A Method for Efficient Quality Control and Enhancement of Mobile Laser Scanning Data

Slaven Kalenjuk*, Werner Lienhart

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in einer FachzeitschriftArtikelBegutachtung

Abstract

The increasing demand for 3D geospatial data is driving the development of new products. Laser scanners are becoming more mobile, affordable, and user-friendly. With the increased number of systems and service providers on the market, the scope of mobile laser scanning (MLS) applications has expanded dramatically in recent years. However, quality control measures are not keeping pace with the flood of data. Evaluating MLS surveys of long corridors with control points is expensive and, as a result, is frequently neglected. However, information on data quality is crucial, particularly for safety-critical tasks in infrastructure engineering. In this paper, we propose an efficient method for the quality control of MLS point clouds. Based on point cloud discrepancies, we estimate the transformation parameters profile-wise. The elegance of the approach lies in its ability to detect and correct small, high-frequency errors. To demonstrate its potential, we apply the method to real-world data collected with two high-end, car-mounted MLSs. The field study revealed tremendous systematic variations of two passes following tunnels, varied co-registration quality of two scanners, and local inhomogeneities due to poor positioning quality. In each case, the method succeeds in mitigating errors and thus in enhancing quality
Originalspracheenglisch
Aufsatznummer857
Seitenumfang30
FachzeitschriftRemote Sensing
Jahrgang14
Ausgabenummer4
DOIs
PublikationsstatusVeröffentlicht - 1 Feb. 2022

ASJC Scopus subject areas

  • Erdkunde und Planetologie (insg.)

Fields of Expertise

  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)

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