Anambra state regional geoid determination using satellite altimetry
Abstract
This study aimed at determining the Anambra State Regional geoid using satellite altimetry. The objectives are to: model the Anambra State Regional Geoid Model using Broadview RADAR Altimeter Toolbox (BRAT) and Sentinel-3 Missions and validate the accuracy of the determined Geoid. The methodology utilized diverse datasets, including Sentinel-3 satellite altimetry, ground measurements, and oceanographic data, to advance the understanding of Earth's geoid. Processing techniques involve data preparation, correction for dynamic ocean topography, and correction for topographic effects using a Digital Elevation Model (DEM). Geoid modeling employs iterative algorithms, with least squares adjustment optimizing the fit of the model to observed data. Validation included a meticulous comparison with 120 Global Navigation Satellite System (GNSS) observations, utilizing statistical indicators such as regression analysis, mean error (ME), root mean square error (RMSE), and standard deviation (SD). Results of the geoid modelling revealed elevations from 18.63m to 21.86m, with a mean of 20.75m and a standard deviation of 0.68m, indicating discernible spatial fluctuations. Geoid slope analysis, ranging from 0.0024 to 1.83 degrees with a mean of 0.0012 degrees and a low standard deviation of 0.00056 degrees, emphasizes a consistent slope pattern crucial for applications like civil engineering. Orthometric heights were derived and rigorously evaluated using regression analysis, mean error (ME), root mean square error (RMSE), and standard deviation (SD). A robust positive correlation (0.812) and R2 (0.657) affirmed the model's explanatory power. Additional metrics, including ME (0.14m), low RMSE (2.75m), and SD (4.61m), collectively confirm the accuracy and reliability of the geoid model.
How to Cite This Article
Okeke, UC, Ono MN (2024). Anambra state regional geoid determination using satellite altimetry . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 5(2), 537-546.