Polarization Orientation Angle Research Articles

Fast building damage mapping using a single post-earthquake PolSAR image: a case study of the 2010 Yushu earthquake

Earthquakes are one of the most destructive natural disasters. Efficiently and quickly acquiring building earthquake damage information can help to reduce the casualties after an earthquake. In this paper, for convenience, speed, and precision, building damage information is extracted using a single post-earthquake PolSAR image. In PolSAR images, the undamaged parallel buildings characterized by double-bounce scattering are different from the collapsed buildings characterized by volume scattering, but the undamaged oriented buildings are very similar to collapsed buildings because of their scattering mechanism ambiguity in the early traditional model-based decomposition. Therefore, the collapsed buildings are difficult to extract accurately. In this paper, the scheme of polarization orientation angle (POA) compensation is employed to enhance the double-bounce scattering power of the oriented buildings, and the difference in the relative contribution change rate of scattering components before and after POA compensation is proposed to further enhance the difference between collapsed buildings and oriented buildings, in order that the collapsed buildings can be extracted more accurately. The “4.14” Yushu earthquake, which occurred in Yushu County, Qinghai province of China, is used as the case study to test the proposed method, and an airborne high-resolution PolSAR image of the urban region of Yushu County is used in the experiment. The experimental results show that the accuracy of building damage information extraction can be improved by the use of the proposed method, compared with the traditional polarimetric classification.

Analysis of Orientation Angle Shifts on the Polarimetric Data Using Radarsat2 Images

Polarization orientation angle (POA) shifts induced by the variations of range and azimuth slopes cause the polarization to rotate about the radar line of sight. Their existence reduces the accuracy measurement of geophysical parameters from polarimetric synthetic aperture radar (PolSAR) images and may generate erroneous scattering characteristics that could be misinterpreted. In real situations, terrain slopes rotate the polarization basis of the polarimetric scattering matrices by an orientation angle shift, and induce significant cross-polarization power. Consequently, it is desirable to compensate the data for the orientation effect before applying scattering model-based decompositions. In this paper, we investigate the compensation effect on the elements of the coherency matrix using the orientation angle extracted from circular polarization technique and from the copolarization signature applied to building areas. The effect of this compensation is that the volume scattering power is consistently decreased, while the double-bounce power is increased. The surface and helix scattering powers are roll invariant. Comparing both methods, we find that the circular polarization algorithm gives mostly the best results except for some targets. In this way, a combined use of both algorithms has been proposed to choose an optimum orientation angle, which can be used directly to compensate POLSAR data to ensure improvement in the overall polarimetric decomposition and classification. We illustrate our results using the polarimetric SAR images acquired on the Algiers city by the RadarSAT2 (FQ19) in C-band.

Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image

After an earthquake, rapidly and accurately obtaining building damage information can help to effectively guide the implementation of the emergency rescue and can reduce disaster losses and casualties. Using a single post-earthquake fully-polarimetric synthetic aperture radar (PolSAR) image to interpret building damage information not only involves a guaranteed data source but is also easy and can be rapidly implemented. This paper is focused on rapid building earthquake damage detection in urban areas using post-earthquake PolSAR data. In PolSAR images, the undamaged buildings parallel to satellite flight pass are different from the collapsed buildings, but the undamaged buildings divergent to satellite flight pass are very similar to collapsed buildings because of their volume scattering characteristics. In this paper, the method of polarization orientation angle (POA) compensation is employed to increase the scattering power of buildings divergent to satellite flight pass, and then Wishart supervised classification is implemented on the PolSAR data after POA compensation. In addition, the two parameters of normalized difference of the dihedral component (NDDC) and ρHHHV are proposed to improve the classification accuracy of the Wishart supervised classification, and both the undamaged buildings and collapsed buildings are determined. The study was carried out after the “4.14” Yushu earthquake in Yushu County, Qinghai province, China. The three damage levels are set for the urban area at the city block scale according to the values of the BBCR building damage index. The experimental results confirm that the scheme proposed in this paper can greatly improve the accuracy of the extraction of building damage information.

Terrain and Surface Modeling Using Polarimetric SAR Data Features

Topography and surface slope variations affect perceived scattering polarization state of imaged targets in polarimetric synthetic aperture radar (PolSAR) applications. Accurate modeling of such effects can be used for both polarimetric data correction (e.g., better target classification) and topographic feature extraction. A framework is established in this paper to model target topography based on analytic relation between surface slopes and PolSAR data and imagery products (polarization orientation angle rotation, in particular). The developed formalism provides both forward, i.e., polarization rotation from topography, and inverse, i.e., terrain slopes from PolSAR data, solutions. The synthetic aperture radar (SAR) imaging scenario or mode is assumed to be general with arbitrary parameters (e.g., squint angle) and includes multi-SAR sensors for target terrain modeling.

