Comparison of TLS to total station accuracy for tree parameter measurement in biomass estimation

Krautz, Nathan (2019) Comparison of TLS to total station accuracy for tree parameter measurement in biomass estimation. [USQ Project]

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Abstract

Biomass estimation is a procedure often used for determining the growth, health, carbon content and contribution a forest has to the environment. For this reason, biomass estimations are an important step in forest decision making and monitoring, requiring accurate measurements.

This project compares the use of terrestrial laser scanners (TLS) and total stations (TS) when measuring the tree parameters of height and diameter at breast height (DBH) for use in biomass estimation.

Allometric equations use accurate height and DBH measurements to estimate the biomass of vegetation. Studies have also shown large differences between TS and TLS measurement of these variables. TS and TLS typically have mm and cm accuracy, however a simple tangent calculation using angle and distance to calculate height causes large errors if the tree is leaning or oddly shaped. Similarly, non-circular tree stems can cause variations in DBH measurement.

This study explores the accuracy of TS and TLS with revised methods of measurement to remove these errors and gain an improved indication of the accuracies of these instruments.

The results of this investigation have shown a dual total station setup method for height measurement achieves an accuracy of 0.052m giving an improved indication of the TLS when compared to this data. Also, a best fit circle approach in DBH measurement using a TLS found greatly improved consistency in measurement compared to other methods and effectively removed the impacts from irregular stem shapes.

Applying the established errors and accuracies to allometric equations, it was found that the TLS methods applied achieve a high level of accuracy for biomass estimation. With continually improving efficiency and visualisation benefits of TLS, this method will continue to grow in popularity.


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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Supervisors: McAlister, Chris
Qualification: Bachelor of Spatial Science (Honours) (Surveying)
Date Deposited: 26 Aug 2021 01:06
Last Modified: 26 Jun 2023 22:39
URI: https://sear.unisq.edu.au/id/eprint/43177

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