On the Evaluation of the Neural Network Khartoum Geoid Model

Kamal Abdellatif Sami; Ammar Mohammed Maryod Aborida

doi:doi:10.11648/j.ajset.20220704.13

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On the Evaluation of the Neural Network Khartoum Geoid Model

Kamal Abdellatif Sami, Ammar Mohammed Maryod Aborida

Published in American Journal of Science, Engineering and Technology (Volume 7, Issue 4)

Received: 15 September 2022 Accepted: 20 October 2022 Published: 4 November 2022

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Abstract

This study was carried out to establish and evaluate an Artificial Neural Networks (ANN) geoid model for the Khartoum State. In the first stage the geometrical geoid heights were obtained from the differences between observed ellipsoidal heights and known orthometric heights of 48 geodetic Ground Control Points (GCP) in the study area. This followed by generating an ANN geoid model to extract the geoid heights from 42 ground control stations in the same study area in the Khartoum State. The main objective of this research study is to apply an ANN to model the Geoid surface using the back propagation algorithm in Khartoum state, through supervised training by geoidal undulations values. The WGS84 GPS/levelling geoid is computed then their results were used for comparison and evaluation of the determined ANN Geoid surface. In this study the geometrical geoid model was determined using the well-known geometrical geoid determination approach taking consideration of the distribution of the existing vertical control points in Khartoum area, with an intention of determining the orthometric heights of any point of unknown heights with uncertainties of less than 5cm. The ANN geoid uncertainties were evaluated and tested at 6 geodetic ground control points. The average difference between the derived geoid heights obtained from the geometrical geoid model, and their corresponding ANN geoid heights was found to be in the range of ±3 cm. Based on the test results of the statistical analysis and the study of a trained artificial neural networks model, the authors were able to estimate the geoid model with acceptable accuracy and can interactively be available for end users. This study showed that, the geoid heights in Khartoum State can be determined with the ANN method with typical accuracy of better than 5cm.

Published in	American Journal of Science, Engineering and Technology (Volume 7, Issue 4)
DOI	10.11648/j.ajset.20220704.13
Page(s)	147-151
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

GPS, GNSS, Geoid, WGS84, UTM, Ellipsoidal Heights, Orthometric Heights

References

[1]	Abdalla, K. A (2003). Datum Transformation and Geoid Determination effects in the Quality of Geodetic Control in Developing Countries. Presented in XXIII General Assembly of the International Union of Geodesy and Geophysics, Sapporo, Japan, Nov. 2003.
[2]	Abdalla, K. A (2006). Vertical Control Network of Al Ain Region. GIS development.net. Proceedings of Map Middle east 2006.
[3]	Ahmed Zaki, Yasmeen Elberry, Hamad Al Ajami, Mostafa Rabah and Rasha Abd El Ghany (2022). Determination of Local geometric geoid model for Kuwait. Journal of Applied Geodesy. jag-July 2022-0017.
[4]	Berkant Konakoglu and Alper Akar (2021). Geoid Undulation using ANNs (RBFNN and GRNN), multiple linear regression (MLR) and interpolation methods: A comparative Study. Earth Sciences Research Journal, Vol. 25, No. 4, December 2021, 371-382.
[5]	Eleje Sylvester Okiemute (2021). Verification of the consistency of the proposed transformation of global geoid method accuracy for local geoid model of Nigeria Determination. FUDMA Journal of Sciences. FUDMA Journal of Sciences, vo;. 5 No. 4 December, 2021, pp. 49-55.
[6]	Fashir, H. H., Salih, A. B. and Abdalla, K. A. (1989)."The Transformation between the Doppler Co-ordinate system and the geodetic Co-ordinate system in Sudan". Published in Australian Journal of Geodesy, Photogrammetry and Surveying, Australia.
[7]	Featherstone, W. E, Denfith, M. C and Kirby, J. F (1998)). Strategies for the Accurate Determination of orthometric Heights from GPS. Survey review, 34, 267.
[8]	Fyfe, C., 2000. Artificial neural networks and information theory. University of Paisley.
[9]	Lars E. Sjöberg, Mohammad Bagherbandi (2017), Gravity Inversion and Integration Theory and Applications in Geodesy and Geophysics. Library of Congress Control Number: 2016963159, Springer International Publishing AG 2017
[10]	Mirko Reguzzoni, Daniela Carrion, Carlo lapiege De Gaetani, Alberta AlBertella, Lorenzo Rossi, Glovanna Sona, Khulan Batsukh, Juan Fernando Toro Herrera,, Kirsten Elger, Riccardo barzaghi and Fernando Sanso (2021). Open Access to regional geoid Models: The International Service for the Geoid. Earth Syst. Sci data, 13, 1653-1666, 2021. Published by Copemicus Publications.
[11]	Mukesh Khare (2007) Artificial Neural Network in Vehicular Pollution Modelling.
[12]	Tata Herbert and Eleje Sylvester Okiemute (2021). Determination of orthometric heights of points using gravimetric/GPS and geodetic levelling approaches. Indian Journal of Engineering, 18 (49), pp. 134-144. April 2021.
[13]	Ugo Falchi, Claudio Parente, Giuseppina Prezioso (2018). Global geoid adjustment on local area for GIS applications using GNSS Perminant Station Coordinates. Published by Vilnius Gediminas Technology University, Vol 44 No. 3 (2018).
[14]	Walker, J. M. (2015) Artificial Neural Networks. doi: 10.1007/978-1-4939-2239-0.
[15]	Zilkoski, R, B and Earlson, E, E. (2005): Guidelines for Establishing GPS –Derived orthometric heights. National Geodetic Survey, Maryland 20910.

