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Estimation and evaluation of GPS geoid heights using an artificial neural network model

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Abstract

The aim of the present study is the employment of the artificial neural network (ANN) model in the estimation and evaluation of geoid heights. For that reason, a number of control points with known orthometric heights in the region of North Greece were measured by GPS and used to test the presented algorithms. The derived ANN geoid heights are compared to those produced by a well-known conventional method through a combined gravimetric geoid. In order to evaluate the computed heights, numerical tests were carried out for points distributed inside and at the borders of the study area. The obtained results show that the ANN model is a competitive approach with certain advantages.

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Authors and Affiliations

  1. Department of Geodesy and Surveying, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Christos Pikridas, Aristidis Fotiou, Symeon Katsougiannopoulos & Dimitrios Rossikopoulos

Authors
  1. Christos Pikridas
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  2. Aristidis Fotiou
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  3. Symeon Katsougiannopoulos
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  4. Dimitrios Rossikopoulos
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Correspondence to Christos Pikridas.

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Pikridas, C., Fotiou, A., Katsougiannopoulos, S. et al. Estimation and evaluation of GPS geoid heights using an artificial neural network model. Appl Geomat 3, 183–187 (2011). https://doi.org/10.1007/s12518-011-0052-2

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  • DOI: https://doi.org/10.1007/s12518-011-0052-2

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