Next Article in Journal
On Probability Characteristics for a Class of Queueing Models with Impatient Customers
Next Article in Special Issue
On Estimating the Hurst Parameter from Least-Squares Residuals. Case Study: Correlated Terrestrial Laser Scanner Range Noise
Previous Article in Journal
An Efficient Method for Forming Parabolic Curves and Surfaces
Previous Article in Special Issue
A Generic Approach to Covariance Function Estimation Using ARMA-Models
Open AccessArticle

Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops

Institute of Engineering Geodesy, University of Stuttgart, Geschwister-Scholl-Str. 24D, 70174 Stuttgart, Germany
Author to whom correspondence should be addressed.
Mathematics 2020, 8(4), 593;
Received: 18 March 2020 / Revised: 7 April 2020 / Accepted: 10 April 2020 / Published: 15 April 2020
(This article belongs to the Special Issue Stochastic Models for Geodesy and Geoinformation Science)
All measurements are affected by systematic and random deviations. A huge challenge is to correctly consider these effects on the results. Terrestrial laser scanners deliver point clouds that usually precede surface modeling. Therefore, stochastic information of the measured points directly influences the modeled surface quality. The elementary error model (EEM) is one method used to determine error sources impact on variances-covariance matrices (VCM). This approach assumes linear models and normal distributed deviations, despite the non-linear nature of the observations. It has been proven that in 90% of the cases, linearity can be assumed. In previous publications on the topic, EEM results were shown on simulated data sets while focusing on panorama laser scanners. Within this paper an application of the EEM is presented on a real object and a functional model is introduced for hybrid laser scanners. The focus is set on instrumental and atmospheric error sources. A different approach is used to classify the atmospheric parameters as stochastic correlating elementary errors, thus expanding the currently available EEM. Former approaches considered atmospheric parameters functional correlating elementary errors. Results highlight existing spatial correlations for varying scanner positions and different atmospheric conditions at the arch dam Kops in Austria. View Full-Text
Keywords: elementary error model; terrestrial laser scanning; variance-covariance matrix elementary error model; terrestrial laser scanning; variance-covariance matrix
Show Figures

Figure 1

MDPI and ACS Style

Kerekes, G.; Schwieger, V. Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops. Mathematics 2020, 8, 593.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop