4.7 Article

Individual tree biomass estimation using terrestrial laser scanning

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Publisher

ELSEVIER
DOI: 10.1016/j.isprsjprs.2012.10.003

Keywords

Terrestrial laser scanning; Aboveground biomass; Individual tree; Features; Stem volume; Stem curve

Funding

  1. Metsamiesten saatio
  2. Finnish Academy project 'Improving the Forest Supply Chain by Means of Advanced Laser Measurements' (L-impact)
  3. Finnish Academy project 'Science and Technology Towards Precision Forestry' (PreciseFor)

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Determination of stem and crown biomass requires accurate measurements of individual tree stem, bark, branch and needles. These measurements are time-consuming especially for mature trees. Accurate field measurements can be done only in a destructive manner. Terrestrial laser scanning (TLS) measurements are a viable option for measuring the reference information needed. TLS measurements provide dense point clouds in which features describing biomass can be extracted for stem form and canopy dimensions. Existing biomass models do not utilise canopy size information and therefore TLS-based estimation methods should improve the accuracy of biomass estimation. The main objective of this study was to estimate single-tree-level aboveground biomass (AGB), based on models developed using TLS data. The modelling dataset included 64 laboratory-measured trees. Models were developed for total AGB, tree stem-, living branch- and dead branch biomass. Modelling results were also compared with existing individual tree-level biomass models and showed that AGB estimation accuracies were improved, compared with those of existing models. However, current biomass models based on diameter-at-breast height (DBH), tree height and species worked rather well for stem- and total biomass. TLS-based models improved estimation accuracies, especially estimation of branch biomass. We suggest the use of stem curve and crown size geometric measurements from TLS data as a basis for allometric biomass models rather than statistical three-dimensional point metrics, since TLS statistical metrics are dependent on various scanning parameters and tree neighbourhood characteristics. (c) 2012 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.

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