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APA Style

Kamal Abdellatif Sami, Ammar Mohammed Maryod Aborida. (2022). On the Evaluation of the Neural Network Khartoum Geoid Model. American Journal of Science, Engineering and Technology, 7(4), 147-151. https://doi.org/10.11648/j.ajset.20220704.13

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ACS Style

Kamal Abdellatif Sami; Ammar Mohammed Maryod Aborida. On the Evaluation of the Neural Network Khartoum Geoid Model. Am. J. Sci. Eng. Technol. 2022, 7(4), 147-151. doi: 10.11648/j.ajset.20220704.13

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AMA Style

Kamal Abdellatif Sami, Ammar Mohammed Maryod Aborida. On the Evaluation of the Neural Network Khartoum Geoid Model. Am J Sci Eng Technol. 2022;7(4):147-151. doi: 10.11648/j.ajset.20220704.13

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@article{10.11648/j.ajset.20220704.13,
  author = {Kamal Abdellatif Sami and Ammar Mohammed Maryod Aborida},
  title = {On the Evaluation of the Neural Network Khartoum Geoid Model},
  journal = {American Journal of Science, Engineering and Technology},
  volume = {7},
  number = {4},
  pages = {147-151},
  doi = {10.11648/j.ajset.20220704.13},
  url = {https://doi.org/10.11648/j.ajset.20220704.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20220704.13},
  abstract = {This study was carried out to establish and evaluate an Artificial Neural Networks (ANN) geoid model for the Khartoum State. In the first stage the geometrical geoid heights were obtained from the differences between observed ellipsoidal heights and known orthometric heights of 48 geodetic Ground Control Points (GCP) in the study area. This followed by generating an ANN geoid model to extract the geoid heights from 42 ground control stations in the same study area in the Khartoum State. The main objective of this research study is to apply an ANN to model the Geoid surface using the back propagation algorithm in Khartoum state, through supervised training by geoidal undulations values. The WGS84 GPS/levelling geoid is computed then their results were used for comparison and evaluation of the determined ANN Geoid surface. In this study the geometrical geoid model was determined using the well-known geometrical geoid determination approach taking consideration of the distribution of the existing vertical control points in Khartoum area, with an intention of determining the orthometric heights of any point of unknown heights with uncertainties of less than 5cm. The ANN geoid uncertainties were evaluated and tested at 6 geodetic ground control points. The average difference between the derived geoid heights obtained from the geometrical geoid model, and their corresponding ANN geoid heights was found to be in the range of ±3 cm. Based on the test results of the statistical analysis and the study of a trained artificial neural networks model, the authors were able to estimate the geoid model with acceptable accuracy and can interactively be available for end users. This study showed that, the geoid heights in Khartoum State can be determined with the ANN method with typical accuracy of better than 5cm.},
 year = {2022}
}

