Volume 11, Issue 1

Robotic total stations (RTS) are frequently used for the measurement of temperature induced bridge deformations or during load testing of bridges. In experimental setups, total stations have also been used for the measurement of dynamic bridge deformations. However, with standard configurations the measurement rate is not constant and on average an update rate of 7–10Hz can be achieved. This is not sufficient for the vibration monitoring of bridges considering their natural frequencies which are also in the same range. In this paper, we present different approaches to overcome these problems. In the first two approaches we demonstrate how the measurement rate to prisms can be increased to 20Hz to determine vertical deformations of bridges. Critical aspects like the measurement resolution of the automated target tracking and the correct sequence of steering commands are discussed. In another approach we demonstrate how vertical bridge vibrations can be measured using an image assisted total station (IATS) and corresponding processing techniques. The advantage of image-based methods is that structural features of a bridge like bolts can be used as targets. Therefore, no expensive prisms have to be mounted and access to the bridge is not required. All approaches are verified by laboratory investigations and their suitability is proven in a field experiment on a 74m long footbridge. In this field experiment the natural frequencies derived from the total station measurements are compared to the results of accelerometer measurements.

This paper reports the findings based on ALOS-1 and GRACE satellite data for the purpose of monitoring land surface subsidence due to groundwater extraction and underground mining activities in the Ordos Basin, China. 42 ALOS-1 PALSAR data (22 images from Frame 790 while 20 scenes from Frame 780) acquired between 8 January 2007 and 19 January 2011 are utilized in the time-series InSAR (TS-InSAR) analysis while the total water storage observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite data are integrated with hydrological modeling results (for soil moisture modelling) to estimate the groundwater depletion rate. Since the results have vast difference in spatial resolution between GRACE (~300 km) and InSAR (~10’s of meters), the two measurements are not comparable over the same region. Instead, we applied them to Haolebaoji surrounding region and ALOS covered area, respectively. The groundwater change series of about –7.3 mm yr –1 between December 2006 and June 2012 is detected, which is then being exploited to explain the groundwater induced subsidence in Haolebaoji, Inner Mongolia. Within ALOS covered region, time-series analysis was carried out to explain the local subsidence. Then the total area size of underground mining sites is estimated, and we concluded that human involved activities contribute a lot to the total velocity and this part of subsidence should be excluded before estimating the final mean velocity (–4.9 mm yr –1 in vertical direction) when comparing with GRACE-based groundwater depletion series. Last but not least, some suggestions are given on how to make a rational comparison between the InSAR derived mean velocity with GRACE-based groundwater depletion trend together. This study could help the local government and associated geotechnical engineers to have a better understanding of the groundwater induced subsidence in this region.

The research project SIMULTAN applies an advanced combination of geophysical, geodetic, and modelling techniques to gain a better understanding of the evolution and characteristics of sinkholes. Sinkholes are inherently related to surface deformation and, thus, of increasing societal relevance, especially in dense populated urban areas. One work package of SIMULTAN investigates an integrated approach to monitor sinkhole-related mass translations and surface deformations induced by salt dissolution. Datasets from identical and adjacent points are used for a consistent combination of geodetic and geophysical techniques. Monitoring networks are established in Hamburg and Bad Frankenhausen (Thuringia). Levelling surveys indicate subsidence rates of about 4–5 mm per year in the main subsidence areas of Bad Frankenhausen with a local maximum of 10 mm per year around the leaning church tower. Here, the concept of combining geodetic and gravimetric techniques to monitor and characterise geological processes on and below the Earth's surface is exemplary discussed for the focus area Bad Frankenhausen. For the different methods (levelling, GNSS, relative/absolute gravimetry) stable network results at identical points are obtained by the first campaigns, i.e., the results are generally in agreement.

The Arenoso reservoir is created by an embankment dam, with central clay core, slates and greywacke shoulders. This kind of engineering structure is subject of deformation due to factors such as changes of water level of the reservoir, seat structure, climate changes, etc. In general, dam monitoring involves measurements both outside (external shell) and inside the structure. A number of control points is established around the area of the dam and the measurements of the displacements of the control points take place at several epochs. In this study high-precision levelling techniques have been used to monitor the vertical deformations. In particular five high-precision levelling profiles were measured in five surveys: February and July 2008, March and July 2013 and August 2014. In this study the design, observations and results are presented. On the one hand the results put in evidence the precision of the observations that are always under 1-mm level. On the other hand these results indicate downstream (southeastward) motion of the thrust block center of the dam probably during the fall and winter. The subsidence reachs here the maximum with a value of −14 cm in 2014 (in respect of February 2008). The displacements observed at the berms of the dam exhibit a similar trend to the displacements observed at the crest but they are significantly smaller, as expected. The accumulative vertical displacements and the settlement index indicate the magnitude of the movements decrease in time, confirming the dam tends to stabilize.

Freeform surfaces like B-splines have proven to be a suitable tool to model laser scanner point clouds and to form the basis for an areal data analysis, for example an areal deformation analysis. A variety of parameters determine the B-spline's appearance, the B-spline's complexity being mostly determined by the number of control points. Usually, this parameter type is chosen by intuitive trial-and-error-procedures. In [10] the problem of finding an alternative to these trial-and-error-procedures was addressed for the case of B-spline curves: The task of choosing the optimal number of control points was interpreted as a model selection problem. Two model selection criteria, the Akaike and the Bayesian Information Criterion, were used to identify the B-spline curve with the optimal number of control points from a set of candidate B-spline models. In order to overcome the drawbacks of the information criteria, an alternative approach based on statistical learning theory was developed. The criteria were evaluated by means of simulated data sets. The present paper continues these investigations. If necessary, the methods proposed in [10] are extended to areal approaches so that they can be used to determine the optimal number of B-spline surface control points. Furthermore, the methods are evaluated by means of real laser scanner data sets rather than by simulated ones. The application of those methods to B-spline surfaces reveals the datum problem of those surfaces, meaning that location and number of control points of two B-splines surfaces are only comparable if they are based on the same parameterization. First investigations to solve this problem are presented.

Today, in geodesy most practical applications is to use a datum to get three dimensional position of a particular point. The geodetic techniques generally provide time dependent coordinates in global datum. The difference between the global datum like international terrestrial reference frame (ITRF) to local datum like Europe fixed reference frame (EUREF) can be up to several centimeters due to different velocity rate of tectonic plates. To get high-precision measurements, there is an increasing need of time dependent transformations from the global level to local level. The present paper treats, this theoretical problem of geodesy by using mathematical dependency between two spatial coordinate systems whose common points are given in both systems. The paper describes four different (projective, affine, similarity and euclidean) modified methodologies for the transformation between global (ITRF) to local (EUREF) by using the Turkish permanent GPS network (TPGN) as an example. The time series from TPGN stations are used to review these transformations from ITRF 2008 to EUREF 2008. The transformation parameters in all cases shows that mostly transform coordinates depends on its counterparts (X to x and Y to y) and others coordinates have very less effect. Finally to show the validity of our model a comparative analysis with standard Bursa-Wolf and Molodensky-Badekas models has been presented. The test shows that our model error is equivalent to standard models, in this view the presented models are acceptable and can improve our understanding in coordinate transformation.