Integration between spaceand ground-based data sets: application on ground deformations measurements

Transcription

1 Integration between spaceand ground-based data sets: application on ground deformations measurements Giuseppe Puglisi Istituto Nazionale di Geofisica e Vulcanologia Sezione di Catania Osservatorio Etneo This work has been carried out in cooperation with: F. Guglielmino (INGV, Sezione di Catania Osservatorio Etneo) G. Nunnari (Dip. IEES; Univ. di Catania) A. Spata (GE Transportation)

2 Outline > Rationale > Methodology > Synthetic test > Applications: Test Cases Etna volcanic sources earthquakes L Aquila: earthquake > Conclusive remarks

3 Rationale

4 GEO WORK PLAN > Task DI-01: Informing Risk Management and Disaster Reduction Component C2: Geohazards Monitoring, Alert, and Risk Assessment. Priority Actions. Apply a fully integrated approach to geohazards monitoring, based on collaboration among existing networks and international initiatives, using new instrumentation such as in-situ sensors, and aggregating space (radar, optical imagery) and ground-based (subsurface) observations. Develop open comprehensive natural-hazards datasets, initially focusing on selected targets (e.g. Supersites).

5 Integration between Space- and Groundbased deformation measurements Geodetic Techniques (GPS, levelling, tilt) DInSAR Time Space From Low to High temporal resolution Point-wise measurements Low temporal resolution Spatial distributed Type From 1D to 3D 1D (LOS) Integration: merging from multiple data sets to an unique data sets ( common visualization) Goal: To take advantage of their complementary nature to obtain: - a continuous 3D deformation map - the complete strain tensor information

6 Methodology

7 Different approaches Gudmundsson et al. (2002) GPS data DInSAR Data Kriging Interpolation Random Markow Field Theory Simulated Annealing Optimization 3D Deform. No strain Samsonov, Tiampo et al. (2006) GPS data DInSAR Data Kriging Interpolation Analytical Optimization 3D Deform. No strain Guglielmino, Nunnari, Puglisi, Spata (2011). SISTEM GPS data DInSAR Data Modified Weighted Least Squares 3D Deform. & Strain

8 The concepts of the SISTEM algorithm Small Deformation Theory Let x o (x 10, x 20, x 30 ) the position of an arbitrary point P surrounded by N points whose position and displacements are respectively x (n) =(x 1(n), x 2(n), x 3(n) ) and u (n) =(u 1(n),u 2(n), u 3(n) ). In a linear approach the small motions around a point P can be modelled by the N equations: ui( n) = Hij x j( n) + U i ( i, j = 1..3) Displacement gradient jui H ij = = Eij + Ω ij u i j Relative position x = x x j( n) j( n) j0 Strain tensor E = ε ij = 1 ( H 2 ij + H ji ) e i e j ε = ε ε ε ε ε ε ε ε Rigid body rotation tensor Ω = ω ij = 1 ( H 2 ij H ji ) e i e j 0 = ω3 ω2 ω 0 ω 1 3 ω2 ω 1 0

9 The concepts of the SISTEM algorithm We assume the Small Deformation Theory, as the mathematical model, and use of the WLS algorithm for searching the parameters of the model. It allows: - To simultaneously define the whole set of parameters - To estimate the internal accuracy of parameters (Variance-Covariance Matrix) - To estimate the whole information about the strain (Strain & Rigid Body Rotation Tensors)

10 Synthetic test

11 The synthetic test Pressure point source (Mogi source) Topography of a synthetic volcano 2 3/ ) ( 4 3 d f d P a x + = µ 2 3/ ) ( 4 3 d f f P a z + = µ Experimental conditions µ=30 GPa ; d=5000m ; a 3 P=10 17 Pa*m 3 Volcano & pressure source ( ) ( ) ( ) w y x e z y x z / 0 2 2, + =

12 The synthetic test East North Up DInSAR Synthetic deformations maps and Experimental Points (EP) Integrated displacements components (SISTEM) Residuals (l), (m), (n): normalized histograms of the corresponding residuals errors, the mean value and standard deviation.

13 The synthetic test Dilatation differential rotation magnitude maximum shear strain Errors as a function of the number of EP (Experimental Points) The accuracy decrease, as the number of GPS points increase (negligible when EP > 50-70) Vertical accuracy is better than the Horizontal accuracy.

