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TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
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TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons

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  • 1. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 1
    Hawaiian Village, Honolulu, Hawaii, 2010 July 25 – 30
    IGARSS10-TU3.L09-4414, Sea Pearl 1/2/3
    Tuesday, 2010 July 27, 13:35 – 15:15
    "Critical Assessment of diverse Polarimetric SAR Systems – pros and cons”
    Wolfgang-Martin Boerner1
    Invited Presentation
    1. UIC-ECE/CSN, 900 W Taylor St, SEL-4210, CHICAGO, IL/USA-60607-7018, + I-312-996-5480, wmb1uic@yahoo.com
    IEEE International Geosciences& Remote Sensing Symposium
  • 2. Wolfgang-Martin Boerner1, Thomas L. Ainsworth2, Eric Pottier3, Ya-Qiu Jin 4, Shane Robert Cloude5, Yoshio Yamaguchi6, Jakob J. vanZyl7, Konstantinos (Kostas) P. Papathanassiou8, Carlos Lopez-Martinez9
    1. UIC-ECE/CSN, 900 W Taylor St, SEL-4210, CHICAGO, IL/USA-60607-7018, + I-312-996-5480, wmb1uic@yahoo.com
    2. NRL-RSD/ISS, Code 7263, 4555 Overlook Ave SW, Bldg-2, WASHINGTON, DC/USA-20375-5351, ainsworth@nrl.navy.mil
    3. Univ-Rennes-1, IETR-SAPHIR, Beaulieu Bat 11D, 263 ave Gen. Leclerc, F-35700 RENNES, FR, +33-2-23235763, eric.pottier@univ­rennes1.fr
    4. Fudan Daxue, East Guan Hua, Floor 11, Room 1103, 220 Handan Road, Yangpu, Shanghai, PRC-200-433, yqjin@fudan.ac.cn
    5. AECL, 26 Westfield Avenue, Cupar, Fife KY15-5AA, Scotland UK, aelc@mac.com
    6. NU-IE, Ikarashi 2 Nocho 8050, NIIGATA-Shi, 950-2128, +81-25-262-6752, yamaguchi@ie.niigata-u.ac.jp
    7. NASA-JPL, CALTECH MS 180-804, 4800 Oak Grove Dr, PASADENA, CA/USA-91109-8099, +1-818-354-1365, Jakob.J.vanZyl@jpl.nasa.gov
    8. DLR-HR, Muenchener-Str. 20, Geb-102, D-82230 OPH-WESSLING, Obb, GER, +49-8153-28-2306, kostas.papathanassiou@dlr.de
    9. UPC-TSC/ARS-Group, North Campus, Bldg. D3, Room 203, Jordi Girona 1 – 3, Barcelona, Spain, ES-08034, clm@ieee.org
    WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 2
  • 3. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 3
    ABSTRACT-1
    Considerable advances have been made during the past decades in polarimetric SAR systems leading to increased ability for recovering inherent polarization information conveyed by vector-electromagnetic wave backscatter. This paper compares the benefits offered by the major types of systems in relation to their application, as a function of their polarimetric architecture. POL-SAR system characterization includes the radar sensor, processing to transform the received data to polarimetric products, and calibration. More complex scattering scenarios require more capable polarimetric data collection and analysis. The system types considered are: Mono-Pol (single polarization, amplitude-only); Dual-Pol (traditional amplitude-only configuration, including HH+VH, VV+HV); Compact-Pol (transmit one polarization in base AB, and coherently receive two orthogonal polarizations in orthogonal base CD, which retain the relative phase between the received polarizations); and Full-Pol (coherent HH, HV, VH and VV).
  • 4. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 4
    ABSTRACT-2
    Under the simplifying assumption of scattering symmetry in monostatic configurations implying HV=VH, the Full-Pol data reduce to the familiar Quad-Pol products (coherent HH, HV and VV). Compact-Pol architectures include: Coherent Linear LH-Pol (HH+HV, or VV+VH, or HH+VV, coherently in each case); Coherent Diagonal/Linear DL-Pol (transmit linear polarization at a diagonal angle of 45* with respect to horizontal, and receive coherently the conventional linear H and V, thus DH+DV); Coherent Circular LR-Pol (coherent RR+RL or LL+LR); Coherent Hybrid Circular/Linear CL-Pol (RH+RV or LH+LV). The amount of acquired data (and of all data-dependent subsystems such as storage and transfer), processing and calibration increases, for greater polarimetric sophistication; and so do mass and volume with greater polarimetric capability. The various architectures have different implications on data rate, swath-width and resolution issues that apply to any multi-channel radar whether polarimetric, interferometric or for multiple frequencies. Given this multi-dimensional possibility space, the paper attempts to identify the benefits of each type of system as a function of implementation, also addressing the forthcoming demands of space-borne POLin SAR and RP (Diff) POLinSAR deployments.
