Ma, Z.; Yang, M.; Liu, J. Regional Gravity Field Modeling Using Band-Limited SRBFs: A Case Study in Colorado. Remote Sens.2023, 15, 4515.
Ma, Z.; Yang, M.; Liu, J. Regional Gravity Field Modeling Using Band-Limited SRBFs: A Case Study in Colorado. Remote Sens. 2023, 15, 4515.
Ma, Z.; Yang, M.; Liu, J. Regional Gravity Field Modeling Using Band-Limited SRBFs: A Case Study in Colorado. Remote Sens.2023, 15, 4515.
Ma, Z.; Yang, M.; Liu, J. Regional Gravity Field Modeling Using Band-Limited SRBFs: A Case Study in Colorado. Remote Sens. 2023, 15, 4515.
Abstract
The use of spherical radial basis functions (SRBFs) in regional gravity field modeling has become popular in recent years. However, to our knowledge, their potential for combining gravity data from multiple sources, particularly data with different spectrum information in the frequency domain, has not been extensively explored. Therefore, band-limited SRBFs, which have good lo-calization characteristics in the frequency domain, are the main tool in this study. We propose a residual and a-prior accuracy comparative analysis method to determine the optimal degree of expansion of SRBFs for gravity data. Using this methodology, we constructed a high-resolution geoid model called ColSRBF2023 in Colorado. The degrees of expansion for terrestrial and airborne data were set to 5200 and 1840, respectively. Results indicate that ColSRBF2023 has a standard deviation (STD) value of 2.3 cm compared to the GSVS17 validate data. This value is 2-6 mm lower than models obtained using different degrees of expansion for gravity data and models from other institutions considered in this study. Additionally, at the 1'×1' grid in the entire target area, ColSRBF2023 has an STD value of 2.4 cm when compared to the validation model. This value is also the best among the options examined in this study. These findings highlight the importance of determining the optimal expansion degree of gravity data, particularly when constructing high-resolution gravity field models in rugged mountainous regions.
Keywords
Gravity field modeling; Band-limited SRBFs; Gravity data combination; Colorado experiment
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