14 Test Case: Mt. Etna GPS & 1 DInSAR Monday, 16 September 2013

15 Etna eruption GPS data + DInSAR Data Type of Geohazard: eruption Source of deformations: magmatic intrusion (dyke) Date of the event: 13 May 2008 Data set: - ~ 60 GPS benchmarks and permanent stations - 1 DInSAR deformation map (ENVISAT) - from June 2007 to May 2008 SISTEM = 3D Surface Motion Map

16 Results of the integration East North Up Errors (cm) displacements (cm)

17 Results of the Integration but SISTEM allows investigating also the strain tensor; two invariants: Volumetric Dilatation Maximum shear These results, which provide both accurate and fine spatial characterization of ground deformation, are hence promising for future studies aimed at improving the knowledge of the dynamic of the Mt. Etna.

18 Test Case: L Aquila Earthquake GPS & > 1 DInSAR Monday, 16 September 2013

19 L Aquila Earthquake GPS data + ALOS Ascending Interferogram + ENVISAT Ascending Interferogram + ENVISAT Descending Interferogram Type of Geohazard: earthquake Source of deformations: fault/s Date of the event: 6 April 2009 Data set: - 75 GPS benchmarks and permanent stations - 3 DInSAR deformation maps (ENVISAT, ALOS) - from April 2008 to May 2009 SISTEM = 3D Surface Motion Map

20 Results of the integration 3D displacement components. max lowering 250 mm Associated standard error. Horizontal error < 15 mm Vertical error < 2.5 mm. 3D strain invariants. F. Colle Praticciolo F. Colle Praticciolo F. del Pettino F. del Pettino F. Di Paganica F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Colle Praticciolo F. Colle Praticciolo F. del Pettino F. del Pettino F. Di Paganica F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Colle Praticciolo F. Colle Praticciolo F. del Pettino F. del Pettino F. Di Paganica F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Colle Praticciolo F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Colle Praticciolo F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Colle Praticciolo F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. del Pettino F. del Pettino F. del Pettino

21 SISTEM results 3D components analysis F. Colle Praticciolo F. Colle Praticciolo F. Colle Praticciolo F. del Pettino F. del Pettino F. Di Paganica F. Di Paganica F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra ROIO CANETRA MT. OCRE FAULT FAULT The cross section show a complex MONTICCHIO-FOSSA FAULT PAGANICA FAULT kinematics whit a main displacements of of the Paganica fault, and involvement of several structure est nord up On the north-east area is evident an increase of the northward motion confirmed by the the GPS velocity field F. del Pettino

22 SISTEM results 3D strain analysis F. Colle Praticciolo F. Colle Praticciolo F. Colle Praticciolo F. del Pettino F. del Pettino F. Di Paganica F. Di Paganica F. Di Paganica F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra F. Di Mont.-Fossa F. Di Bazzano F. Roio-Canetra MT. OCRE FAULT ROIO CANETRA FAULT PAGANICA FAULT Dilatation Diff_rotation Max Shear The 3D strain analysis evidence a strong dilatation between the Paganica and Roio Canetra Fault associated whit a Max Shear Strain located along the Monticchio-Fossa fault. It is noteworthy a compression corresponding to the Paganica fault trace MONTICCHIO-FOSSA FAULT F. del Pettino

23 Test Case: Etna Earthquake GPS, Leveling & > 1 DInSAR

24 Etna Earthquake Levelling data + GPS data + ENVISAT Ascending Interferogram + ENVISAT Descending Interferogram + 2 ALOS Ascending Interferograms Type of Geohazard: earthquake Source of deformations: fault/s Date of the event: 3 April 2010 Data set: 35 GPS benchmarks and permanent stations - 4 DInSAR deformation maps (ENVISAT, ALOS) - 1 levelling line (20 benchmarks) - from October 2009 to May 2010 SISTEM = 3D Surface Motion Map

