Automatic optimization of height network configurations for detection of surface deformations

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 theoremfrom 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.