PCI Geomatics Synthetic Aperture Radar Processing Capabilities

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Overview of PCI's software capability for working with SAR imagery

Overview of PCI's software capability for working with SAR imagery

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  • 1. Synthetic Aperture Radar (SAR) PCI expertise and capabilities January 2013
  • 2. 70 + Employees > 25,000 licenses installed worldwide HQ: Toronto Awards & Accolades Offices in: Innovation Awards Gatineau, for60 Resellers USA, ChinaWorldwide GXL Geomatica
  • 3. WHERE DOESPCI GEOMATICSFIT
  • 4. GEOSPATIAL VALUE CHAINImage Image Pre- Image Tools & Value-AddedCollection Processing Processing Work Flow Content Selected CapabilitiesSatellite Orthorectification Image Extraction Display , Storage and Google Maps/Earth DisseminationSAR (Radar) Atmospheric Spatial Analysis Microsoft Bing Maps correction Ingestion ToolsLIDAR Image Classification Location Based Services Image Mosaiking Enterprise IntegrationAirborne Camera Customized Vertical Applications – Pan Sharpening Algorithms Open Source natural resource,Other Image Sensing Development weather, land planning, etc. Selected Competitors/PartnersDigital Globe PCI Geomatics PCI Geomatics PCI Geomatics Google / Yahoo / MicrosoftVexcel / Microsoft ERDAS (Leica) Definiens AG ESRI / Intergraph ESRI / IntergraphGeoEye ENVI (ITT) ERDAS (Leica) Pixel Factory Vertical Applications (e.g., (InfoTerra) RapidEye for Agriculture and ENVI (ITT) Iunctus for Oil and Gas) Page 4
  • 5. WHAT MAKESPCI GEOMATICSDIFFERENT
  • 6. We provide…Powerful and scalable image processing solutions that let you quickly and efficiently produce informationproducts from any type of imagery SCALABLE TO WE ARE UNMATCHED ANY SIZE SENSOR AUTOMATED PROJECT AGNOSTIC WORKFLOWS BUILDING HIGH SPEED ADVANCED SOLUTIONS MULTI FOR RADAR CPU / GPU CAPABILITY 30 YEARS
  • 7. WHICH SOLUTION IS RIGHT FOR YOU? $1M $500Price($000’s) $200 $10 10 GB 100 GB 500 GB 1 - 5TB 5 - 10TB Page 7
  • 8. PCI – SAR technology development Canada has been an innovator in SAR data acquisition and processing since the early 1980s – PCI has been involved since the beginning PCI Geomatics participated in GlobeSAR program, delivered training and software PCI Geomatics developed technology through Canadian Government (SAR Polarimetry Workstation) PCI Geomatics works with multi-sensor SAR imagery Page 8
  • 9. SAR Sensor Support RADARSAT 1 & 2 TerraSAR-X Cosmo-SkyMed, UAVSAR PALSAR ASAR ERS 1 & 2 Page 9
  • 10. Generic SAR Capabilities Support for Single, Dual, Quad, Data Automatic Calibration* Automatic Geocoding* Speckle Filtering (many) Statistical & Analysis Capabilities Ortho-rectification, Integration and Visualization with Optical Data * If available Page 10
  • 11. Generic SAR Capabilities Supported Calibration Types • Sigma, • Beta, • Gamma, • None Multi-Channel Representations • Scattering • Covariance • Coherence • Kennaugh Page 11
  • 12. Advantages for applications Key Advantages of Commercial Radar Imagery – Data collections are independent of lighting and cloud conditions – Frequent imaging supports routine change detection – Provides effective wide area (100 –500+ km swath) coverage – A variety of information is contained in the return signal that can be extracted Key Maritime Missions: – Large Area Maritime Domain Awareness – Efficient Tasking of Patrol Assets – Monitoring Port Activity Key Terrestrial Missions: – Change Detection – Disaster Response – DEM Generation Page 12
  • 13. Application examples Change Detection Page 13
  • 14. Change Detection Methods1. Amplitude Change Detection2. Coherence Change Detection3. Polarimetric Analysis and Change Detection Page 14
  • 15. 1. Amplitude Change Detection Different sensors / beam modes / resolutions can be used in combination Revisit is more important in this case than matching geometry Presence / absence of features readily observed Page 15
  • 16. Change Detection Results Phoenix AirportSunday May 4, 2008
  • 17. Change Detection Results Phoenix AirportWeds. May 28, 2008
  • 18. Detected ChangesPhoenix Airport Change Map May 4 , 2008 May 28, 2008
  • 19. 2. Coherent Change Detection Measures phase differences in SAR signal Geometry must be matching (repeat pass) Multiple collections over same area from different sensors/orbits can be combined Page 19
  • 20. Coherent Change DetectionChange inCoherence (phase)Image 1 Page 20
  • 21. Coherent Change DetectionChange inCoherence (phase)Image 2Acquired 11 min. later Page 21
