Sensitivity Analysis of Digital Elevation Models in Geoid Modelling for Indian region

Digital Elevation Models (DEMs) are fundamental components in geodetic computations, serving as key inputs in geoid modelling processes. Mostly, the freely available DEMs are used for geoid modelling without considering its impact on the developed geoid. Considering the criticality of terrain and downward continuation corrections calculated from DEMs, this research work explores the sensitivity of geoid models to variations in DEMs, aiming to elucidate the impact of different DEMs on the accuracy and precision of geoid modelling. The study aims at a comprehensive sensitivity analysis framework to assess the influence of DEM resolution, terrain representation, and fitting methods on regional geoid modelling in India. The selected study area consists of three states of India (Haryana, Punjab, and Himachal Pradesh) bounding approximately 169,500 km² of the area (73.5≤λ≤77.5 and 29≤ϕ≤33 of longitude and latitude, respectively) of vast topography including Indo-Gangetic Plain, Shivalik Hills, lofty hills, deep valleys, and verdant forests. This study employs Least Squares Modification of Stokes formula with Additive Corrections (LSMSAC) method developed by the Royal Institute of Technology, Sweden and evaluates four DEMs, Cartosat, Merit, Palsar and SRTM. For surface correction (fitting), 24 GNSS points are used with 4,5 & 7 parameter fitting models which is validated with 15 other GNSS point based on elementary statistics. This investigation offers insights into selection of an optimal DEM by obtaining RMSE between developed geoid using various DEMs and 15 GNSS points. Based on the obtained results by considering above-mentioned DEMs with various fitting models, the Cartosat DEM outperformed other DEMs by obtaining lowest RMSE (0.078603m) with 7 parameter fitting model. Surprisingly, the lowest RMSE (0.064557m) is obtained by Cartosat DEM with 4 parameter model which could be because of Cartosat DEM being an India specific DEM. While comparing the efficacy of developed geoid between globally available DEM, Merit performed best with lowest RMSE (0.078657m). Out of 90 combinations of each DEM for various sets of Degree/order of Global Geopotential model (GGM), integration cap size; the best result is obtained by 180 degree of GGM and 0.8 integration cap size for each DEM. Presented study improved our understanding in assessing the sensitivity of geoid models to various DEMs. This research aids geodesists, geophysicists, and remote sensing specialists in making informed decisions while selecting a suitable DEM for geoid computations. The findings presented in this paper contribute to the ongoing efforts to enhance the precision and reliability of geoid modelling techniques, ultimately improving our understanding of Earth's gravity field.