywords

Ground-based lidar; Forest structure; Biomass; Vegetation; New England forests

Funding

  1. NASA [NNG06GI92G, NNX08AE94A]
  2. National Key Basic Research Development Program of China [2007CB714400]
  3. NASA [NNX08AE94A, 102244] Funding Source: Federal RePORTER

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A ground-based, upward-scanning, near-infrared lidar, the Echidna (R) validation instrument (EVI), built by CSIRO Australia, retrieves forest stand structural parameters, including mean diameter at breast height (DBH), stem count density (stems/area), basal area, and above-ground woody biomass with very good accuracy in six New England hardwood and conifer forest stands. Comparing forest structural parameters retrieved using EVI data with extensive ground measurements, we found excellent agreement at the site level using five EVI scans (plots) per site (R-2 = 0.94-0.99): very good agreement at the plot level for stem count density and biomass (R-2 = 0.90-0.85); and good agreement at the plot level for mean DBH and basal area (R-2 = 0.48-0.66). The observed variance at site and plot levels suggest that a sample area of at least 1 ha (10(4) m(2)) is required to estimate these parameters accurately at the stand level using either lidar-based or conventional methods. The algorithms and procedures used to retrieve these structural parameters are dependent on the unique ability of the Echidna (R) lidar to digitize the full waveform of the scattered lidar pulse as it returns to the instrument, which allows consistent separation of scattering by trunks and large branches from scattering by leaves. This successful application of ground-based lidar technology opens the door to rapid and accurate measurement of biomass and timber volume in areal sampling scenarios and as a calibration and validation tool for mapping biomass using airborne or spaceborne remotely sensed data. (C) 2011 Elsevier Inc. All rights reserved.

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