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A novel three-direction datum transformation of geodetic coordinates for Egypt using artificial neural network approach

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Abstract

The geodetic datum transformation in-between local and global systems seen in the world are inspiring for the engineering applications. In this context, the Egyptian geodetic network has a limited observation for the terrestrial and satellite of the geodetic networks. Transforming the coordinates of the Egyptian datum, here we demonstrate the datum transformation in three directions from global to local coordinates that utilized the artificial neural network (ANN) technique as a new tool of datum transformation in Egypt. A conventional, which are the Helmert and Molodensky, and numerical, which are the regression, minimum curvature surface, and ANN, datum transformation techniques are investigated and compared over the available data in Egypt. The results showed an accurate transforming datum using ANN technique for both common and check points, and the novel model improved the transformation coordinates by 37 to 72% in space directions. A comparison between the conventional and numerical techniques shows that the accuracy of the developed ANN model is 20.16 cm in terms of standard deviation based on the residuals of the projected coordinates.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B2010120).

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Correspondence to Jong Wan Hu.

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Elshambaky, H.T., Kaloop, M.R. & Hu, J.W. A novel three-direction datum transformation of geodetic coordinates for Egypt using artificial neural network approach. Arab J Geosci 11, 110 (2018). https://doi.org/10.1007/s12517-018-3441-6

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  • DOI: https://doi.org/10.1007/s12517-018-3441-6

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