2019
DOI: 10.22364/bjmc.2019.7.4.06
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The Best Robust Estimation Method to Determine Local Surface

Abstract: Geoid/quasi-geoid modelling in a local (small) area is often made with polynomials. The optimal version of a polynomial is found by testing its successive versions using different statistical parameters, i.e. with different degree and number of coefficients. In this publication, the authors presented 3 approaches to search for an optimal version of the polynomial. Two of them were based on one of the robust estimation methods, i.e. the Danish method. Therefore, the question arises whether this method is suitab… Show more

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Cited by 5 publications
(3 citation statements)
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References 16 publications
(15 reference statements)
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“…Through the years many interpolation methods have been involved in generating conversion surfaces (in local and regional scales) enabling transition between geometric and physical heights, e.g., polynomial regression (Borowski and Banaś, 2019;Gucek and Bašić, 2009;Kim et al, 2018;Zhong, 1997), neural networks (Aky-ilmaz et al, 2009;Kaloop et al, 2021), geographically weighted regression (Dawod and Abdel-Aziz, 2020), kriging (Ligas and Szombara, 2018;Orejuela et al, 2021), least-squares collocation (LSC) (You, 2006), Inverse Distance Weighting (IDW) (Radanović and Bašić, 2018) to mention only a few. Very often, conversion surfaces take the form of corrector surfaces due to the use of global geopotential models or gravimetric models generated prior to eliminating inconsistencies by fitting to GNSS/levelling data (Elshambaky, 2018;You, 2006).…”
Section: Introductionmentioning
confidence: 99%
“…Through the years many interpolation methods have been involved in generating conversion surfaces (in local and regional scales) enabling transition between geometric and physical heights, e.g., polynomial regression (Borowski and Banaś, 2019;Gucek and Bašić, 2009;Kim et al, 2018;Zhong, 1997), neural networks (Aky-ilmaz et al, 2009;Kaloop et al, 2021), geographically weighted regression (Dawod and Abdel-Aziz, 2020), kriging (Ligas and Szombara, 2018;Orejuela et al, 2021), least-squares collocation (LSC) (You, 2006), Inverse Distance Weighting (IDW) (Radanović and Bašić, 2018) to mention only a few. Very often, conversion surfaces take the form of corrector surfaces due to the use of global geopotential models or gravimetric models generated prior to eliminating inconsistencies by fitting to GNSS/levelling data (Elshambaky, 2018;You, 2006).…”
Section: Introductionmentioning
confidence: 99%
“…In the adjustment results, the correction values of the gross error and noise were too large. Using this characteristic, the weight of the observation value was adjusted according to the Danish weight function [35] (Equation ( 7)) and stopped until the set number of iterations was fulfilled or less than the set threshold.…”
Section: Iterative Optimal Ellipse Fittingmentioning
confidence: 99%
“…Качество построения ЦМР как источника точной геопространственной информации [27][28][29] в том числе c исправлением высот по локальным моделям геоидов [30], напрямую зависит от его выбора [31][32][33]. Авторы работ [34][35][36] отмечают целесообразность применения следующих методов пространственной интерполяции для построения ЦМР [37][38][39]:…”
Section: Introductionunclassified