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Evaluating the Impact of the Recent Combined and Satellite-Only Global Geopotential Model on the Gravimetric Geoid Model

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Abstract Geoid represents Earth’s surface, ocean, and gravitational field, which influence the elevations, shape, and mass distribution of the geopotential surface, a hypothetical surface that is perpendicular to the direction of gravity at every point. This geopotential surface serves as a reference for measuring elevations and is used as a fundamental reference surface for geodetic and surveying purposes. In this study, the Least Squares Modification of Stokes Formula (LSMS) with Additive Corrections (AC), also known as the KTH method, is used to generate a new gravimetric geoid model for Peninsular Malaysia. The KTH method was developed at the Royal Institute of Technology (KTH) in Stockholm-Sweden. The dataset used is the most recent global digital elevation model, Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global, generated by the National Aeronautics and Space Administration (NASA) and the National Imagery and Mapping Agency (NIMA). In addition to this elevation data, the dataset includes the Global Geopotential Model (GGM), which is composed of the XGM2016, XGM2019e, Tongji_GGMG2021S, and Tongji-Grace02k models. Furthermore, it incorporates sets of regional gravity data, including terrestrial gravity, airborne gravity, and marine gravity anomalies, all of which are derived from the Technical University of Denmark (DTU 21). The actual 45 Global Navigation Satellite System (GNSS)-levelling points data have been compared to the gravimetric geoid model developed in this study and the geoid acquired from Department of Survey and Mapping Malaysia (DSMM). According to the statistical results, NXGM2019e provides better accuracy, with the Root Mean Square Error (RMSE) geoid model errors of ±0.033 m, compared to the deviations in free-air anomalies, XGM2019e, which has the minimum RMSE of 10.291 mGal. Meanwhile, Tongji-GMMG2021S has the maximum RMSE of 14.792 mGal. The geoid is derived from the XGM2019e model and has maximum and minimum values of 0.032 m and 0.147 m, respectively, with mean residuals of 0.089 m. In conclusion, the XGM2019e has the potential to determine a precise local geoid model for Peninsular Malaysia
Title: Evaluating the Impact of the Recent Combined and Satellite-Only Global Geopotential Model on the Gravimetric Geoid Model
Description:
Abstract Geoid represents Earth’s surface, ocean, and gravitational field, which influence the elevations, shape, and mass distribution of the geopotential surface, a hypothetical surface that is perpendicular to the direction of gravity at every point.
This geopotential surface serves as a reference for measuring elevations and is used as a fundamental reference surface for geodetic and surveying purposes.
In this study, the Least Squares Modification of Stokes Formula (LSMS) with Additive Corrections (AC), also known as the KTH method, is used to generate a new gravimetric geoid model for Peninsular Malaysia.
The KTH method was developed at the Royal Institute of Technology (KTH) in Stockholm-Sweden.
The dataset used is the most recent global digital elevation model, Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global, generated by the National Aeronautics and Space Administration (NASA) and the National Imagery and Mapping Agency (NIMA).
In addition to this elevation data, the dataset includes the Global Geopotential Model (GGM), which is composed of the XGM2016, XGM2019e, Tongji_GGMG2021S, and Tongji-Grace02k models.
Furthermore, it incorporates sets of regional gravity data, including terrestrial gravity, airborne gravity, and marine gravity anomalies, all of which are derived from the Technical University of Denmark (DTU 21).
The actual 45 Global Navigation Satellite System (GNSS)-levelling points data have been compared to the gravimetric geoid model developed in this study and the geoid acquired from Department of Survey and Mapping Malaysia (DSMM).
According to the statistical results, NXGM2019e provides better accuracy, with the Root Mean Square Error (RMSE) geoid model errors of ±0.
033 m, compared to the deviations in free-air anomalies, XGM2019e, which has the minimum RMSE of 10.
291 mGal.
Meanwhile, Tongji-GMMG2021S has the maximum RMSE of 14.
792 mGal.
The geoid is derived from the XGM2019e model and has maximum and minimum values of 0.
032 m and 0.
147 m, respectively, with mean residuals of 0.
089 m.
In conclusion, the XGM2019e has the potential to determine a precise local geoid model for Peninsular Malaysia.

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