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Gilad Even-Tzur  - - - 
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Publication Record
Distribution of Articles published per year 
(2013 - 2017)
Total number of journals
published in
 
4
 
Publications
Article 1 Read 0 Citations Kinematic Datum Based on the ITRF as a Precise, Accurate, and Lasting TRF for Israel Hagi Ronen, Gilad Even-Tzur Published: 01 November 2017
Journal of Surveying Engineering, doi: 10.1061/(ASCE)SU.1943-5428.0000228
DOI See at publisher website
Article 0 Reads 0 Citations Invariance property of coordinate transformation Gilad Even-Tzur Published: 21 April 2017
Journal of Spatial Science, doi: 10.1080/14498596.2017.1316688
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Article 1 Read 0 Citations Gross-Error Detection in GNSS Networks Using Spanning Trees Gilad Even-Tzur, Mayas Nawatha Published: 01 August 2016
Journal of Surveying Engineering, doi: 10.1061/(asce)su.1943-5428.0000175
DOI See at publisher website
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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.
Article 1 Read 0 Citations Application of extended free net adjustment constraints in two-step analysis of deformation network Gilad Even-Tzur, Lior Shahar Published: 12 May 2015
Acta Geodaetica et Geophysica, doi: 10.1007/s40328-015-0119-3
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Two-step analysis of deformation network enables the extraction of geodynamical quantities from geodetic measurements campaigns in two steps. In the first step the measurements’ mathematical model is realized for each monitoring campaign and in the second step the deformation model is examined. The mathematical model is usually conceived as being absolutely correct, while the validity of the deformation model and its system noise is frequently limited. The deformation model is commonly presented by kinematic model although dynamic model might describes the geophysical reality more accurately. Dynamic model is usually characterized by nonlinearity, which makes difficult the analysis of deformations in relative to a stable datum. Therefore, many of the control networks that are used for deformation monitoring and are measured by geodetic measurements are currently defined by kinematic models. In monitoring networks, global effects can impair the data processing and the deformation analysis and cause the deviation of the network solution. Extended free net adjustment constraints is a mathematical method that effectively coping with global effects. An extended solution of geodetic network for deformation monitoring includes the solution of extended parameters, in addition to those received in a standard solution. Such a solution enables to sterilize the geodetic measurements from their datum definition content in the first step, and extract the deterministic movement in the second step. The paper shows the great potential of using combination of the extended free net adjustment constrains and the two-step analysis of deformation networks.
Article 0 Reads 0 Citations Velocity Field across the Carmel Fault Calculated by Extended Free Network Adjustment Constraints Gilad Even-Tzur, Joerg Reinking Published: 01 January 2013
Journal of Applied Geodesy, doi: 10.1515/jag-2013-0054
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The Carmel Fault is one of the major geological structures of northern Israel. It is the northwestern part of Carmel-Tirtza Fault System and a northwestern branch of the Dead Sea Fault. The Carmel Fault region is covered by a monitoring geodetic network consisting of 23 sites, which were measured four times between 1999 and 2010 by means of GPS. The site velocities can be estimated only if the datum of the network has not been changed between measurement epochs. The GPS vectors must be adjusted so that the datum will remain undisturbed throughout the measurement campaigns. Usually we assume that GPS vectors define the network datum components of orientation and scale. Fluctuations in the GPS orbits could affect the orientation and scale between monitoring campaigns and therefore, in this study, we assume that GPS vectors are not immune to changes in their datum content. An appropriate approach is taken to prevent the inclusion of these components in the adjustment of a 4D network. If not, the result will be an inevitable mixture between the deformation parameters and the datum components of the GPS vectors. In this study the GPS vectors from each campaign are stripped from their datum content using the extended free network adjustment constraints. The datumless measurements are used to define the datum by preliminary coordinates and linear constraints, which remain constant for all monitoring campaigns, as well as to define the position of the network points and their velocities. Later on, the variations across the network geometry can be modeled by means of a physical model.