WorldWideScience

Sample records for multiple sar images

  1. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2016-04-01

    Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  2. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    Science.gov (United States)

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  3. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  4. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  5. SAR image dataset of military ground targets with multiple poses for ATR

    Science.gov (United States)

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  6. Bistatic SAR: Imagery & Image Products.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  7. A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs

    Directory of Open Access Journals (Sweden)

    Min-Kyu Kim

    2015-12-01

    Full Text Available This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs. The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

  8. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    Directory of Open Access Journals (Sweden)

    J. Tao

    2012-09-01

    Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

  9. Multiple Input - Multiple Output (MIMO) SAR

    Data.gov (United States)

    National Aeronautics and Space Administration — This effort will research and implement advanced Multiple-Input Multiple-Output (MIMO) Synthetic Aperture Radar (SAR) techniques which have the potential to improve...

  10. Automatic Coregistration for Multiview SAR Images in Urban Areas

    Science.gov (United States)

    Xiang, Y.; Kang, W.; Wang, F.; You, H.

    2017-09-01

    Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  11. AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

    Directory of Open Access Journals (Sweden)

    Y. Xiang

    2017-09-01

    Full Text Available Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  12. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  13. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

  14. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  15. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Science.gov (United States)

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  16. Deep learning for SAR image formation

    Science.gov (United States)

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  17. SAR Image Classification Based on Its Texture Features

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  18. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  19. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  20. The Establishment of the SAR images database System Based on Oracle and ArcSDE

    International Nuclear Information System (INIS)

    Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

    2014-01-01

    Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

  1. SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

    Directory of Open Access Journals (Sweden)

    Zhang Xinzheng

    2017-10-01

    Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

  2. Imaging in severe acute respiratory syndrome (SARS)

    International Nuclear Information System (INIS)

    Antonio, G.E.; Wong, K.T.; Chu, W.C.W.; Hui, D.S.C.; Cheng, F.W.T.; Yuen, E.H.Y.; Chung, S.S.C.; Fok, T.F.; Sung, J.J.Y.; Ahuja, A.T.

    2003-01-01

    Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a novel coronavirus, and has become pandemic within a short period of time. Imaging plays an important role in the diagnosis, management and follow-up of patients with SARS. The current status of imaging in SARS is presented in this review

  3. Attribute Learning for SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-04-01

    Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

  4. Relevant Scatterers Characterization in SAR Images

    Science.gov (United States)

    Chaabouni, Houda; Datcu, Mihai

    2006-11-01

    Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

  5. Precision Rectification of Airborne SAR Image

    DEFF Research Database (Denmark)

    Dall, Jørgen; Liao, M.; Zhang, Zhe

    1997-01-01

    A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR...

  6. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  7. Compressed Sensing mm-Wave SAR for Non-Destructive Testing Applications Using Multiple Weighted Side Information

    Directory of Open Access Journals (Sweden)

    Mathias Becquaert

    2018-05-01

    Full Text Available This work explores an innovative strategy for increasing the efficiency of compressed sensing applied on mm-wave SAR sensing using multiple weighted side information. The approach is tested on synthetic and on real non-destructive testing measurements performed on a 3D-printed object with defects while taking advantage of multiple previous SAR images of the object with different degrees of similarity. The tested algorithm attributes autonomously weights to the side information at two levels: (1 between the components inside the side information and (2 between the different side information. The reconstruction is thereby almost immune to poor quality side information while exploiting the relevant components hidden inside the added side information. The presented results prove that, in contrast to common compressed sensing, good SAR image reconstruction is achieved at subsampling rates far below the Nyquist rate. Moreover, the algorithm is shown to be much more robust for low quality side information compared to coherent background subtraction.

  8. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  9. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

    2014-01-01

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  10. Fast Superpixel Segmentation Algorithm for PolSAR Images

    Directory of Open Access Journals (Sweden)

    Zhang Yue

    2017-10-01

    Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

  11. Space Radar Image of West Texas - SAR scan

    Science.gov (United States)

    1999-01-01

    This radar image of the Midland/Odessa region of West Texas, demonstrates an experimental technique, called ScanSAR, that allows scientists to rapidly image large areas of the Earth's surface. The large image covers an area 245 kilometers by 225 kilometers (152 miles by 139 miles). It was obtained by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying aboard the space shuttle Endeavour on October 5, 1994. The smaller inset image is a standard SIR-C image showing a portion of the same area, 100 kilometers by 57 kilometers (62 miles by 35 miles) and was taken during the first flight of SIR-C on April 14, 1994. The bright spots on the right side of the image are the cities of Odessa (left) and Midland (right), Texas. The Pecos River runs from the top center to the bottom center of the image. Along the left side of the image are, from top to bottom, parts of the Guadalupe, Davis and Santiago Mountains. North is toward the upper right. Unlike conventional radar imaging, in which a radar continuously illuminates a single ground swath as the space shuttle passes over the terrain, a Scansar radar illuminates several adjacent ground swaths almost simultaneously, by 'scanning' the radar beam across a large area in a rapid sequence. The adjacent swaths, typically about 50 km (31 miles) wide, are then merged during ground processing to produce a single large scene. Illumination for this L-band scene is from the top of the image. The beams were scanned from the top of the scene to the bottom, as the shuttle flew from left to right. This scene was acquired in about 30 seconds. A normal SIR-C image is acquired in about 13 seconds. The ScanSAR mode will likely be used on future radar sensors to construct regional and possibly global radar images and topographic maps. The ScanSAR processor is being designed for 1996 implementation at NASA's Alaska SAR Facility, located at the University of Alaska Fairbanks, and will produce digital images from the

  12. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  13. Research on Airborne SAR Imaging Based on Esc Algorithm

    Science.gov (United States)

    Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

    2017-09-01

    Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  14. RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

    Directory of Open Access Journals (Sweden)

    X. T. Dong

    2017-09-01

    Full Text Available Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC. In this paper, extend chirp scaling algorithm (ECS is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  15. SAR image effects on coherence and coherence estimation.

