Search results

Filters

  • Journals
  • Date

Search results

Number of results: 6
items per page: 25 50 75
Sort by:

Abstract

The adjustment problem of the so-called combined (hybrid, integrated) network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length) on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients). While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional model of the GNSS observations.
Go to article

Abstract

The paper attempts to determine an optimum structure of a directional measurement and control network intended for investigating horizontal displacements. For this purpose it uses the notion of entropy as a logarithmical measure of probability of the state of a particular observation system. An optimum number of observations results from the difference of the entropy of the vector of parameters X X ˆ H ' corresponding to one extra observation. An increment of entropy interpreted as an increment of the amount of information about the state of the system determines the adoption or rejection of another extra observation to be carried out.
Go to article

Abstract

The paper presents the results of real time measurements of test geodetic control network points using the RTK GPS and RTX Extended technologies. The Trimble RTX technology uses the xFill function, which enables real measurements without the need for constant connection with the ASG EUPOS system reference stations network. Comparative analyses of the results of measurements using the methods were performed and they were compared with the test control network data assumed to be error-free. Although the Trimble RTX technology is an innovative measurement method which is rarely used now, the possibilities it provides in surveying works, including building geodetic control networks, are satisfactory and it will certainly contribute to improving the organisation of surveying works.
Go to article

Abstract

Mining activity influence on the environment belongs to the most negative industrial influences. Land subsidence can be a consequence of many geotectonic processes as well as due to anthropogenic interference with rock massif in part or whole landscape. Mine subsidence on the surface can be a result of many deep underground mining activities. The presented study offers the theory to the specific case of the deformation vectors solution in a case of disruption of the data homogeneity of the geodetic network structure in the monitoring station during periodical measurements in mine subsidence. The theory of the specific solution of the deformation vector was developed for the mine subsidence at the Košice-Bankov abandoned magnesite mine near the city of Košice in east Slovakia. The outputs from the deformation survey were implemented into Geographic Information System (GIS) applications to a process of gradual reclamation of whole mining landscape around the magnesite mine. After completion of the mining operations and liquidation of the mine company it was necessary to determine the exact edges of the Košice-Bankov mine subsidence with the zones of residual ground motion in order to implement a comprehensive reclamation of the devastated mining landscape. Requirement of knowledge about stability of the former mine subsidence was necessary for starting the reclamation works. Outputs from the presented specific solutions of the deformation vectors confirmed the multi-year stability of the mine subsidence in the area of interest. Some numerical and graphical results from the deformation vectors survey in the Košice-Bankov abandoned magnesite mine are presented. The obtained results were transformed into GIS for the needs of the self-government of the city of Košice to the implementation of the reclamation works in the Košice-Bankov mining area.
Go to article

Abstract

Generally, gross errors exist in observations, and they affect the accuracy of results. We review methods to detect the gross errors by Robust estimation method based on L1-estimation theory and their validity in adjustment of geodetic networks with different condition. In order to detect the gross errors, we transform the weight of accidental model into equivalent one using not standardized residual but residual of observation, and apply this method to adjustment computation of triangulation network, traverse network, satellite geodetic network and so on. In triangulation network, we use a method of transforming into equivalent weight by residual and detect gross error in parameter adjustment without and with condition. The result from proposed method is compared with the one from using standardized residual as equivalent weight. In traverse network, we decide the weight by Helmert variance component estimation, and then detect gross errors and compare by the same way with triangulation network In satellite geodetic network in which observations are correlated, we detect gross errors transforming into equivalent correlation matrix by residual and variance inflation factor and the result is also compared with the result from using standardized residual. The results of detection are shown that it is more convenient and effective to detect gross errors by residual in geodetic network adjustment of various forms than detection by standardized residual.
Go to article

Abstract

Land surveyors, photogrammetrists, remote sensing engineers and professionals in the Earth sciences are often faced with the task of transferring coordinates from one geodetic datum into another to serve their desired purpose. The essence is to create compatibility between data related to different geodetic reference frames for geospatial applications. Strictly speaking, conventional techniques of conformal, affine and projective transformation models are mostly used to accomplish such task. With developing countries like Ghana where there is no immediate plans to establish geocentric datum and still rely on the astro-geodetic datums as it national mapping reference surface, there is the urgent need to explore the suitability of other transformation methods. In this study, an effort has been made to explore the proficiency of the Extreme Learning Machine (ELM) as a novel alternative coordinate transformation method. The proposed ELM approach was applied to data found in the Ghana geodetic reference network. The ELM transformation result has been analysed and compared with benchmark methods of backpropagation neural network (BPNN), radial basis function neural network (RBFNN), two-dimensional (2D) affine and 2D conformal. The overall study results indicate that the ELM can produce comparable transformation results to the widely used BPNN and RBFNN, but better than the 2D affine and 2D conformal. The results produced by ELM has demonstrated it as a promising tool for coordinate transformation in Ghana.
Go to article

This page uses 'cookies'. Learn more