Polarimetric SAR Data Correction and Terrain Topography Measurement Based on the Radar Target Orientation Angle

Topographic variations caused by the range and the azimuth terrain slopes induce polarization orientation changes which cause the polarization to rotate about the line of sight. The existence of these variations reduce the accuracy measurement of geophysical parameters from polarimetric synthetic aperture radar (PolSAR) images. For this reason most inversion studies are best done in area of flat earth. In area which has significant terrain variations require compensation for topography. In real situations, terrain slopes rotate the polarization basis of the polarimetric scattering matrices by an orientation angle shift, and induce significant cross-polarization power. In this paper, two methods have been investigated using the polarimetric orientation angle (PAO): the first one involves the rotation of the polarimetric scattering and coherency matrices to achieve maximum azimuthally asymmetry for polarimetric data compensation to ensure accurate estimation of geophysical parameters in rugged terrain areas. The second approach has been developed which measures azimuth and range terrain slopes that are related to shifts in polarization orientation angle. Terrain elevation maps relative to a plane parallel to the radar line of sight can then be generated by integrating these slopes requiring only one PolSAR flight pass by combing orientation angle estimation and a shape-from-shading technique (SFS) which is mostly used by the computer vision community. Experimental results with C-band polarimetric RADARSAT2 data are used evaluate the data compensation algorithm and DEM generation.

Amplitude- and Phase-Controlled Surface Plasmon Polariton Excitation with Metasurfaces

Surface plasmon polaritons (SPPs) have shown high potential for various applications in various fields, ranging from physics, chemistry, and biology to integrated photonic circuits due to their the strong confinement of light to the metal surface. Exciting an SPP from a free-space photon in a controllable manner is an essential step toward more complex and integrated applications. Methods for coupling photons to SPPs are numerous, but in order to control the amplitude and phase of an SPP, most of these methods require bulky or multiple optical components or sensitive adjustments that are difficult to control. Here we present a novel approach for an independent control of the amplitude and phase of an SPP excited by a normally incident beam using a metasurface. The full control in amplitude and phase is achieved via the polarization state and polarization orientation angle of the electrical field of the incoming light. We experimentally demonstrate the functionality of such a metasurface consisting of peri...

Polarimetric Calibration of CASMSAR P-Band Data Affected by Terrain Slopes Using a Dual-Band Data Fusion Technique

For airborne synthetic aperture radar (SAR) polarimetric calibration (PolCAL) based on distributed targets, it is important to ensure the removal of both the polarimetric distortion and terrain slope effect. This paper proposes a new technique for PolCAL in mountainous areas, without the use of corner reflectors (CRs). The technique based on dual-band data fusion consists of two steps. First, the polarization orientation angle shift (POAS), as a priori asymmetry information, is derived from X-band interferometry and applied to P-band fully-polarimetric data. Second, the crosstalk and cross-polarization (cross-pol) channel imbalance are iteratively determined using the POAS after dual-band data fusion. The performance and feasibility of the technique was evaluated by CRs. It was demonstrated that the proposed technique is capable of deriving the distortion parameters and performs better than the methods presented in Quegan and Ainsworth et al. The signal-to-noise ratio (SNR) and pedestal height have been investigated in polarimetric signatures. The proposed technique is useful for PolCAL in mountainous areas and for monitoring systems without CRs in long-term operation.

Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance

Model-based decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition which assumes the target to be reflection symmetric was later relaxed in the Yamaguchi et al. decomposition with the addition of the helix parameter. Since then many decomposition have been proposed where either the scattering model was modified to fit the data or the coherency matrix representing the second order statistics of the full polarimetric data is rotated to fit the scattering model. In this paper we propose to modify the Yamaguchi four-component decomposition (Y4O) scattering powers using the concept of statistical information theory for matrices. In order to achieve this modification we propose a method to estimate the polarization orientation angle (OA) from full-polarimetric SAR images using the Hellinger distance. In this method, the OA is estimated by maximizing the Hellinger distance between the un-rotated and the rotated $T_{33}$ and the $T_{22}$ components of the coherency matrix $\mathbf{[T]}$. Then, the powers of the Yamaguchi four-component model-based decomposition (Y4O) are modified using the maximum relative stochastic distance between the $T_{33}$ and the $T_{22}$ components of the coherency matrix at the estimated OA. The results show that the overall double-bounce powers over rotated urban areas have significantly improved with the reduction of volume powers. The percentage of pixels with negative powers have also decreased from the Y4O decomposition. The proposed method is both qualitatively and quantitatively compared with the results obtained from the Y4O and the Y4R decompositions for a Radarsat-2 C-band San-Francisco dataset and an UAVSAR L-band Hayward dataset.