  • 22. Coherent Change Detection Loss of Coherence is indicated by Dark ColourNote:Loss of Coherence for Trees Page 22
  • 23. Cross Sensor Change Detection Sample CCD over Flevoland TerraSAR-X and RADARSAT-2 acquisitions Two sets of repeat pass collections PCI Technology used to achieve high cross-sensor image registration Page 23
  • 24. Flevoland, May 07/2010 RADARSAT-2 Total Power Page 24
  • 25. Flevoland, May 07/2010 RADARSAT-2 Total Power Page 25
  • 26. Cross Sensor Change Detection (May 04 - May 07, 2010)Optical (Google Map™) TSX-1/RSAT-2 Change Map Page 26
  • 27. Cross Sensor Change Detection (May 04 - May 07, 2010)Target May 04 TSX-1/RSAT-2 Change Map Page 27
  • 28. Cross Sensor Change Detection (May 04 - May 07, 2010)No Target May 07 TSX-1/RSAT-2 Change Map Page 28
  • 29. Cross Sensor Change Detection (May 04 - May 07, 2010)No Target May 04 TSX-1/RSAT-2 Change Map Page 29
  • 30. Cross Sensor Change Detection (May 04 - May 07, 2010) TSX-1/RSAT-2 Change MapOptical (Google Map™) Page 30
  • 31. Cross Sensor Change Detection (May 04 - May 07, 2010)Optical (Google Map™) TSX-1/RSAT-2 Change Map Page 31
  • 32. Application examples Ship detection (polarimetry) Page 32
  • 33. 3. Polarimetric Analysis and Change Detection Basics of Polarimetry Polarimetric information for ship dectection Page 33
  • 34. Some Polarimetric Basics VFor a singlepolarization, thereturn isproportional to thetarget crosssection. HFor HH we wouldget a returnindicated by red.For VV it would beblue. So the amount of return we get depends on target orientation and polarization Page 34
  • 35. Some Polarimetric Basics VFor a singlepolarization, thereturn isproportional to thetarget crosssection.For HH we would Hget a returnindicated by red.For VV it would beblue. So the amount of return we get depends on target orientation and polarization Page 35
  • 36. Some Polarimetric Basics X Polarimetric radar data provides full scattering information in the direction of the line of sight Y Y X We want to compare these targets. Page 36
  • 37. Some Polarimetric Basics Polarimetric radar data provides full scattering information in the direction of the Y line of sight Y H X Y X H We can do some fancy arithmetic and rotate the scattering matrix until we get a maximum X and a minimum Y. Then we can compare their properties. Page 37
  • 38. Non-polarimetric Parameters Time 2001-02-30 12:34:56 GMT Position: 12:01:21.58 N 34:14:43.37 W Incidence Angle: 27.15° Estimated Length: 226 m Estimated Heading: 260° Estimated Velocity: 9.70 m/s Page 38
  • 39. Polarimetric Processing Steps Ingest Full Polarimetric Data (Optionally) calibrate to σ Apply multi-channel speckle filter Decompose (Cloude-Pottier) image into (16) polarimetric classes Iterate (3-5 times) to enhance classification and remove outliers Exclude pixels from the largest class (which will be water) Generate land mask * Generate polarimetric parameters using FOCUS, SPW and SPTA from remaining (non-masked) pixels Page 39
  • 40. Example Polarimetric Ship Analysis Page 40
  • 41. Polarimetric InformationMaximum of the degree of polarization: 0.7916655Minimum of the degree of polarization: 0.09595539Maximum of the completely polarized component: 2.520944Minimum of the completely polarized component: 0.2940039Orientation of Maximum Polarisation 70Ellipticity of Maximum Polarisation -5Maximum of the completely unpolarized component: 2.769960Minimum of the completely unpolarized component: 0.6619406Maximum of the scattered intensity: 3.210612 LLMinimum of the scattered intensity: 2.850842Coefficient of Variation: 0.1160221Fractional Power: 0.7920792 HH VVPedestal Height 1.318336HH / HV Ratio 4.014223HH / HV Correlation 0.2035844 RRHH / VV Ratio 0.9518262 Page 41HH / VV Correlation 0.3857002
  • 42. Polarimetric Signature Information V LL 5° Ellipticity 70° Orientation H VVMaximum Return V LL RR Secondary HH Return Max Return H - 20° OrientationStrong Secondary Return Page 42 RR
  • 43. Power DistributionBy Polarization HH HVVVBy Type Double DiffuseSurfaceBy Scatterer Primary SecondaryTertiary
  • 44. Polarimetric Decompositions Cloude-Pottier Target Average % High % Medium % Low Entropy 0.8480822 2.253302 76.30148 21.44522Anisotropy 0.5064220 55.63326 44.36674Alpha Angle 43.200062 27.50583 30.53613 41.95804 Touzi (ICTD)Target Tilt Dominant Eigen Symmetric Symmetric Helicity Angle Value Scattering Type Scattering Type (Symmetry) (deg) Magnitude Phase (deg)-27.432373 0.5600992 10.467688 -50.483246 5.841676 van Zyl % Unclassified % Odd % Even % Diffuse 1.892744 48.264984 23.343849 26.498423 Page 44
