Individual tree TLS point clouds for tree volume estimation

Dataset

This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern. The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands. Individual trees were semi-automatically segmented from the co-registered TLS point clouds.

Background

Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data. Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories. In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM). Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.

Funding Information:

This work was supported by:
  • NFI
  • WSL

Related Publications

Bornand, A., Rehush, N., Morsdorf, F., Thürig, E., Abegg, M., 2022. Individual tree volume estimation with terrestrial laser scanning: evaluating reconstructive and allometric approaches. Agricultural and Forest Meteorology 341, 1–41. https://doi.org/10.1016/j.agrformet.2023.109654

Citation:

Bornand, Aline (2023). Individual tree TLS point clouds for tree volume estimation. EnviDat. doi:10.16904/envidat.403.

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Data and Resources

Metadata

Field Values
DOI 10.16904/envidat.403
Publication State Published
Authors
  • Email: aline.bornandfoo(at)wsl.ch ORCID: 0000-0001-7712-5571 Given Name: Aline Family Name: Bornand Affiliation: WSL Additional Affiliation : UZH DataCRediT: Collection, Validation, Curation, Publication
Contact Person Given Name: Aline Family Name: Bornand Email: aline.bornandfoo(at)wsl.ch Affiliation: WSL ORCID: 0000-0001-7712-5571
Subtitles
Publication Publisher: EnviDat Year: 2023
Dates
  • Type: Collected Date: 2020-11-24 End Date: 2021-02-25
Version 1.0
Type dataset
General Type Dataset
Language English
Location Switzerland
Content License Creative Commons Attribution Share-Alike (CC-BY-SA)    [Open Data]
Last Updated August 30, 2023, 07:33 (UTC)
Created April 21, 2023, 09:07 (UTC)

Custom Metadata

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