URBAN AREA EXTRACTION USING AIRBORNE X-BAND FULLY POLARIMETRIC PI-SAR2 IMAGERY

Abstract. In this paper, we present a method to extract urban areas from X-band fully polarimetric synthetic aperture radar (SAR) data. It is known that very high resolution (VHR) SAR can extract buildings, but it requires more processes to map urban areas that should include other objects. The proposed method is mainly composed of two classifications. One classification uses total power of scattering and volume scattering derived by using four component decomposition method with correction of the polarization orientation angle (POA) effect. The other classification uses polarimetric coherency between SHH and SVV . The two results are intersected and final urban areas are extracted after post-classification processing. We applied the proposed method to airborne X-band fully polarimetric SAR data of Polarimetric and Interferometric Airborne Synthetic Aperture Radar System (Pi-SAR2), developed by the National Institute of Information and Communications Technology (NICT), Japan. The validation show that the results of the proposed method were acceptable, with an overall accuracy of approximately 80 to 90% at 100-m spatial scale.

Automatic GCP Extraction in Mountainous Areas Using DEM and PolSAR Data

Mountainous areas in synthetic aperture radar (SAR) images suffer severe geometric distortions caused by different look directions. Consequently, ground control point (GCP) extraction hardly obtains accurate results for aircraft positioning. Based on the digital elevation model (DEM) and polarimetric SAR (PolSAR) data, we propose a method for extracting GCPs in mountainous areas by introducing the polarization orientation angle shift (POAS) to minimize geometric distortions. In this method, DEM data are used as the reference map by providing POASs at arbitrary look directions to make up for the look-direction sensitivity of POASs transformed from PolSAR data. The geometric distortions between POASs transformed from DEM and PolSAR data are effectively reduced by calculating the POASs from DEM data at the same look direction and look angles of the PolSAR data. In contrast to the SAR data, which have a large dynamic range, the values of POAS are limited to a small interval. Therefore, the illumination distortions induced by visualization can be reduced. Finally, the GCP extraction between the POAS images is conducted by bilateral filter scale-invariant feature transform. Experiments using various data at different look directions demonstrate that the proposed method obtains better-quality GCPs but less invalid keypoints than the method using only intensity images for mountainous areas.

Urban density mapping of global megacities from polarimetric SAR images

We propose an algorithm for estimating urban density from polarimetric synthetic aperture radar (SAR) images, and compare the urban density patterns of global megacities. SAR images are uniquely able to detect structural information of objects, but they are very sensitive to orientation angle. This issue has been an obstacle to applying SAR images to urban areas. Kajimoto and Susaki (2013b) proposed an algorithm to handle this issue. The effects of polarization orientation angle (POA) are removed by rotating the coherency matrix and then calculating the mean and standard deviation of scattering power by POA domain. The algorithm can estimate urban density from a single fully polarimetric SAR image but has the drawback that the generated urban density maps of multiple images are not comparable with each other because the algorithm generates a relative urban density valid only within the analyzed image. We therefore extend the method by calculating POA-domain statistics from all images of interest so that the generated maps can be compared. Estimated urban densities are assessed on two types of urban density generated from GIS data, building-to-land ratio and floor-area ratio. We demonstrate that the extended method can estimate urban density with reasonable accuracy. Finally, we generate two scattergrams of indices derived from urban density maps of global megacities. An analysis using the scattergrams indicates insightful information about the patterns of urban development. We conclude that the proposed algorithm and the analysis using the obtained results are beneficial to understanding the conditions in megacities.

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.

Generalized Polarimetric Model-Based Decompositions Using Incoherent Scattering Models

The model-based scattering decomposition pioneered by Freeman and Durden has stimulated research in characterizing polarimetric synthetic aperture radar (PolSAR) scattering phenomenon and its applications. The Freeman and Durden decomposition as originally developed is based on three scattering models for volume, surface, and double bounce. It is known that the decomposition often produces negative scattering powers for a large number of pixels. This implies that the scattering models are inconsistent with the data. In this paper, we investigate the model deficiency problem and propose several algorithms to mitigate it. To achieve this, we developed an incoherent scattering model based on the polarization orientation angle distribution of phase differences. Two approaches are taken to reduce the number of negative power pixels: 1) adopt a volume scattering model by including variable shape factor while keeping the original surface and double bounce models unchanged, and 2) incorporate the incoherent surface or double bounce model while keeping the original volume model. In addition, the combination of 1) and 2) is explored, and the effect of polarization orientation compensation on these algorithms is investigated. The effectiveness of these approaches is compared using L-band AIRSAR and E-SAR PolSAR data. It will be shown that model efficiency is improved with occurrence of negative power reduced to an insignificant level.