  • 45. van Zyl Decomposition Radar Measurement Physical Meaning Odd Number Bounce Flat Surface Even Number Bounce Superstructure Diffuse Scattering Complex / Random Page 45
  • 46. Symmetric Scattering Decomposition Trihedral (odd number of bounces) Cylinder (weak return in one direction) Dipole (no return in one direction) Quarter Wave (delay in second direction) Dihedral (even number of bounces) Narrow Dihedral (with one direction attenuated) Page 46
  • 47. Classification based upon Polarimetric Signatures ?1-56 - 1011 - 1516 - 20
  • 48. Classification based upon Polarimetric Signatures ?1-56 - 1011 - 1516 - 20
  • 49. Polarimetric Power Distribution Comparison Polarization Type Scatterer Page 49
  • 50. Application examplesDigital Elevation Extraction Page 50
  • 51. Multi-Channel InputHHHV SpanVHVV
  • 52. Stereo DEMs Find highest correlation within search window R1R2Compute Stereo Intersection Generate DEM
  • 53. Geometric Problem Intermediate Angle What the Radar Sees
  • 54. Geometric Problem Shallow Angle
  • 55. Stereo DEMs All or Maximum Overlap Next Pair Image match based upon Power Linear or Decibels Image A Image B No Overlap, Look Direction Angular Difference Suitable Pair ? Downsample Image A Downsample Image B to User Specs to Epipolar Image ASpacing Affects DEM Detail Level Extract Window Area Extract Search Area Ignore Background Find Common Points (No Data) Pixels Stereo Intersection Store Elevation No Last Pair ? Blend Overlap Areas Last, Average, High Score Arbitrate Values Write Failed Value where Fill Gaps/Holes “gaps” remain Remove “buildings “ * Write Final DEM
  • 56. Suggestions for Selection of Stereo PairsSelection of Stereo Image Pairs Candidate pair should have more than 50 % overlap Candidate pair should have nominally the same resolution Best results obtained from same-side (i.e., descending/descending or ascending/ascending) image pairs Candidate pair should have matching polarizations Large incident angle (i.e., S7 ) are preferable (to minimize terrain displacement effects) The larger the difference between incident angles, the greater the parallax in the stereo pair (recommend 5 - 25 angular difference) Opposite-side (i.e., ascending/descending) image pairs only recommended for very low relief areas; with similar tonal characteristics
  • 57. Application examplesFlood Monitoring Page 57
  • 58. SAR derived real time floodinginformation – Manitoba, Canada
  • 59. RADARSAT-2 acquisitionApril 15, 2011 - 00:11 UTCRed River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 60. RADARSAT-2 acquisitionApril 18, 2011 - 12:32 UTCRed River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 61. RADARSAT-1 acquisitionApril 20, 2011 - 00:15 UTCRed River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 62. RADARSAT-2 acquisitionApril 22, 2011 - 00:07 UTCRed River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 63. RADARSAT-2 acquisitionApril 25, 2011 - 12:27 UTCRed River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 64. RADARSAT-2 acquisitionApril 21, 2011 - 00:36 UTCAssiniboine River Approximate location of air photo © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
  • 65. Assiniboine River April 20, 2011 at PTH 21 near previous Radarsat image
  • 66. Application examplesOcean Features Page 66
  • 67. Wind Speed AnalysisSteps: #1: Convert to calibrated data (SARINGEST) #2: Boxcar Filter (19 x 19) #3: Convert filtered HV data to decibel #4: If HV data ( < -21 dB) apply Paris Vachon algorithm to generate Windspeed in m/s.Purple = 10 m/s to red = 16 m/s. Page 67
  • 68. RADARSAT HV in dB Page 68
  • 69. Derived Windspeed Page 69
  • 70. Page 70
  • 71. Summary of PCI CapabilitiesSoftware / scalable Experience/ know-how Geomatica Radar Suite  Dedicated development www.pcigeomatics.com/sar team  Includes SPW and Target  Senior SAR scientist on Analysis  Ingest, correct Multi-sensor staff SAR data  30 years of experience  SAR training available SAR for GXL  Custom implementation of SAR analysis for large volume processing Page 71
  • 72. Contact PCI GeomaticsTORONTO GATINEAU50 West Wilmot 490 St-Joseph Boulevard www.pcigeomatics.comRichmond Hill, ON Gatineau, QCCanada, M4B 1M5 Canada, J8Y 3Y6 info@pcigeomatics.comPhone: (905) 764-0614 Phone: (819) 770-0022Fax: (905) 764-9064 Fax: (905) 770-0098 @pcigeomatics www.pcigeomatics.tv www.facebook.com/pcigeomatics www.linkedin.com/company/pci-geomatics www.flickr.com/pcigeomatics Page 72