Abstract
Levellings are performed to observe height changes of different epochs at discrete surveying points. A reliable estimation of surface deformations by a bivariate polynomial needs a sufficient configuration of the underlying network. Because the spacial distribution of the surveying points is not homogeneous in the discussed regions, the network configuration has to be optimized. This study proposes an optimization procedure that estimates the optimal number and position of the surveying points considered for a reliable analysis. Furthermore, the already existing observations are accepted or rejected due to the network’s geometry. Therefore, two different approaches are combined. First, the sampling theorem from time series analysis is used to estimate the number and position of the surveying points. Second, the partial redundancies from statistics take the reliability into account. Applying the optimization procedure to several test regions, the benefit of the optimized network configurations is discussed.
© 2013 by Walter de Gruyter GmbH & Co.
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- Models for assessing the spatial distribution of geodetic point patterns: application to geoid prediction quality
- Automatic optimization of height network configurations for detection of surface deformations
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Articles in the same Issue
- Masthead
- Velocity Field across the Carmel Fault Calculated by Extended Free Network Adjustment Constraints
- Models for assessing the spatial distribution of geodetic point patterns: application to geoid prediction quality
- Automatic optimization of height network configurations for detection of surface deformations
- Comparison of two robust estimations by expectation maximization algorithms with Huber’s method and outlier tests
- Estimation of Measurement Uncertainty of kinematic TLS Observation Process by means of Monte-Carlo Methods
- A comparison of particle swarm optimization (PSO) and genetic algorithm (GA) in second order design (SOD) of GPS networks