文献类型：期刊文献

英文题名：Regional Gravity Field Modeling Using Band-Limited SRBFs: A Case Study in Colorado

作者：Ma, Zhiwei[1];Yang, Meng[2,3];Liu, Jie[4]

第一作者：Ma, Zhiwei

通讯作者：Ma, ZW[1]

机构：[1]Henan Univ Econ & Law, Sch Engn Management & Real Estate, Zhengzhou 450046, Peoples R China;[2]Sun Yat Sen Univ, Sch Geospatial Engn & Sci, Zhuhai 519082, Peoples R China;[3]Sun Yat Sen Univ, Key Lab Comprehens Observat Polar Environm, Minist Educ, Zhuhai 519082, Peoples R China;[4]Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R China

第一机构：河南财经政法大学工程管理与房地产学院

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Sch Engn Management & Real Estate, Zhengzhou 450046, Peoples R China.|[1048420]河南财经政法大学工程管理与房地产学院;[10484]河南财经政法大学;

年份：2023

卷号：15

期号：18

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20234014835787);Scopus(收录号：2-s2.0-85173057893);WOS:【SCI-EXPANDED(收录号:WOS:001075248600001)】；

基金：The authors are very grateful to the NGS, the ISG, and the ICGEM for providing gravity, GPS/leveling, geoid and GGM data.

语种：英文

外文关键词：regional gravity field modeling; band-limited SRBFs; the residual and a priori accuracy comparative analysis method; gravity data combination; Colorado

摘要：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 for data with different spectrum information in the frequency domain, has not been extensively explored. Therefore, band-limited SRBFs, which have good localization characteristics in the frequency domain, were taken as the main tool in this study. To determine the optimal expansion degree of SRBFs for gravity data, a residual and a priori accuracy comparative analysis method was proposed. Using this methodology, the expansion degrees of terrestrial and airborne data were determined to be 5200 and 1840, respectively, and then a high-resolution geoid model called ColSRBF2023 was constructed for use in Colorado. The results indicated that ColSRBF2023 had a standard deviation (STD) of 2.3 cm with respect to the GSVS17 validation data. This value was 2-6 mm lower than models obtained using different expansion degrees for gravity data and models from other institutions considered in this study. Furthermore, when comparing it with the validation geoid model on a 1 ' x 1 ' grid, ColSRBF2023 exhibited an STD value of 2.4 cm, which was also the best among the examined models. These findings highlight the importance of determining the optimal expansion degree of gravity data, particularly for constructing high-resolution gravity field models in rugged mountainous areas.