tu3.l09 - critical assessment of diverse polarimetric sar systems – pros and cons
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Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 1
Hawaiian Village, Honolulu, Hawaii, 2010 July 25 – 30
IGARSS10-TU3.L09-4414, Sea Pearl 1/2/3Tuesday, 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
Communications, Sensing & Navigation Lab
• 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@univ rennes1.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
Communications, Sensing & Navigation Lab
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).
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 4
ABSTRACT-2Under 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.
Communications, Sensing & Navigation Lab
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.
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 6
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.
ABSTRACT-4
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 7
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 8
Polarimetric Imaging Radar Hierarchy R.K.RaneyRadar Result
Orthogonal Tx polsCoherent Dual Rx
One Tx Pol, Coherent Dual Rx
One polarization
Processing Nomenclature
Real image
No assumptionsReciprocity &
symmetry
4x4 scattering matrix
3x3 scattering matrix
Symmetry assumptions
No symmetry assumptions
Pseudo 3x3 scattering matrix
2x2 covariance matrix
Full polarization Quadrature polarization
Compact polarization
Two Rx pols
Two Tx pols
Magnitude
2 magnitudes & co-pol
phase
2 magnitudes
2 magnitudes
Like- and Cross-pol
images
2 orthogonal Like-pol images
2 orthogonal Like-pol images & CPD
Dual polarization
Mono-polarization
No HV
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 9
HH HVVV
Compact-RH Compact-RV Touzi AnisotropyFull-Pol
Ship Detection Using the Convair-580 (30 to 60 incidence angle)Touzi et al, “Ship detection and characterization using polarimetric SAR”. CJRS, Special issue on RADARSAT-2, June 2004
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 10
Red: Sendai7602_HH polarization
Green: Sendai7603_HH polarization
Blue: Sendai7604_HH polarization
N
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 11
Square path data
Flight direction
Communications, Sensing & Navigation Lab
Ascending
2006/8/17ALPSRP029970850-1.1A 2006/10/2ALPSRP036680850-1.1A
ALOS-PALSAR Polarimteric Mode
TomakomaiHokkaido
Descending
ALPSRP030192750-1.1D2006/8/19
ALPSRP091090850-1.1A2007/10/10
Yoshio Yamaguchi
©JAXA, METI
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 12
Communications, Sensing & Navigation Lab
POLSAR image analysis
<Average>
Pauli Basis
Eigenvalue
Scattering Power DecompositionCovariance matrix Coherency matrix
Entropy, Alpha-angle, Anisotropy
Scattering matrix= Quad. Pol. data
Pd, Pv, Ps, Pc
VVHVHHColor-Composite
HH-VV, 2HV, HH+VV
λ1 λ2 λ3
HV Basis
HH, 2HV, VV
Ps Pv
Pd
volume scattering
double bounce
surface scattering
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 13
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 14
The four-component decomposition of scattering powers Ps, Pd, Pv, and Pc
Communications, Sensing & Navigation Lab
ALPSRP072570650-1.1A
32.825N130.364E
2007/6/5
©JAXA, METI
Fugen-dakeUnzen
Google earth optical image
ALOS-PALSAR pol. image
Ps Pv
Pd
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 15
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 16
Rader line of sight
Deorientation
Rotation of imsge
4-compornent scattering power decomposition algorithm using rotated coherency matrix
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 17
4-compornent scattering power decomposition algorithm using rotated coherency matrix
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 18
4-compornent scattering power decomposition algorithm using rotated coherency matrix
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 19
Four-component decomposition New rotated decomposition
Scattering power decomposition by rotation of coherency matrix for Niigata City area in Niigata Prefecture of Japan
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 20
Deorientation
(a) Original decomposition (b) Decomposition after T33 rotation
(c) Patch A: orthogonal urban (d) Patch B: oriented urban (e) Patch C: forest
Sapporo City, Hokkaido Prefecture, Japan
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 21
Interest area
0m
3800m
Data fusion of DEM and RADARSAT SAR images By CSRSR.
Monitoring of ongoing surface deformation along Cheleng-Pu fault
Taiwan
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 22
“Natural hazards are inevitable. Natural disasters are not.”
Communications, Sensing & Navigation Lab
©JAXA, METI
Scattering power decomposition
Ps Pv
Pd
Pauli-basis
HV-basis
2007/3/10
-7.942N112.870E
Indonesia
T33 Rotation
ALPSRP059887030-P1.1__A
HH, 2HV, VV (50 up)
HH-VV, 2HV, HH+VV (80 up)
Pd, Pv, Ps (80 up)
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 23
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 24
Ascending
Data no.ALPSRP178330260
ALOS-PALSAR Polarimetric Mode
Philippines
© METI, JAXA
Yoshio Yamaguchi
2009/5/30
13.501N123.551E
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 25
Ps Pv
Pd
Scattering power Decomposition
Google Earth optical image
Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
Data no.ALPSRP178330260
Philippines
2009/5/30
13.501N123.551E
©METI, JAXA
N
Mt. Mayon
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 26
Ps Pv
Pd
Scattering power Decomposition
Google Earth optical image
Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
Data no.ALPSRP211880260
Philippines
2010/1/15
13.498N123.561E
©METI, JAXA
N
Mt. Mayon
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 27
Ps Pv
Pd
Scattering power Decomposition
Google Earth optical image
Decomposed image (Ps, Pd, Pv) with rotation 2*12 window
Data no.ALPSRP225300260-P1.1__A
Philippines
2010/4/17
13.498N123.568E
©METI, JAXA
N
Mt. Mayon
Communications, Sensing & Navigation Lab
WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 28
2009/5/30
2010/1/15
2010/4/17
Mt. MayonPhilippines
Ps Pv
Pd
Communications, Sensing & Navigation Lab
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 conditionsand at day and night
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