Exploitation of historical satellite SAR archives for mapping and monitoring landslides at regional and local scale

Transcription

1 Exploitation of historical satellite SAR archives for mapping and monitoring landslides at regional and local scale (A. Ferretti (TRE), A. Tamburini (TRE), M. Bianchi (TRE), M. Broccolato (Regione Valle D Aosta) & D.C.G. Martelli (Imageo) Iolanda Iannicella Venice, March 23 rd 2011 Copyright - Tele-Rilevamento Europa

2 TRE: from research to business 20 years of research in Data Signal Processing Radar Group, Eln. Dept. Politecnico di Milano. May 1999: Permanent Scatterers Technique Patent IT, EU, USA (ext. Australia, Japan) POLIMI PS Technique - PSInSAR March 2000: TRE foundation first spin-off company of Politecnico di Milano worldwide exclusive licensee of the patent June 2005: ISO 9001:2000 certification January 2008: TRE-Canada foundation. TRE expands in North America, creating a Canadian subsidiary

3 Outline Technical background: from DInSAR to SqueeSAR Precision assessment Case study: Valle d Aosta Impact of SAR data on landslide inventory projects Conclusions

4 SAR satellites to measure range data A synthetic aperture radar (SAR) works by illuminating the Earth with a beam of coherent microwave radiation such as a laser. Target: measuring the sensor-target distance Radar satellite R (sensor-target distance) = T (time tx/rx). C (light (g vel.) R Earth 4

5 How to extract info from SAR data Processing techniques for processing SAR data in order to exploit the information about surface displacement: DInSAR: Differential Interferometry, based on the comparison of a pair of radar images PSInSAR : (patented in 1999 by Politecnico di Milano) it s based on a multi-image approach in order to extract quantitative, point-wise and precise measurements of surface displacement SqueeSAR : (patend pending 2009) it s the second generation of PSInSAR analysis exploiting both point wise (permanent scatterers) and d spatially distributed ib t d scatterers (DS).

6 Basic principle 1 st acquisition 2 nd acquisition Δt = 8/11/24/35 days R1 R2 Area affected by surface deformation Detection of possible range variations ΔR

7 L Aquila, Italy - 6 Apr Cosismic Interferogram Satellite: ENVISAT Date: Bn = 148m Bt = 70gg 7

8 PSInSAR : a multi image approach time t 1 t 2 R1 R2 Rn t n ΔR12 displacement ΔR12 PS ΔR n t1 t2 tn ΔR n time

9 What is a Permanent Scatterer PS are radar targets exhibiting stable radar returns: man-made objects, pipelines, poles, outcrops,......

10 Basic info provided by PSInSAR PS Position o [m] (Lat, Lon, Height) PS Velocity [mm/yr] (Annual displacement rate) Long Beach, CA PS Time Series [mm] (Displacement acquisition per acquisition)

11 What is SqueeSAR? SqueeSAR is the sophisticated new algorithm developed by TRE A second generation PSInSAR analysis: exploiting both point wise (permanent scatterers) and spatially distributed scatterers (DS) The Basic Principle Provide information in low-reflectivity homogeneous areas previously unidentified with PSInSAR Spatial averaging g enhanced signal to noise ratio Main advantages Significantly increased number of ground measurement points identified Reduced standard deviation of time series

12 Permanent Scatterers PS Permanent Scatterers are ground points that consistently return a stable signal response to the satellite Received signal PS Signal No PS Vegetated areas do NOT produce PS Signal? Noise? Can more deformation data be extracted? Range

13 Distributed Scatterers (DS) Adjacent pixels are analysed for similar signal characteristics over the entire satellite image. Signals are averaged and applied to form a Distributed Scatterer (DS) Signal Received signal DS Range 13

14 Examples of DS Typical DS targets: Homogenous Ground Scattered Outcrops

15 Alpine area, Italy 69 RSAT images PSInSAR 15

16 Alpine area, Italy 69 RSAT images PSInSAR SqueeSAR SqueeSAR 16

17 Precision PS measurements are differential with respect to a reference radar target supposed motionless. The precision depends on # of images, PS density, climatic conditions, distance from the REF... Average Single LOS displacement Displacement Rate Measurement Precision (1σ) < 1 mm/yr ± 5 mm Typical < 1 km from the reference point, 5 year dataset

