Si-Wei Chen

Tsunami Damage Investigation of Built-Up Areas Using Multitemporal Spaceborne Full Polarimetric SAR Images

This paper explores the use of full polarimetric synthetic aperture radar (PolSAR) images for tsunami damage investigation from the polarimetric viewpoint. The great tsunami induced by the earthquake of March 11th, 2011, which occurred beneath the Pacific off the northeastern coast of Japan, is adopted as the study case using the Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar multitemporal PolSAR images. The polarimetric scattering mechanism changes were quantitatively examined with model-based decomposition. It is clear that the observed reduction in the double-bounce scattering was due to a change into odd-bounce scattering, since a number of buildings were completely washed away, leaving relatively a rough surface. Polarization orientation (PO) angles in built-up areas are also investigated. After the tsunami, PO angle distributions from damaged areas spread to a wider range and fluctuated more strongly than those from the before-tsunami period. Two polarimetric indicators are proposed for damage level discrimination at the city block scale. One is the ratio of the dominant double-bounce scattering mechanism observed after-tsunami to that observed before-tsunami, which can directly reflect the amount of destroyed ground-wall structures in built-up areas. The second indicator is the standard deviation of the PO angle differences, which is used to interpret the homogeneity reduction of PO angles. Experimental results from after- and before-tsunami comparisons validate the efficiency of these indexes, since the built-up areas with different damage levels can be well discriminated. In addition, comparisons between before-tsunami pairs further confirm the stability of the two polarimetric indexes over a long temporal duration. These interesting results also demonstrate the importance of full polarimetric information for natural disaster assessment.

General Polarimetric Model-Based Decomposition for Coherency Matrix

Orientation angle compensation was incorporated into model-based decomposition to cure overestimation of the volume scattering contribution for interpretation of polarimetric synthetic aperture radar (PolSAR) data. The compensation is based on rotating the coherency matrix to minimize the cross-polarization term. However, this processing cannot always guarantee that the double- and odd-bounce scattering components will be rotated back to zero orientation angle and left with zero cross-polarization power. As a result, built-up patches with large orientation angles may still suffer from the scattering mechanism ambiguity. In this paper, double- and odd-bounce scattering models were generalized to fit the cross-polarization and off-diagonal terms, by separating their independent orientation angles. A general decomposition framework is proposed that utilizes all elements of a coherency matrix. The residual minimization criterion is used for model inversion. All the model parameters are simultaneously obtained using a nonlinear least squares optimization technique. The manual intervention, branch conditions, and negative power issues are avoided. The performance and advantages of this approach are demonstrated and evaluated with spaceborne L-band ALOS/PALSAR and airborne X-band Pi-SAR PolSAR data sets. Comparison studies are also carried out and demonstrate that further improved decomposition performance is achieved by the proposed method, especially in oriented built-up areas.

Deorientation Effect Investigation for Model-Based Decomposition Over Oriented Built-Up Areas

Deorientation processing has been incorporated into model-based decomposition to cure the overestimation of volume scattering contribution, by rotating the coherency matrix to minimize the cross-polarization term. First, the derivation of the rotation angle is clarified for avoiding the ambiguity. Moreover, even with the implementation of deorientation processing, oriented built-up areas with large orientation angles are still misjudged as volume scattering dominant. Further to the investigation of the deorientation effect, we focus on oriented built-up patches. A parameter, named dominant polarization orientation angle (DPOA), is introduced to label each patch. The behavior of the deorientation on coherency matrix and model-based decomposition over purely oriented built-up areas with respect to DPOA is disclosed. Experimental studies from the Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) polarimetric SAR data set demonstrate that model-based decompositions with deorientation work well for oriented built-up areas when |DPOA| ≤ 22.5°. However, for large |DPOA| (e.g., |DPOA| >; 22.5°), even with the deorientation processing, for the conventional decompositions which assume that only the volume scattering contributes to the cross-polarization term, the decomposed volume scattering power may also be dominant even for purely oriented built-up areas. Thereby, misinterpretation still occurs, motivating further advancements.

