IAG-IASPEI 2017

講演情報

Poster

IAG Symposia » G02. Static gravity field

[G02-P] Poster

2017年8月1日(火) 15:30 〜 16:30 Shinsho Hall (The KOBE Chamber of Commerce and Industry, 3F)

15:30 〜 16:30

[G02-P-09] Topographic correction and covariance function modelling over the coastal regions

Adili Abulaitijiang1, Riccardo Barzaghi2, Ole Baltazar Andersen1, Per Knudsen1 (1.DTU Space, Technical University of Denmark, Copenhagen, Denmark, 2.Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy)

Using the conventional remove-compute-restore (only removing the Global Geopotential Models) technique, the theoretical assumption of homogeneity and isotropy in the Least Square Collocation (LSC) algorithm is not always satisfied in the coastal regions and mountainous regions. High resolution bathymetry data (e.g., SRTM30, spatial resolution of around 1 Km) is used to account for the strong correlation in the short wavelength (1~10 km) gravity features with topography and bathymetry. Hence, the Topographic Correction (TC) is a critical step in the reduction of the gravity functionals (e.g., height anomaly and gravity anomaly), to comply with the theoretical assumption of LSC.
DTU has been working on the improved coastal marine gravity from satellite altimetry (mainly CryoSat-2). Previous studies show that the terrain correction using Residual Terrain Model (RTM) w.r.t. residual gravity anomalies are slightly different w.r.t the residual height anomalies over the shallow regions close to the coast (or regions including islands). This should be well examined when the (sea level) height anomalies are to be reduced by TC and further the marine gravity field is derived using LSC. In this work, the TC computation (both w.r.t. the height anomalies and gravity) will be conducted in several regions (patches) around Mediterranean, Chile, islands of Indonesia where the true gravity data is available for validation. Both the spatial integration and FFT approach will be tested due to the steep topographic changes in the selected regions. The reduction performance is then evaluated through proper covariance function modelling and analysis before the LSC.