    Energy Technology Data Exchange (ETDEWEB)

    Bickel, Douglas Lloyd

    2014-01-01

    Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

  16. Synthetic aperture design for increased SAR image rate

    Science.gov (United States)

    Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

    2009-03-03

    High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

  17. Guided SAR image despeckling with probabilistic non local weights

    Science.gov (United States)

    Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

    2017-12-01

    SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

  18. Detecting and Georegistering Moving Ground Targets in Airborne QuickSAR via Keystoning and Multiple-Phase Center Interferometry

    Directory of Open Access Journals (Sweden)

    R. P. Perry

    2008-03-01

    Full Text Available SAR images experience significant range walk and, without some form of motion compensation, can be quite blurred. The MITRE-developed Keystone formatting simultaneously and automatically compensates for range walk due to the radial velocity component of each moving target, independent of the number of targets or the value of each target's radial velocity with respect to the ground. Target radial motion also causes moving targets in synthetic aperture radar images to appear at locations offset from their true instantaneous locations on the ground. In a multichannel radar, the interferometric phase values associated with all nonmoving points on the ground appear as a continuum of phase differences while the moving targets appear as interferometric phase discontinuities. By multiple threshold comparisons and grouping of pixels within the intensity and the phase images, we show that it is possible to reliably detect and accurately georegister moving targets within short-duration SAR (QuickSAR images.

  19. Advanced InSAR imaging for dune mapping

    Science.gov (United States)

    Havivi, Shiran; August, Yitzhak; Blumberg, Dan G.; Rotman, Stanley R.

    2015-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970's, remote sensing imagery both optical and radar, are used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of Aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two images or more. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This research aims to demonstrate how interferometric decorrelation, or, coherence change detection, can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the Nitzanim coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically and

  20. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

  1. SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

    Directory of Open Access Journals (Sweden)

    A. Rezaeian

    2015-12-01

    Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  2. Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

    Science.gov (United States)

    Rezaeian, A.; Homayouni, S.; Safari, A.

    2015-12-01

    Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  3. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Directory of Open Access Journals (Sweden)

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  4. Object Georeferencing in UAV-Based SAR Terrain Images

    Directory of Open Access Journals (Sweden)

    Łabowski Michał

    2016-12-01

    Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

  5. Multi-look polarimetric SAR image filtering using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper

    2000-01-01

    Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

  6. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

    Science.gov (United States)

    Xu, Xin; Gui, Rong; Pu, Fangling

    2018-01-01

    Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

  7. Fusion method of SAR and optical images for urban object extraction

    Science.gov (United States)

    Jia, Yonghong; Blum, Rick S.; Li, Fangfang

    2007-11-01

    A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

  8. SIMULATION OF SHIP GENERATED TURBULENT AND VORTICAL WAKE IMAGING BY SAR

    Institute of Scientific and Technical Information of China (English)

    Wang Aiming; Zhu Minhui

    2004-01-01

    Synthetic Aperture Radar (SAR) imaging of ocean surface features is studied. The simulation of the turbulent and vortical features generated by a moving ship and SAR imaging of these wakes is carried out. The turbulent wake damping the ocean surface capillary waves may be partially responsible for the suppression of surface waves near the ship track. The vortex pair generating a change in the lateral flow field behind the ship may be partially responsible for an enhancement of the waves near the edges of the smooth area. These hydrodynamic phenomena as well as the changes of radar backscatter generated by turbulence and vortex are simulated.An SAR imaging model is then used on such ocean surface features to provide SAR images.Comparison of two ships' simulated SAR images shows that the wake features are different for various ship parameters.

  9. IMAGE ENHANCEMENT AND SPECKLE REDUCTION OF FULL POLARIMETRIC SAR DATA BY GAUSSIAN MARKOV RANDOM FIELD

    Directory of Open Access Journals (Sweden)

    M. Mahdian

    2013-09-01

    Full Text Available In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF, which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.

  10. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  11. Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

    Science.gov (United States)

    Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

    2018-04-01

    To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

  12. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

    2011-01-01

    This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

  13. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  14. Restoration of polarimetric SAR images using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  15. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Science.gov (United States)

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  16. The Generalized Gamma-DBN for High-Resolution SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Zhiqiang Zhao

    2018-06-01

    Full Text Available With the increase of resolution, effective characterization of synthetic aperture radar (SAR image becomes one of the most critical problems in many earth observation applications. Inspired by deep learning and probability mixture models, a generalized Gamma deep belief network (g Γ-DBN is proposed for SAR image statistical modeling and land-cover classification in this work. Specifically, a generalized Gamma-Bernoulli restricted Boltzmann machine (gΓB-RBM is proposed to capture high-order statistical characterizes from SAR images after introducing the generalized Gamma distribution. After stacking the g Γ B-RBM and several standard binary RBMs in a hierarchical manner, a gΓ-DBN is constructed to learn high-level representation of different SAR land-covers. Finally, a discriminative neural network is constructed by adding an additional predict layer for different land-covers over the constructed deep structure. Performance of the proposed approach is evaluated via several experiments on some high-resolution SAR image patch sets and two large-scale scenes which are captured by ALOS PALSAR-2 and COSMO-SkyMed satellites respectively.

  17. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  18. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  19. 3D Tomographic SAR Imaging in Densely Vegetated Mountainous Rural Areas in China and Sweden

    Science.gov (United States)

    Feng, L.; Muller, J. P., , Prof

    2017-12-01

    3D SAR Tomography (TomoSAR) and 4D SAR Differential Tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to unscramble complex scenes with multiple scatterers mapped into the same SAR cell. In addition to this 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas, and recent cryospheric ice investigations, emerging tomographic remote sensing applications include forest applications, e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to develop solutions for temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China and L and P band airborne SAR data (BioSAR 2008 - ESA) in the Krycklan river catchment, Northern Sweden. The new TanDEM-X 12m DEM is used to assist co - registration of all the data stacks over China first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract

  20. SAR image classification based on CNN in real and simulation datasets

    Science.gov (United States)

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  1. CFAR Edge Detector for Polarimetric SAR Images

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning; Nielsen, Allan Aasbjerg

    2003-01-01

    Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polar...

  2. Combined DEM Extration Method from StereoSAR and InSAR

    Science.gov (United States)

    Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.

    2015-06-01

    A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.

  3. Two dimensional estimates from ocean SAR images

    Directory of Open Access Journals (Sweden)

    J. M. Le Caillec

    1996-01-01

    Full Text Available Synthetic Aperture Radar (SAR images of the ocean yield a lot of information on the sea-state surface providing that the mapping process between the surface and the image is clearly defined. However it is well known that SAR images exhibit non-gaussian statistics and that the motion of the scatterers on the surface, while the image is being formed, may yield to nonlinearities. The detection and quantification of these nonlinearities are made possible by using Higher Order Spectra (HOS methods and more specifically, bispectrum estimation. The development of the latter method allowed us to find phase relations between different parts of the image and to recognise their level of coupling, i.e. if and how waves of different wavelengths interacted nonlinearly. This information is quite important as the usual models assume strong nonlinearities when the waves are propagating in the azimuthal direction (i.e. along the satellite track and almost no nonlinearities when propagating in the range direction. In this paper, the mapping of the ocean surface to the SAR image is reinterpreted and a specific model (i.e. a Second Order Volterra Model is introduced. The nonlinearities are thus explained as either produced by a nonlinear system or due to waves propagating into selected directions (azimuth or range and interacting during image formation. It is shown that quadratic nonlinearities occur for waves propagating near the range direction while for those travelling in the azimuthal direction the nonlinearities, when present, are mostly due to wave interactions but are almost completely removed by the filtering effect coming from the surface motion itself (azimuth cut-off. An inherent quadratic interaction filtering (azimuth high pass filter is also present. But some other effects, apparently nonlinear, are not detected with the methods described here, meaning that either the usual relation developed for the Ocean-to-SAR transform is somewhat incomplete

