Strategies for Measuring Large Scale Ground Surface Deformations: PSI Wide Area Product Approaches

Transcription

1 Strategies for Measuring Large Scale Ground Surface Deformations: PSI Wide Area Product Approaches J. Duro (1), R. Iglesias (1), P. Blanco-Sánchez (1), D. Albiol (1), T. Wright (2), N. Adam (3), F. Rodríguez (3), R. Brcic (3), A. Parizzi (3), F. Novali (4), P. Bally (5) (1) (2) (3) (4) (5)

2 Outline Motivation Terrafirma Project Wide Area Product (WAP) PSI processing for WAP PSI Processing for each individual track/frame Data merging Parallel Tracks Calibration Performance Analysis and Discussion Multi-seed Impact Phase noise impact APS impact Persistent scatterers spatial distribution Calibration and final results Conclusion and future work

3 Outline Motivation Terrafirma Project Wide Area Product (WAP) PSI processing for WAP PSI Processing for each individual track/frame Data merging Parallel Tracks Calibration Performance Analysis and Discussion Multi-seed Impact Phase noise impact APS impact Persistent scatterers spatial distribution Calibration and final results Conclusion and future work

4 Motivation Terrafirma Project Terrafirma is a pan-european Terrain Motion Hazard Information Service Terrafirma was started in 2003 by NPA Group. The 3 rd Stage of the project was led by Altamira Information. Terrafirma is an open service partnership where competitor providers work together to produce a standardised and validated advanced products and services. Terrafirma services have been delivered to over 90 users via a Service Level Agreement, which includes User Feedback and Utility reports. The Terrafirma service offering includes the wide-area map designed to enable the delivery of seamless motion maps over wide areas utilising the Sentinel-1 satellites. Terrafirma services help to identify and mitigate risk

5 Motivation Wide Area Product Possible definitions WAP? A) Multi PSI 1 or + frames at F.R. & F.W. 1 or + clusters of points linked to a ref. Delivered as independent DB PSs repeated at overlapping regions? What s the difference w.r.t classical PSI approach? B) Wide area PSI 2 < frames at F.R. & F.W. Calibrated with or without GPS (offsets?, ramps?) Unique reference point? Unique DB (without PSs overlap)? Measure large-scale motions (plate tectonics)? C) Others. GREECE 10 frames (GPS calibrated) WAP product definition is linked to the objectives Different options can be found

6 Outline Motivation Terrafirma Project Wide Area Product (WAP) PSI processing for WAP PSI Processing for each individual track/frame Data merging Parallel Tracks Calibration Performance Analysis and Discussion Multi-seed Impact Phase noise impact APS impact Persistent scatterers spatial distribution Calibration and final results Conclusion and future work

7 PSI Processing for WAP Large AOI to be covered Larissa Orbit Tracks - 64 ERS1&2 SAR images Differential Interferograms Volos Orbit Track - 74 ERS1&2 SAR images Differential Interferograms N 0m 45km 90km

8 PSI Processing for WAP PSI Processing for each individual track/frame + merging Larissa Frame Calibrated Joint Displacement Map seed Volos Frame Deformation rate [mm/y] seed Calibration by means of Common area Statistics

9 PSI Processing for WAP Possible final product Altamira Information WAP PSI over Larissa and Volos Tracks Unique reference point Full swath at full resolution Millions of measurement points in the DB Deformation rate [mm/y] Track merging without overlap

10 PSI Processing for WAP Can we trust large scale motion trend retrieved by WAP PSI? Altamira-Information WAP PSI over Larissa and Volos Tracks aquifer aquifer landslides Deformation rate [mm/y]

11 Outline Motivation Terrafirma Project Wide Area Product (WAP) PSI processing for WAP PSI Processing for each individual track/frame Data merging Parallel Tracks Calibration Performance Analysis and Discussion Multi-seed Impact Phase noise impact APS impact Persistent scatterers spatial distribution Calibration and final results Conclusion and future work

12 Performance Analysis and Discussion Development of a simulator for performance tests Phase Noise Impact Residual Orbit Impact APS impact PSC density Network construction Simulated Large-Scale Velocity Δvi αi αi Interf Gen Temp & Spat Baselines PSI Single or multi-seed Plane Adjust. Δvo αo Residue

13 Performance Analysis and Discussion Multi-seed Impact Simulated velocity PSI Velocity (1 seed) PSI Velocity (6 seeds) Difference seed seed Differents offsets between clusters seed Inci = 2 cm/year αi = 7 degrees seed seed seed seed -1cm/y 1cm/y -1cm/y 1cm/y -1cm/y 1cm/y -1cm/y 1cm/y 1 seed is mandatory to measure large scale motion trends

14 Performance Analysis and Discussion Phase noise impact Interferometric Phase Noise Values Coherence VS Phase Stdev Estimated Plane Characteristics HIGH AGREEMENT GOOD AGREEMENT LOW AGREEMENT Simu Velocities Δv i 2.0 cm/y Δv i 1.5 cm/y Interf Gen Δv i 0.5 cm/y Interf Gen Interf Gen + PSI Estimated Plane PSI Velocity Δvo ramp increment [cm/y] α o ramp orientation [cm/y] Coherence Coherence Strong phase noise is required produce an impact

