Journal of Surveying Engineering

Precise three-dimensional positioning by the hidden point bar method is investigated. The investigation includes development of both closed form and least squares solutions, as well as calibration of the hidden point bar. The method is applied in the field at the University of Calgary Central Heating and Cooling Plant. In this application, known movements are introduced and then recovered using the hidden point bar method. The differences between known and recovered movements are $0.11\mathrm{mm}$ or less. Special advantages of the hidden point bar method are that the target point does not have to be visible from the measurement instrument and the bar placed on the target can be set at any convenient orientation.

A robust strategy for controlling the influence of outliers on model parameters and variance components is proposed based on the principle of robust M estimation. The robust estimators for parameters and variance components are derived. A practical robust estimator similar to Helmert’s one for maximum likelihood estimation is obtained. The robustness and efficiency of the new robust estimation procedure is demonstrated and compared with those of the classical least squares method by applying a practical global positioning system network in China.

Position fixing by hidden points bar from one theodolite is an Industrial Surveying practice used as a last resort in difficult environments of measurements. Determination of the coordinates of inaccessible points sought is performed by least squares adjustment with constraints. Conventional methods of coordinate determination check the efficiency of the method. In the present adjustment, normally of low redundancy, the assignment of accurate provisional values to the aforementioned coordinates constitutes an essential task.

This article is based on digital terrain models (DTMs) and their applications in civil engineering carried out at the Public University of Navarre. One of the drawbacks of the use of these synthetic surfaces is the need to characterize their quality, a very important issue for its economic importance but difficult to determine in a nonempirical manner. We will review the techniques most commonly used to estimate the quality of the models and propose a new method for the control of the quality of DTM in applications for which a high accuracy is required. Among the advantages of this method is that no reference model is needed, and there is a possibility of estimating the errors obtained when using a DTM. The proposed method offers good results and adequately allows one to characterize the roughness of the surfaces evaluated. The sensitivity analysis of the model shows that the volumetric errors are highly sensitive to the density of points sampled, while the height errors remain highly stable.

The map projection problem involves transforming the graticule of meridians and parallels of a sphere onto a plane using a specified mathematical method according to certain conditions. Map projection transformations are a research field dealing with the method of transforming one kind of map projection coordinates to another. The conversion from geographical to plane coordinates is the normal practice in cartography, which is called forward transformation. The inverse transformation, which yields geographical coordinates from map coordinates, is a more recent development due to the need for transformation between different map projections, especially in Geographic Information Systems (GIS). The direct inverse equations for most of the map projections are already in existence, but for the projections, which have complex functions for forward transformation, defining the inverse projection is not easy. This paper describes an iteration algorithm to derive the inverse equations of the Winkel tripel projection using the Newton–Raphson iteration method.

The global positioning system (GPS) is a constellation of 24 navigation satellites developed and deployed by the U.S. Department of Defense to provide worldwide real-time positioning capability to its numerous users around the globe. When two or more GPS receivers operate simultaneously, the use of differential GPS positioning has been widely adopted in many engineering applications to improve the positioning accuracy by reducing common errors contained in the concurrent GPS signals. The currently adopted approach to solve the GPS double-differenced pseudorange equations is based on the least-squares principle and requires the use of an iterative procedure. In this study, an algebraic, direct solution of the double-differenced pseudorange equations is introduced. It is demonstrated by experimental data that this noniterative method provides highly compatible positioning results with the traditional least-squares approach.

Cultural heritage recording and engineering surveying are prime applications for terrestrial laser scanners (TLSs) because of the high spatial resolution, high accuracy, and fast data capture rates this technology offers. To date, insufficient attention has been given to the many error sources contributing to the uncertainty of scanner datasets. A full error budget for directly georeferenced terrestrial laser scanner networks that considers both relevant error sources fundamental to surveying and those unique to sampled laser scanner systems is derived. In the case of the latter, new probabilistic models are proposed for angular positional uncertainty due to laser beamwidth and centroid-based target pointing. Analysis of a cultural heritage-recording project in Ayutthaya, Thailand, highlights the disparity between “expected” precision and the more realistic precision indicated by the error budget and demonstrates that the beamwidth error can be a significant factor. The causes and effects of several systematic errors inherent to TLS datasets are also discussed.