Polarimetric SAR Analysis of Tsunami Damage Following the March 11, 2011 East Japan Earthquake

The earthquake and tsunami of March 11, 2011 killed more than 15 000 people in Eastern Japan. The importance of remote sensing in understanding the damage caused by natural disasters is quite significant, and many data sets were acquired after the events. In this paper, we demonstrate the importance and the potential of full polarimetric synthetic aperture radar (SAR) images for damage assessment. Full polarimetric SAR images acquired by the spaceborne ALOS/PALSAR system from the Japan Aerospace Exploration Agency (JAXA) on November 21, 2010 and April 8, 2011 and acquired by the airborne Pi-SAR2 system from the National Institute of Information and Communications Technology (NICT) on March 12 and 18, 2011 are used for this analysis. Model-based decomposition is applied and clearly shows the scattering mechanism changes at the seriously damaged downtown of Ishinomaki city and the flooded areas near the main stream of the Kitakami River. Polarization orientation angle is estimated to provide additional information to understand the damage effect in the built-up areas. Eigenvalue-eigenvector-based decomposition analysis is also employed to further confirm the scattering mechanism changes of the flooded areas. ALOS/PALSAR does not have fine enough resolution; however, the difference of the scattering mechanisms is sufficient to identify the damaged and flooded areas. In addition, the Pi-SAR2 data sets are used to analyze the flooded paddy fields in Natori city. The relative backscattering values are compared with the multitemporal images and the cross-polarization component (HV) is observed to be more sensitive to the flooded boundary. The automatically detected flooding maps using the cross-polarization component were found to provide relatively accurate results.

Modeling and Interpretation of Scattering Mechanisms in Polarimetric Synthetic Aperture Radar: Advances and perspectives

Recent advances in scattering modeling and model-based decomposition theorem were reviewed. The notable achievements include orientation compensation processing, nonnegative eigenvalue constraint, generalized scattering models, complete information utilization, full-parameter inversion strategy, and the polarimetric-interferometric decomposition scheme. These advances contribute to make scattering models more adaptive, better fit observations and guarantee physically meaningful decomposition solutions. The key features of these advances have been summarized. Performance evaluation and further development perspectives were also discussed. One promising way is to fuse multiple data to better model scattering mechanisms, such as the polarimetric-interferometric modeling attempts. Besides, with the progress in PolSAR sensors, imaging modes (e.g., bistatic, hybrid-polarization and multi-incident-angle modes) and application requirements, the development of specific scattering mechanism interpretation techniques, multiangular decomposition, and compact/hybrid decomposition techniques are also highly preferred.

PolInSAR Complex Coherence Estimation Based on Covariance Matrix Similarity Test

Most polarimetric synthetic aperture radar interferometry (PolInSAR) data processing procedures and their applications are based on the polarimetric complex coherence descriptor. The reliable estimation of the complex coherence requires selecting sufficient homogeneous pixels for generating an unbiased estimator. In this paper, two indicators using only polarimetric and both polarimetric and interferometric information are derived as the similarity measures for complex Wishart distributed PolInSAR covariance matrix, respectively. Using these indicators, a double similarity test scheme, which shows high sensitivity to both polarimetric and interferometric properties, is proposed for similar pixel selection. The full information utilization could characterize the homogeneous pixels more accurately. Furthermore, since the similarity test has the potential to reject the pixels with different populations, it is suitable to be applied in a large searching area (e.g., 15 × 15 window) to accept sufficient homogeneous pixels. Thereby, combining with unbiased estimator, reliable estimation is achieved. The efficiency and advantage of the proposed estimation scheme are demonstrated with the aid of simulated and real PolInSAR data sets.

Adaptive Model-Based Polarimetric Decomposition Using PolInSAR Coherence

The overestimation of volume scattering power and the scattering mechanism ambiguity are still present in model-based decompositions even with the implementation of the deorientation processing. These effects are demonstrated and investigated. One possible reason is because of the limited dynamic range of the models themselves that are not fully satisfied for the mixed scene cases. An empirical volume scattering model is proposed, using the repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) coherence, to extend the model dynamic range to be more adaptive. PolInSAR coherence is sensitive to different types of forests and terrains. The proposed model inherits these characteristics. In addition, it considers the cross-polarization power induced by oriented man-made structures. Thereby, a model-based polarimetric decomposition scheme is developed. The efficiency of the proposed method is demonstrated using E-SAR airborne and ALOS/PALSAR spaceborne repeat-pass PolInSAR datasets. Comparative experiments are carried out and show that the proposed decomposition overcomes the scattering mechanism ambiguity between forests and oriented built-up areas, since it successfully identifies the oriented buildings as double- or odd-bounce man-made structures while keeping the volume scattering dominant for the forests. Besides, the stable decomposition performance over the oriented built-up patches with quite different orientation angles also validates the improvement of the proposed decomposition. In addition, the demonstrations with short and long temporal baselines validate the generality of the proposed method.