18 Precision Average Single LOS displacement Displacement Rate Measurement Precision (1σ) < 1 mm/yr ± 5 mm Typical < 1 km from the reference point, 5 year dataset

19 What is actually measured?

20 Ascending and Descending orbit N N S S Ascending Descending

21 Measurements along the Line Of Sight θ θ PS PS d PS d real d real d PS

22 Case study: Landslide Inventory in Valle d Aosta

23 Landslide inventory at regional scale: Valle d Aosta 23

24 Landslide inventory: Interferometry vs Geomorphology

25 Highway tunnel Italy

26 Verifying the effect of remedial works 26

27 Before the reactivation of the landslide (October 2000)

28 After the reactivation of the landslide ( )

29 Before and after landslide reactivation sp postamento LOS (mm m) Landslide reactivation & works ERS RADARSAT /05/90 31/01/93 28/10/95 24/07/98 19/04/01 14/01/04 10/10/06 06/07/09 01/04/12 data Courtesy Regione Valle d Aosta 29

30 Bosmatto landslide (Gressoney, Italy)

31 Bosmatto landslide monitoring system Volume: m 3 Monitoring system 7 wire extensometers 8GPSbenchmarks (manual reading). 3 GPS automatic stations 1 AWS 1 piezometer

32 Bosmatto landslide PS distribution (ESA-ERS data)

33 Traditional vs PS results October 2000 Measurements are projected along satellite LOS Courtesy Regione Valle d Aosta

34 Piano Straordinario di Telerilevamento SAR scenes PS 34

35 Conclusions 1/2 The PSInSAR TM /SqueeSAR TM technique enables to overcome the errors introduced into signal phase values by atmospheric artifacts, which typically affect the traditional i interferometric i approach The PSInSAR TM /SqueeSAR TM technique provides high precision and high areal density displacement measurements over long periods of time Two main families of targets can be recognised: point-wise targets (Permanent Scatterers, PS), where the reflected energy comes from a single or a few connected pixels, and Distributed Scatterers (DS), defined as statistically homogeneous groups of pixels in a radar image The availability of an increased number of satellite radar sensors improves spatial resolution (down to 1 m), as well as better temporal frequency of acquisition (down to a few days, rather than a monthly update);

36 Conclusions 2/2 At regional scale: integration of PS data (long term), conventional monitoring instrumentation (short term) results and landslide inventory at regional scale (geology-geomorphology) will improve: landslide areal extent evaluation unmapped phenomena detection landslide activity assessment At local scale: integration between PS and traditional ground based monitoring data allows for interpreting the behavior of landslides over long periods, supporting the design of traditional monitoring networks, and verifying the efficiency of remedial works. There is a growing number of data sources available: COSMO-SkyMed, Sk M TerraSAR-X, RADARSAT-2, ALOS-PALSAR. And, in the future, the ESA SENTINEL 1A/B mission, specifically designed for interferometric applications

37 Venice from satellite

38 Thanks for your attention!

39 Tele-Rilevamento Europa Ripa di Porta Ticinese Milano Italia www. TRE Canada Inc. # Granville Street Vancouver, BC, V6C 1T2 Canada

40 Present and Future

41 Radar satellites available ERS 1+2 Historical Analysis Monitoring Repeat Time (days) 35 Envisat 35 RADARSAT-1 RADARSAT C-band Higher res solution COSMO SkyMed 4 From 2013: Sentinel TerraSAR-X 11 X-band Present Day Future

42 Single building monitoring Milano, Duomo Venezia, La Giudecca

43 RADARSAT-1 vs TerraSAR-X PS Density y[ [PS/Km 2 ] = 132 PS Density y[ [PS/Km 2 ] =

44 Time Series comparison zoom RADARSAT-1 (1 img every 24dd) TerraSAR-X (1 img every 11dd) 44