  4. Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

    DEFF Research Database (Denmark)

    Sandholt, Inge; Skriver, Henning

    1999-01-01

    The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

  5. a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

    Science.gov (United States)

    Li, L.; Yang, H.; Chen, Q.; Liu, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

  6. High Resolution SAR Imaging Employing Geometric Features for Extracting Seismic Damage of Buildings

    Science.gov (United States)

    Cui, L. P.; Wang, X. P.; Dou, A. X.; Ding, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover & bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.

  7. Bone scintigraphy in post-SARS patients and compared with magnetic resonance imaging

    International Nuclear Information System (INIS)

    Wang Qian; Huang Lili; Qin Shuling

    2004-01-01

    Objective: To study the characteristics of bone scintigraphy in post-SARS patients and evaluate the usefulness of bone scintigraphy in the prediction of avascular osteonecrosis (AVN) comparing with the MR imaging.. Methods: Our study included 66 patients who were diagnosed as SARS based on the diagnostic criteria issued by the Ministry of Health of China (MHC), including 46 women and 20 men. Their ages ranged from 19 to 63 years (mean, 31.6±0.1 years). All of the patients were treated with methyprednisonlone, rabavirin, broad spectrum antimicrobials and supportive therapy. Dosage of methyprednisonlone was 80∼800 mg/d for 4-72 days. Of them, varied seat of joint pain occurred in 47 patients 3 to 18 weeks after the onset of SARS. Since multiple joints were involved in many patients, bone scintigraphy was performed for screening AVN. The other 19 patients without of evident joint pain were also examined as their demand. Informed consents were obtained in all of the examined patients. No previously joint pain or trauma history was found in this group of patients. Of the 66 patients, planer X-ray was performed in 34 of the symptomatic patients previous to the scintigraphy, but it was negative in all. MR examination was performed in 54 patients before or after the scintigraphy, and the interval between two the tests was average of 8 days (range, 0 to 30 days). In addition, 27 consecutive cases aged lower than 45 years (mean, 40.4±0.8 years) with breast cancer who underwent bone scintigraphy for screening metastastic disease and had negative results were also involved as a control group. Whole body skeletal scintigraphy was performed 3 hours after intravenous administration of technetium-99m methylene-diphosphonate 740 MBq. Increased uptake lesion seen in the limb joints was defined as positive, but 'hot patella' sign was considered to be non diagnostic value. When a lesion was found in the whole body imaging, corresponding regional image was further taken. Two

  8. Multi-image Matching of Airborne SAR Imagery by SANCC

    Directory of Open Access Journals (Sweden)

    DING Hao

    2015-03-01

    Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

  9. Flood extent and water level estimation from SAR using data-model integration

    Science.gov (United States)

    Ajadi, O. A.; Meyer, F. J.

    2017-12-01

    Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

  10. A Novel 3D Imaging Method for Airborne Downward-Looking Sparse Array SAR Based on Special Squint Model

    Directory of Open Access Journals (Sweden)

    Xiaozhen Ren

    2014-01-01

    Full Text Available Three-dimensional (3D imaging technology based on antenna array is one of the most important 3D synthetic aperture radar (SAR high resolution imaging modes. In this paper, a novel 3D imaging method is proposed for airborne down-looking sparse array SAR based on the imaging geometry and the characteristic of echo signal. The key point of the proposed algorithm is the introduction of a special squint model in cross track processing to obtain accurate focusing. In this special squint model, point targets with different cross track positions have different squint angles at the same range resolution cell, which is different from the conventional squint SAR. However, after theory analysis and formulation deduction, the imaging procedure can be processed with the uniform reference function, and the phase compensation factors and algorithm realization procedure are demonstrated in detail. As the method requires only Fourier transform and multiplications and thus avoids interpolations, it is computationally efficient. Simulations with point scatterers are used to validate the method.

  11. Combined acquisition technique (CAT for neuroimaging of multiple sclerosis at low specific absorption rates (SAR.

    Directory of Open Access Journals (Sweden)

    Armin Biller

    Full Text Available PURPOSE: To compare a novel combined acquisition technique (CAT of turbo-spin-echo (TSE and echo-planar-imaging (EPI with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF burden is limited by the specific absorption rate (SAR for patient safety. SAR limits restrict high-field MRI applications, in particular. MATERIAL AND METHODS: The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation. RESULTS: Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen's kappa of within-rater/across-CAT/TSE lesion detection κCAT = 1.00, at an inter-rater lesion detection agreement of κLES = 0.82. CAT reduced the SAR burden significantly compared to TSE (p<0.001. Mean SAR differences between TSE and CAT were 29.0 (± 5.7 % for the T2-contrast and 32.7 (± 21.9 % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations. Average SPL of CAT was no louder than during TSE. Sensations of CAT- vs. TSE-induced heating, noise and scanning vibrations did not differ. CONCLUSION: T2-/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning.

  12. Enhancement of SAR images using fuzzy shrinkage technique

    Indian Academy of Sciences (India)

    This paper presents speckle noise reduction in SAR images using a combination of curvelet and fuzzy logic technique to restore speckle-affected images. This method overcomes the limitation of discontinuity in hard threshold and permanent deviation in soft threshold. First, it decomposes noise image into different ...

  13. Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2017-02-01

    Full Text Available By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.

  14. Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2017-08-01

    Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

  15. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  16. On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

    Directory of Open Access Journals (Sweden)

    Zhen Xu

    2018-03-01

    Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

  17. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon

    2015-01-01

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  18. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng

    2015-02-03

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  19. Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

    Science.gov (United States)

    Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

    2018-04-01

    Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

  20. Combined Acquisition Technique (CAT) for Neuroimaging of Multiple Sclerosis at Low Specific Absorption Rates (SAR)

    Science.gov (United States)

    Biller, Armin; Choli, Morwan; Blaimer, Martin; Breuer, Felix A.; Jakob, Peter M.; Bartsch, Andreas J.

