The RADARSAT Constellation Mission (RCM) is equipped with three SAR satellites (RCM1, RCM2 and RCM3) flying in a constellation configuration. Each SAR is equipped with Compact polarimetry (CP) capabilities. It is now admitted that the actual SAR technology does not permit the generation of a perfectly circular polarization and this may significantly affect CP information [1], [2]. Recently, a new CP calibration model [2], which explicitly takes into account the non-circularity of transmitted polarization, in addition to polarimetric antenna distortion matrix and channel imbalances, was introduced and validated using ALOS2 CP data. In this study, the Touzi CP calibration model [2] is extended to the RCM. The high isolation of RCM antennas (cross-talk lower than -40 dB) permits a simplification of the Touzi CP model and its use as the basis of a convenient method for measurement of RCM CP axial ratio (AR) using Amazonian rainforests. The Touzi CP calibration model is also used to setup the requirements on CP calibration. These new requirements on CP calibration lead to the conclusion that the current RCM calibration meets the CP requirements for all the RCM beams with AR lower (or equal) than 0.5 dB (5m-CP2-to-14, and 30mSC beams within the incidence angle range 20° -to- 43°). A new calibration method based on the Touzi RCM CP-calibration model is developed (and validated) for the correction of the non-circularity of RCM CP beams with AR larger than 0.5dB.

Wetlands with at least 30-40 cm of peat accumulated on the surface represent an important class of wetlands named peatland. Although peatlands globally only cover 3% of the land surface they store 30% of the terrestrial carbon. Therefore, it is important to maintain and protect peatlands to prevent greenhouse gas release. Unfortunately, major peatland transformations have been detected in the boreal and subarctic peatland regions. Permafrost degradation across Canada’s vast peatlands threatens Canada’s existing energy infrastructure network and the relative vulnerability of peatlands is a critical knowledge gap that represents a substantial risk in new infrastructure development projects. Uninformed management of, and thus subsequent loss of, vulnerable peatlands over the next decade represents one of the most significant impacts on Canada’s carbon balance resulting from land management and resource development. Cost-effective peatland & permafrost mapping and monitoring should be possible due to advances in the technology of earth observation satellites. In particular, the sensitivity of polarimetric L-band ALOS, ALOS2 and upcoming ALOS4, to peatland subsurface water flow, should permit accurate discrimination of bogs from fens; two important wetland classes of similar vegetation that can hardly be discriminated by Visible near-infrared satellites, C-band dual and polarimetric satellite SAR (Radarsat2, RCM, Sentinel), and conventional L-band (single- & dual-pol) SARs. Recently, we have shown that polarimetric long penetrating L-band ALOS permits a clear discrimination of bogs and fens using their different hydrological properties [1], [2]. This has been demonstrated for boreal peatlands (in La Baie des Mines, the Athabasca oil sand exploration region), and subarctic peatlands located at the Wapusk National Park ([3], [4], [2]). it is shown that among all the parameters generated by the Touzi, Cloude-Pottier [5] and Freeman [6] ICTDs, only the dominant scattering type phase ϕs1generated by the Touzi decomposition [7], [8] is sensitive to peatland subsurface water flow. The complementary information provided by the Touzi discriminators [9], which exploits the extrema of the degree of polarization (DoP), permits an enhanced separation of treed peatlands from upland forests [4]. Recently, we have shown that the excellent performances of polarimetric ALOS2 in term of NESZ (-37 dB) permits the demonstration of the unique long penetration L-band SAR capabilities for enhanced detection and mapping of discontinuous permafrost (up to 50cm) in the vicinity of Namur Lake, in Northern Alberta [10]. The use of ALOS2 images collected at 27°incidence angle and the medium scattering type phase ϕs2provided by the Touzi decomposition leads to more accurate mapping of relatively deep permafrost (up to 50 cm under the peatland surface) than the Lidar-Landsat permafrost map obtained by Alberta Geological Survey [10]. In this study, polarimetric ALOS2 images collected at 25° are used for characterization of peatlands and permafrost in the Wapusk National Park. The results obtained permit the confirmation of the unique information provided by the dominant scattering type ϕs1and the medium scattering type phase ϕs2for enhanced mapping of peatlands, and charcterization of relatively deep subsurface permafrost (up to 50cm).

The potential of long penetrating L-band SAR (ALOS2 and UAVSAR) and very long penetrating P-band AIRMOSS are investigated for permafrost characterization along the Innuvik-Tuktoyaktuk Highway (ITH) corridor and surrounding environment. The dominant and medium scattering phases generated by the Touzi decomposition [1] are investigated for optimum polarimetric SAR information extraction. It is shown that the medium scattering type phase, ϕs2, performs better than the dominant scattering type phase, ϕs1, for subsurface permafrost mapping. The excellent NESZ (-37 dB) capabilities of ALOS2 and its accurate calibration permits the detection of relatively deep permafrost (up to 60 cm). These results are confirmed with the polarimetric L-band airborne UAVSAR of excellent NESZ (-48 dB). The very long penetrating capabilities of the P-band polarimetric AIRMOSS and its excellent NESZ (-48 dB) should permit detection and characterization of deeper permafrost.

The most popular model-based decompositions (MBD) are reconsidered in the context of the estimation theory. It is shown that a large processing window is required to reduce the bias on the individual scattering contribution due the target scattering Reflection symmetry assumption. This limits the MBD efficiency in areas of non stationarity radar backscattering, such as urban areas. Eigenvector-based decompositions (EVBD)are also reconsidered. The effect of polarization basis change on target scattering description is investigated using the Cloude-Pottier ICTD, and the Touzi decomposition. The latter, which is an extension of the Kennaugh-Huynen method (originally developed for dominant coherent scattering) to partially coherent scattering, was originally developed to correct for the Cloude-Pottier scattering decomposition ambiguities. It is shown that the Touzi decomposition is the EVBD that permits the decomposition of both coherent and partially coherent scattering in terms of unique and polarization basis-invariant parameters.

The RADARSAT Constellation Mission (RCM) launched on the 12thof June 2019 is equipped with three SAR satellites (RCM1, RCM2 and RCM3) flying in a constellation configuration. Each SAR is equipped with Compact polarimetry (CP) capabilities. It is now admitted that the actual SAR technology does not permit the generation of a perfectly circular polarization and this may significantly affect CP information [1], [2]. Recently, a new CP calibration model [2], which explicitly takes into account the non-circularity of transmitted polarization, in addition to polarimetric antenna distortion matrix and channel imbalances, was introduced and validated using ALOS2 CP data. In this study, the Touzi CP calibration model [2] is extended to the RCM. The extended Freeman-Van Zyl calibration method introduced in [3] is used for the measurement of the RCM polarimetric distortion matrices using RCM data collected over (3.5m) corner reflectors (CR) deployed at the CSA calibration site (Saint-Hubert, Québec). It is shown that the three RCM satellite antennas are highly isolated with a cross-talk lower than -40 dB. This permits a simplification of the Touzi CP model and its use as the basis of a convenient method for measurement of RCM CP axial ratio (AR) using Amazonian rainforests. The Touzi CP calibration model is used to setup the requirements on CP calibration. Since the baseline RCM CP calibration method is based on the Freeman calibration model [4], which assumes that the transmitted circular polarization is perfectly circular, the new requirements setup on CP calibration leads to the conclusion that the current RCM calibration meets the CP requirements for all the RCM beams with AR lower (or equal) than 0.5 dB (5m-CP2-to-14, and 30mSC beams within the incidence angle range 20°-to- 43° ). A new calibration method based on the Touzi RCM CP-calibration model is developed (and validated) for the correction of the non-circularity of RCM CP beams with AR larger than 0.5dB.

