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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
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Sensors and Materials, Volume 34, Number 1(3) (2022)
Copyright(C) MYU K.K.
pp. 367-382
S&M2816 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2022.3665
Published in advance: January 5, 2022
Published: January 31, 2022

Orthometric Corrections Using Gridded Gravity Data Derived from Digital Elevation Model [PDF]

Hong Sool Lee, Kwang Bae Kim, Chang Uk Woo, and Hong Sik Yun

(Received September 27, 2021; Accepted December 2, 2021)

Keywords: gridded gravity data, gravity, height, digital elevation model, orthometric correction

In this study, gridded gravity data (GGD) were generated by using the correlation between gravity and the height extracted from a high-resolution digital elevation model (DEM) in an area where the national control points where gravity was measured are not densely distributed. Comparison of the measured gravity and the gravity generated by using GGD, which is produced by the linear regression analysis of the height extracted from DEM at the national control points, revealed that the accuracy of GGD is about 33 mGal. The difference is very small at about 4 and 5 mm, when comparing the orthometric correction for each section and the cumulative orthometric correction calculated using the gravity interpolated from GGD with the results calculated from the measured gravity, respectively. Thus, it is considered that the orthometric correction can be effectively calculated by using the gravity interpolated from GGD at the points where there are no measured gravity data. If the gravity distribution measured at national control points becomes dense, it is expected to further improve the accuracy of the gravity interpolated from the GGD, which is generated by using the linear correlation between the gravity and the height extracted from high-resolution DEM.

Corresponding author: Kwang Bae Kim


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Cite this article
Hong Sool Lee, Kwang Bae Kim, Chang Uk Woo, and Hong Sik Yun, Orthometric Corrections Using Gridded Gravity Data Derived from Digital Elevation Model, Sens. Mater., Vol. 34, No. 1, 2022, p. 367-382.



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