Automatic quality assessment of terrestrial laser scans

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Original languageEnglish
Pages (from-to)333-353
Number of pages21
JournalJournal of Applied Geodesy
Volume17
Issue number4
Early online date7 Apr 2023
Publication statusPublished - 26 Oct 2023

Abstract

This work addresses the topic of a quality modelling of terrestrial laser scans, including different quality measures such as precision, systematic deviations in distance measurement and completeness. For this purpose, the term "quality"is first defined in more detail in the field of TLS. A distinction is made between a total of seven categories that affect the quality of the TLS point cloud. The focus in this work lies on the uncertainty modeling of the TLS point clouds especially the distance measurement. It is demonstrated that influences such as the intensity and the incidence angle can lead to systematic deviations in the distance measurement of more than 1 mm. Based on these findings, it is presented that systematic deviations in distance measurement can be divided into four classes using machine learning classification approaches. The predicted classes can be useful for deformation analysis or for processing steps like registration. At the end of this work the entire quality assessment process is demonstrated using a real TLS point cloud (40 million points).

Keywords

    classification, machine learning, quality assessment, systematic deviations, uncertainty modelling

ASJC Scopus subject areas

Cite this

Automatic quality assessment of terrestrial laser scans. / Hartmann, Jan Moritz; Heiken, Max Leonard; Alkhatib, Hamza et al.
In: Journal of Applied Geodesy, Vol. 17, No. 4, 26.10.2023, p. 333-353.

Research output: Contribution to journalArticleResearchpeer review

Hartmann JM, Heiken ML, Alkhatib H, Neumann I. Automatic quality assessment of terrestrial laser scans. Journal of Applied Geodesy. 2023 Oct 26;17(4):333-353. Epub 2023 Apr 7. doi: 10.1515/jag-2022-0030
Hartmann, Jan Moritz ; Heiken, Max Leonard ; Alkhatib, Hamza et al. / Automatic quality assessment of terrestrial laser scans. In: Journal of Applied Geodesy. 2023 ; Vol. 17, No. 4. pp. 333-353.
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