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

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  • Juliána Chudá

    (Department of Forest Harvesting, Logistics and Ameliorations, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Jozef Výbošťok

    (Department of Forest Harvesting, Logistics and Ameliorations, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Julián Tomaštík

    (Department of Forest Resources Planning and Informatics, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • František Chudý

    (Department of Forest Resources Planning and Informatics, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Daniel Tunák

    (Department of Forest Resources Planning and Informatics, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Michal Skladan

    (Department of Forest Harvesting, Logistics and Ameliorations, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Ján Tuček

    (Department of Forest Resources Planning and Informatics, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia)

  • Martin Mokroš

    (Department of Forest Harvesting, Logistics and Ameliorations, Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, 96001 Zvolen, Slovakia
    Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, 165 21 Prague, Czech Republic
    Department of Geography, University College London, Gower Street, London WC1E 6BT, UK
    NERC National Centre for Earth Observation (NCEO), University College London, London WC1E 6BT, UK)

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.

Suggested Citation

  • Juliána Chudá & Jozef Výbošťok & Julián Tomaštík & František Chudý & Daniel Tunák & Michal Skladan & Ján Tuček & Martin Mokroš, 2024. "Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology," Land, MDPI, vol. 13(1), pages 1-23, January.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:1:p:93-:d:1318674
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    References listed on IDEAS

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    1. Abdurahman Yasin Yiğit & Seda Nur Gamze Hamal & Murat Yakar & Ali Ulvi, 2023. "Investigation and Implementation of New Technology Wearable Mobile Laser Scanning (WMLS) in Transition to an Intelligent Geospatial Cadastral Information System," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
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      Keywords

      position; SLAM; tree; mapping; forest;
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