IRG2018: A regional geoid model in Iran using Least Squares Collocation

Abstract

The aim of this study is to determine an accurate geoid model for Iran based on the Least Squares Collocation method in the framework of the Remove — Compute — Restore technique. In areas suffering from a lack of homogeneous and accurate gravity anomaly data, as is the case of Iran, the choice of the most compatible global gravity model has a significant impact on the estimated form of the geoid. Different combined and satellite-only global gravity models were therefore analyzed for Iran, and EIGEN6C4 was selected as the best one. The Shuttle Radar Topography Mission height model was used for the residual terrain correction. The covariance modeling, a crucial step in the Least Squares Collocation method, was based on two strategies. In the first, the study area was divided into four sub-areas, and then an individual empirical covariance was computed and a covariance model fitted to each of them. In the second, an empirical covariance was computed using all terrestrial gravity data, and a unique covariance model was fitted to it. Despite some border effects, the former strategy showed slightly better performance according to the resulting statistics, and therefore it was preferred for the estimation of the geoid model called IRG2018. To remove the offset of IRG2018 with respect to GNSS/Leveling-derived geoid heights, two alternative approaches were tested: subtracting a fitting polynomial surface or directly using the GNSS/Leveling data as an input to the IRG2018 computation process. Evaluation of the results, based on an independent control set of approximately half of available GNSS/Leveling points, showed an advantage of the latter approach, with an estimated accuracy of about 20 cm in terms of RMS.