Method for enhancing visibility of hazy images based on polarimetric imaging

A novel polarimetric dehazing method is proposed based on three linear polarization images (0°, 45°, and 90°). The polarization orientation angle of the light scattered by the haze particles is introduced in the algorithm. No additional image-processing algorithm is needed in the postprocessing. It is found that the dehazed image suffers from little noise and the details of the objects close to the observer can be preserved well. In addition, this algorithm is also proved to be useful for preserving image colors. Experimental results demonstrate that such an algorithm has some universality in handling all kinds of haze. We think that this robust algorithm might be very suitable for real-time dehazing.

Urban Density Estimation From Polarimetric SAR Images Based on a POA Correction Method

In this paper, an algorithm for estimating urban density from polarimetric synthetic aperture radar (SAR) images is proposed. Polarization orientation angle (POA) and four power components derived by four-component decomposition are used in the algorithm. In particular, in urban areas, SAR data are generally affected by factors such as the interval between buildings, building height, and building azimuth angle. Here, building azimuth (orientation) angle means the relative azimuth between the wall normal and the radar's ground range direction. The interval between buildings and building height are used for building density calculation such as the building-to-land ratio and the floor area ratio. However, building azimuth angle which depends on satellite orbit has almost no relation with building density. The scattering intensity of microwaves emitted from SAR has a strong dependence on this building azimuth angle. Therefore, the main part of this paper is focused on the correction of this angular effect. The first step in the POA correction method is the extraction of homogeneous-POA city districts. In the second step, each power component's scattering intensity is normalized for all pixels in a particular POA interval separately for different POA types of districts. In the case of Tokyo metropolitan area, Japan, estimated urban density from ALOS/PALSAR data has correlation coefficients of nearly 0.7 with the building-to-land ratio and 0.5 with the floor area ratio on the scale of hundreds of meter. In the areas where strong POA dependence is seen, the improvement of the correlation coefficient runs up to approximately 0.2.

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.

Urban-Area Extraction From Polarimetric SAR Images Using Polarization Orientation Angle

In this letter, an algorithm is proposed that robustly extracts urban areas from polarimetric synthetic aperture radar images. Polarization orientation angle (POA), volume scattering power (Pv) derived by four-component decomposition, and total power (TP) are utilized in the proposed algorithm. The dependence of the four decomposition components on POA can be lessened by rotating the elements of the coherency matrix by the POA. However, a level of POA dependence remains even after the correction. The proposed algorithm utilizes POA-corrected components, but pixels are grouped into several categories according to POA. First, urban and farmland training data are selected for each category in a study area. Then, urban and mountain areas are separated from farmland, bare ground, and sea by utilizing the Pv-TP scattergram. Finally, a measure of the POA randomness between neighboring pixels is used to discriminate between urban areas with nearly homogeneous POA and mountain areas with randomly distributed POAs. When performing classification on more than one study area, thresholds manually selected for one of the study areas are used to automatically estimate thresholds for the other areas. An accuracy assessment demonstrates that POA-based categorization and utilization of POA randomness contribute to improving classification accuracy.

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 ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">POA</sub> ), 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 <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">POA</sub> 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 | <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">POA</sub> | ≤ 22.5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> . However, for large | <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">POA</sub> | (e.g., | <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">POA</sub> | >; 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.

AN IMPROVED SAR RADIOMETRIC TERRAIN CORRECTION METHOD AND ITS APPLICATION IN POLARIMETRIC SAR TERRAIN EFFECT REDUCTION

A new SAR radiometric terrain correction method was proposed to reduce the terrain efiects in sloped regions. Based on this method, a procedure for polarimetric SAR terrain efiect reduction was proposed, including geometric correction, shadow detection, radiometric terrain correction, and polarization orientation angle shift compensation. Experiments using RADARSAT-2 polarimetric SAR data of the Three Gorges Area, China demonstrated the efiectiveness of the proposed radiometric terrain correction method. Both visual and quantitative analyses showed that after the proposed radiometric terrain correction method was applied, the contrast between difierent slopes that caused by local incidence angle difierences, foreshortening, and layover was signiflcantly reduced. The difierence of backscattering intensity on slopes facing the radar sensor and facing away from the sensor was reduced from 12.5dB before radiometric correction to 1.3dB. The overall accuracy of land use/land cover classiflcation was improved by 11.2 percent using the terrain corrected polarimetric SAR data.

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.