Volume 2, Issue 4

Application of terrestrial laser scanning for engineering and documentation projects requiring high accuracy is often prohibitive due to the error budget of terrestrial laser scanners (TLS) which is worse than that of alternative instruments such as total stations. However, by separating the errors of TLS into random and systematic components, the influence of both can be reduced significantly. Approaches for reducing the influence of random noise rely on averaging. One method is introduced briefly as it is relevant for the task of the proposed systematic error removal. We discuss the correction of cyclic distance measurement errors of TLS in detail. For the investigated scanner, these cyclic errors are the most dominant systematic errors. The proposed approach is based on an on-the-job determination of a distance correction function which allows reducing the magnitude of the occurring distance errors by a factor of ten, reducing the systematic errors to less than 0.5 mm. The massive amount of data acquired by TLS is exploited using robust statistical methods. The algorithm developed relies on small, flat surfaces found automatically in the scene. Hence, the method can be applied on engineering project data without requiring additional laboratory experiments. Therefore, it is not essential that the errors are constant over time. By the introduction of on-the-job correction procedures as the one proposed, the systematic errors of TLS can be decreased significantly. This makes them more suitable to be used as an alternative to single point measurement devices.

Development of new technologies for monitoring structural and ground deformations puts new demands on the design and analysis of the multi-sensor systems. Design and analysis of monitoring schemes require a good understanding of the physical process that leads to deformation. Deterministic modelling of the load-deformation relationship provides information on the magnitude and location of expected critical deformations as well as delineates the deformation zone. By combining results of deterministic modelling with geometrical analysis, one can find the deformation mechanism and explain the cause of deformation in case of irregular behaviour of the investigated object. The concept is illustrated by four practical examples.

This paper presents a model to predict the GDOP value (Geometric Dilution of Precision) and the probability of its occurrence at a point in space and time using airborne LiDAR (Light Detection and Ranging) data and the ultra-rapid product (URP) available from the International GPS Service. LiDAR data help to classify the terrain around a GPS (Global Positioning System) receiver into categories such as ground, opaque objects, translucent objects and transparent regions as per their response to the transmission of GPS signal. Through field experiments it is established that URP can be used satisfactorily to determine GDOP. Further experiments have shown that the translucent objects (mainly trees here) lower the GDOP quality as they obstruct the GPS signal. LiDAR data density on trees is used as a measure of the translucency of trees to the GPS signal. Through GPS observations taken in field a relationship has been established between LiDAR data density on trees and the probability that a satellite which is behind the tree is visible at the GPS receiver. A model is presented which, for all possible combinations of visible satellites, computes the GDOP value along with the probability of occurrence of this GDOP. A few results are presented to show the performance of the model developed and its possible application in location based queries.

The IGS announced the switch from a relative to an absolute phase centre variation model on 5 October 2006 after detailed discussions concerning how the model switch would benefit global and regional networks, as well as the IGS products. However, there was no dedicated study on the major concern of this paper – the influence of the model switch on local engineering networks, especially on coordinate estimates, which are key factors in engineering constructions. The data set considered in this paper is a bridge control network with baselines ranging in length from 200 to 7000 metres, utilising different GPS antenna types. In addition, high correlations between coordinate estimates, antenna phase centre variations and troposphere parameters are also considered. The results demonstrate that the antenna model switch does not produce significant differences to coordinate estimates within local engineering networks.

A new mathematical model to estimate the International VLBI Service (IVS) reference point and additional parameters of a Very Long Baseline Interferometry (VLBI) radio telescope was developed by Lösler and Hennes (2008). To verify this analysis procedure a reference point determination was carried out on the 20 m radio telescope at the “Fundamentalstation Wettzell” (Germany) from April to May 2008. This paper describes the terrestrial local survey, the analysis methodology and the results obtained, in particular the accuracy of the determination of the IVS reference point.

The Colli Albani Volcano has recently developed particular interest in the geophysical community for some peculiar characteristics imputable to a recent residual volcanic activity, thus evidencing that it cannot be considered extinguished yet. On April 2006 an airborne laser scanning (ALS) survey of the Albano and Nemi craters has been carried out to obtain a high resolution digital terrain model (DTM) of the area. We have compared the accuracy of the ALS heights with those obtained by a fast GPS kinematic survey, obtaining maximum deviation within 50 cm. Then, we have integrated the ALS survey of the craters and the bathymetry of the Albano lake to achieve a complete DTM, useful for morphological studies. In addition, with a GNSS/RTK survey (July 2007) we have estimated the Albano and Nemi mean lake levels respectively at 288.16 m and 319.02 m (asl). Based on the integrated DTM and the newly estimated water level values, we have evaluated about 21.7 · 10 6 of m 3 the water volume loss of the Albano lake from 1993 to 2007, with an average rate of about 1.6 · 10 6 m 3 /yr.