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TY  - JOUR
T1  - On the Evaluation of the Neural Network Khartoum Geoid Model
AU  - Kamal Abdellatif Sami
AU  - Ammar Mohammed Maryod Aborida
Y1  - 2022/11/04
PY  - 2022
N1  - https://doi.org/10.11648/j.ajset.20220704.13
DO  - 10.11648/j.ajset.20220704.13
T2  - American Journal of Science, Engineering and Technology
JF  - American Journal of Science, Engineering and Technology
JO  - American Journal of Science, Engineering and Technology
SP  - 147
EP  - 151
PB  - Science Publishing Group
SN  - 2578-8353
UR  - https://doi.org/10.11648/j.ajset.20220704.13
AB  - This study was carried out to establish and evaluate an Artificial Neural Networks (ANN) geoid model for the Khartoum State. In the first stage the geometrical geoid heights were obtained from the differences between observed ellipsoidal heights and known orthometric heights of 48 geodetic Ground Control Points (GCP) in the study area. This followed by generating an ANN geoid model to extract the geoid heights from 42 ground control stations in the same study area in the Khartoum State. The main objective of this research study is to apply an ANN to model the Geoid surface using the back propagation algorithm in Khartoum state, through supervised training by geoidal undulations values. The WGS84 GPS/levelling geoid is computed then their results were used for comparison and evaluation of the determined ANN Geoid surface. In this study the geometrical geoid model was determined using the well-known geometrical geoid determination approach taking consideration of the distribution of the existing vertical control points in Khartoum area, with an intention of determining the orthometric heights of any point of unknown heights with uncertainties of less than 5cm. The ANN geoid uncertainties were evaluated and tested at 6 geodetic ground control points. The average difference between the derived geoid heights obtained from the geometrical geoid model, and their corresponding ANN geoid heights was found to be in the range of ±3 cm. Based on the test results of the statistical analysis and the study of a trained artificial neural networks model, the authors were able to estimate the geoid model with acceptable accuracy and can interactively be available for end users. This study showed that, the geoid heights in Khartoum State can be determined with the ANN method with typical accuracy of better than 5cm.
VL  - 7
IS  - 4
ER  -

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Author Information

Kamal Abdellatif Sami

Department of Surveying Engineering, University of Khartoum, Khartoum, Sudan
Ammar Mohammed Maryod Aborida

Department of Surveying Engineering, Omdurman Islamic University, Khartoum, Sudan

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APA Style

Kamal Abdellatif Sami, Ammar Mohammed Maryod Aborida. (2022). On the Evaluation of the Neural Network Khartoum Geoid Model. American Journal of Science, Engineering and Technology, 7(4), 147-151. https://doi.org/10.11648/j.ajset.20220704.13

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ACS Style

Kamal Abdellatif Sami; Ammar Mohammed Maryod Aborida. On the Evaluation of the Neural Network Khartoum Geoid Model. Am. J. Sci. Eng. Technol. 2022, 7(4), 147-151. doi: 10.11648/j.ajset.20220704.13

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AMA Style

Kamal Abdellatif Sami, Ammar Mohammed Maryod Aborida. On the Evaluation of the Neural Network Khartoum Geoid Model. Am J Sci Eng Technol. 2022;7(4):147-151. doi: 10.11648/j.ajset.20220704.13

