Journal of Surveying Engineering

The network-based real-time kinematic (NRTK) global navigation satellite system (GNSS) technique was proposed for the first time to monitor the dynamic response of bridges. It could receive corrections from an established remote continuously operating reference station (CORS) network instead of a user-defined local reference station. To validate the feasibility of the NRTK-GNSS technique, laboratory and field experiments were both conducted at the University of Nottingham, U.K., and the Wilford suspension bridge, a footbridge close to the university’s campus. The conventional real-time kinematic (RTK)-GNSS and accelerometer techniques were synchronously considered for validating the accuracy of the NRTK-GNSS technique. A wavelet packet filtering scheme was designed to process full-scale experimental data according to the characteristics of NRTK-GNSS measurement noise. The dynamic displacements and vibration frequencies of the bridge were successfully identified from the NRTK-GNSS data with satisfactory accuracy. In conclusion, the study confirms that the proposed NRTK-GNSS can be a potential technique for the dynamic monitoring of bridges, with adequate performance and lower operational cost. It will be a powerful monitoring tool for structural health monitoring with continuous enhancement in the hardware and algorithm.

Three strategies are employed to estimate the covariance matrix of the unknown parameters in an error-in-variable model. The first strategy simply computes the inverse of the normal matrix of the observation equations, in conjunction with the standard least-squares theory. The second strategy applies the error propagation law to the existing nonlinear weighted total least-squares (WTLS) algorithms for which some required partial derivatives are derived. The third strategy uses the residual matrix of the WTLS estimates applicable only to simulated data. This study investigated whether the covariance matrix of the estimated parameters can precisely be approximated by the direct inversion of the normal matrix of the observation equations. This turned out to be the case when the original observations were precise enough, which holds for many geodetic applications. The three strategies were applied to two commonly used problems, namely a linear regression model and a two-dimensional affine transformation model, using real and simulated data. The results of the three strategies closely followed each other, indicating that the simple covariance matrix based on the inverse of the normal matrix provides promising results that fulfill the requirements for many practical applications.

The ballastless track can overcome the disadvantages of a traditional ballast track, such as lower longitudinal and lateral permanent stability and expensive maintenance, and is thus suitable for a high-speed railway (HSR) that is 350 km/h or even faster. The continuous track slabs in the ballastless track have very precise geometric parameters and must be precisely installed to guarantee the ride comfort of a high-speed train. Therefore, the so-called CPIII control network was built, for which both careful field surveying and rigorous data adjustment were performed. In this paper, how the CPIII network is built in a hierarchical procedure will be systematically introduced. More importantly, a new data-processing strategy is proposed, including free and constrained network adjustment realized by using different S-datum matrices. In free network adjustment, data snooping and variance component estimation (VCE) are interactively implemented for excluding outliers and retrieving realistic observation precisions. In constrained network adjustment, quasi-stable adjustment along with hypothesis testing is implemented to select the stable control points, followed by tightly constrained adjustment to obtain the coordinates of CPIII points. With the first ballastless track HSR in China as an example, the performance of proposed data-processing strategies is demonstrated, showing the importance and efficiency of data snooping, VCE, and selection of stable points. Following the strategy of network design, field data collection, and data processing, the ultraprecision results with reasonable quality control can be achieved to meet HSR demand.

The use of geodetic techniques, in particular of the global positioning system (GPS), or other global navigation satellite systems (GNSS), for monitoring different kinds of deformations is a common practice. This is typically performed by setting a network of geodetic GPS/GNSS receivers, allowing accuracies in the order of millimeters. The use of lower-cost devices has been recently studied, showing that good results can be achieved. In this paper, the impact of the software used for the data analysis is also investigated to verify whether a fully low-cost monitoring system, i.e., both hardware and software, can be set up. This is done by performing a series of relative positioning experiments in which data are processed by different software packages. The main result is that by using a low-cost u-blox EVK-6T GPS receiver and analyzing its data with free and open-source software, movements of the order of a few millimeters can be detected when a short baseline with daily solutions is used.

The use of terrain and elevation data is critical for a number of applications in science and engineering. Typically, the quality of digital elevation models (DEMs) is assessed using external and independent point data sources to arrive at an overall RMS value for the errors. The utility of such a single-valued overall assessment depends on the spatial extent of the area under consideration and the terrain variability (both over time and space), as well as the application requirements. This paper aimed to understand the suite of parameters that are important to consider in deriving a DEM error budget. Specifically, terrain slope, land-cover type, information loss, and data measurement schemes were investigated. A region in western Canada spanning the Rocky Mountains was used to numerically quantify errors using two Global Positioning System (GPS) datasets: precise point positioning (PPP) profiles and GPS on benchmarks. Three digital elevation models [Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM2), Shuttle Radar Topography Mission 1 Arc-Second Digital Elevation Model Version 3 (SRTM1v3), and Canadian Digital Elevation Model (CDEM)] were assessed. Results highlight the importance of selecting ground-control points based on the region’s characteristics (e.g., slope, tree cover). This leads to more representative RMS values that improve DEM uncertainty estimations. Finally, a mathematical method [projection onto convex sets (POCS)] for filling data gaps in the GPS data profiles was implemented, and results demonstrate the utility of this approach over conventional interpolation schemes.