In this study, the dominant and medium scattering phases generated by the Touzi decomposition are investigated for discontinuous permafrost mapping in peatland regions. Polarimetric ALOS2, LIDAR and field data were collected in the middle of August 2014, at the maximum permafrost thaw conditions, over discontinuous permafrost distributed within wooded palsa bogs and peat plateaus near the Namur Lake (Northern Alberta). The ALOS2 image, which was miscellaneously calibrated with antenna cross-talk (-33dB), much higher than the actual ones, is recalibrated. This leads to a reduction of the residual calibration error (down to -43 dB), and permit a significant improvement of the dominant and medium scattering type phase (20°-to-30°) over peatlands underlain by discontinuous permafrost. The Touzi decomposition, Cloude-Pottier α-H incoherent target scattering decomposition, and the HH-VV phase difference are investigated, in addition to the conventional multi-polarization (HH, HV, and VV) channels, for discontinuous permafrost mapping using the recalibrated ALOS2 image. A LiDAR-based permafrost classification developed by Alberta Geological Survey (AGS) is used, in conjunction with the field data collected during the ALOS2 image acquisition, for the validation of the results. It is shown that the dominant and scattering type phases are the only polarimetric parameters which can detect peatland subsurface discontinuous permafrost. The medium scattering type phase, ϕs2, performs better than the dominant scattering type phase, ϕs1, and permits a better detection of subsurface discontinuous permafrost in peatland regions. ϕs2also allows for better discrimination of areas underlain by permafrost from the non-permafrost areas. The medium Huynen maximum polarisation return (m2) and the minimum degree of polarisation (DoP), pmin, can be used to remove the scattering type phase ambiguities that might occur in areas with deep permafrost (more than 50cm depth). The excellent performances of polarimetric PALSAR2 in term of NESZ (-37 dB) permit the demonstration of the very promising L-band long penetration SAR capabilities for enhanced detection and mapping of relatively deep (up to 50 cm) discontinuous permafrost in peatlands regions [1].

Compact-hybrid SAR (CP) is a dual-polarization (dual-pol) SAR mode that transmits a circular polarization (CirP) and measures the received signal at the horizontal and vertical antenna polarization. It is now admitted that the actual SAR technology does not permit the generation of a perfectly CirP and this may significantly affect CP radiometric and phase information. Since all the existing CP calibration models assume a perfectly transmitted CirP, there is an immediate need for the development of a new model that permits efficient assessment and calibration of CP non-circularity. In this article, a new general polarimetric hybrid SAR model (PolHyb) is introduced for both dual- (CP) and quad-polarization hybrid SAR modes. PolHyb explicitly includes the transmitted polarization non-circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination. The non-circularity of transmitted polarization is expressed in terms of the axial ratio (AR), which used to be popular in the 1960s for characterization of circularly polarized (transmit and receive) dual- and quad-polarization radar. The new CP model derived from PolHyb is adapted to PALSAR2-CP and used as the basis of an efficient method for an assessment of CP non-circularity using Amazonian rainforests. PALSAR2-CP data collected at four different beams (H2-6 to H2-9), with incidence angle varying between 30° and 45°, allows for the first ever demonstration of non-circularity of PALSAR2 CP transmitted polarization. Although it is lower than 0.5 dB for H2-6 and H2-7, the AR of PALSAR2-CP transmitted polarization increases significantly with incidence angle to reach up to 1 dB at Beam H2-8, and 2.3 dB at the highest incidence angles of Beam H2-9.

The RADARSAT Constellation Mission (RCM) planned for launch in June 2019 will involve three small SAR satellites flying in a constellation configuration. Each satellite SAR will be equipped with Compact (i.e. Hybrid) capabilities in addition to single-polarization (HH, HV, VV), and conventional (HH-HV, VV-VH, and HH-VV) dual-polarization. Compact (CP) SAR transmits a circular polarization and measures the received signal at the horizontal and vertical antenna polarization. It is now admitted that the actual SAR technology does not permit the generation of a perfectly circular polarization and this may significantly affect CP information [1], [2]. All the existing CP calibration models are mainly based on the Freeman CP model [3], which assumes that the transmitted polarization is perfectly circular. Recently, a new CP calibration mode [2], [4], which explicitly takes into account the non circularity of transmitted polarization, in addition to conventional antenna distortion matrix channel imbalance and Faraday rotation contamination, is introduced and validated using ALOS2-CP data [2], [5]. In this study, the new CP calibration model will be adapted to the RCM. The strategy adopted for RCM CP calibration is described. Preliminary results obtained with RCM data will be presented at the conference.

Recent climate warming has been pronounced in the arctic and sub-arctic region with the average annual temperature increasing between 2 - 3° since the 1950 [1] . Accelerated temperature increases have driven declines in sea ice extent, snow cover duration, glacier mass, and increase in permafrost temperatures [1] . Increasing evidence from the permafrost zone suggests the abrupt permafrost thaw may be the norm for many parts of the Artic and sub-arctic landscape 1950 [1] , [2] . Climate warming is causing the initiation and expansion of abrupt permafrost thaw (called thermokarst), which even though it occurs at point locations, often cause much deeper permafrost thaw to occur more rapidly. Repeated mapping and/or monitoring of ongoing permafrost indicator changes in infrastructure corridor and surrounding lands is important for the assessment of transportation and energy infrastructure safety, and predicting eminent collapse.

Cost-effective permafrost characterization and monitoring should be possible due to advances in the technology of earth observation satellites. In particular, the long-penetration capabilities of L-band ALOS2-PALSAR2 should permit large scale mapping of discontinuous permafrost in peatland areas. Recently, it has been shown that the long penetrating polarimetric L-band ALOS is very promising for boreal and subractic peatland mapping and monitoring [1], [2]. The unique information provided by the Touzi decomposition [3], [4], and the Touzi scattering phase in particular, on peatland subsurface water flow permits enhanced discrimination of bogs from fens; two peat- land classes that can hardly be discriminated using conventional optical remote sensing. In this study, the Touzi scattering phase is investigated for mapping discontinuous permafrost in peatland regions Northern Alberta. Polarimetric ALOS-2 (FP6-4) and field data were collected in August 2014 over discontinuous distributed within wooded palsa bogs and peat plateaus near the Namur Lake (Northern Alberta). The ALOS2 image is re-calibrated to reduce the residual error from -33 dB down to -43 dB. This permits full exploiting the excellent ALOS2 performance in term of low noise floor (NESZ about -38 dB) to increase the sensitivity of the Touzi phase to deep permafrost. It is shown that the information provided by the scattering type phase permits enhanced mapping of discontinuous permafrost. The results obtained with the long penetrating L-band polarimetric PALSAR2 are much better than the ones obtained with conventional discontinuous permafrost mapping methods based on Lidar and optical (Landsat and Spot) images.