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@article{10.11648/j.ajset.20220704.13,
  author = {Kamal Abdellatif Sami and Ammar Mohammed Maryod Aborida},
  title = {On the Evaluation of the Neural Network Khartoum Geoid Model},
  journal = {American Journal of Science, Engineering and Technology},
  volume = {7},
  number = {4},
  pages = {147-151},
  doi = {10.11648/j.ajset.20220704.13},
  url = {https://doi.org/10.11648/j.ajset.20220704.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20220704.13},
  abstract = {This study was carried out to establish and evaluate an Artificial Neural Networks (ANN) geoid model for the Khartoum State. In the first stage the geometrical geoid heights were obtained from the differences between observed ellipsoidal heights and known orthometric heights of 48 geodetic Ground Control Points (GCP) in the study area. This followed by generating an ANN geoid model to extract the geoid heights from 42 ground control stations in the same study area in the Khartoum State. The main objective of this research study is to apply an ANN to model the Geoid surface using the back propagation algorithm in Khartoum state, through supervised training by geoidal undulations values. The WGS84 GPS/levelling geoid is computed then their results were used for comparison and evaluation of the determined ANN Geoid surface. In this study the geometrical geoid model was determined using the well-known geometrical geoid determination approach taking consideration of the distribution of the existing vertical control points in Khartoum area, with an intention of determining the orthometric heights of any point of unknown heights with uncertainties of less than 5cm. The ANN geoid uncertainties were evaluated and tested at 6 geodetic ground control points. The average difference between the derived geoid heights obtained from the geometrical geoid model, and their corresponding ANN geoid heights was found to be in the range of ±3 cm. Based on the test results of the statistical analysis and the study of a trained artificial neural networks model, the authors were able to estimate the geoid model with acceptable accuracy and can interactively be available for end users. This study showed that, the geoid heights in Khartoum State can be determined with the ANN method with typical accuracy of better than 5cm.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - On the Evaluation of the Neural Network Khartoum Geoid Model
AU  - Kamal Abdellatif Sami
AU  - Ammar Mohammed Maryod Aborida
Y1  - 2022/11/04
PY  - 2022
N1  - https://doi.org/10.11648/j.ajset.20220704.13
DO  - 10.11648/j.ajset.20220704.13
T2  - American Journal of Science, Engineering and Technology
JF  - American Journal of Science, Engineering and Technology
JO  - American Journal of Science, Engineering and Technology
SP  - 147
EP  - 151
PB  - Science Publishing Group
SN  - 2578-8353
UR  - https://doi.org/10.11648/j.ajset.20220704.13
AB  - This study was carried out to establish and evaluate an Artificial Neural Networks (ANN) geoid model for the Khartoum State. In the first stage the geometrical geoid heights were obtained from the differences between observed ellipsoidal heights and known orthometric heights of 48 geodetic Ground Control Points (GCP) in the study area. This followed by generating an ANN geoid model to extract the geoid heights from 42 ground control stations in the same study area in the Khartoum State. The main objective of this research study is to apply an ANN to model the Geoid surface using the back propagation algorithm in Khartoum state, through supervised training by geoidal undulations values. The WGS84 GPS/levelling geoid is computed then their results were used for comparison and evaluation of the determined ANN Geoid surface. In this study the geometrical geoid model was determined using the well-known geometrical geoid determination approach taking consideration of the distribution of the existing vertical control points in Khartoum area, with an intention of determining the orthometric heights of any point of unknown heights with uncertainties of less than 5cm. The ANN geoid uncertainties were evaluated and tested at 6 geodetic ground control points. The average difference between the derived geoid heights obtained from the geometrical geoid model, and their corresponding ANN geoid heights was found to be in the range of ±3 cm. Based on the test results of the statistical analysis and the study of a trained artificial neural networks model, the authors were able to estimate the geoid model with acceptable accuracy and can interactively be available for end users. This study showed that, the geoid heights in Khartoum State can be determined with the ANN method with typical accuracy of better than 5cm.
VL  - 7
IS  - 4
ER  -

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