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ACCURACY ASSESSMENT OF HEIGHTS OBTAINED FROM TOTAL STATION AND LEVEL INSTRUMENT USING TOTAL LEAST SQUARES AND ORDINARY LEAST SQUARES METHODS

*Richard Fiifi Annan  -  University of Mines and Technology, Ghana
Yao Yevenyo Ziggah  -  University of Mines and Technology, Ghana
John Ayer  -  Kwame Nkrumah University of Science and Technology, Ghana
Christian Amans Odutola  -  China University of Geosciences, Wuhan, China

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Abstract

Spirit levelling has been the traditional means of determining Reduced Levels (RL’s) of points by most surveyors.  The assertion that the level instrument is the best instrument for determining elevations of points needs to be reviewed; this is because technological advancement is making the total station a very reliable tool for determining reduced levels of points. In order to achieve the objective of this research, reduced levels of stations were determined by a spirit level and a total station instrument. Ordinary Least Squares (OLS) and Total Least Squares (TLS) techniques were then applied to adjust the level network. Unlike OLS which considers errors only in the observation matrix, and adjusts observations in order to make the sum of its residuals minimum, TLS considers errors in both the observation matrix and the data matrix, thereby minimising the errors in both matrices. This was evident from the results obtained in this study such that OLS approximated the adjusted reduced levels, which compromises accuracy, whereas the opposite happened in the TLS adjustment results. Therefore, TLS was preferred to OLS and Analysis of Variance (ANOVA) was performed on the preferred TLS solution and the RL’s from the total station in order to ascertain how accurate the total station can be relative to the spirit level.

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Keywords: Levelling; Least Squares; Analysis of Variance

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  1. Acar, M., et al. (2006). Deformation analysis with total least squares. Natural Hazards and Earth System Science, 6(4), 663–669
  2. https://scholar.google.com/scholar?q=Deformation+analysis+with+Total+Least+Squares&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  3. Akyilmaz, O. (2007). Total least squares solution of coordinate transformation. Survey Review, 39(303), 68–80
  4. http://doi.org/10.1179/003962607X165005">CrossRef [↗] | https://scholar.google.com/scholar?q=Total+least+squares+solution+of+coordinate+transformation&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  5. Brown, L. C., & Berthouex, P. M. (2002). Statistics for Environmental Engineers. CRC press
  6. https://scholar.google.com/scholar?q=Statistics+for+Environmental+Engineers+2002&btnG=&hl=en&as_sdt=0%2C5&oq=Statistics+for+Environmental+Engineers">Google Scholar [↗]
  7. Ghilani, C. D., & Wolf, P. R. (2014). Elementary Surveying (13th ed.). Pearson Education Inc., Upper Saddle River, New Jersey
  8. https://scholar.google.co.id/scholar?q=Ghilani%2C+C.+D.%2C+%26+Wolf%2C+P.+R.+%282014%29.+Elementary+Surveying&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  9. Golub, G. H., & van Loan, C. F. (1980). An analysis of the total least squares problem. SIAM Journal on Numerical Analysis, 17(6), 883–893
  10. http://dx.doi.org/10.1137/0717073">CrossRef [↗] | https://scholar.google.co.id/scholar?q=An+analysis+of+the+total+least+squares+problem&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  11. Jackson, S. L. (2013). Statistics Plain and Simple. Cengage Learning, Boston
  12. https://scholar.google.co.id/scholar?q=Statistics+Plain+and+Simple&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  13. Jin, Y., Tong, X., & Li, L. (2011). Total least squares with application in geospatial data processing. In Geoinformatics, 2011 19th International Conference on (pp. 1–3)
  14. https://doi.org/10.1109/GeoInformatics.2011.5980717">CrossRef [↗] | https://scholar.google.co.id/scholar?q=Total+least+squares+with+application+in+geospatial+data+processing&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  15. Lee, J., & Rho, T. (2001). Application to leveling using total station. In New Technology for a New Century International Conference FIG Working Week 2001. Seoul, Korea: FIG Conference Proceedings
  16. https://www.google.co.id/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=Application%20to%20leveling%20using%20total%20station.%20In%20New%20Technology%20for%20a%20New%20Century%20International%20Conference%20FIG%20Working%20Week%202001">Google Scholar [↗]
  17. Markovsky, I., & Van Huffel, S. (2007). Overview of total least-squares methods. Signal Processing, 87(10), 2283–2302
  18. http://dx.doi.org/10.1016/j.sigpro.2007.04.004">CrossRef [↗] | https://scholar.google.co.id/scholar?q=Overview+of+total+least-squares+methods&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  19. Okwuashi, O., & Eyoh, A. (2012a). 3D coordinate transformation using total least squares. Academic Research International, 3(1), 399–405
  20. https://scholar.google.co.id/scholar?q=3D+coordinate+transformation+using+total+least+squares&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  21. Okwuashi, O., & Eyoh, A. (2012b). Application of total least squares to a linear surveying network. Journal of Science and Arts, 4(21), 401–404
  22. https://scholar.google.co.id/scholar?q=Application+of+total+least+squares+to+a+linear+surveying+network&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  23. Rutherford, A. (2001). Introducing ANOVA and ANCOVA: a GLM approach. SAGE Publications Ltd., London
  24. https://scholar.google.co.id/scholar?q=Introducing+ANOVA+and+ANCOVA%3A+a+GLM+approach&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]
  25. Schofield, W., & Breach, M. (2007). Engineering Surveying (6th ed.). Elsevier Ltd, Oxford, Great Britain
  26. https://www.google.co.id/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=Engineering+Surveying+2007">Google Scholar [↗]
  27. Uren, J., & Price, W. F. (2010). Surveying for engineers (4th ed.). Palgrave Macmillan, New York
  28. https://scholar.google.co.id/scholar?q=Surveying+for+engineers&btnG=&hl=en&as_sdt=0%2C5">Google Scholar [↗]

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