    2014-01-01

    Purpose To compare a novel combined acquisition technique (CAT) of turbo-spin-echo (TSE) and echo-planar-imaging (EPI) with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF) burden is limited by the specific absorption rate (SAR) for patient safety. SAR limits restrict high-field MRI applications, in particular. Material and Methods The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS) patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL) and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation. Results Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen’s kappa of within-rater/across-CAT/TSE lesion detection κCAT = 1.00, at an inter-rater lesion detection agreement of κLES = 0.82). CAT reduced the SAR burden significantly compared to TSE (pCAT were 29.0 (±5.7) % for the T2-contrast and 32.7 (±21.9) % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations). Average SPL of CAT was no louder than during TSE. Sensations of CAT- vs. TSE-induced heating, noise and scanning vibrations did not differ. Conclusion T2−/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning. PMID:24608106

  1. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  2. Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank

    Directory of Open Access Journals (Sweden)

    Shuangshang Zhang

    2017-11-01

    Full Text Available In this study, the C-band radar backscatter features of the shallow water topography of Subei Bank in the Southern Yellow Sea are statistically investigated using 25 ENVISAT (Environmental Satellite ASAR (advanced synthetic aperture radar and ERS-2 (European Remote-Sensing Satellite-2 SAR images acquired between 2006 and 2010. Different bathymetric features are found on SAR imagery under different sea states. Under low to moderate wind speeds (3.1~6.3 m/s, the wide bright patterns with an average width of 6 km are shown and correspond to sea surface imprints of tidal channels formed by two adjacent sand ridges, while the sand ridges appear as narrower (only 1 km wide, fingerlike, quasi-linear features on SAR imagery in high winds (5.4~13.9 m/s. Two possible SAR imaging mechanisms of coastal bathymetry are proposed in the case where the flow is parallel to the major axes of tidal channels or sand ridges. When the surface Ekman current is opposite to the mean tidal flow, two vortexes will converge at the central line of the tidal channel in the upper layer and form a convergent zone over the sea surface. Thus, the tidal channels are shown as wide and bright stripes on SAR imagery. For the SAR imaging of sand ridges, all the SAR images were acquired at low tidal levels. In this case, the ocean surface waves are possibly broken up under strong winds when propagating from deep water to the shallower water, which leads to an increase of surface roughness over the sand ridges.

  3. Information theoretic bounds for compressed sensing in SAR imaging

    International Nuclear Information System (INIS)

    Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

    2014-01-01

    Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities

  4. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case.

    Science.gov (United States)

    Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming

    2017-12-22

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  5. Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

    Directory of Open Access Journals (Sweden)

    Maria Daniela Graziano

    2016-06-01

    Full Text Available A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

  6. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Directory of Open Access Journals (Sweden)

    Dongyang Ao

    2017-12-01

    Full Text Available The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS in the synthetic aperture radar (SAR images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  7. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Science.gov (United States)

    Ao, Dongyang; Hu, Cheng; Tian, Weiming

    2017-01-01

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917

  8. Millimeter wave radar system on a rotating platform for combined search and track functionality with SAR imaging

    Science.gov (United States)

    Aulenbacher, Uwe; Rech, Klaus; Sedlmeier, Johannes; Pratisto, Hans; Wellig, Peter

    2014-10-01

    Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.

  9. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Nina Merkle

    2017-06-01

    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  10. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

    Science.gov (United States)

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-01-01

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

  11. SAR image formation with azimuth interpolation after azimuth transform

    Science.gov (United States)

    Doerry,; Armin W. , Martin; Grant D. , Holzrichter; Michael, W [Albuquerque, NM

    2008-07-08

    Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

  12. Enhancement of SAR images using fuzzy shrinkage technique in ...

    Indian Academy of Sciences (India)

    Shivakumara Swamy Puranik Math

    2017-08-03

    Aug 3, 2017 ... not use threshold approach only by proper selection of shrinking parameter the speckle in SAR image is ... but cost estimation of hyper-parameters will be high. The ..... To find the effectiveness of the proposed image in a.

  13. Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

    Directory of Open Access Journals (Sweden)

    Xiaoli Ding

    2009-02-01

    Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

  14. A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

    Directory of Open Access Journals (Sweden)

    Min Liu

    2018-03-01

    Full Text Available Sidelobe reduction is a very primary task for synthetic aperture radar (SAR images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.

  15. SAR image regularization with fast approximate discrete minimization.

    Science.gov (United States)

    Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

    2009-07-01

    Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

  16. Urban Monitoring Based on SENTINEL-1 Data Using Permanent Scatterer Interferometry and SAR Tomography

    Science.gov (United States)

    Crosetto, M.; Budillon, A.; Johnsy, A.; Schirinzi, G.; Devanthéry, N.; Monserrat, O.; Cuevas-González, M.

    2018-04-01

    A lot of research and development has been devoted to the exploitation of satellite SAR images for deformation measurement and monitoring purposes since Differential Interferometric Synthetic Apertura Radar (InSAR) was first described in 1989. In this work, we consider two main classes of advanced DInSAR techniques: Persistent Scatterer Interferometry and Tomographic SAR. Both techniques make use of multiple SAR images acquired over the same site and advanced procedures to separate the deformation component from the other phase components, such as the residual topographic component, the atmospheric component, the thermal expansion component and the phase noise. TomoSAR offers the advantage of detecting either single scatterers presenting stable proprieties over time (Persistent Scatterers) and multiple scatterers interfering within the same range-azimuth resolution cell, a significant improvement for urban areas monitoring. This paper addresses a preliminary inter-comparison of the results of both techniques, for a test site located in the metropolitan area of Barcelona (Spain), where interferometric Sentinel-1 data were analysed.

  17. The artificial object detection and current velocity measurement using SAR ocean surface images

    Science.gov (United States)

    Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey

    2017-10-01

    Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.

  18. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

    Science.gov (United States)

    Guo, Hao; Wu, Danni; An, Jubai

    2017-08-09

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

  19. Advanced Interferometric Synthetic Aperture Imaging Radar (InSAR) for Dune Mapping

    Science.gov (United States)

    Havivi, Shiran; Amir, Doron; Schvartzman, Ilan; August, Yitzhak; Mamman, Shimrit; Rotman, Stanely R.; Blumberg, Dan G.

    2016-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of

  20. STUDY ON THE CLASSIFICATION OF GAOFEN-3 POLARIMETRIC SAR IMAGES USING DEEP NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    J. Zhang

    2018-04-01

    Full Text Available Polarimetric Synthetic Aperture Radar(POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  1. Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

    Science.gov (United States)

    Zhang, J.; Zhang, J.; Zhao, Z.