  • 5. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 5
    ABSTRACT-3
    Since SEASAT (Mono-Pol HH, L-band), space-based SAR systems are gradually becoming polarimetrically more capable, including ENVISAT (Dual-Pol, C-band), ALOS-PALSAR (Full-Pol or Quad-Pol, depending on processing algorithm, L-band), TerraSAR-X (Full-Pol or Quad-Pol, X-band), and RADARSAT-2 (Full-Pol or Quad-Pol, C-band). Planetary examples include Magellan (Venus: HH, S-band), Cassini (Saturn: Mono-Pol – amplitude-only, Ku-band), two Mini-SARs (Moon: CL-Pol, S-band or S- and X-band), for which mass and data rate (or data volume) are critical parameters.
    Polarimetric diversity implies additional costs and impacts the mission operation scenario defined by user requirements and/or technological constraints. However, the paper hazards recommendations for the polarimetric architecture of future space-based SAR Systems; and it is concluded that any so-called cost-saving measures are ill-conceived and that we need to focus fully on the advancement of fully polarimetric SAR systems technology and stop all of the regressive approaches which will only take us back to the child stage of SAR concept initiation.
     
  • 6. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 6
    ABSTRACT-4
    Contributing remarks by Dr. Lopez-Martinez
    Respect to your comments about compact-pol it is true that it is a step back concerning PolSAR. For instance, in terms of data classification, the lack of complete polarimetric information may lead to misclassification. From my experience, people are demanding operational classification. So, if we do not have fully polarimetric information, we will not be able to demonstrate this capability.
    Nevertheless, there is a more "dramatic" reading of the history of compact-pol vs full-pol. Final users are not polarimetric experts, so they are not able to distinguish compact-pol from full-pol. So, if they see poor results from compact-pol data, they will assume the same type of results with full-pol. I guess, it should be necessary to show what is lost from full-pol to compact-pol.
  • 7. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 7
  • 8. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 8
    Orthogonal Tx pols
    Coherent Dual Rx
    Pseudo 3x3 scattering matrix
    One Tx Pol, Coherent Dual Rx
    Symmetry assumptions
    2x2 covariance matrix
    No symmetry assumptions
    2 magnitudes & co-pol phase
    Two Tx pols
    Two Rx pols
    2 magnitudes
    2 magnitudes
    One polarization
    Magnitude
    Polarimetric Imaging Radar Hierarchy R.K.Raney
    Nomenclature
    Result
    Processing
    Radar
    4x4 scattering matrix
    No assumptions
    Full polarization
    Reciprocity & symmetry
    Quadrature polarization
    3x3 scattering matrix
    Compact polarization
    No HV
    2 orthogonal Like-pol images & CPD
    2 orthogonal Like-pol images
    Dual polarization
    Like- and Cross-pol images
    Mono-polarization
    Real image
  • 9. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 9
    Ship Detection Using the Convair-580 (30to 60 incidence angle)
    Touzi et al, “Ship detection and characterization using polarimetric SAR”. CJRS, Special issue on RADARSAT-2, June 2004
    HH
    HV
    VV
    Compact-RV
    Touzi Anisotropy
    Full-Pol
    Compact-RH
  • 10. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 10
    N
    Red: Sendai7602_HH polarization
    Green: Sendai7603_HH polarization
    Blue: Sendai7604_HH polarization
  • 11. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 11
    Flight direction
    Square path data
  • 12. ALOS-PALSAR Polarimteric Mode
    Ascending
    Descending
    2006/8/19
    2006/8/17
    ALPSRP029970850-1.1A 2006/10/2
    ALPSRP036680850-1.1A
    ALPSRP030192750-1.1D
    Tomakomai
    Hokkaido
    ©JAXA, METI
    2007/10/10
    Yoshio Yamaguchi
    ALPSRP091090850-1.1A
    WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 12
  • 13. Pd
    Ps
    Pv
    Color-Composite
    POLSAR image analysis
    Scattering matrix
    = Quad. Pol. data
    HV Basis
    HH, 2HV, VV
    VV
    HV
    HH
    Pauli Basis
    HH-VV, 2HV, HH+VV
    <Average>
    Eigenvalue
    Entropy, Alpha-angle, Anisotropy
    λ1