ALOS2-PALSAR2, which was launched on the 24th of May 2014, is equipped with an experimental Compact mode (CP) ([1], [2]), that can collect CP images at various incidence angles (H2-1 to H2-9, from 18° to 44°). PALSAR2-CP transmits a circular polarization and measures the received signal at the horizontal and vertical antenna polarization. Recently, it was brought out that the actual technology does not permit the generation of a perfectly circular polarization [3]. The transmitted polarization is non circular, and the non circularity varies with incidence angle. Since all the calibration methods developed for CP assume that the transmitted polarization is perfectly circular, there is immediate requirement for the development of a new CP calibration model that includes the transmitted polarization non circularity. In this study, a new CP calibration model, which explicitly includes the transmitted polarization non circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination, is introduced. The new CP model is adapted to ALOS2-PALSAR2 and used as the basis of a new method for assessment of CP non circularity using Amazonian rainforests, at low Faraday rotation. ALOS2-CP data collected at four different beams (H26 to H29), with incidence angle varying between 30° and 44°, permit the first ever demonstration of non circularity of ALOS2 CP transmitted polarization. It is shown that the transmitted polarization axis ratio of ALOS2-CP increases with incidence angle, and can reach up to 2.5 dB at the most raising incidence angle (44°) of the beam H29.

The complementarity of the “scattered” and “received” wave polarization signatures is demonstrated for enhanced characterization of peatlands and surrounding upland forest scattering. Polarimetric L-band ALOS-PALSAR collected in the Athabasca oil sand exploration region, with peatlands and upland forests partially affected by multiple wildfire, are used. It is shown that the scattered wave polarization signature [1], which represents the explicit variations of the degree of polarization (DoP) and the total scattered intensity RO with transmitted polarization, permits enhanced discrimination of treed bogs from upland forests, and improved identification of fire damages in peat-lands and surrounding forests. The technique introduced in [2] for scattered wave optimization is used as a convenient method for efficient exploitation of the scattered wave polarization signature. The Touzi decomposition [3] is adopted for the optimization of the received wave polarization signature. The unique potential of the scattering type phase generated with the Touzi decomposition is confirmed for enhanced discrimination of poor fens from bogs. These two important pealand classes cannot be separated with the scattered wave optimization, the conventional multi-polarization (HH-HV - VV) channels, the Freeman and Cloude-Pottier decompositions [4], [5]. Finally, the Touzi decomposition is combined with the extrema of the scattered wave main parameters (DoP and RO) for optimum extraction of polarimetric PALSAR information. The comparison with optical Landsat-TM confirms the valuable added information that long penetrating polarimetric L-band PALSAR can provide for enhanced peatland classification and efficient assessment of peat health in burned peatlands.

ALOS-2-PALSAR is equipped with an experimental Compact mode (CP), which can collect CP images at various incidence angles. PALSAR2-CP transmits a circular polarization and measures the received signal at the horizontal and vertical antenna polarization. Recently, it was brought out that the actual SAR technology does not permit the generation of a perfectly circular polarization and this may significantly affect CP information [1]. Since all the calibration methods assume that the transmitted polarization is perfectly circular, there is an immediate need for a new CP calibration model that is more suitable to actual CP SARs. In this study, a new CP calibration model that takes into account the non circularity of transmitted polarization, in addition to conventional SAR transmitter and receiver distortion matrices, is introduced. The CP calibration model is used as the basis for the development of an efficient method that permits the measurement of transmitted polarization axis ratio, and its variations with incidence angle. The method is validated using PALSAR2-CP data collected at various incidence angles on the Amazonian forests. It is shown that the transmitted polarization axis ratio varies with PALSAR2-CP beam, and can reach up to 1.1 dB for the CP mode (H2-8) (at about 37° incidence angle).

The most popular model-based decompositions (MBD) are reconsidered in the context of the estimation theory. It is shown that a large processing window is required to reduce the bias on the individual scattering contribution due the target scattering Reflection symmetry assumption. This limits the MBD efficiency in areas of non stationarity radar backscattering, such as urban areas. Eigenvector-based decompositions (EVBD) are also reconsidered. The effect of polarization basis change on target scattering description is investigated using the Cloude-Pottier ICTD, and the Touzi decomposition. The latter, which is an extension of the Kennaugh-Huynen method to partially coherent scattering, was originally developed to correct for the Cloude-Pottier scattering decomposition ambiguities. It is shown that the Touzi decomposition is the EVBD that permits the decomposition of both coherent and partially coherent scattering in terms of unique and polarization basis-invariant parameters.

ALOS-2, which was launched on the 24thof May 2014, is equipped with a fully polarimeric L-band SAR (PALSAR-2) [1, 2]. Unlike ALOS-PALSAR, which used to collect polarimetric (PLR) data at one incidence angle (about 22°) [3], PALSAR-2 offers the possibility of providing PLR measurements at various beams (FP6-3 to FP6-6), with incidence angle varying from 25° to 35° [4]. Recently, several investigations [5, 6, 8, 9] have been conducted on the assessment and calibration of polarimetric ALOS2, in the context of the ALOS2 calibration-validation (Cal-Val) working group. PALSAR-2 distortion matrix is measured using CRs deployed in the Amazonian forest [5]. The extended Freeman-Van Zyl calibration method introduced in [7] is used for accurate assessment of PALSAR-2 calibration parameters [6]. Six data sets collected over the Amazonian forest (with CRs) are used to assess PALSAR-2 distortion matrix for five beams (FP3 to FP7) with incidence angle varying from 25° to 40°. It is shown that PALSAR2 antenna is highly isolated with low cross-talk (lower than -40 dB) [6]. These results are in agreements with the ones obtained in [8, 9] with different calibration methods.

The potential of polarimetric L-band PALSAR and the Touzi decomposition [1] for peatland classification and mapping is confirmed using a series of polarimetric ALOS acquisitions collected in the Athabasca oil sand exploration region (near Fort McMurray, Alberta). The sensitivity of the scattering type phase to peatland subsurface water flow permits an enhanced discrimination of poor fen from bogs; two wetland classes that can hardly be discriminated by optic and conventional SAR sensors. The complementary information provided by the new “scattered wave” polarization signature [2] and its optimization, is also confirmed. The extrema of the degree of polarization (DoP) permit accurate assessment of peat health in burned treed bogs. The dynamic range (dRo) of the total scattered wave intensity permits better discrimination of burned from healthy forests in comparison with the intensity parameters generated with the incoherent target scattering decomposition (ICTD) and the conventional multi-polarization channels (HH, HV and VV). The added value of polarimetric L-band SAR information to Optics (Landsat TM) sensors for assessment of fire damages over peatlands is well demonstrated. While optics sensors can identify well burned forest and peatlands areas, accurate assessment of peat health in burned treed bogs can only be obtained using the peat subsurface information provided by the long penetrating L-band polarimetric ALOS.