    2018-04-01

    Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  2. Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

    Science.gov (United States)

    Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

    2017-12-01

    This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

  3. Autofocus algorithm for curvilinear SAR imaging

    Science.gov (United States)

    Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

    2012-05-01

    We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.

  4. Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

    Science.gov (United States)

    Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

    2018-04-01

    Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

  5. RESEARCH ON COORDINATE TRANSFORMATION METHOD OF GB-SAR IMAGE SUPPORTED BY 3D LASER SCANNING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    P. Wang

    2018-04-01

    Full Text Available In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D plane coordinate system with the common three-dimensional (3D terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  6. Research on Coordinate Transformation Method of Gb-Sar Image Supported by 3d Laser Scanning Technology

    Science.gov (United States)

    Wang, P.; Xing, C.

    2018-04-01

    In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D) plane coordinate system with the common three-dimensional (3D) terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  7. SAR Imaging through the Earth’s Ionosphere

    Science.gov (United States)

    2013-11-06

    Xiaoqing Pi, Anthony Freeman, Bruce Chapman, Paul Rosen, and Zhenhong Li . Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar. J...resolution SAR phase correction. IEEE Trans. Aerosp. Electron. Syst., 30(3):827–835, 1994. [30] Lianlin Li and Fang Li . Ionosphere tomography based on...Manduchi and G. A. Mian . Accuracy analysis for correlation-based image registartion algorithms. In Proceedings of the 1993 IEEE International

  8. Fast iterative censoring CFAR algorithm for ship detection from SAR images

    Science.gov (United States)

    Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

    2017-11-01

    Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

  9. Potential of TCPInSAR in Monitoring Linear Infrastructure with a Small Dataset of SAR Images: Application of the Donghai Bridge, China

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2018-03-01

    Full Text Available Reliably monitoring deformation associated with linear infrastructures, such as long-span bridges, is vitally important to assess their structural health. In this paper, we attempt to employ satellite interferometric synthetic aperture radar (InSAR to map the deformation of Donghai Bridge over a half of an annual cycle. The bridge, as the fourth longest cross-sea bridge in the world, located in the north of Hangzhou Bay, East China Sea where the featureless sea surface largely occupied the radar image raises challenges to accurately co-register the coherent points along the bridge. To tackle the issues due to co-registration and the limited number of synthetic aperture radar (SAR images, we adopt the termed temporarily-coherent point (TCP InSAR (TCPInSAR technique to process the radar images. TCPs that are not necessarily coherent during the whole observation period can be identified within every two SAR acquisitions during the co-registration procedure based on the statistics of azimuth and range offsets. In the process, co-registration is performed only using the offsets of these TCPs, leading to improved interferometric phases and the local Delaunay triangulation is used to construct point pairs to reduce the atmospheric artifacts along the bridge. With the TCPInSAR method the deformation rate along the bridge is estimated with no need of phase unwrapping. The achieved result reveals that the Donghai Bridge suffered a line-of-sight (LOS deformation rate up to −2.3 cm/year from January 2009 to July 2009 at the cable-stayed part, which is likely due to the thermal expansion of cables.

  10. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  11. First Image Products from EcoSAR - Osa Peninsula, Costa Rica

    Science.gov (United States)

    Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon

    2016-01-01

    Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

  12. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

    OpenAIRE

    Guo, Hao; Wu, Danni; An, Jubai

    2017-01-01

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred f...

  13. Extraction of lead and ridge characteristics from SAR images of sea ice

    Science.gov (United States)

    Vesecky, John F.; Smith, Martha P.; Samadani, Ramin

    1990-01-01

    Image-processing techniques for extracting the characteristics of lead and pressure ridge features in SAR images of sea ice are reported. The methods are applied to a SAR image of the Beaufort Sea collected from the Seasat satellite on October 3, 1978. Estimates of lead and ridge statistics are made, e.g., lead and ridge density (number of lead or ridge pixels per unit area of image) and the distribution of lead area and orientation as well as ridge length and orientation. The information derived is useful in both ice science and polar operations for such applications as albedo and heat and momentum transfer estimates, as well as ship routing and offshore engineering.

  14. Ka-band InSAR Imaging and Analysis Based on IMU Data

    Directory of Open Access Journals (Sweden)

    Shi Jun

    2014-02-01

    Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

  15. Target discrimination method for SAR images based on semisupervised co-training

    Science.gov (United States)

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  16. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    Directory of Open Access Journals (Sweden)

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  17. Imaging manifestations of the cavitation in pulmonary parenchyma of SARS

    International Nuclear Information System (INIS)

    Yuan Chunwang; Zhao Dawei; Wang Wei; Jia Cuiyu; Bai Chunsheng

    2004-01-01

    Objective: To investigate the imaging appearances of cavitation in pulmonary parenchyma and the clinical features of the cases of SARS. Methods: Chest imaging films and clinical data of 180 patients with clinically confirmed SARS were analyzed retrospectively. The imaging manifestations of cavitation and the clinical features of the patients were observed and evaluated. Results: Of 180 patients, cavitations were showed in 5 (2.8%), which were all found through X-ray or CT scanning. Most of them were round or irregular, and had thick wall. The 5 patients all had been in hospital and treated with more dosage antibiotics, antivirus medicines and glucocorticoid for long time, the glucocorticoid was used for 25-65 d, and in the first 10-15 days the dosage was 160-240 mg per day. In hospitalization, one of them had been diagnosed diabetes mellitus, four had increased fasting blood sugar, the counts of white blood cells [(14.1-20.4) x 10 9 /L] increased significantly, the percent of neutrophils might increased also. Meanwhile, there was a continue increase of lactate dehydrogenase (228.00-475.00 U/L), glutamic dehydrogenase (10.08-60.00 U/L) and hydroxybutyrate dehydrogenase (190.00-444.00 U/L) in lab examination. Conclusion: SARS can cause cavitation in pulmonary parenchyma in posterior process of the disease. CT scanning can find the cavitation earlier and accurately, catching the imaging features of them is helpful in differential diagnosis, guiding therapy and estimating prognosis

  18. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  19. On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image

    Science.gov (United States)

    Wang, Xiaochen; Shao, Yun; Tian, Wei; Li, Kun

    2018-06-01

    This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China's Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

  20. SAR Image Simulation of Ship Targets Based on Multi-Path Scattering

    Science.gov (United States)

    Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.

    2018-04-01

    Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.

  1. Investigation of Joint Visibility Between SAR and Optical Images of Urban Environments

    Science.gov (United States)

    Hughes, L. H.; Auer, S.; Schmitt, M.

    2018-05-01

    In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.

