Journal of Surveying Engineering

Global Navigation Satellite System (GNSS) surveys performed in critical environments (e.g., urban canyons, mountainous areas, or areas of dense vegetation) usually suffer from a lack of satellite coverage as a result of obstacles such as buildings and vegetation. GNSS mission-planning software provides an estimate of satellite visibility and dilution-of-precision (DOP) values along a planned trajectory to establish the best time frame over which to perform the survey. However, such an estimate is not reliable in a complex scenario because the surrounding environmental morphology is not considered. This paper introduces a new method to improve the prediction of GNSS satellite visibility. This method involves computing GNSS satellites position by means of the orbital parameters, as well as using three-dimensional digital surface models (DSMs) to develop a more reliable mission plan. The time evolution of key parameters describing the GNSS constellation is computed by means of a visibility georeferenced map for both dynamic and static surveys.

A study of deformations, which is based on the use of geodetic measurements, is usually performed by defining a kinematic model. Such a model, when used to describe a complex geophysical environment, can lead to a partial estimation of the deterministic dynamics, which characterize the entire network. Usually, in a case of deterministic nonlinear movements in the network, there is no possibility to determine a stable datum that may serve as a basis for deformation analysis. Today, the concept of stability in time ascribes rigidity to a congruent datum. This paper redefines the concept of the datum congruency and presents the development of a new dynamic datum, which more closely represents geophysical reality. The new datum changes the main characteristics of a traditional datum and successfully overcomes some of its inherent disadvantages. As an example, the proposed algorithm of the dynamic datum is applied to obtain a deformation analysis in the Carmel fault environs, one of the major geological structures in northern Israel.

The geometric calibration of time-of-flight range cameras is a necessary quality assurance measure performed to estimate the interior orientation parameters. Self-calibration from a network of range imagery of an array of signalized targets arranged in one or two planes can be used for this purpose. The latter configuration requires the addition of a parametric model for internal light scattering biases in the range observations to the background plane due to the presence of the foreground plane. In a previous study of MESA Imaging SwissRanger range cameras, such a model was developed and shown to be effective. A new parametric model is proposed here because the scattering error behavior is camera model dependent. The new model was tested on two pmdtechnologies range cameras, the CamCube 3.0 and CamBoard nano, and its effectiveness was demonstrated both graphically and statistically. The improvement gained in the root-mean square of the self-calibration range residuals of 22 and 32%, respectively, indicates the model’s ability to compensate for the scattering error. A reduction in correlation between the camera position and rangefinder offset of up to 10% was achieved, which is consistent with previous findings. In addition, a systematic approach for designing the optimal separation between the foreground and background planes is presented.

It has been routine work to determine the elevations of points on Earth’s surface for a wide range of purposes. However, surveyors are now facing new challenges because of the increasing demand for high-quality measurements despite potential errors caused by Earth’s dynamics, which introduce time-dependent signals in the points being investigated. Classical level network adjustment works well when benchmark elevations are known precisely and remain constant over time. However, the traditional approach fails to consider possible ground motions in a single process of network adjustment. This study proposes a time-variant model and unified least-squares technique for level network adjustment. The main emphasis of this approach is to accommodate the time-dependent behaviors of benchmarks caused by ground motions and other unknown sources. The numerical results from a simulated test and a real case study show that the proposed approach can capture the time-dependent signals of benchmarks. Consequently, significant perturbations in benchmarks can be identified, and an improved analysis for level network adjustment thus can be achieved.

The deflection of the vertical is an important parameter that combines both physical (astronomic) and geometric (geodetic) determined quantities. This paper introduces an alternative didactic approach based on rotations of three-dimensional right-handed local frames that simplifies such concepts as the derivation of Laplace’s equation and facilitates understanding of vertical deflection components and their transformations under different assumptions. Variations in deflections of the vertical as a consequence of geometric changes introduced by the future replacement of the North American Datum of 1983 (NAD 83) are also investigated.

In geodetic networks, observations are measured repetitively, and the mean values of these observations are used for network adjustment, outlier detection, deformation analysis, etc. These repetitive observations are independent, and if one of them has outlier, the effect of the outlier decreases depending on the computed mean value. Also, the mean operator—a kind of least-squares estimation—smears the effects of the outlier over other observations. In this case, the detectability and reliability rates of the outlier detection method decrease. Moreover, the undetectable outliers spoil both of the estimated parameters and their standard deviations, causing incorrect results. To form a univariate sample, the same quantity must be measured at least twice for geodetic networks. The univariate case is simpler than the multivariate case, and if the repetitive observations may be analyzed as a univariate case, more reliable results can be obtained for outlier detection. In this study, the univariate analysis method was proposed for repetitive geodetic observations. The reliability of the univariate method was measured based on its mean success rate compared with the mean success rates of classical methods. The leveling network was simulated, and analyses were carried out. The results obtained from the univariate case are more reliable than those obtained from classical ones.

This paper describes a new model for precise point positioning (PPP), which overcomes the drawbacks of existing PPP models. This model is based on between-satellite single-difference (BSSD), which cancels out the receiver clock error, receiver initial phase bias, and receiver hardware delay. The decoupled clock (DC) corrections, which were provided by Natural Resources Canada (NRCan), were applied to account for code and carrier-phase satellite clock corrections, satellite hardware delay, and satellite initial phase bias. The results from three PPP models (namely, undifferenced-DC, BSSD, and BSSD-DC) were compared with the traditional (i.e., undifferenced) PPP solution. It is shown that the proposed BSSD models improves the PPP convergence time by up to 50% and improves the solution precision by more than 60% in comparison with the traditional PPP model.

Knowledge of the actual refraction coefficient is essential in leveling surveys and precise electromagnetic distance measurement reduction. The most common method followed by the surveyor for its determination is based on the use of simultaneous reciprocal zenith observations. The commonly used formula is only an approximation valid for approximately horizontal sightings, whereas the exact geometric solution turns out to be very complicated so that an iterative computation procedure is suggested instead. In the present paper, the goal is to derive a compact formula from the complete solution that is easy to implement and retains the necessary accuracy for horizontal and slanted sightings. In addition, the paper will also focus on the common situation for the surveyor where isolated observations have to be done and no partially compensating procedures—e.g., leap-frog or middle point—are possible. If temperature vertical profiles are unknown then the refraction coefficient cannot be reliably determined. Some surveyors may customarily use then an average value, e.g., $k=0.13$, perhaps being unaware of the risks involved in such simplistic assumption. In the present paper, it is also a goal to present a useful and simple formula for approximately estimating the refraction coefficient in terms of easily accessible parameters to correct the bulk of the refraction effect in single observations, always bearing in mind that determination of the refraction coefficient by means of a model may turn out to be somewhat inaccurate, but still better than the blind use of a universal $k$.