PALSAR2 distortion matrix is measured using corner reflectors (CR) deployed in the Amazonian forest. The Amazonian forest near the geomagnetic equator provides ideal sites for the assessment of PALSAR antenna parameters, at free Faraday rotation. The extended Freeman-Van Zyl calibration method [1] introduced and validated for ALOS-PALSAR calibration is used for the assessment of PALSAR-2 calibration parameters. Six data sets collected over the Amazonian forest (with CRs) are used to assess PALSAR-2 distortion matrix for five beams (FP3 to FP7) with incidence angle varying from 25° to 40°. It is shown that PALSAR2 antenna is highly isolated with very low cross-talk (lower than -40 dB).

The scattered wave is represented in terms of two independent and rotation invariant parameters: the degree of polarization (DoP) and the total scattered intensity R0. The scattered wave polarization signature is introduced as a convenient graphical representation of the variations of the two scattered wave observable parameters as a function of the transmitting antenna polarization. It is shown that the signature of the DoP and the total scattered intensity (R0) provide information on ocean and ship scattering that is complementary to that provided by the conventional received wave intensity polarization signature. While R0polarization signature of the ocean's Bragg scattering is sensitive to wind speed and synthetic aperture radar illumination angle, the DoP polarization signature appears to depend mainly on ocean surface roughness. The large dynamic range and low pedestal height of ship DoP polarization signature, in comparison with that of the ocean, favors the use of DoP for ship detection in comparison with R0. Optimization of the scattered wave parameters appears to be a convenient tool for efficient ship detection. The scattered wave optimization technique introduced by R. Touzi et al. in the nineties, is reconsidered and applied for enhanced ship detection. It is shown that the excursion of DoP, Δp, and the minimum DoP, pmin, permits a significant improvement in ship-sea contrast in comparison with conventional (i.e., scalar) single channel polarizations (HH, VV, and HV). The additional information provided by the maximum DoP, pmaxsolves for ship ambiguities with land targets. Quantification of the ship-ocean contrast is reconsidered in the context of nonstationary ship signal. The ship peak signal quantification appears to be the most suitable method for accurate measurement of ship-ocean contrast in the presence of a nonstationary ship signal. The local pmin performs better than the peak of Δp and single polarizations (HH, VV, and HV). The added value of polarimetric RS2 information for ship detection is demonstrated using wide swath (50 km) polarimetric RADARSAT-2 data collected at 29° and 40° incidence angle over vessels (validated with Automatic Identification System data) in the Strait of Georgia, near Vancouver, Canada.

This paper uses RADARSAT-2 QUADPOL fully POLarimetric Inteferometric Synthetic Aperture Radar (POLInSAR) data to detect agriculture crop fields changes using coherence optimization method. The RADARSAT-2 POLInSAR data, acquired in July and September 2010, contains wheat, corn and soybean fields. Interferogram and coherence images were generated using single polarimetric data and fully polarimetric data. The coherence optimization method was carried out by maximizing the complex Lagrangian function. The optimized coherence image from the largest eigenvalue can correctly detect changes in the agricultural fields which cannot be detected using single coherence image. The results were validated using ground truth information.

The state of the art in compact SAR calibration is reconsidered. It is shown that all the existing Compact calibration methods are built on the assumption that the Compact transmits a perfect circular polarization (CP). Unfortunately, the actual technology does not permit the generation of a perfect CP wave. The impact of non circularity of the transmitted polarization on Compact polarization information is assessed. The variations with incidence angles of the helicity and ellipticity of the transmitted polarization are simulated for C-band and L-band Compact SAR using Radarsat-2 and Alos data. This permits quantification of the resulting radiometric error on RH and RV dual-pol measurements. The impact of the non circularity of the transmitted polarization on the degree of polarization (DoP) and Compact polarization synthesis is also quantified. The requirements on the calibration of compact SAR for the extraction of a meaningful polarimetric SAR information from compact, are then setup.

Target scattered wave polarization signature is introduced for the representation of the variations of the main scattered wave parameters as a function of the transmitting antenna polarization. It is shown that the signature of the degree of polarization (DoP) and the total scattered intensity (R0) provide important information that is complementary to the Van Zyl conventional received intensity polarization signatures. As a result, the DoP optimization is used as an additional source of information in complement with target scattering decomposition for optimum characterization of peatlands and their surrounding upland forests. The study is conducted using polarimetric L-band PALSAR data collected over boreal peatlands in the Athabasca oil sand exploration region (near Fort McMurray, Alberta). The potential of polarimetric L-band PALSAR and the Touzi decomposition for monitoring water flow beneath the peat surface is confirmed. The scattering type phase permits an enhanced discrimination of poor fen from bogs; two wetland classes that can hardly be discriminated by optic and conventional SAR sensors. The complementary information provided by the DoP optimization permits better discrimination of burned from healthy forests. The DoP dynamic range as well as the scattering phase, which is sensitive to peatland subsurface water flow, permit the right assessment of peat health in burned black-spruce bogs.

Independent assessment and calibration of polarimetric RADARSAT-2 (RS2) synthetic aperture radar (SAR) are conducted using “uncalibrated” data collected at various incidence angles (from 20°to 40°). Analysis of the response of a transponder deployed at HV and VH configurations permits high-precision measurement of RS2 antenna crosstalks. It is shown that the RS2 antenna is highly isolated (better than -32 dB) with crosstalks stable with incidence angle. A new calibration method based on transponder measurements is introduced. It is shown that the transponder calibration method removes almost completely the low antenna crosstalk with a residual crosstalk lower than -43 dB. Only one transmitter-receiver distortion matrix measured at a given incidence angle is required for accurate calibration of the 20 polarimetric modes of the RS2 SAR from 20°to 40°. Uncalibrated RS2 single-look complex (SLC) data with real and imaginary parts provided in 32-bit floating point are required for an effective application of the transponder calibration method. RS2 “calibrated” data are also considered for the assessment of the actual RS2 polarimetric calibration. It is shown that RS2 calibration meets comfortably the CEOS Cal-Val requirements with a residual crosstalk lower than -32 dB. The RS2 calibration accuracy does depend on the mode (i.e., incidence angle) with residual crosstalk that varies between - 32 and -43 dB. To assess the impact of the residual crosstalk on polarimetric applications, the RS2 data are recalibrated using transponder measurements. Each data set was processed four times with a different lookup table (LUT) to reconstruct the 32-bit floating-point data prior to the application of the transponder calibration method. It is shown that the recalibration may not be required for natural targets of relatively high HV backscattering (higher than - 26 dB), such as forests. Data recalibration improves significantly the accuracy of targets of low HV backscattering measurements, whereas like polarization (HH and VV) does not seem to be affected by the residual antenna crosstalk (-32 dB). Urban targets that manifest significant helicity scattering may have their like polarization affected and require data recalibration. However, RS2 data recalibration requires the deployment of a transponder (at HV and VH polarization) for each mode (i.e., incidence angle). Data symmetrization is introduced as a more convenient way to improve polarimetric RS2 data quality without the need to deploy transponders. It is shown that the symmetrization of the modes with the highest residual crosstalk significantly improves the calibration accuracy with a residual crosstalk lower than -37 dB. The latter is negligible as the RS2 noise floor of β°lies between -30 and -34 dB.

