Evaluating the performance of various models for deriving orthometricheights using Global Navigation Satellite System (GNSS) data

Orthometric heights are vital for fields such as topographic mapping, construction, engineering, and geophysical studies. This study examines the performance of five Global Geopotential Models (GGMs) and Global Navigation Satellite System (GNSS) data in deriving orthometric heights to determine the optimum model. Data from 21 ground control points were collected using South GNSS receivers, processed for ellipsoidal height, and compared with geoid undulations from five GGMs (EGM 2008, EIGEN-6C4, GECO, SGG-UGM-2, and XGM 2019e) to determine the orthometric heights. The derived heights were validated against existing orthometric data. The geoid models showed a high correlation (0.999), with EGM 2008, GECO, SGG-UGM-2, and XGM 2019e displaying similar standard deviations (0.06-0.07 m). EIGEN-6C4, however, was an outlier, with a higher standard deviation (SD = 4.8750 m) and lower minimum value (Min = 2.467m). Root Mean Square Errors (RMSEs) ranged between 10.92 m and 11.27 m for all models. Statistical tests, including t-tests and ANOVA, showed no significant difference between most models at a 95% confidence level, though GECO and XGM 2019e had a small, statistically significant difference. XGM 2019e was identified as the most precise model, showing a near-perfect correlation with other models with the least standard deviation.