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Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology

Chudá, Juliána; Výbošt’ok, Jozef; Tomaštík, Julián; Chudý, František; Tunák, Daniel; Skladan, Michal; Tucek, Ján; (2024) Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology. Land , 13 (1) , Article 93. 10.3390/land13010093. Green open access

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Abstract

In this study, we evaluated the performance of GeoSLAM ZEB Horizon and Stonex X120GO SLAM handheld mobile laser scanners (HMLS) to address two primary objectives. First, we aimed to assess and compare the accuracy of positioning achieved using HMLS instruments. Second, we sought to investigate the influencing factors and their impact on estimation accuracies. The factors influencing the accuracy of positioning in HMLS Simultaneous Localization and Mapping-aided solutions were defined, considering the scanner type, distance from the trajectory, forest structure, tree species, and Diameter at Breast Height. The same type of trajectory was tested in five different stand structures. The evaluation of GeoSLAM HMLS point clouds yielded an average positional RMSE of 17.91 cm, while the data extracted from the Stonex HMLS resulted in an average positional RMSE of 17.33 cm. These results underscore the significant potential of HMLS technology in addressing the critical need for precise positioning data in various applications, from forestry management to environmental monitoring, wildlife habitat assessment, and climate change studies. By harnessing the power of handheld mobile laser scanners, our research aims to enhance the accuracy and efficiency of geospatial data capture in challenging.

Type: Article
Title: Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/land13010093
Publisher version: http://dx.doi.org/10.3390/land13010093
Language: English
Additional information: Copyright © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: Position; SLAM; tree; mapping; forest
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10189040
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