China is the largest rice producer in the world. Guizhou province is an important rice growing area in the southwest of China. However, rice monitoring with remote sensing data has great difficulties in this region due to its perennial cloud-coverage weather and undulating terrain. With the emergence of polarimetric SAR data and state of art methods for polarization information extraction, rice monitoring in this region is more promising. In this study, multi-temporal RADARSAT-2 polarimetric SAR data set was acquired in Guizhou, China. The Freeman-Durden, Cloude-Pottier and the Touzi decompositions were used for classification and rice scattering mechanism analysis.

In the southwest of China, Synthetic aperture radar (SAR) is anticipated to provide an important tool for forestry inventory because of its all weather capabilities. In this paper, Zhazuo area in Guizhou Province of southwest China, with typical Karst landform, was selected as the test site, and six RADARSAT-2 polarimetric images were used for experiments. Methods for forest mapping based on polarimetric decomposition and multi-temporal polarimetric SAR data fusion were proposed. Experiments showed that polarimetric signatures of forest were significantly different with other targets, and fusion of multi-temporal RADARSAT-2 images can effectively improve image quality and enhance forest and deforestation information.

Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The hierarchical grouping is based upon a powerful segmentation technique previously developed. The approach is applied on a 9-look polarimetric SAR image. Textured and non-textured image regions are considered. The K and Wishart distributions are used respectively. The unsupervised classification results can be very useful for image analysis and further supervised classification. The obtained region groups constitute an important simplification of the image.

The potential of L-band PALSAR for monitoring water flow beneath the peat surface is demonstrated on a bog near Lac Saint Pierre (Canada). Two polarimetric ALOS acquisitions collected at spring and fall under different water conditions are used. The Touzi decomposition, which was shown to be very promising for peatland characterization using the C-band Convair 580 SAR, is applied. Like in, the information provided by the multi-polarization (HH, HV, and VV), the scattering type magnitude (the Cloude α or the Touzi αs), the single scattering eigenvalues and the entropy, cannot detect the presence of water underneath the peat surface. The Touzi scattering phase is shown to be the only target scattering decomposition parameter that can detect water flow variations beneath the peat surface. The fall acquisition that took place after two days rain permits demonstrating that the wave can penetrate deep into the acrotelm layer to detect the rain water that has sinked rapidly into the peat layer of high hydraulic conductivity. The spring acquisition at dry conditions permits better discrimination of poor fen from bog. The wave, which cannot detect deep water flow in the bog sublayer of low hydraulic conductivity (the catotelm), is more sensitive to the shallower fen subsurface water and this makes possible the separation of poor fen from shrub bog. The requirement for polarimetric PALSAR acquisition during summer is brought out for more effective exploitation of PALSAR unique long wavelength penetration capabilities in monitoring arctic peatland transformations related to climate change stress.

An independent assessment and calibration of polarimetric RADARSAT-2 (RS2) are conducted using transponder measurements extracted from uncalibrated data collected at various incidence angles between 20° and 40°. It is shown that RS2 antenna is highly isolated (better than -32 dB), and only crosschannel relative phase correction is required to provide calibrated data that meet comfortably the CEOS Cal-Val requirements. To take full advantage of the excellent RS2 performance in terms of low noise floor (-38 dB), transponder measurements are used for high precision assessment of RS2 calibration parameters. It is shown that the antenna cross-talks are stable with incidence angle, and only one transmitter-receiver distortion matrix is required for accurate calibration of the 20 modes of RS2 (Right looking) from 20° to 40°. A new method based on high precision transponder measurements is introduced for polarimetric RS2 calibration. Data collected at various incidence angles are used to validate the calibration. Transponder measurements using calibrated data indicate a residual cross-talk lower than -43 dB. The residual cross-channel error is lower than 0.3 dB in radiometry, and 5° in phase.

The issue of antenna cross-polarization isolation has been previously discussed for the design of fully polarimetric synthetic aperture radars (SARs). Dual-polarized antennas with cross-polarization isolation that is better than -30 dB are desirable for more convenient polarimetric data calibration since measurements of antenna crosstalk (magnitude and phase) variations with incidence angle are not required. For an antenna with significant polarization crosstalk, it is still possible to retrieve pure polarization measurements of HH, HV, VH, and VV provided that the four corresponding received voltages are measured. However, it is not possible to recover from cross-polarization contamination for single- or dual-polarization measurements. Therefore, it is important to set up a minimum requirement on dual-polarized antenna isolation so that single- and dual-polarization applications are not unduly affected. In this letter, the minimum requirement on cross-polarization antenna isolation is investigated for operational use of C-band SARs in maritime surveillance applications. Calibrated polarimetric RADARSAT-2 data are used to simulate single- and dual-polarization data with cross-polarization contamination for a dual-polarized antenna with cross-polarization isolation ranging from -20 to -35 dB. It is shown that the cross-polarization HV (or VH) channel can be significantly affected, particularly at steep incidence angles. As a result, key applications that require the use of pure HV, such as ship detection and wind-speed measurements, are significantly affected. A requirement for a minimum of -30-dB antenna isolation is established. Antennas with cross-polarization isolation better than -35 dB are desirable for reliable exploitation of HV data at steep incidence angles.

Urban areas include features (buildings) of coherent scattering as well as areas such as parks that manifest partially coherent scattering due to the significant natural variability in the scattering properties. While high- resolution coherent target decomposition(CTD) can be used for characterization of buildings, incoherent target scattering decomposition (ICTD) is more suitable for analysis of partially coherent targets [11]. In contrast to CTD, ICTD preserves the polarimetric information of the latter at the expanse of the requirement for use of coarse-resolution for unbiased estimation of ICTD parameters [9]. The Touzi decomposition [10], [15] permits a unified roll invariant decomposition of both coherent and partially coherent scattering. In this paper, a multi-resolution technique is introduced to adapt the Touzi decomposition to the coherence nature of target scattering. The multi- resolution mixture CTD-ICTD decomposition is validated using polarimetric Convair 580 SAR data collected over Ottawa city. Implications on the use of the new multi-resolution decomposition for the unified analysis of coherent and partially coherent target scattering are discussed.

Karst forest physiognomy occupy a large area of Guizhou, southwest China. It is a rare forest resource in the earth and urgently needed to carry out protection. Due to synthetic aperture radar (SAR) data's ability to acquire images through clouds, it was tested as an alternative to optical data to map changes of land use/land cover, to estimate biophysical parameters of vegetation types, and to detect deforestation. The main goal of this paper is to analyze the potential of the spaceborne full polarimetric data in distinguishing the different types of forest in southwest China. Different polarimetric target decompositions, such as eigenvetor-based decomposition (Cloude-Pottier's decomposition and Touzi Decomposition) and scattering model-based decomposition (Freeman decomposition), were used in this paper to extract forested areas from the scene. To further divide the extracted forested area into deciduous and coniferous forest., Supervised polarimetric classification procedures based on Freeman decomposition is presented in this paper.

The 17 papers in this special issue focus on the calibration and validation of ALOS sensors and their use for bio- and geophysical parameter retrievals.

