Atmospheric Water Vapor Effect on GNSS Signals and InSAR Data
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1 Atmospheric Water Vapor Effect on GNSS Signals and InSAR Data Basic Concept and Preliminary Results F. Alshawaf 1, S. Hinz 1, A. Thiele 1 T. Fuhrmann 2, B. Heck 2, A. Knöpfler 2, X. Luo 2, M. Mayer 2, A. Schenk 2, M. Westerhaus 2 1 IPF - Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany 2 GIK - Geodetic Institute, Karlsruhe Institute of Technology, Germany KIT Universität des Landes Baden-Württemberg und nationales Großforschungszentrum in der Helmholtz-Gemeinschaft
2 Outline Motivation and Concept Research Group Current Status Conclusion and Outlook
3 Motivation Atmospheric water vapor (WV): Highly variable in time and space. Delays GNSS, InSAR signals Has to be accurately determined for high-precision positioning and InSAR applications (i.e. deformation measurements) Also for climate studies and weather forecasting GNSS-based WV results are limited in spatial resolution (mainly point-wise) InSAR provides an atmospheric phase image (good spatial resolution, e.g., 20m) Fusion of GNSS and InSAR measurements for water vapor determination NASA Image GNSS: Global Navigation Satellite Systems InSAR: Interferometric Synthetic Aperture Radar
4 GNSS and InSAR Precise Point Positioning (PPP) strategy is investigated Retrieval of the absolute neutrospheric delay Spatial stacking of phase residuals, necessary for eliminating MP and PCV effects Next step: Use high spatial and temporal resolution meteorological data for IPWV determination
5 InSAR Measurement of phase image Single acquisition (weeks) Large-scale measurement (area) Differential measurement (in time) Interferometric SAR: If: Earth was flat. The satellite orbit was fixed. No Deformations. Then: Atmospheric delay, simple
6 InSAR InSAR phase is given by: int where: f 1 topo 2 displ : flat Earth phase (a) (a) atm flat noise (b) topo atm displ : Topographic phase (b) : Atmospheric phase (c) : Phase due to Earth s surface displacement noise : Phase noise (c)
7 Research Group Geodetic Institute Institute of Photogrammetry and Remote Sensing Prof. Berhard Heck Dr. Michael Mayer Andreas Knöpfler Thomas Fuhrmann Xiaoguang Luo Dr. Malte Westerhaus Andreas Schenk Prof. Stefan Hinz Fadwa Alshawaf Antje Thiele GNSS Analysis InSAR Analysis Geophysical Institute Institute for Meteorology and Climate Research Atmospheric Enviromental Research Prof. Franz Meyer Prof. Harald Kunstmann Benjamin Fersch WRF Model
8 Current status GNSS data acquisition and availability Σ 75 GPS stations Germany (approx. 2002) SAPOS Baden-Württemberg SAPOS Rheinland-Pfalz BFO, BKG France (approx. 2007) RENAG RGP Teria Orpheon EOST Switzerland (approx. 2009) swisstopo
9 Current status InSAR data acquisition and availability ERS (C-Band) in Tandem images Analyze the change of atmosphere over year seasons. Envisat (C-Band) images ( 35 days apart) InSAR pairs, small spatial baselines Low activity of ionosphere Future acquisitions ALOS/PalSAR (L-Band) For Ionospheric studies TerraSAR-X (X-Band) since 2007 (shorter temporal baseline, 11 days ) Track 294 Track 294 Track 215 Track
10 Outlook Meteorological data Evaluation of the results (IPWV) WRF Model Simulations of meteorological data Temporal & spatial resolutions: 10 min,1km. Comparability to InSAR, GPS Interpolations are required Meteorological data Evaluation of the results GNSS Analysis PPP and DGPS method - determination of IPWV Inclusion of meteorological data Validation with radiometer Water vapor tomography IPWV results InSAR Analysis Extraction of suitable InSAR pairs (coherence map) Master definition, PSI investigation Estimation of atmosphere water vapor Comparability to GNSS results
11 Thank you for attention!
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