We assess the performance of synthetic aperture radar (SAR) compact polarimetry architectures based on mixed basis measurements, where the transmitter polarization is either circular or orientated at 45/spl deg/(/spl pi//4), and the receivers are at horizontal and vertical polarizations with respect to the radar line of sight. An original algorithm is proposed to reconstruct the full polarimetric (FP) information from this architecture. The performance assessment is twofold: it first concerns the level of information preserved in comparison with FP, both for point target analysis and crop fields classification, using L-band SIRC/XSAR images acquired over Landes forest and Jet Propulsion Laboratory AIRSAR images acquired over Flevoland. Then, it addresses the space implementation complexity, in terms of processed swath, downloading features, power budget, calibration, and ionospheric effects. The polarization uniqueness in transmission of this mixed basis mode, hereafter referred to as the /spl pi//4 mode, maintains the standard lower pulse repetition frequency operation and hence maximizes the coverage of the sensor. Because of the mismatch between transmitter and receiver basis, the power budget is deteriorated by a factor of 3 dB, but it can partly be compensated.

For a given transmission polarization, the four-element Stokes vector captures all of the information inherent to the dual-polarized backscattered signals. Stokes parameters are linear combinations of the like-polarized power, the cross-polarized power, and the cross product between the complex image amplitudes in the two receive channels. Most so-called dual-polarized synthetic aperture radar (SAR) systems provide only the like- and cross-product images, ignoring the cross product. In so doing, potentially valuable information is thrown away. For most dual-polarized SARs, data sufficient to generate the Stokes parameters can be generated with small marginal cost. A practical and sufficient output data format would be a mapping of the (complex) cross product between the two channels, as well as their respective images

Circular-transmit/linear-receive compact polarimetry synthetic aperture radar systems combine coherent dual polarization with wide-swath imaging. The polarization information in these data may be represented as a Stokes vector, or one can reconstruct several quadpolarized covariance elements. Two reconstruction algorithms have been published in the literature: one by Souyris et al. and a refined algorithm by Nord et al. We investigated the application of these two algorithms for reconstructing ocean clutter for the purpose of detecting targets. We tested the assumptions underlying these algorithms and found that they were not valid for ocean scenes. We present a simple empirical reconstruction model whose reconstruction and target detection performance is superior to the two published algorithms.

We present a study of the polarimetric information content of dual-pol imaging modes and dual-pol imaging extended by polarimetric scattering models. We compare Wishart classifications both among the partial polarimetric datasets and against the full quad-pol dataset. Our emphasis is the inter-comparisons between the classification results based on dual-pol modes, compact polarimetric modes and scattering model extensions of the compact polarimetric modes. We primarily consider novel dual-pol modes, e.g. transmitting a circular polarization and receiving horizontal and vertical polarizations, and the pseudo-quad-pol data derived from polarimetric scattering models based on dual-pol data. We show that the overall classification accuracy of the pseudo-quad-pol data is essential the same as the classification accuracy obtained directly employing the underlying dual-pol imagery.

A sparse pine forest is investigated at X-band on a single-pass polarimetric synthetic aperture radar interferometry (PolInSAR) data set using HH and HV channels. These first preliminary results show that the associated phase centers present a significant vertical separation (about 6 m) allowed by penetration through gaps in the canopy. Forest parameter inversion using the random volume over ground (RVoG) model is evaluated and adapted at this frequency. The forest height can be retrieved accurately by supposing a high mean extinction coefficient (around 1.6 (dB/m). The penetration depth is estimated to be around 4 m, based on the forest height ground measurements. Finally, a time-frequency analysis using a sublook decomposition is performed to increase the vertical separation of the polarimetric phase centers. As a consequence, RVoG-inversion performance is improved, and a penetration depth that is in better accordance with a previous work (of the order of 2 m) is found. This paper has shown that the height inversion of a pine forest was possible using PolInSAR X-band data and that the performance was more dependent on the forest density than at lower frequencies.

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric??(CP) synthetic aperture radar??(SAR) images. The parameter is denoted as the "CP ratio". In model simulations we investigated the sensitivity of the CP ratio to the dielectric constant, ice thickness, ice surface roughness, and radar incidence angle. From the results of the simulations we deduced optimal sea ice conditions and radar incidence angles for the ice thickness retrieval. C-band SAR data acquired over the Labrador Sea in circular transmit and linear receive??(CTLR) mode were generated from RADARSAT-2 quad-polarization images. In comparison with results from helicopter-borne measurements, we tested different empirical equations for the retrieval of ice thickness. An exponential fit between the CP ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region, we found a root mean square (rms) error of 8???cm and a maximum correlation coefficient of??0.94 for the retrieval procedure when applying it to level ice between 0.1??and 0.8???m thick.