Wetlands continue to be under threat, and there is a major need for mapping and monitoring wetlands for better management and protection of these sensitive areas. Only a few studies have been published on wetland characterization using polarimetric synthetic aperture radars (SARs). The most successful results have been obtained using the phase difference between HH and VV polarizations, phiHH- phiVV, which has shown promise for separating flooded wetland classes. Recently, we have introduced a new decomposition, the Touzi decomposition, which describes target scattering type in terms of a complex entity, the symmetric scattering type. Huynen's target helicity is used to assess the symmetric nature of target scattering. In this paper, the new complex-scattering-type parameters, the magnitude alphasand phase Phialphas, are investigated for wetland characterization. The use of the dominant-scattering-type phase Phialphasmakes it possible to discriminate shrub bogs from poor (sedge or shrub) fens. These two classes cannot be separated using phiHH- phiVV, or the radiometric scattering information provided by alphas, the Cloude alpha, the entropyH, and the multipolarization HH-HV-VV channels. phialphas, which cannot detect deep (45 cm below the peat surface) water flow in a bog, is more sensitive to the shallower (10-20-cm) fen beneath water, and this makes possible the separation of poor fens from shrub bogs. Phialphasalso permits the discrimination of conifer-dominated treed bog from upland deciduous forest under leafy conditions. Target helicity information is exploited to introduce a new parameter, the target asymmetry. The latter is shown very promising for detection of forest changes between leafy and no-leaf conditions. The analysis of low-entropy marsh scattering showed that both the scattering-type magnitude and phase alphasand Phialphas, respectively, as well as the maximum polarization intensity of the dominant scatteringm, are needed for a better understanding of marsh complex scattering mechanisms. The unique information provided by the new roll-invariant decomposition parameters are demonstrated using repeat-pass Convair-580 polarimetric C-band SAR data collected in June and October 1995 over the RAMSAR Mer Bleue wetland site near Ottawa (Canada).

Polarimetric Phased-Array-type L-band Synthetic Aperture Radar (PALSAR) system parameters are assessed using data sets collected over several calibration sites. The data collected over the Amazonian rain forest help validate the hypothesis that Faraday rotation is zero near the equator. The analysis of the Amazonian forest data and the response of the corner reflectors deployed there during the PALSAR acquisitions lead to the conclusion that the antenna is highly isolated (better than -35 dB). These results are confirmed using the data collected over calibration sites located in Sweden and Canada. The 5-m-height corner reflector deployed at the Remningstorp (Sweden) calibration site by Chalmers University of Technology provides accurate measurement of antenna parameters and detection of a (2deg -3deg) Faraday rotation during day-time acquisitions, whereas no Faraday rotation was noted during night-time acquisitions. Small Faraday rotation angles (2deg-3deg) have been measured using acquisitions over the DLR Oberpfaffenhofen and the Ottawa calibration sites. The presence of small but still significant Faraday rotation (2deg-3deg) induces a corner reflector return at the cross-polarization HV and VH that should not be interpreted as the actual antenna crosstalk. These results show that the PALSAR antenna is highly isolated (better than -35 dB), and diagonal antenna distortion matrices (with zero crosstalk terms) can be used for accurate calibration of PALSAR polarimetric data.

Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The approach is applied on a 9-look polarimetric SAR image. Textured and non-textured image regions are considered. The K and Wishart distributions are used respectively. The obtained region groups constitute an important simplification of the image and a good initial classification map. Multiplying the class map by the image of scalar texture component produces an image almost identical to the original where speckle 'color' noise variation is filtered out.

In this study, the Touzi and Cloude-Pottier decompositions are compared for land cover characterization using ALOS/PALSAR polarimetric data collected at September, 4, 2006, over the Weinan region of Shanxi Province in China, the most useful parameters are combined for land cover classification. The classification results are assessed and validated using Landsat TM image of Weinan area acquired at August, 9, 2006.

The Touzi decomposition is investigated for wetland characterization. Like the Cloude alpha scattering type, the magnitude alphasof the symmetric scattering is not effective for vegetation type discrimination. The phase Phialphasof the symmetric scattering type has to be used for enhanced characterization of wetland vegetation species. A new tool is introduced for assessment of the scattering type phase coherence, and the phase of the dominant scattering type is shown to be very promising for wetland target classification. The unique information provided by Phialphasfor enhanced wetland class discrimination is demonstrated using Convair-580 polarimetric C-band SAR data collected over the Mer Bleue wetland in the East of Ottawa, Canada. The use of Phialphasmakes possible the discrimination of shrub bog from sedges fen, and permits even the discrimination between conifer dominated treed bog from upland deciduous forest under leafy conditions.

Polarimetric PALSAR system parameters are assessed using data sets collected over various calibration sites. The data collected over the Amazonian forest permits validating the zero Faraday rotation hypotheses near the equator. The analysis of the Amazonian forest data and the response of the corner reflectors deployed during the PALSAR acquisitions lead to the conclusion that the antenna is highly isolated (better than -35 dB). Theses results are confirmed using data collected over the Sweden and Ottawa calibration sites. The 5-m height trihedrals deployed in the Sweden calibration site by the Chalmers University of technology permits accurate measurement of antenna parameters, and detection of 2-3 degree Faraday rotation during day acquisition, whereas no Faraday rotation was noted during night acquisition. Small Faraday rotation angles (2-3 degree) have been measured using acquisitions over the DLR Oberpfaffenhofen and the Ottawa calibration sites. The presence of small but still significant Faraday rotation (2-3 degree) induces a CR return at the cross-polarization HV and VH that should not be interpreted as the actual antenna cross-talk. PALSAR antenna is highly isolated (better than -35 dB), and diagonal antenna distortion matrices (with zero cross-talk terms) can be used for accurate calibration of PALSAR polarimetric data.

The Kennaugh-Huynen scattering matrix con-diagonalization is projected into the Pauli basis to derive a new scattering vector model for the representation of coherent target scattering. This model permits a polarization basis invariant representation of coherent target scattering in terms of five independent target parameters, the magnitude and phase of the symmetric scattering type introduced in this paper, and the maximum polarization parameters (orientation, helicity, and maximum return). The new scattering vector model served for the assessment of the Cloude-Pottier incoherent target decomposition. Whereas the Cloude-Pottier scattering type alpha and entropy H are roll invariant, beta and the so-called target-phase parameters do depend on the target orientation angle for asymmetric scattering. The scattering vector model is then used as the basis for the development of new coherent and incoherent target decompositions in terms of unique and roll-invariant target parameters. It is shown that both the phase and magnitude of the symmetric scattering type should be used for an unambiguous description of symmetric target scattering. Target helicity is required for the assessment of the symmetry-asymmetry nature of target scattering. The symmetric scattering type phase is shown to be very promising for wetland classification in particular, using polarimetric Convair-580 synthetic aperture radar data collected over the Ramsar Mer Bleue wetland site to the east of Ottawa, Ontario, Canada

Wetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, the hydrological and carbon cycles, and wildlife habitat and biodiversity. Mapping wetlands and monitoring their change in a systematic and repeatable manner for the Canadian Wetland Inventory (CWI), led by the Canadian Wildlife Service of Environment Canada (EC), are important in order to manage and protect significant wetland areas in Canada. The use of RADARSAT-1 Synthetic Aperture Radar (SAR) data has been shown to be important for wetland water extent characterization. However, the limited capability of RADARSAT-1's single-polarization C-band SAR in vegetation type discrimination makes the use of clear-sky- dependent visible near-infrared (VNIR) satellite data necessary for wetland mapping. In this paper, the unique polarimetric capability of RADARSAT-2 is investigated for wetland classification. The roll invariant incoherent target decomposition, the TSVM-ICTD [11], is used for optimum characterization of wetland target scattering. It is shown that like RADARS AT-1 HH polarization, the magnitude of the complex symmetric scattering is not effective for vegetation type discrimination. The phase of the symmetric scattering type has to be used for a more complete characterization of wetland vegetation species. This new phase scattering parameter introduced in [11] has been shown to be very promising for wetland classification using Convair-580 polarimetric SAR data.