    λ2
    λ3
    double
    bounce
    Scattering Power Decomposition
    Covariance matrix Coherency matrix
    surface
    scattering
    volume
    scattering
    Pd, Pv, Ps, Pc
    WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 13
  • 14. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 14
    The four-component decomposition of scattering powers Ps, Pd, Pv, and Pc
  • 15. Pd
    Ps
    Pv
    Fugen-dake
    Unzen
    32.825N
    130.364E
    Google earth optical image
    ALOS-PALSAR pol. image
    ALPSRP072570650-1.1A
    ©JAXA, METI
    2007/6/5
    WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 15
  • 16. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 16
    4-compornent scattering power decomposition algorithm
    using rotated coherency matrix
    Rader line of sight
    Deorientation
    Rotation of imsge
  • 17. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 17
    4-compornent scattering power decomposition algorithm using rotated coherency matrix
  • 18. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 18
    4-compornent scattering power decomposition algorithm using rotated coherency matrix
  • 19. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 19
    Four-component decomposition New rotated decomposition
    Scattering power decomposition by rotation of coherency matrix
    forNiigata City area in Niigata Prefecture of Japan
  • 20. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 20
    Sapporo City, Hokkaido Prefecture, Japan
    (a) Original decomposition
    (b) Decomposition after T33 rotation
    (e) Patch C: forest
    (d) Patch B: oriented urban
    (c) Patch A: orthogonal urban
    Deorientation
  • 21. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 21
    Interest area
    3800m
    0m
    Monitoring of ongoing surface deformation along Cheleng-Pu fault
    Data fusion of DEM and
    RADARSAT SAR images
    By CSRSR.
    Taiwan
  • 22. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 22
    “Natural hazards are inevitable. Natural disasters are not.”
  • 23. Pd
    Ps
    Pv
    Scattering power decomposition
    2007/3/10
    Pd, Pv, Ps (80 up)
    T33 Rotation
    Pauli-basis
    HH-VV, 2HV, HH+VV (80 up)
    HV-basis
    Indonesia
    -7.942N
    112.870E
    ALPSRP059887030-P1.1__A
    ©JAXA, METI
    HH, 2HV, VV (50 up)
    WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 23
  • 24. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 24
    ALOS-PALSAR Polarimetric Mode
    Philippines
    Ascending
    13.501N
    123.551E
    2009/5/30
    Data no.
    ALPSRP178330260
    © METI, JAXA
    Yoshio Yamaguchi
  • 25. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 25
    Pd
    Ps
    Pv
    Mt. Mayon
    Philippines
    13.501N
    123.551E
    2009/5/30
    N
    Google Earth optical image
    Data no.
    ALPSRP178330260
    ©METI, JAXA
    Scattering power
    Decomposition
    Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
  • 26. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 26
    Pd
    Ps
    Pv
    Mt. Mayon
    Philippines
    13.498N
    123.561E
    2010/1/15
    N
    Google Earth optical image
    Data no.
    ALPSRP211880260
    ©METI, JAXA
    Scattering power
    Decomposition
    Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
  • 27. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 27
    Pd
    Ps
    Pv
    Mt. Mayon
    Philippines
    13.498N
    123.568E
    2010/4/17
    N
    Google Earth optical image
    Data no.
    ALPSRP225300260-P1.1__A
    ©METI, JAXA
    Scattering power
    Decomposition
    Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
  • 28. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 28
    Philippines
    Pd
    Ps
    Pv
    Mt. Mayon
    2009/5/30
    2010/1/15
    2010/4/17
  • 29. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 29
    FOUNDATIONS AND RELEVANCE OF MODERN
    EARTH REMOTE SENSING & ITS ACTIVITIES
    Conclusions:
    The Electromagnetic Spectrum:
    A Natural Global Treasure
    Terrestrial Remote Sensing with PolSAR:
    The Diagnostics of the Health of the Earth
    at all weather and volcanic conditions
    and at day and night

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