25 DInSAR Satellite Data ENVISAT data We analyzed : the ascending pair related to 07/10/ /05/2010 and the descending pair related to 18/11/ /04/2010 time interval The ENVISAT images show the general seaward movement of the eastern flank of Mt. Etna well. They also show very intense but local LOS displacements on the ENVISAT ascending interferogram and a lower variation for the descending geometry Indeed, both vertical (lowering) and horizontal (eastwards) components of motion on the southern side of the fault, produce a strong lengthening of the LOS distance for ascending geometry, while the two components act in opposite ways for the descending geometry, resulting in lower LOS distance variations compared to the ascending data set The differences in the LOS displacements between ascending and descending geometry, are probably due to the oblique normal/left-lateral kinematics of the PFS (as deduced also by GPS and leveling data

26 DInSAR Satellite Data ALOS data We analyzed two frames covering two adjacent tracks (track 637 and 638), both along ascending path, referring to 21/02/ /04/2010 (track 637) and 22/03/ /05/2010 (track 638). It is worth noting that the deformation patterns, are the same for the two tracks. In particular, a deformation of about 23 cm in the LOS of PALSAR has been measured. The ALOS images confirmed a strong ground deformation in the near field of the fault, rapidly decreasing on moving away from it. This pattern is not imaged by ENVISAT ascending data because it exceeds the ASAR maximum detectable deformation gradient for C-band frequency, which is 1.4 cm per pixel. LOS deformation of about 23 cm, detected by ALOS, is due mainly to the horizontal component because the maximum vertical displacement measured by leveling data is only of 7cm.

27 Comparison Levelling & LOS ENVISAT In order to compare the SAR data with the in situ measurements, we extracted LOS displacements of those pixels closest to the leveling benchmarks; in Figure the vertical displacements measured by leveling are plotted together with the ascending LOS displacements of their nearest pixels. The plot shows a very good agreement between the two datasets, and as expected the magnitude of the LOS displacements is higher due to the contribution of the eastward motion of the southern side of the fault. Finally, both leveling and DInSAR data confirm that an intense local deformation episode occurred very close to the PFS, affecting a narrow strip ( 500 m) along the southern side of the fault.

28 SISTEM Results The 3D components analysis shows a maximum eastward movement (370 mm) associated with maximum relative vertical displacements (70 mm) in a narrow area along the PFS. The cross sections indicate the strong displacements occurring very close to the PFS and, on its southern side, the widespread ESEward motion of the eastern flank of Mt. Etna. Furthermore, the three cross sections highlight the opposite movement of the fault hanging wall (generally trending south) with respect to the footwall, due to the elastic rebound of the PFS involved by earthquakes.

29 Conclusive Remarks

30 Conclusive remarks - 1 Geodetic and DInSAR integration based on small deformation theory Geodetic and DInSAR data are simultaneous integrated without the preliminary step of the Kriging interpolation Products: Deformation field and relevant standard errors Strain tensor and relevant standard errors Rigid body rotation tensor and relevant standard errors The SISTEM method was applied effectively on areas where the geodetic networks (GPS, leveling) well cover the area and frequent SAR passes are available.

31 Conclusive remarks - 2 Future developments (within MED-SUV): To include different kind of geodetic data, such as EDM, Tilt To apply the algorithm to the time series (both GPS and DInSAR) To use the SISTEM to optimize the configuration of the ground-based networks and/or for the tasking of future EO missions To optimize the algorithm for a semi-automatic processing (from supervised to nearly-unsupervised processing)

32 References Bonforte A., Guglielmino F. and Puglisi G., Interaction between magma intrusion and flank dynamics at Mt. Etna in 2008, imaged by integrated dense GPS and DInSAR data. Bull. Volcanol., in print. Guglielmino F., Anzidei M., Briole P., Elias P. and Puglisi G. (2012). 3D displacement maps of the 2009 L Aquila earthquake (Italy) by applying the SISTEM method to GPS and DInSAR data. Terra Nova, Vol 00, No. 0, 1 7. doi: /ter Guglielmino F., Bignami C., Bonforte A., Briole P., Obrizzo F., Puglisi G., Stramondo S. and Wegmuller U. (2011). Analysis of satellite and in situ ground deformation data integrated by the SISTEM approach: The 3 April 2010 earthquake along the Pernicana fault (Mt. Etna - Italy) case study. Earth Planet. Sci. Lett., 312, Guglielmino F., Nunnari G., Puglisi G. and Spata A. (2011). Simultaneous and integrated strain tensor estimation from geodetic and satellite deformation measurements to obtain three-dimensional displacement maps. IEEE Trans. Geosci. Remote Sens., 49, Thanks for your attention