CSK AO project workshop. AO CSK 3655 Continuous subsidence monitoring employing Cosmo-Skymed constellation.

Transcription

1 CSK AO project workshop AO CSK 3655 Continuous subsidence monitoring employing Cosmo-Skymed constellation. Pablo Blanco Sánchez, Roman Arbiol, Fernando Pérez Roma 8/5/11

2 Outline Project objectives Data description. Comments on Baselines distribution. Cosmo-Skymed for DInSAR deformation monitoring: Single interferograms (vs. Envisat) Persistent scatterers (vs. Envisat) Conclusions, future work and recommendations.

3 Project main objectives Analyze CSK data for Persistent Scatterers deformation monitoring. Performance/improvements w.r.t Envisat data. CSK performances in a regional subsidence monitoring project. Catalonian government project in partnership with the geological survey of Catalonia (IGC). 3

4 Project s data Data obtained: 1 Stripmap Bages area [June 1, December 11] 19 Stripmap Barcelona area [July 1,January 1] 3 Stripmap Girona area [May 1, February 1] Stripmap Tarragona area [May 1, February 1] Number of images < 5 per frame, coherence approach. Low baseline approach in order to avoid geometrical decorrelation. CSK large orbital tube. 4

5 CSK data coverage 5

6 Bages 8 Distribucio espacio-temporal 18 Baseline distribution Bncrit = 497 m Baseline (m) 4 % interferograms Bn (meters) Baseline distribution Bncrit = 497 m Temps (anys) Temporal distribution % interferograms % interferograms Bn (meters) T (days) 6

7 Girona 14 Distribucio espacio-temporal Baseline distribution Bncrit = 39 m Baseline (m) % interferograms Bn (meters) - 5 Baseline distribution Bncrit = 39 m -4-6 % interferograms Temps (anys) Temporal distribution T (days) % interferograms Bn (meters) º incidence angle, lower critical baseline, rejection of some interferograms. 7

8 Underground mining subsidence monitoring Case study: Surface subsidence monitoring caused by underground potasic mining activities. Single interferogram along time approach due to temporal decorrelation. Fringe pattern correlated with mine exploitation. Low spatial baselines required. 8

9 Underground mining subsidence monitoring 1 tall def. filtre mitjana, th =.33,size filt = Envisat 5 CSK ( days) azimuth 16/3 days good compromise movement magnitude vs. temporal decorrelation. Spatial resolution improvement, better spatial pattern detection. No large and frequent images stacks needed but low baselines pairs required 9

10 Single interferogram analysis High resolution/wavelength sensitivity allows to detect high spatial deformation gradients 1

11 Persistent Scatter DInSAR Large spatial deformation pattern, spatial averaging may cause magnitude understimation. CSK vs. Envisat: Increasing of useful points. Improvement of the deformation pattern retrieval. Structure damage identification. 11

12 Persistent Scatterers DInSAR x utm = 48646, y utm = , coher =.3, vel = -.48 cm/a temps (a) x utm = 4836, y utm = , coher =.3, vel = -.74 cm/a temps (a) x utm = 4851, y utm = 4631, coher =.43, vel = cm/a temps (a) x utm = 48578, y utm = , coher =.34, vel = -.43 cm/a temps (a) x utm = 48476, y utm = 46393, coher =.7, vel = -3.3 cm/a temps (a) 1

13 Persistent Scatterers DInSAR 13

14 Persistent Scatterers DInSAR 14

15 Persistent Scatterers DInSAR x utm = 48398, y utm = , coher =.57, vel = -.68 cm/a temps (a) x utm = 48, y utm = , coher =.46, vel = -.56 cm/a temps (a) x utm = 4811, y utm = , coher =.56, vel = -.49 cm/a temps (a) x utm = 4811, y utm = , coher =.58, vel = -.46 cm/a temps (a) 15

16 Barcelona CSK AO project wokshop. Rome March 1 16

17 Airport 17

18 Delta Industrial area 18

19 Conclusions/Recommendations Still work to do to analyze all data Csk: High resolution + X band + higher repeat time, improvement on the density of coherent pixels, improvement of the results and interpretation of phenomena. At least our geologist colleagues are happy with that. New phenomena is observed, surface + structural deformation, refinement of the models? e-geos: Two years gap Interferometric dataset reduced price. Something similar for several frames within a regional framework? Baseline information on catalogue data to select suitable data. 19