15 Performance Analysis and Discussion Residual orbit impact Simulated Velocity Simulated Orbital Ramp PSI Velocity Residue Est. Plane 150 Temporal Distribution Δv i 2 cm/year α i 7 deg. # Interf Δv o 2.3 cm/year α o 8 deg. 0-1cm/y 1cm/y Acquiston date -1cm/y 1cm/y -1cm/y 1cm/y -0.3cm/y 0.3cm/y -1cm/y 1cm/y orbit inaccuracies only in one SLC appearing in 10 interferograms Residual ramp 3mm/y + 1 o error Orbit state vectors inaccuracies have an important impact on the measurements of large scale motion trends

16 Performance Analysis and Discussion Residual orbit compensation Possible Strategies Original Interferf Est. Residual Orbit Compensated Interf. - First order de-trending by means of range and azimuth FFT analysis. - Second order orbit inaccuracies compensation. - Phase model fit to carry out a correction of the orbit state vectors - When large-scale motion is expected, distinguishing between displacement signals and phase patterns due to orbit inaccuracies is a key issue

17 Performance Analysis and Discussion APS impact LOW APS TURBULENCE MEDIUM APS TURBULENCE HIGH APS TURBULENCE Simulated velocity PSI velocity Residue Modulus PSI velocity Residue Modulus PSI velocity Residue Modulus Estimated Plane Δv i = 2 cm/year α i = 7 degrees High residue Δv o = 2.4 cm/year α o = 5 degrees -1cm/y 1cm/y -1cm/y 1cm/y 0 cm/y 0.3 cm/y -1cm/y 1cm/y 0 cm/y 0.3 cm/y -1cm/y 1cm/y 0 cm/y 0.3 cm/y -1cm/y 1cm/y Perfect Performance! Good Performance! Bad Performance in areas with steep topography Atmospheric signal delays originate important local residuals which decreases the accuracy in trends retrieval

18 Performance Analysis and Discussion APS compensation APS model from global meteorological data (ERA-I from the ECMWF) APS model fitted from interferometric phases APS estimated inside the PSI processing by the application of several filters LOW APS TURBULENCE Original Interf. APS model HIGH APS TURBULENCE Comp. Interf. Orig. Interfef. APS model Comp. Interf.

19 Performance Analysis and Discussion Persistent scatterers spatial distribution Simulations made with medium APS turbulences (gave good performance in previous tests) High density Mid density Low density Medium APS turbulences PSI velocity PSI velocity PSI velocity PSI velocity Residue Modulus Δv i = 2 cm/year α i = 7 degrees + APS -0.3cm/y 0.3cm/y -0.3cm/y 0.3cm/y -0.3cm/y 0.3cm/y -1cm/y 1cm/y 0 cm/y 0.3 cm/y

20 Performance Analysis and Discussion Persistent scatterers spatial distribution High density Mid density Low density Residue Modulus Residue Modulus Residue Modulus Model Coherence Δv i = 2 cm/year α i = 7 degrees + APS Model Coherence in large links decrease due to APS 0cm/y 0.3cm/y 0cm/y 0.3cm/y 0cm/y 0.3cm/y Higher density is required if APS compensation is made inside PSI processing Accurate processing with low density can be only achieved by using external data (APS model, GPS)

21 Outline Motivation Terrafirma Project Wide Area Product (WAP) PSI processing for WAP PSI Processing for each individual track/frame Data merging Parallel Tracks Calibration Performance Analysis and Discussion Multi-seed Impact Phase noise impact APS impact Persistent scatterers spatial distribution Calibration and final results Conclusion and future work

22 Summary and conclusions Different processing options can be adopted to achieve wide area coverage Main difference resides in keeping one unique reference or not for all the PS measurements Processing with a unique reference and tracks calibration are compulsories for large scale motion trends retrievals Orbit state vectors inaccuracies have the greatest impact on the accuracy of large scale motions Atmospheric perturbations originate more local errors which can also reduce the accuracy over large scale (depending on the unwrapping strategy) High PS density allows to overcome rapid phase variations Low density of PSs have an important impact on the measurement of large scale trends: Require the use of external data: Numerical models to generate the APS a priori and/or GPS data for cluster calibration Advance phase filtering strategies or more redundancy on the PS network configuration are required In case of high quality data (high density PSs, a lot of interferograms, good orbit state vectors) large scale motion trends can be measured with good accuracy

23 Open questions for the RT What should be the scope of WAP? It is really needed Wide Area Product at full resolution? It is required to have a unique spatial reference? What is the benefit of Sentniel-1 for WAP? What is the accuracy and the robustness of the numerical weather models for based APS compensation on this automatically? Can we achieve a good spatial resolution with this model based data for a proper correction of the local turbulences? Can we perform PSI clusters calibration with available GPS data? Can GPS network provide a good density to calibrate PSI WAP data? It is precise enough for LOS calibration? question and suggestions are welcome THANKS FOR YOUR ATTENTION!