  2. The Radiometric Measurement Quantity for SAR Images

    OpenAIRE

    Döring, Björn J.; Schwerdt, Marco

    2013-01-01

    A Synthetic Aperture Radar (SAR) system measures among other quantities the terrain radar reflectivity. After image calibration, the pixel intensities are commonly expressed in terms of radar cross sections (for point targets) or as backscatter coefficients (for distributed targets), which are directly related. This paper argues that pixel intensities are not generally proportional to radar cross section or derived physical quantities. The paper further proposes to replace the inaccurate term...

  3. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory

    Directory of Open Access Journals (Sweden)

    Rui Zhou

    2018-01-01

    Full Text Available Synthetic aperture radar (SAR equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  4. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

    Science.gov (United States)

    Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

    2018-01-31

    Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  5. THz-SAR Vibrating Target Imaging via the Bayesian Method

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2017-01-01

    Full Text Available Target vibration bears important information for target recognition, and terahertz, due to significant micro-Doppler effects, has strong advantages for remotely sensing vibrations. In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. A real vibration measurement experiment of idle cars was performed to validate the range model. Simulated SAR data of vibrating targets and a tank model in a real background in 220 GHz show good performance at low SNR. Rapidly evolving high-power terahertz devices will offer viable THz-SAR application at a distance of several kilometers.

  6. AUTOMATIC CALCULATION OF OIL SLICK AREA FROM MULTIPLE SAR ACQUISITIONS FOR DEEPWATER HORIZON OIL SPILL

    Directory of Open Access Journals (Sweden)

    B. Osmanoğlu

    2012-07-01

    Full Text Available The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m3 of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries. For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellitebased oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR satellites are a major contributer of monitoring marine environments for oil spill detection. We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band, Envisat ASAR (C-band and Alos-PALSAR (L-band sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days allow us to eliminate artifacts and increase accuracy. Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.

  7. Bistatic SAR: Proof of Concept.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

    2014-10-01

    Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

  8. A comparative study on methods of improving SCR for ship detection in SAR image

    Science.gov (United States)

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  9. Change detection in polarimetric SAR images using complex Wishart distributed matrices

    DEFF Research Database (Denmark)

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

    In surveillance it is important to be able to detect natural or man-made changes e.g. based on sequences of satellite or air borne images of the same area taken at different times. The mapping capability of synthetic aperture radar (SAR) is independent of e.g. cloud cover, and thus this technology...... scattering matrix, and after suitable preprocessing the outcome at each picture element (pixel) may be represented as a 3 by 3 Hermitian matrix following a complex Wishart distribution. One approach to solving the change detection problem based on SAR images is therefore to apply suitable statistical tests...... in the complex Wishart distribution. We propose a set-up for a systematic solution to the (practical) problems using the likelihood ratio test statistics. We show some examples based on a time series of images with 1024 by 1024 pixels....

  10. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  11. Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

    Science.gov (United States)

    Zhang, X.; Xiong, B.; Kuang, G.

    2018-04-01

    In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

  12. Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments

    Directory of Open Access Journals (Sweden)

    Shiran Havivi

    2018-05-01

    Full Text Available Rapid damage mapping following a disaster event, especially in an urban environment, is critical to ensure that the emergency response in the affected area is rapid and efficient. This work presents a new method for mapping damage assessment in urban environments. Based on combining SAR and optical data, the method is applicable as support during initial emergency planning and rescue operations. The study focuses on the urban areas affected by the Tohoku earthquake and subsequent tsunami event in Japan that occurred on 11 March 2011. High-resolution TerraSAR-X (TSX images of before and after the event, and a Landsat 5 image before the event were acquired. The affected areas were analyzed with the SAR data using only one interferometric SAR (InSAR coherence map. To increase the damage mapping accuracy, the normalized difference vegetation index (NDVI was applied. The generated map, with a grid size of 50 m, provides a quantitative assessment of the nature and distribution of the damage. The damage mapping shows detailed information about the affected area, with high overall accuracy (89%, and high Kappa coefficient (82% and, as expected, it shows total destruction along the coastline compared to the inland region.

  13. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Directory of Open Access Journals (Sweden)

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  14. Time domain SAR raw data simulation using CST and image focusing of 3D objects

    Science.gov (United States)

    Saeed, Adnan; Hellwich, Olaf

    2017-10-01

    This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.

  15. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  16. Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

    Directory of Open Access Journals (Sweden)

    Zhao Yi-chao

    2015-10-01

    Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

  17. Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2014-10-01

    Full Text Available Due to its special imaging characteristics, Synthetic Aperture Radar (SAR has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

  18. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  19. Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

    Directory of Open Access Journals (Sweden)

    Maria Daniela Graziano

    2017-10-01

    Full Text Available A novel technique for ship wake detection has been recently proposed and applied on X-band Synthetic Aperture Radar images provided by COSMO/SkyMed and TerraSAR-X. The approach shows that the vast majority of wake features are correctly detected and validated in critical situations. In this paper, the algorithm was applied to 28 wakes imaged by Sentinel-1 mission with different polarizations and incidence angles with the aim of testing the method’s robustness with reference to radar frequency and resolution. The detection process is properly modified. The results show that the features were correctly classified in 78.5% of cases, whereas false confirmations occur mainly on Kelvin cusps. Finally, the results were compared with the algorithm performance on X-band images, showing that no significant difference arises. In fact, the total false confirmations rate was 15.8% on X-band images and 18.5% on C-band images. Moreover, since the main criticality concerns again the false confirmation of Kelvin cusps, the same empirical criterion suggested for the X-band SAR images yielded a negligible 1.5% of false detection rate.

  20. Characterizing and estimating noise in InSAR and InSAR time series with MODIS

    Science.gov (United States)

    Barnhart, William D.; Lohman, Rowena B.

    2013-01-01

    InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

  1. Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

    Directory of Open Access Journals (Sweden)

    Hui Meng

    2017-02-01

    Full Text Available The image intensities of low-backscattering areas in synthetic aperture radar (SAR images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

  2. Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

    Directory of Open Access Journals (Sweden)

    Timo Balz

    2016-09-01

    Full Text Available The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%.

  3. Mars Mission Concepts: SAR and Solar Electric Propulsion

    Science.gov (United States)

    Elsperman, M.; Klaus, K.; Smith, D. B.; Clifford, S. M.; Lawrence, S. J.