The potential of compact polarimetry (CP) mode at longer wavelengths in a space environment for surface parameter estimation is investigated. CP consists of transmitting a single polarization while receiving two polarizations. At longer wavelengths, one of the main challenges associated with CP from space is Faraday rotation (FR) estimation and correction. In this paper, an estimation procedure...

The current study investigates the potential of multi‐temporal RADARSAT ScanSAR Narrow Beam B (SCNB) data to monitor rice crop growth and condition where special emphasis was given to the signature analysis of the crop. The study area is located in the Baleshwar and Bhadrak districts of Orissa. The temporal variations of radar backscatter of all land‐cover classes were analysed as a function of time. The analysis of the Synthetic Aperture Radar (SAR) backscatter coefficient (σ0) of rice crop shows significant temporal behaviour and a large dynamic range during its growth period, which is due to the interaction of microwave radiation with the crop canopy, increasing from the transplanting stage to the reproductive stage. This temporal variation of SAR backscatter clearly differentiates rice fields from other land‐cover classes. Separability studies among different class pairs carried out using t‐test and Bhattacharya distance show that all the rice classes are separable from each other except the early rice, which was mixed with far sides of hills and shadow. Knowledge‐based decision rule classifier based on the temporal evaluation of SAR backscatter was attempted to classify rice and non‐rice areas, and achieved more than 98% accuracy in the case of rice class. The results are promising and confirm the possibility of operational use of RADARSAT data for rice crop growth monitoring.

78We develop a large-scale rice fields mapping method using wide-swath SAR data. 78Multi-track datasets are used to increase the observation frequency. 78The temporal change of backscatter in each track is an effective classifier. 78Precise planted area estimations are hampered by the coarse resolution. 78Operational application is possible in integrated systems using ancillary data.

The rice cropping system in Asia is undergoing major changes to cope with increasing demography and changing climate, making rice monitoring a critical issue. Past studies have demonstrated the use of C-band synthetic aperture radar (SAR) data to map rice areas. The methods were based on the temporal change of intensity backscattering coefficient of vertically or horizontally co-polarized data (VV or HH). In this paper, we assess the use of the HH/VV polarization ratio derived from Advanced SAR (ASAR) data from ENVISAT data for the production of rice paddy maps. The approach is based on past knowledge on the polarization behavior of rice canopy, i.e., VV backscattering is much lower than HH during a large part of the rice season, due to the attenuation of the wave by the vertical structure of the plants. The methodology is developed for the Mekong Delta, Vietnam, where a complex cropping pattern is found (one to three crops of rice per year). The approach includes a statistical analysis of the HH/VV distributions of rice and non-rice classes at different dates. The analysis results confirm that HH/VV can be used as classifier and point out the need for relevant speckle filtering prior to classification. A classification method is developed and applied to single- and multidate data sets. The methods are tested at one district of the province of An Giang and extended to the whole province. Comparisons of the mapping results to geographic-information-system land-use data and official agricultural statistics show very good agreement. The method will be further applied to the entire Mekong Delta.

Rice is one of the three largest food grains in the world. Radar remote sensing has been proven to be an effective tool for rice monitoring. With the emergence of spaceborne polarimetric synthetic aperture radar (SAR) satellites, research on polarization backscatter behaviors and identification methods for rice are of great significance and attract the attention of remote sensing communities. The Zhazuo area located in Guizhou province of southwest China was selected as the test site for this study. The RADARSAT-2 polarimetric data acquired on four different dates were used to analyze the polarization backscatter behaviors and temporal variation of rice. Identification methods for rice based on polarization combinations and polarization decompositions were developed. The results indicated that HH with HH/HV was the optimal polarization combination for rice identification, with an accuracy of up to 86.65%. Based on the Pauli decomposition, rice can be discriminated effectively, with an accuracy of about 87.00%. Furthermore, using combinations of different polarization decompositions the identification results were greatly improved. The combination of the Pauli decomposition and the parameter 脦虏 derived from eigenvector-eigenvalue-based decomposition was best for rice identification, with an accuracy of up to 93.51%.

