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A synthetic covariance matrix for monitoring by terrestrial laser scanning

  • Stephanie Kauker EMAIL logo and Volker Schwieger
Published/Copyright: March 20, 2017
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Abstract

Modelling correlations within laser scanning point clouds can be achieved by using synthetic covariance matrices. These are based on the elementary error model which contains different groups of correlations: non-correlating, functional correlating and stochastic correlating. By applying the elementary error model on terrestrial laser scanning several groups of error sources should be considered: instrumental, atmospheric and object based. This contribution presents calculations for the Leica HDS 7000. The determined variances and the spatial correlations of the points are estimated and discussed. Hereby, the mean standard deviation of the point cloud is up to 0.6 mm and the mean correlation is about 0.6 with respect to 5 m scanning range. The change of these numerical values compared to previous publications as Kauker and Schwieger [17] is mainly caused by the complete consideration of the object related error sources.

Award Identifier / Grant number: SCHW 838/7-1

Funding statement: The investigations published in this article are granted by the DFG (Deutsche Forschungsgemeinschaft) under the sign SCHW 838/7-1. The authors cordially thank the funding agency.

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Received: 2017-1-30
Accepted: 2017-2-14
Published Online: 2017-3-20
Published in Print: 2017-6-27

© 2017 Walter de Gruyter GmbH, Berlin/Boston

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