    2012-12-01

    Introduction: The time has come to leverage technology advances (including advances in autonomous operation and propulsion technology) to reduce the cost and increase the flight rate of planetary missions, while actively developing a scientific and engineering workforce to achieve national space objectives. Mission Science at Mars: A SAR imaging radar offers an ability to conduct high resolution investigations of the shallow (Models uniquely useful for exploration planning and science purposes. Since the SAR and the notional high-resolution stereo imaging system would be huge data volume producers - to maximize the science return we are currently considering the usage of laser communications systems; this notional spacecraft represents one pathway to evaluate the utility of laser communications in planetary exploration while providing useful science return.. Mission Concept: Using a common space craft for multiple missions reduces costs. Solar electric propulsion (SEP) provides the flexibility required for multiple mission objectives. SEP provides the greatest payload advantage albeit at the sacrifice of mission time. Our concept involves using a SEP enabled space craft (Boeing 702SP) with a highly capable SAR imager that also conducts autonomous rendezvous and docking experiments accomplished from Mars orbit. Our concept of operations is to launch on May 5, 2018 using a launch vehicle with 2000kg launch capacity with a C3 of 7.4. After reaching Mars it takes 145 days to spiral down to a 250 km orbit above the surface of Mars when Mars SAR operations begin. Summary/Conclusions: A robust and compelling Mars mission can be designed to meet the 2018 Mars launch window opportunity. Using advanced in-space power and propulsion technologies like High Power Solar Electric Propulsion provides enormous mission flexibility to execute the baseline science mission and conduct necessary Mars Sample Return Technology Demonstrations in Mars orbit on the same mission. An

  4. The Intercomparison of X-Band SAR Images from COSMO‑SkyMed and TerraSAR-X Satellites: Case Studies

    Directory of Open Access Journals (Sweden)

    Simone Pettinato

    2013-06-01

    Full Text Available The analysis of experimental data collected by X-band SAR of COSMO-SkyMed (CSK® and TerraSAR-X (TSX images on the same surface types has shown significant differences in the signal level of the two sensors. In order to investigate the possibility of combining data from the two instruments, a study was carried out by comparing images collected with similar orbital and sensor parameters (e.g., incidence angle, polarization, look angle at approximately the same date on two Italian agricultural test sites. Several homogenous agricultural fields within the observed area common to the two sensors were selected. Some forest plots have also been considered and used as a reference target. Direct comparisons were then performed between CSK and TSX images in different acquisition modes. The analysis carried out on the agricultural fields showed that, in general, the backscattering coefficient is higher in TSX Stripmap images with respect to CSK-Himage (about 3 dB, while CSK-Ping Pong data showed values lower than TSX of about 4.8 dB. Finally, a difference in backscattering of about 2.5 dB was pointed out between CSK-Himage and Ping-Pong images on agricultural fields. These results, achieved on bare soils, have also been compared with simulations performed by using the Advanced Integral Equation Model (AIEM.

  5. (Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

    Science.gov (United States)

    Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

    2018-02-01

    The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

  6. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  7. Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map

    Directory of Open Access Journals (Sweden)

    CHEN Min

    2016-03-01

    Full Text Available A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.

  8. PSInSAR technology and its use for monitoring of the Earth's surface deformation; Technologia PSInSAR a jej vyuzitie na monitorovanie deformacii zemskeho povrchu

    Energy Technology Data Exchange (ETDEWEB)

    Batorova, K [Univerzita Komenskeho v Bratislave, Prirodovedecka fakulta, Katedra inzinierskej geologie, 84215 Bratislava (Slovakia)

    2012-04-25

    Method of permanent reflex points (PSInSAR) allows to monitor the time evolution of deformations of the Earth's surface with a millimeter precision. For deformation size determination there are used the maps of movement speed or time delay of line set of data that are obtained by evaluating of SAR images. SAR files must be processed using the basic mathematical calculation presented in the work, with an emphasis on the parameters used in geology. Extensive processing of multiple SAR imagery showed that they can be used during monitoring of the field with an accurate identification of the objects on the Earth's surface, which provide a stable reflection of radar rays transmitted from the satellite. These objects are known as permanent reflection points (PS). PS can be geo-referenced, allowing accurate determination of the movement size of the Earth's surface deformation. In this paper an example of using of PSInSAR technology for monitoring of slope movements on the territory of Slovakia is presented. (authors)

  9. A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

    Directory of Open Access Journals (Sweden)

    Xu Yongli

    2017-01-01

    Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.

  10. An Adaptive Ship Detection Algorithm for Hrws SAR Images Under Complex Background: Application to SENTINEL1A Data

    Science.gov (United States)

    He, G.; Xia, Z.; Chen, H.; Li, K.; Zhao, Z.; Guo, Y.; Feng, P.

    2018-04-01

    Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.

  11. The retrieval of two-dimensional distribution of the earth's surface aerodynamic roughness using SAR image and TM thermal infrared image

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Renhua; WANG; Jinfeng; ZHU; Caiying; SUN; Xiaomin

    2004-01-01

    After having analyzed the requirement on the aerodynamic earth's surface roughness in two-dimensional distribution in the research field of interaction between land surface and atmosphere, this paper presents a new way to calculate the aerodynamic roughness using the earth's surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the earth's surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil surface moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface's equivalent geometric roughness-height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A completely two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmospheric eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area, this paper first establishes a scale

  12. Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

    Science.gov (United States)

    Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

  13. LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

    Directory of Open Access Journals (Sweden)

    I. Schvartzman

    2016-06-01

    Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

  14. Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis

    Science.gov (United States)

    Kojima, S.; Hensley, S.

    2012-12-01

    There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume

  15. MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

    Directory of Open Access Journals (Sweden)

    R. Dwivedi

    2016-06-01

    Full Text Available In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS and Small Baseline (SB methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS based PS-InSAR and the Small Baselines Subset (SBAS techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

  16. Design and realization of an active SAR calibrator for TerraSAR-X

    Science.gov (United States)

    Dummer, Georg; Lenz, Rainer; Lutz, Benjamin; Kühl, Markus; Müller-Glaser, Klaus D.; Wiesbeck, Werner

    2005-10-01

    TerraSAR-X is a new earth observing satellite which will be launched in spring 2006. It carries a high resolution X-band SAR sensor. For high image data quality, accurate ground calibration targets are necessary. This paper describes a novel system concept for an active and highly integrated, digitally controlled SAR system calibrator. A total of 16 active transponder and receiver systems and 17 receiver only systems will be fabricated for a calibration campaign. The calibration units serve for absolute radiometric calibration of the SAR image data. Additionally, they are equipped with an extra receiver path for two dimensional satellite antenna pattern recognition. The calibrator is controlled by a dedicated digital Electronic Control Unit (ECU). The different voltages needed by the calibrator and the ECU are provided by the third main unit called Power Management Unit (PMU).

