2020
DOI: 10.3390/math8040593
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Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops

Abstract: 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 distribute… Show more

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Cited by 13 publications
(10 citation statements)
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“…An error model for TLS measurement was proposed [ 89 ], where the error was estimated based on the distance to the object and the incident angle. A stochastic model for TLS observations was proposed in reference [ 90 ]. The current error model was extended by classifying atmospheric parameters as randomly correlated basic errors.…”
Section: Key Issues In the Application Of Tls Technologymentioning
confidence: 99%
“…An error model for TLS measurement was proposed [ 89 ], where the error was estimated based on the distance to the object and the incident angle. A stochastic model for TLS observations was proposed in reference [ 90 ]. The current error model was extended by classifying atmospheric parameters as randomly correlated basic errors.…”
Section: Key Issues In the Application Of Tls Technologymentioning
confidence: 99%
“…An explanation of the parameters and their role in the functional mode is given in Kerekes and Schwieger (2020).…”
Section: B Stochastic Modelmentioning
confidence: 99%
“…Wang et al [ 263 ] introduced a combined model by integrating external models related to atmospheric refraction, beam wander and incidence angle into a seven-parameter similarity transformation model to detect external errors and register multiple scans. Kerekes et al [ 264 ] presented a stochastic model for TLS observations. By classifying the atmospheric parameters as stochastic correlating elementary errors, the currently elementary error model is expanded.…”
Section: Critical Issues In Applicationmentioning
confidence: 99%