This paper discusses the optimization problem of first-order design (FOD) of global positioning system (GPS) networks. The classical least-squares technique was revised for the formulation of the objective function of FOD of geodetic networks. Furthermore, the efficacy of particle swarm optimization (PSO), an iterative heuristic global optimization technique influenced by group behavior of a social animal, was examined for solving the optimization problem of FOD of three example geodetic networks. It was observed that PSO efficiently provides an optimal solution with a high convergence rate.

Many methods and techniques have been developed to detect gross errors in geodetic measurements, but none seems to have prevailed. Statistical tests and robust methods are the most common approaches for detecting outliers in geodetic measurements. Least-squares adjustment and iterative attitudes are the essence of those methods. In this paper, closing loops in Global Navigation Satellite System (GNSS) networks are used to detect gross errors. Spanning trees are used to define a set of independent loops in the network. Careful examination of the misclosure of loops assists in defining the faulty vectors. The method is very effective and delivers another alternative for outlier detection without using adjustment computation and statistical tests. The method of outlier detection by means of spanning trees is presented and tested against well-known methods like convectional statistical tests (w-test, τ-test, and t-test) and robust M-estimation methods (Andrews, Huber, and Danish). A number of tests were performed on a GNSS network that contains 115 points and 917 vectors to detect gross errors in different scenarios, and the results are presented in the paper. Based on the results of the presented tests, it is seen that the w-test and the M-estimation methods correctly detect all outliers in the GNSS network, whereas τ-tests and t-tests do not always detect the correct errors. The new method for detection of gross errors by means of spanning trees performs quite well and can correctly exclude all outliers with only one iteration.

Terrestrial laser scanning (TLS) and structure-from-motion photogrammetry (SfM) can both provide dense and accurate point clouds. Therefore, they can be used to perform a morphological analysis of the façades of a masonry building, which relies on evaluation of the differences between the point cloud and a reference regular surface fitted to it. To compare TLS and SfM performance in morphological analysis, multimodal surveys were carried out on the square cross-section, 48-m-high Garisenda Tower in Bologna, Italy (reference surface: plane), and the circle cross-section, 42-m-high Caorle’s leaning bell tower in Venice, Italy (reference surface: moving cylinder). The results show that the TLS- and SfM-based morphologies are qualitatively the same, and the relative differences are lower than 10%–20% under the condition that the viewpoint positions (VPs) are optimal. Also, the overall geometries are correctly described by both the techniques. The main conclusion is that, if no particular constraints exist (e.g., unavoidable suboptimal VPs, night surveys are needed, or trees hide the surface), TLS and SfM have similar performance in morphological analysis.

The clothoid (also known as Cornu spiral or Euler spiral) is a curve that is characterized by its curvature being proportional to its length. This property makes it very useful as a transition curve when designing the layout of roads and railway tracks. This paper presents an analysis of two methods for computing the clothoid: the classical method, which is based on the use of explicit formulas obtained from Taylor expansions of sine and cosine functions, and an alternative algorithm, which is based on the numerical solution of the initial value problems giving the clothoid parametrization. This alternative method is simple and efficient, and its effectiveness is shown through its application to three classical problems of horizontal road alignment.

This paper presents a closed-form procedure for the coarse registration of three-dimensional (3D) point clouds using automatically extracted linear features, which have been manually matched. Corresponding linear features are defined by nonconjugate endpoints that do not necessarily define compatible direction vectors. Because the point clouds could be derived from different sources (e.g., laser scanning data sets and/or photogrammetric point clouds that are referenced to arbitrary reference frames), the proposed procedure estimates the scale, shift, and rotation parameters that relate the reference frames of these data sets. The proposed approach starts with a quaternion-based procedure for initial estimation of the transformation parameters using the minimal number of required conjugate line pairs (i.e., two noncoplanar linear features from each point cloud). The initial estimate of the transformation parameters is then used to ensure the compatibility of the direction vectors of the involved linear features. The modified direction vectors together with the endpoints of the linear features are used for deriving a better estimate of the transformation parameters. Experimental results from both simulated and real data sets verified the feasibility of the proposed procedure in providing good quality for the approximate parameters of the transformation parameters for point-based fine registration procedures.