Uniform Polarimetric Matrix Rotation Theory and Its Applications

This paper presents the development of a uniform polarimetric matrix rotation theory in the rotation domain along the radar line of sight for polarimetric synthetic aperture radar (PolSAR) data interpretation. The uniform representation of each coherency matrix element is a sinusoidal function in the rotation domain. A set of oscillation parameters, including oscillation amplitude, oscillation center, angular frequency, and initial angle, is proposed to fully characterize the scattering behavior in the rotation domain. A set of rotation angle parameters, including stationary angle, null angle, and minimization/maximization angles, is derived to indicate specific states of the rotation property. The rotation relationships between the coherency and covariance matrices with linear and circular polarization bases are established. A look-up table for these parameters is provided, and their physical meanings are interpreted. These derived parameters directly link to the Huynen parameters. Therefore, the proposed theory has the ability to achieve a desired state of one Huynen parameter by rotating the polarimetric matrix at a designated rotation angle. This theory also generalizes both the classic polarization orientation angle originally derived from the covariance matrix in a circular polarization basis and the deorientation theory developed from the minimization of the cross-polarization term. The roll-invariant terms have also been summarized. Finally, multifrequency Pi-SAR and AIRSAR PolSAR data sets are used to demonstrate the derived parameters. One oscillation amplitude parameter has been verified to be especially suitable for characterization of oriented man-made targets. Two angle parameters are sensitive to the reflection symmetry condition and crop types. Therefore, a simple unsupervised classification scheme has been developed and demonstrated. Further utilization perspectives of the proposed theory have been discussed.

Urban Damage Level Mapping Based on Scattering Mechanism Investigation Using Fully Polarimetric SAR Data for the 3.11 East Japan Earthquake

A quick response to a large-scale natural disaster such as earthquake and tsunami is vital to mitigate further loss. Remote sensing, especially the spaceborne sensors, provides the possibility to monitor a very large scale area in a short time and with regular revisit circle. Damage ranges and damage levels of the destructed urban areas are extremely important information for rescue planning after an event. Rapid mapping of the urban damage levels with synthetic aperture radar (SAR) is still challenging. Compared with single-polarization SAR, fully polarimetric SAR (PolSAR) has a better potential to understand the urban damage from the viewpoint of scattering mechanism investigation. In radar polarimetry, the dominant double-bounce scattering mechanism in an urban area is primarily induced by the ground-wall structures and can reflect the changes of these structures. In this sense, urban damage level in terms of destroyed ground-wall structures can be indicated by the reduction of the dominant double-bounce scattering mechanism, which is the basis of this study. This work first establishes and validates the linear relationship between the urban damage level and the proposed polarimetric damage index using polarimetric model-based decomposition. Then, efforts are focused on the development of a rapid urban damage level mapping technique which mainly includes two steps of urban area extraction and polarimetric damage level estimation. The 3.11 East Japan earthquake and tsunami inducing great-scale destruction are adopted for study using L-band multitemporal spaceborne PolSAR data. Experimental studies demonstrate that the estimated damage levels are closely consistent to the ground-truth. The final urban damage level map for the full scene is generated thereafter. Results achieved in this study further validate the necessity of exploring fully polarimetric technique for damage assessment.

General polarimetric model-based decomposition for coherency matrix

Orientation angle compensation was incorporated into model-based decomposition to cure overestimation of the volume scattering contribution for interpretation of polarimetric synthetic aperture radar (PolSAR) data. The compensation is based on rotating the coherency matrix to minimize the cross-polarization term. However, this processing cannot always guarantee that the double- and odd-bounce scattering components will be rotated back to zero orientation angle and left with zero cross-polarization power. As a result, built-up patches with large orientation angles may still suffer from the scattering mechanism ambiguity. In this paper, double- and odd-bounce scattering models were generalized to fit the cross-polarization and off-diagonal terms, by separating their independent orientation angles. A general decomposition framework is proposed that utilizes all elements of a coherency matrix. The residual minimization criterion is used for model inversion. All the model parameters are simultaneously obtained using a nonlinear least squares optimization technique. The manual intervention, branch conditions, and negative power issues are avoided. The performance and advantages of this approach are demonstrated and evaluated with spaceborne L-band ALOS/PALSAR and airborne X-band Pi-SAR PolSAR data sets. Comparison studies are also carried out and demonstrate that further improved decomposition performance is achieved by the proposed method, especially in oriented built-up areas.