PALSAR L-band SAR will be affected by Faraday rotation. In this study, PALSAR system is briefly described, and the Freeman calibration method is considered for PALSAR calibration. However, this method requires the deployment of a minimum of one corner reflector (CR) for the calibration of each scene, and this is not convenient in practice. In this paper, the use of human-made and natural symmetric targets is investigated for the calibration of SAR subject to Faraday rotation. The target scattering vector model (TSVM), which permits a unified decomposition of point and distributed target scattering, is used to derive a new calibration method that does not require the deployment of CRs. It is shown that the orientation (i.e. target tilt angle) and roll invariant maximum polarization parameters of symmetric target scattering can be used to measure and remove Faraday rotation and channel imbalance errors from PALSAR data. Antenna gain and cross-talk incidence angle variations are measured using data acquisitions over the Amazonian forests, under low Faraday rotation conditions.

In this paper, we briefly preview and demonstrate how the technical improvements included in RADARSAT-2 will impact the system's potential utility for 32 applications in the fields of agriculture, cartography, disaster management, forestry, geology, hydrology, oceans, and sea and land ice.

A new model, the target scattering vector model (TSVM), is introduced for decomposition of coherent scattering. The model that is inspired from Kennaugh and Huynen [1965] con-diagonalization method, Cameron and the SSCM coherent scattering decomposition [1996] represents coherent scattering of symmetric and non-symmetric targets in term of five independents parameters; the target orientation angle and four orientation invariant target parameters. The TSVM is integrated in Cloude's incoherent decomposition method to derive a general scattering decomposition method, the TSVM-coherency characteristic decomposition, which can be applied to both single and multi-look SAR data for characterization of point and distributed targets. The conditions requested for a successful application of the TSVM-coherency characteristic decomposition are discussed.

PALSAR L-band SAR is affected by Faraday rotation. In this study, PALSAR system is briefly described, and Freeman's method is considered for the calibration of PALSAR. Unless channel imbalances are measured abroad, a reference point target has to be deployed for each scene to be calibrated. For practical reasons, the use of symmetric targets is investigated for calibration and validation of polarimetric PALSAR data

A hierarchical stepwise optimization process is developed for polarimetric synthetic aperture radar image segmentation. We show that image segmentation can be viewed as a likelihood approximation problem. The likelihood segment merging criteria are derived using the multivariate complex Gaussian, the Wishart distribution, and the K-distribution. In the presence of spatial texture, the Gaussian-Wishart segmentation is not appropriate. The K-distribution segmentation is more effective in textured forested areas. The validity of the product model is also assessed, and a field-adaptable segmentation strategy combining different criteria is examined.

The symmetric scattering characterization method (SSCM) has been recently introduced for high-resolution characterization of certain targets under coherent conditions. SSCM is based on the Poincare/spl acute/ sphere representation, which supports a high-resolution decomposition of symmetric target scattering, as well as assessment and validation of the backscatter coherence. In this paper, the SSCM is investigated for ship characterization using Convair-580 polarimetric synthetic aperture radar (SAR) data. It is shown that the target Poincare/spl acute/ parameters permit identification of dominant scatterers with a significant symmetric scattering component. The polarization orientation angle of these quasi-symmetric scatterers is used to derive an estimate of the ship's pitch angle, under certain conditions. The effect of SAR system focus setting errors and Doppler centroid mistracking on the SSCM performance is investigated. It is shown that the SSCM is sensitive to the system focus setting and Doppler centroid shift. The first-order effects of these errors can be removed prior to the application of the SSCM method.

The methods currently used for classification or segmentation of polarimetric SAR images are based on the multivariate complex Gaussian model. This should limit the application of these methods to "homogeneous" Gaussian areas, since their performances are significantly degraded in the presence of spatial texture. We show that image segmentation can be viewed as a likelihood approximation problem. The optimum criterion is derived for segmentation of K-distributed textured polarimetric SAR images. The product model is assessed and applied only within areas in which the model is valid. The new method is validated for ice type segmentation using Convair-580 SAR data collected in 1993 over Cornwallis Island in Canada.

In this overview, reasons are provided on why we do need to place multi-modal, multi-band single and multiple pass POLinSAR monitoring platforms into air and space. The questions "on what POLinSAR monitoring can provide that POL-SAR and IN-SAR by themselves cannot accomplish" is assessed; whereupon facts and justifications on placing POL-IN-BISAR satellite clusters into space are presented. Reasons for this technology becoming a basic requirement for current, near-future and much more so for future all day & night year-round monitoring of the terrestrial covers are analyzed in view of the un-abating and uncontrollable terrestrial population explosion, which has, does and for ever will result in unavoidable conflicts deteriorating unfortunately at times into terrorism. The pertinent questions on how to reduce the exorbitant cost for initiating this "home-globe security protection" technology are therefore also broached, and the expected benefits are laid out. The pertinent National and International airborne and space borne multi-modal, multi-band SAR remote sensing and security conflict surveillance support agencies are herewith invited for co-sponsoring our proposal, which is timely and fleets of orbiting multi-band POLinSAR platforms are urgently required to be placed into space.

This paper reviews results from the post launch and commissioning period of ENVISAT in the alternating polarization mode of the ASAR instrument. Particular emphasis is placed on intercomparison of data from point targets deployed in Canada, and the Netherlands and differences in their information are explored.

Ship characterization is investigated using the symmetric scattering characterization method (SSCM), which was introduced by Touzi and Charbonneau (2002). The SSCM method appears to be very promising for ship identification. Identification of ship targets with significant symmetric scattering is shown to lead to accurate pitch measurement, under certain conditions.

A hierarchical stepwise optimization process is used for polarimetric SAR image segmentation. The process starts with small sets of pixels as segments and then sequentially merges the segment pair that minimises a stepwise criterion. The polarimetric information could be represented by a covariance matrix. The proposed criterion is based upon the testing of the equality of covariance matrices of adjacent regions. The segmentation of SAR images is greatly complicated by the presence of coherent speckle. We are using spatial constraints and contour shapes in order to improve the segmentation results.

In this paper, we preview and demonstrate how the technical improvements included in RADARSAT-2 will impact the system's potential utility for 32 applications in the fields of agriculture, cartography, disaster management, forestry, geology, hydrology, oceans, and sea and land ice.

