Abstract

We present a new application of terrestrial laser scanning and mathematical modelling for the quantitative change detection of tree biomass, volume, and structure. We investigate the feasibility of the approach with two case studies on trees, assess the accuracy with laboratory reference measurements, and identify the main sources of error, and the ways to mitigate their effect on the results. We show that the changes in the tree branching structure can be reproduced with about ±10% accuracy. As the current biomass detection is based on destructive sampling, and the change detection is based on empirical models, our approach provides a non-destructive tool for monitoring important forest characteristics without laborious biomass sampling. The efficiency of the approach enables the repeating of these measurements over time for a large number of samples, providing a fast and effective means for monitoring forest growth, mortality, and biomass in 3D.

Highlights

  • The monitoring of forest resources has traditionally concentrated on the volume of stem wood

  • We have shown that the structure of trees can be characterized in detail based on Terrestrial laser scanning (TLS) measurements combined with 3D quantitative structure modelling

  • Typical ranges of the standard deviations of the 10 models of each cut are 5%–15% for the branch volume and 1%–2% for the branch length

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Summary

Introduction

The monitoring of forest resources has traditionally concentrated on the volume of stem wood. This is because human interest in forests has strongly focused on this economically most valuable forest characteristic. It is acknowledged that several ecosystem services that forests provide are related to the whole biomass of trees rather than the stem only. These services include, for example, carbon sequestration, forest bioenergy resources and forest biodiversity value. Tree biomass is monitored using established but rather coarse methods. A common method of biomass monitoring (such as that in the IPCC Guidelines [1]) is based on allometric equations (e.g., [1,2])

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