PCI Geomatics Synthetic Aperture Radar Processing Capabilities
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PCI Geomatics is a leading geospatial software and solutions company with over 70 employees and 25,000 licenses installed worldwide. They provide powerful and scalable image processing solutions to extract information from satellite imagery such as SAR (Synthetic Aperture Radar) and LIDAR. Their capabilities include orthorectification, image classification, change detection, and digital elevation model extraction. They support a variety of sensors and applications in areas such as maritime surveillance, disaster response, and natural resource monitoring.
PCI Geomatics Synthetic Aperture Radar Processing Capabilities
- 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, for 60 Resellers USA, China Worldwide GXL Geomatica
- 4. GEOSPATIAL VALUE CHAIN Image Image Pre- Image Tools & Value-Added Collection Processing Processing Work Flow Content Selected Capabilities Satellite Orthorectification Image Extraction Display , Storage and Google Maps/Earth Dissemination SAR (Radar) Atmospheric Spatial Analysis Microsoft Bing Maps correction Ingestion Tools LIDAR Image Classification Location Based Services Image Mosaiking Enterprise Integration Airborne Camera Customized Vertical Applications – Pan Sharpening Algorithms Open Source natural resource, Other Image Sensing Development weather, land planning, etc. Selected Competitors/Partners Digital Globe PCI Geomatics PCI Geomatics PCI Geomatics Google / Yahoo / Microsoft Vexcel / Microsoft ERDAS (Leica) Definiens AG ESRI / Intergraph ESRI / Intergraph GeoEye ENVI (ITT) ERDAS (Leica) Pixel Factory Vertical Applications (e.g., (InfoTerra) RapidEye for Agriculture and ENVI (ITT) Iunctus for Oil and Gas) Page 4
- 6. We provide… Powerful and scalable image processing solutions that let you quickly and efficiently produce information products 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 $500 Price ($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 Methods 1. Amplitude Change Detection 2. Coherence Change Detection 3. 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 Airport Sunday May 4, 2008
- 17. Change Detection Results Phoenix Airport Weds. May 28, 2008
- 18. Detected Changes Phoenix 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 Detection Change in Coherence (phase) Image 1 Page 20
- 21. Coherent Change Detection Change in Coherence (phase) Image 2 Acquired 11 min. later Page 21
- 22. Coherent Change Detection Loss of Coherence is indicated by Dark Colour Note: 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 Map Optical (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 V For a single polarization, the return is proportional to the target cross section. H For HH we would get a return indicated by red. For VV it would be blue. So the amount of return we get depends on target orientation and polarization Page 34
- 35. Some Polarimetric Basics V For a single polarization, the return is proportional to the target cross section. For HH we would H get a return indicated by red. For VV it would be blue. 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 Information Maximum of the degree of polarization: 0.7916655 Minimum of the degree of polarization: 0.09595539 Maximum of the completely polarized component: 2.520944 Minimum of the completely polarized component: 0.2940039 Orientation of Maximum Polarisation 70 Ellipticity of Maximum Polarisation -5 Maximum of the completely unpolarized component: 2.769960 Minimum of the completely unpolarized component: 0.6619406 Maximum of the scattered intensity: 3.210612 LL Minimum of the scattered intensity: 2.850842 Coefficient of Variation: 0.1160221 Fractional Power: 0.7920792 HH VV Pedestal Height 1.318336 HH / HV Ratio 4.014223 HH / HV Correlation 0.2035844 RR HH / VV Ratio 0.9518262 Page 41 HH / VV Correlation 0.3857002
- 42. Polarimetric Signature Information V LL 5° Ellipticity 70° Orientation H VV Maximum Return V LL RR Secondary HH Return Max Return H - 20° Orientation Strong Secondary Return Page 42 RR
- 43. Power Distribution By Polarization HH HV VV By Type Double Diffuse Surface By Scatterer Primary Secondary Tertiary
- 44. Polarimetric Decompositions Cloude-Pottier Target Average % High % Medium % Low Entropy 0.8480822 2.253302 76.30148 21.44522 Anisotropy 0.5064220 55.63326 44.36674 Alpha 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 ? 1-5 6 - 10 11 - 15 16 - 20
- 48. Classification based upon Polarimetric Signatures ? 1-5 6 - 10 11 - 15 16 - 20
- 49. Polarimetric Power Distribution Comparison Polarization Type Scatterer Page 49
- 50. Application examples Digital Elevation Extraction Page 50
- 51. Multi-Channel Input HH HV Span VH VV
- 52. Stereo DEMs Find highest correlation within search window R1 R2 Compute 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 A Spacing 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 Pairs Selection 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 examples Flood Monitoring Page 57
- 58. SAR derived real time flooding information – Manitoba, Canada
- 59. RADARSAT-2 acquisition April 15, 2011 - 00:11 UTC Red River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
- 60. RADARSAT-2 acquisition April 18, 2011 - 12:32 UTC Red River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
- 61. RADARSAT-1 acquisition April 20, 2011 - 00:15 UTC Red River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
- 62. RADARSAT-2 acquisition April 22, 2011 - 00:07 UTC Red River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
- 63. RADARSAT-2 acquisition April 25, 2011 - 12:27 UTC Red River © Her Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.
- 64. RADARSAT-2 acquisition April 21, 2011 - 00:36 UTC Assiniboine 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 examples Ocean Features Page 66
- 67. Wind Speed Analysis Steps: #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 Capabilities Software / 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 Geomatics TORONTO GATINEAU 50 West Wilmot 490 St-Joseph Boulevard www.pcigeomatics.com Richmond Hill, ON Gatineau, QC Canada, M4B 1M5 Canada, J8Y 3Y6 info@pcigeomatics.com Phone: (905) 764-0614 Phone: (819) 770-0022 Fax: (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