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Related Experiment Video

Updated: Nov 2, 2025

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Published on: September 12, 2017

Sampling forests with terrestrial laser scanning.

Peter B Boucher^1,2, Ian Paynter³, David A Orwig⁴

¹School for the Environment, University of Massachusetts, Boston, MA, USA.

Annals of Botany

|June 10, 2021

Summary

This summary is machine-generated.

Terrestrial laser scanners (TLSs) capture forest data but face occlusion issues. New strategies improve TLS forest survey quality and representativeness by assessing sample completeness and adapting methods.

Keywords:

TLS Terrestrial LiDAR scanning forest inventory forest survey forestry sampling timber cruise

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Last Updated: Nov 2, 2025

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Published on: October 11, 2016

Area of Science:

Forestry and Remote Sensing
Ecological Survey Methods

Background:

Terrestrial laser scanners (TLSs) offer advanced forest survey capabilities.
Forest complexity causes occlusion, limiting TLS line of sight and data completeness.
Incomplete TLS samples impact forest survey quality and efficiency.

Purpose of the Study:

Evaluate occlusion sources and prevalence in TLS forest scans.
Assess the impact of incomplete TLS samples on forest stem data.
Test strategies to improve TLS sample quality and representativeness.

Main Methods:

Utilized 761 TLS scans and field data from Harvard Forest (ForestGEO).
Compared TLS-observed stem sets with field-derived sets (fixed range and line-of-sight models).
Evaluated four methods to correct stem densities for occlusion effects.

Main Results:

Non-stem objects were the primary cause of TLS line-of-sight occlusion.
Transect and point TLS samples were more representative than plot samples for some stem properties.
Calculating sampled area from TLS scans enhanced stem density estimations.

Conclusions:

TLS forest surveys require adaptable sampling strategies.
In-progress assessment of sample quality is crucial for TLS data.
Dynamic adaptation of sampling methods can improve forest survey outcomes.