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  • Error in target-based georeferencing and registration in terrestrial laser scanning

    Rights statement: This is the author’s version of a work that was accepted for publication in Computers & Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Geosciences, 83, 2015 DOI: 10.1016/j.cageo.2015.06.021

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Error in target-based georeferencing and registration in terrestrial laser scanning

Research output: Contribution to journalJournal article

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<mark>Journal publication date</mark>10/2015
<mark>Journal</mark>Computers and Geosciences
Volume83
Number of pages11
Pages (from-to)54-64
Publication StatusPublished
Early online date6/07/15
<mark>Original language</mark>English

Abstract

Terrestrial laser scanning (TLS) has been used widely for various applications, such as measurement of movement caused by natural hazards and Earth surface processes. In TLS surveying, registration and georeferencing are two essential steps, and their accuracy often determines the usefulness of TLS surveys. So far, evaluation of registration and georeferencing errors has been based on statistics obtained from the data processing software provided by scanner manufacturers. This paper demonstrates that these statistics are incompetent measures of the actual registration and georeferencing errors in TLS data and, thus, should no longer be used in practice. To seek a suitable replacement, an investigation of the spatial pattern and the magnitude of the actual registration and georeferencing errors in TLS data points was undertaken. This led to the development of a quantitative means of estimating the registration- or georeferencing-induced positional error in point clouds. The solutions proposed can aid in the planning of TLS surveys where a minimum accuracy requirement is known, and are of use for subsequent analysis of the uncertainty in TLS datasets.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Computers & Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Geosciences, 83, 2015 DOI: 10.1016/j.cageo.2015.06.021