Regional Ground Surface Mass Variations Inversed by Radial Point-mass Model Method with Spatial Constraints

• Main Authors: GUO Feixiao, SUN Zhongmiao, ZHAO Jun, MIAO Yuewang, XIAO Yun
• Format: Article
• Language: zho
• Published: Surveying and Mapping Press 2018-05-01
• Series: Acta Geodaetica et Cartographica Sinica
• Subjects: GRACE satellite; time-variable gravity; point-mass model; spatial constraints; regularization; Helmert variance component estimation
• Online Access: http://html.rhhz.net/CHXB/html/2018-5-592.htm

Radial point-mass model method is the disturbance gravity downward continuation in essence, which is an ill-posed problem. In general, the regularization method is an efficient way to get the reliable solution. To solve this problem, the radial point-mass model method is improved by using Helmert variance component estimation with adding spatial constraints from a practical point of view. Taking South America continent as study area, radial point-mass model method with spatial constraints is verified by experimental results. The experiments results show that the condition number of normal equations is decreasing obviously after adding spatial constraints. The inversion results of radial point-mass model method with spatial constraints are consistent with results of other methods. Furthermore, the radial point-mass model method with spatial constraints provides an alternative way to monitor regional surface mass variations by satellite gravimetry.