Cameron's coherent target decomposition (CTD) and classification are discussed in the context of SAR, and the limitations of Cameron's classification are examined. It is shown that these methods may lead to a coarse and misleading scattering segmentation because of the large radiometric dispersion tolerated in each of the elemental scatterer classes, as well as the implicit assumption on the coherence nature of target scattering. A new method, named the symmetric scattering characterization method (SSCM), is introduced to better exploit the information provided by the largest target symmetric scattering component, under coherent conditions. The SSCM, which expressed the symmetric scattering in term of the Poincare sphere angles, permits a better characterization of target symmetric scattering and the generation of coherent scattering segmentation of much higher resolution, in comparison with Cameron's segmentation.

Speckle filter performance depends strongly on the speckle and scene models used as the basis for filter development. These models implicitly incorporate certain assumptions about speckle, scene, and observed signals. In this study, the multiplicative and the product speckle models, which have been used for the development of most of the well-known filters, are analyzed, and their implicit assumptions with regard to the stationarity-nonstationarity nature of speckle are discussed. This leads to the definition of two categories of speckle filters: the stationary and the nonstationary multiplicative speckle model filters. The various approximate models used for the multiplicative speckle noise model are assessed as functions of speckle and scene characteristics to derive the requirements on scene signal variations for the validity of both the stationary and nonstationary multiplicative speckle models. Speckle filtering is then studied in the context of estimation theory, so as to develop a procedure for speckle filtering. It is shown that speckle filtering can be effective only in locally stationary scenes. Regions in which the signals are not stationary have to be filtered separately using a priori scene templates for the best matching of nonstationary scene features. The use of multiresolution techniques is crucial for accurate estimation of filter parameters. Under the guidance of the speckle filtering procedure, structural-multiresolution versions of the Lee (1980) and Frost et al. (1982) filters are developed for optimum application of these filters in the context of nonstationary scene signals.

Cameron's coherent target decomposition (CTD) theory and the classification method that Cameron developed for operational use of his CTD are reconsidered. It is shown that Cameron's classification leads to a coarse scattering segmentation because of the large class dispersion that corresponds to a synthetic aperture radar (SAR) system with about /spl plusmn/8-dB channel imbalance. The application of Cameron's method within known SAR radiometric calibration requirements limits the utility of the classification. In addition, Cameron's classification is applied under the implicit assumption on the coherence nature of target scattering, and this might yield erroneous results within areas of noncoherent scattering. A new method, named the symmetric scattering characterization method (SSCM), is introduced to better exploit the information provided by the largest target symmetric scattering component in the context of coherent scattering. The Poincare/spl acute/ sphere is used as the basis for a more complete representation of symmetric scattering than Cameron's unit disk, thus enabling the SSCM to generate better segmentation of target symmetric scattering with much higher resolution. In order to limit the application of the SSCM to targets of coherent scattering, new methods are developed for assessment and validation of the coherent nature of point and extended target scattering.

In dual- or multiple-channel synthetic aperture radar (SAR) imaging modes, cross-channel correlation is a potential source of information. The sample coherence magnitude is calculated over a moving window to generate a coherence magnitude map. High-resolution coherence maps may be useful to discriminate fine structures. Coarser resolution is needed for a more accurate estimation of the coherence magnitude. In this study, the accuracy of coherence estimation is investigated as a function of the coherence map resolution. It is shown that the space-averaged coherence magnitude is biased toward higher values. The accuracy of the coherence magnitude estimate obtained is a function of the number of pixels averaged and the number of independent samples per pixel (i.e., the coherence map resolution). A method is proposed to remove the bias from the space-averaged sample coherence magnitude. Coherence magnitude estimation from complex (magnitude and phase) coherence maps is also considered. It is established that the magnitude of the averaged sample coherence estimate is slightly biased for high-resolution coherence maps and that the bias reduces with coarser resolution. Finally, coherence estimation for nonstationary targets is discussed. It is shown that the averaged sample coherence obtained from complex coherence maps or coherence magnitude maps is suitable for estimation of nonstationary coherence. The averaged sample (complex) coherence permits the calculation of an unbiased coherence estimate, provided that the original signals can be assumed to be locally stationary over a sufficiently coarse resolution cell.

Barakat [1987] derived the Stokes parameter statistics, applicable to one-look synthetic aperture radar (SAR) images, of a partially polarized wave backscattered from a Gaussian area. In this paper, the statistics of the Stokes parameters and of the phase difference are derived as a function of the mean effective phase difference and the degree of coherence for one-look and multilook SAR data. The statistics of the degree of coherence are also derived for multilook SAR data. It is shown that the estimator currently used for calculation of the degree of coherence is biased under low coherence conditions.

The principle of speckle reduction in polarimetry is reconsidered. It is shown that polarimetric data can be speckle reduced if and only if all the elements of the Mueller matrix are filtered, which is equivalent to filtering the scattering vector covariance matrix. Assuming that speckle is multiplicative and stationary, the algorithms proposed by S.L.Lee et al. (1991) and S.Goze et al. (1993) are extended to filter the covariance matrix of reciprocal and nonreciprocal targets on one-look and multilook images. The problem of estimation of the first- and second-order statistics of the four-channel speckle vector is discussed, and a solution is proposed for one-look and multilook images.>

A general polarimetric model for orbital and Earth synthetic aperture radar (SAR) systems that explicitly includes key radar architecture elements and is not dependent on the reciprocity assumption is developed. The model includes systems whose receiving configuration is independent of the transmitted polarization (one configuration), as well as systems with two distinct receiving configurations, depending on the commanded transmitted polarization (H or V). Parameters that are independent of target illumination angle and those with illumination angle dependence are considered separately, allowing calibration approaches which are valid for targets at different illumination angles. The calibration methods presented make use of the model linearity to provide tests for the radar model accuracy and for SAR data quality. X-band polarimetric SAR are used to validate the theory and illustrate the calibration approach. The extension of the model and calibration method to other radar systems is discussed.>

The peak method currently used for the phase measurement of a point target signal, which takes the phase of the peak reflector response as the signal phase estimate, is analyzed and shown to be sensitive to focus. A novel method based on the integration of complex data is proposed for the extraction of signal parameters of a point target in the presence of clutter. This method, called the complex integration method, is shown to be nearly insensitive in both phase and magnitude to processor focus.>

A method is developed for optimizing the degree of polarization of a partially polarized wave reflected by a nonstationary scattering object. The method permits, for a scattered wave and a given target characterized by its Mueller matrix, analytic computation of the maximum and minimum values of the degree of polarization, and the corresponding transmitted polarizations. A procedure for the optimization of the scattered wave intensity is also proposed. The degree of polarization and the total scattered intensity extrema are then analyzed experimentally on JPL data. It is shown that several entities such as the received intensity extrema, the coefficient of variation, the fractional polarization and the span, which are currently used for target discrimination, can be deduced from combinations of the maximum and minimum values of the degree of polarization and the scattered wave intensity. Finally, a classification of the San Francisco image, based on these indices, is conducted for a better understanding of the specific physical meaning of each index.>