A novel approach to a three-dimensional (3D) model creation from data sets obtained by laser scanning or photogrammetry is presented, including a description of the method and efficient numerical algorithms for 3D model creation for surveying applications. The presented method solves the fundamental problem of surface reconstruction by constructing models using differential geometry and partial differential equations. The time-relaxed eikonal equation was used to obtain the distance function from the cloud of points, and the 3D model was then created by the evolution of an initial guess by the advection equation regularized by curvature, where the advective velocity is given by the gradient of the computed distance function. The partial differential equations were discretized by the finite-difference schemes, and the results of the 3D model creation are presented and discussed.

This work presents the results of global positioning system (GPS) data processing using the phase residuals method (PRM)—L1 carrier phase from two satellites—to monitor the dynamic behavior of a small concrete bridge. The bridge tested, the Jaguari Bridge, is a small, curvd, reinforced concrete bridge. The bridge over the Jaguari River is a reinforced concrete bridge built in 1999, located on Fernão Dias Highway (BR 381), positioned at Kilometer 946, Minas Gerais, Brazil. The small concrete bridge was chosen for this study because its construction type is found in great numbers throughout Brazil. In parallel, there was a significant increase of pathologies in these structures as a result of lack of maintenance procedures. The detection of small vibrations of spans, for example, which is a good indicator of the health of a structure, can be monitored by GPS. The challenge in this case is trying to detect with GPS the dynamic displacement that has an amplitude close to 5 mm. Application of the PRM on GPS data allowed the detection of this very small dynamic vibration. In addition, this is the first case of success with applying GPS as a tool for monitoring the dynamic behavior of small concrete bridges. The experiment consisted of sessions conducted during 2 days and used two GPS receivers (with a 100-Hz recording rate) over the central span of the Jaguari Bridge in 2014. The continuous wavelet transform (CWT) was used as a filter technique to analyze the frequencies generated by residues from double-difference data processing.

The error-in-variable (EIV) model takes the error of all variables into account and has been widely applied to many practical problems arising in environmental study, geology, geographic information science (GIS), and geodesy. Coordinate transformations are among the most frequently encountered problems in spatial data processing, and the EIV model can be built based on two sets of coordinates. In some applications, physical parameters—such as the shift, rotation angle, and scale factor—have constraints. Current implementations of the constrained EIV (CEIV) model do not consider physical constraints explicitly. The purpose of this paper is to convert physical constraints into mathematical forms and to use constrained total least squares (CTLS) to solve the CEIV problem of two-dimensional (2D) affine transformation. The effectiveness of this method is illustrated through a numerical example.

This study investigated long-term observations from three pairs of closely spaced, continuously operating reference stations (CORS): STVI and VITH (2008–2014, 0.6 km apart), BYSP and PRHL (2008–2014, 3.2 km apart), and CRO1 and VIKH (1995–2014, 23 km apart), in the region of Puerto Rico and Virgin Islands. The Global Positioning System (GPS) antennas of STVI, BYSP, and CRO1 are mounted on ground-based monuments. The GPS antennas of VITH, PRHL, and VIKH are mounted on building-based monuments. This study indicated that there is no considerable difference between building-based and ground-based CORS with regard to the precision of daily positions and the reliability of long-term site velocities. The amplitude of thermal movements associated with daily temperature changes and the wind drift associated with air pressure change from a 2-story concrete building fell below the detectable levels of the present high-precision GPS technique determined by Precise Point Positioning (PPP) processing. Further analysis indicated that (1) building-based CORS can retain more complete GPS observations and provide a more stable multipath environment, and (2) the large and heavy mass of the building and its foundation can decrease the amplitude of seasonal signals and filter certain short-period motions. As a result, the building-based CORS have the potential to perform better than the ground-based CORS as long as their monuments are firmly fixed on 1-story or 2-story concrete buildings and the buildings themselves are stable.

Civil engineering projects require the orthometric height of points (i.e., the height of points above geoid). Thus, to make use of the Global Navigation Satellite System (GNSS) in engineering surveying, geoid undulation (i.e., the separation between an ellipsoid and geoid surface) must be known. In this study, an attempt has been made to determine the geoid undulation using the astro-geodetic method. Observations were taken in a network of seven stations spread over 300 km² around Dehra Dun, India. Astronomical observations of seven stars belonging to different constellations were taken with a theodolite having a least count of 1.0 s. Global positioning system (GPS) observations were taken using dual-frequency geodetic GPS receivers with a 0.1-mm-accurate digital level. Values of astro-geodetic geoid undulations (of stations) have been found close to that computed from field levelling. Further, the values have been compared with those obtained from global geoid models such as EIGEN6C3stat and EGM2008, and the astro-geodetic method was found to provide better accuracy than the global geoid models. Therefore, it can be concluded that the astro-geodetic method is the better choice for reducing GPS observation to orthometric height. In the future, the astro-geodetic method may be used to develop an accurate geoid model in general and for Indian topography in particular.