Synthetic aperture radar for paddy rice crop mapping is operational in many countries in southeast Asia due to the unique temporal backscatter signature when the rice grows above the water surface. Although the rapid increase of up to 10 dB or more allows for the identification and subsequent mapping of the rice crop extent the saturation of the backscatter signal during the later growth stages makes yield determination difficult. The development of polarimetric decomposition techniques may improve the capability to estimate rice production as the phase centre of the backscatter is expected to change as the crop matures and the water distribution in the plant parts changes. These changes can potentially be related to crop yield using growth models. This capability for monitoring growth stage and enhancing yield estimation is explored with a multitemporal RADARSAT-2 polarimetric data set of a rice growing region in China. The Freeman urden, the Cloude ottier, and the Touzi decompositions were used for classification and then evaluated as a function of the growth stage, which was monitored in the rice paddies during the image acquisition period. The Touzi decomposition produced the best classification accuracy when six or more parameters were used in the classification, but all polarimetric decompositions produced suitable accuracies for rice mapping. This indicated only one date of imagery is needed for rice identification when polarimetric data are available. The results also demonstrated some sensitivity to the growth stage in the polarimetric decompositions, especially with the Freeman urden and the Touzi parameters. A controlled experiment is planned to further develop the methodology for using polarimetric decompositions for rice monitoring and yield estimation.

Polarimetric RADARSAT-2 data of rice and wetlands are used to simulate compact polarimetry (CP) mode data from the upcoming RADARSAT Constellation Mission (RCM). The simulated CP data are then used to evaluate the information content for rice and wetland mapping using supervised classification, and the results are compared for linear and circular polarization combinations and polarimetric decompositions from the fully polarimetric data and the simulated CP data. The results are consistent for both rice and wetlands and show that the classification accuracy increases as one goes up the polarization hierarchy. The circular polarizations produced the best classification results for the polarization combinations. This result requires further research to verify. Although the CP data did not perform as well as the fully polarimetric data, the results were better than for dual polarization, and this mode may offer the best option for rice and wetland mapping applications because of swath coverage. Note that both the compact simulations and the fully polarimetric data produced operationally suitable classification accuracies. Additional research is underway to evaluate the monitoring capability of this new CP mode. This article describes the approach used for the analyses and the classification results for both rice and wetlands.

Rice is the most important food grain crop in India and contributes to more than 40 percent of the country’s food grain production. Spaceborne remote sensing offers economically viable and accurate production and area statistics. The utility of optical remote sensing in mapping rice cropped area is limited by persistent cloud cover during monsoon season. Temporal availability of SAR data has facilitated an operational procedure to monitor the rice crop. The current study discriminates rice crop, using single date hybrid polarimetric data available from RISAT-1 SAR. This was subjected to Raney m-δ, m-χ decompositions, and supervised classification was performed. The accuracy was estimated using the field points. The results were compared with rice map generated using optical sensor Resourcesat-2 LISS-IV and statistical data. The spatial agreement between the estimate from RISAT-1 and LISS-IV data was found to be 85 percent. The class kappa value was 0.94 and 0.92 for LISS-IV and RISAT-1, respectively.

本文将SVM用于全极化SAR图像分类,并提出一种新的应用于 SVM分类的特征选择算法.该算法以支持向量个数作为特征评估准则,利用顺序前进法加入特征.基于NASA/JPL实验室AIRSAR系统的L波段荷兰 Flevoland全极化数据的与RELIEF-F算法的对比实验表明,在特征个数更少(或相当)的情况下,本文特征选择算法能在更广泛的SVM参数取值 范围内获得更高的分类精度.

[1] We introduce a new technique derived from the classical Stokes parameters for analysis of polarimetric radar astronomical data. This decomposition is based on m (the degree of polarization) and chi (the Poincar ellipticity parameter). Analysis of the crater Byrgius A demonstrates how m-chi can more easily differentiate materials within ejecta deposits and their relative thicknesses. We use Goldschmidt crater to demonstrate how m-chi can differentiate coherent deposits of water ice. Goldschmidt crater floor is found to be consistent with single bounce Bragg scattering suggesting the absence of water ice and further corroborating adsorbed H to mineral grains or an H2O frost as plausible explanations for a H2O/OH detection by near-infrared instruments.

A synthetic aperture radar (SAR) with hybrid-polarity (CL-pol) architecture transmits circular polarization and receives two orthogonal, mutually coherent linear polarizations, which is one manifestation of compact polarimetry. The resulting radar is relatively simple to implement and has unique self-calibration features and low susceptibility to noise. It also enables maintenance of a larger swath coverage than fully polarimetric SAR systems. A research team composed of various departments of the Government of Canada evaluated this compact polarimetry mode configuration for application to soil moisture estimation, crop identification, ship detection, and sea-ice classification. This paper presents an overview of compact polarimetry, the approach developed for evaluation, and preliminary results for applications important to the Government of Canada. The implications of the results are also discussed with respect to future SAR missions such as the Canadian RADARSAT Constellation Mission, the American DESDynI, and India鈥檚 RISAT.