Optimizing line-plot size for personal laser scanning: modeling distance-dependent tree detection probability along transects

doi:10.3832/ifor4588-017

Optimizing line-plot size for personal laser scanning: modeling distance-dependent tree detection probability along transects

Tim Ritter , Andreas Tockner, Ralf Krassnitzer, Sarah Witzmann, Christoph Gollob, Arne Nothdurft

iForest - Biogeosciences and Forestry, Volume 17, Issue 5, Pages 269-276 (2024)
doi: https://doi.org/10.3832/ifor4588-017
Published: Sep 07, 2024 - Copyright © 2024 SISEF

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Geo-mapping

Personal laser scanning (PLS) systems are gaining popularity in forest inventory research and practice. They are primarily utilized on circular or compact rectangular sample plots to mitigate potential instrument drift and enhance tree detection rates, and a closed-loop scan path is usually implemented to achieve these objectives, ensuring thorough coverage of the plot. This study introduced a novel approach by applying the distance-sampling framework to PLS data collected during walks along line transects. Modeling the distance-dependent probability of tree detection using PLS coupled with automatic routines for point cloud processing aimed to ascertain the optimal width of line-plots to maximize tree detection rates. The optimized plots exhibited tree detection rates exceeding 99%, which facilitated accurate estimates of tree density, basal area, and growing stock volumes. This proposed method demonstrated considerable potential for data collection while walking along line transects in forests. For instance, the otherwise unproductive working time of field crews moving between systematically arranged sample plots can be utilized for additional data collection without generating additional costs. This innovative approach not only enhances operational efficiency but also establishes a foundation for further advancements to explore PLS applications in forest management practices.

Keywords

Personal Laser Scanning, Lidar, Forest Inventory, Distance Sampling, Line Transect Sampling, Tree Detection

Authors’ address

(1)

0000-0001-7520-628X
0000-0001-6833-6713

0000-0002-4882-5920
0000-0002-7036-5115
0000-0002-7065-7601
University of Natural Resources and Life Sciences, Vienna - BOKU, Department of Forest and Soil Science, Institute of Forest Growth, Vienna (Austria)

Corresponding author

Tim Ritter
tim.ritter@boku.ac.at

Citation

Ritter T, Tockner A, Krassnitzer R, Witzmann S, Gollob C, Nothdurft A (2024). Optimizing line-plot size for personal laser scanning: modeling distance-dependent tree detection probability along transects. iForest 17: 269-276. - doi: 10.3832/ifor4588-017

Academic Editor

Marco Borghetti

Paper history

Received: Feb 15, 2024
Accepted: Jul 26, 2024

First online: Sep 07, 2024
Publication Date: Oct 31, 2024
Publication Time: 1.43 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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