  17. Bistatic sAR data processing algorithms

    CERN Document Server

    Qiu, Xiaolan; Hu, Donghui

    2013-01-01

    Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so sign

  18. A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

    Science.gov (United States)

    Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

    2018-03-01

    Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

  19. Satellite on-board real-time SAR processor prototype

    Science.gov (United States)

    Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

    2017-11-01

    A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and

  20. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Energy Technology Data Exchange (ETDEWEB)

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  1. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    Gaussian smoothed SAR image spectra have been evaluated from 512 x 512 pixel subscenes of image mode ERS-1 SAR scenes off Goa, Visakhapatnam, Paradeep and Portugal. The two recently acquired scenes off Portugal showed the signature of swell...

  2. A neural network detection model of spilled oil based on the texture analysis of SAR image

    Science.gov (United States)

    An, Jubai; Zhu, Lisong

    2006-01-01

    A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

  3. Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region.

    Science.gov (United States)

    Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao

    2017-05-25

    Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure-up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data.

  4. TESTING THE GENERALIZATION EFFICIENCY OF OIL SLICK CLASSIFICATION ALGORITHM USING MULTIPLE SAR DATA FOR DEEPWATER HORIZON OIL SPILL

    Directory of Open Access Journals (Sweden)

    C. Ozkan

    2012-07-01

    Full Text Available Marine oil spills due to releases of crude oil from tankers, offshore platforms, drilling rigs and wells, etc. are seriously affecting the fragile marine and coastal ecosystem and cause political and environmental concern. A catastrophic explosion and subsequent fire in the Deepwater Horizon oil platform caused the platform to burn and sink, and oil leaked continuously between April 20th and July 15th of 2010, releasing about 780,000 m3 of crude oil into the Gulf of Mexico. Today, space-borne SAR sensors are extensively used for the detection of oil spills in the marine environment, as they are independent from sun light, not affected by cloudiness, and more cost-effective than air patrolling due to covering large areas. In this study, generalization extent of an object based classification algorithm was tested for oil spill detection using multiple SAR imagery data. Among many geometrical, physical and textural features, some more distinctive ones were selected to distinguish oil and look alike objects from each others. The tested classifier was constructed from a Multilayer Perception Artificial Neural Network trained by ABC, LM and BP optimization algorithms. The training data to train the classifier were constituted from SAR data consisting of oil spill originated from Lebanon in 2007. The classifier was then applied to the Deepwater Horizon oil spill data in the Gulf of Mexico on RADARSAT-2 and ALOS PALSAR images to demonstrate the generalization efficiency of oil slick classification algorithm.

  5. Use of SAR data for proliferation monitoring

    International Nuclear Information System (INIS)

    Lafitte, M.; Robin, J.P.

    2013-01-01

    Synthetic Aperture Radar (SAR) is an active and coherent system. SAR images are complex data which contain both amplitude and phase information. The analysis of single SAR data required a very good experience and a good understanding of SAR geometry regarding layover, shadowing, texture and speckle. Image analyst can depicts and describes most of the facilities related to nuclear proliferation and weapons of mass destruction (WMD). The Amplitude Change Detection (ACD) technique consists of a combination of two or three SAR amplitude data acquired with similar orbit and frequency parameters on different dates. That technique provides a very good overview of the changes and particularly regarding vehicles activity and constructions ongoing within the area of interest over the monitoring period. One of the particularities of the SAR systems is to be coherent. The phase of a single image is not exploitable. Thus when two or more SAR data have been acquired with identical orbit and frequency parameters, the phases shift are indicators of changes such as structural changes, terrain subsidence or motion. The Multi-Temporal Coherence (MTC) product merged the two type of information previously detailed: the ACD and coherence analysis. It consists of the combination of two amplitude images and the corresponding coherence computed image. The MTC image may highlights changes between two states of a target which on the ACD analysis appeared unchanged. EUSC uses the difference interferometry techniques in order to estimate volumes that have changed between two acquisition dates. The paper is followed by the slides of the presentation. (A.C.)

  6. SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

    Directory of Open Access Journals (Sweden)

    Shengli Song

    2016-08-01

    Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

  7. SAR Raw Data Generation for Complex Airport Scenes

    Directory of Open Access Journals (Sweden)

    Jia Li

    2014-10-01

    Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

  8. GOTCHA experience report: three-dimensional SAR imaging with complete circular apertures

    Science.gov (United States)

    Ertin, Emre; Austin, Christian D.; Sharma, Samir; Moses, Randolph L.; Potter, Lee C.

    2007-04-01

    We study circular synthetic aperture radar (CSAR) systems collecting radar backscatter measurements over a complete circular aperture of 360 degrees. This study is motivated by the GOTCHA CSAR data collection experiment conducted by the Air Force Research Laboratory (AFRL). Circular SAR provides wide-angle information about the anisotropic reflectivity of the scattering centers in the scene, and also provides three dimensional information about the location of the scattering centers due to a non planar collection geometry. Three dimensional imaging results with single pass circular SAR data reveals that the 3D resolution of the system is poor due to the limited persistence of the reflectors in the scene. We present results on polarimetric processing of CSAR data and illustrate reasoning of three dimensional shape from multi-view layover using prior information about target scattering mechanisms. Next, we discuss processing of multipass (CSAR) data and present volumetric imaging results with IFSAR and three dimensional backprojection techniques on the GOTCHA data set. We observe that the volumetric imaging with GOTCHA data is degraded by aliasing and high sidelobes due to nonlinear flightpaths and sparse and unequal sampling in elevation. We conclude with a model based technique that resolves target features and enhances the volumetric imagery by extrapolating the phase history data using the estimated model.

  9. Applicability of interferometric SAR technology to ground movement and pipeline monitoring

    Science.gov (United States)

    Grivas, Dimitri A.; Bhagvati, Chakravarthy; Schultz, B. C.; Trigg, Alan; Rizkalla, Moness

    1998-03-01

    This paper summarizes the findings of a cooperative effort between NOVA Gas Transmission Ltd. (NGTL), the Italian Natural Gas Transmission Company (SNAM), and Arista International, Inc., to determine whether current remote sensing technologies can be utilized to monitor small-scale ground movements over vast geographical areas. This topic is of interest due to the potential for small ground movements to cause strain accumulation in buried pipeline facilities. Ground movements are difficult to monitor continuously, but their cumulative effect over time can have a significant impact on the safety of buried pipelines. Interferometric synthetic aperture radar (InSAR or SARI) is identified as the most promising technique of those considered. InSAR analysis involves combining multiple images from consecutive passes of a radar imaging platform. The resulting composite image can detect changes as small as 2.5 to 5.0 centimeters (based on current analysis methods and radar satellite data of 5 centimeter wavelength). Research currently in progress shows potential for measuring ground movements as small as a few millimeters. Data needed for InSAR analysis is currently commercially available from four satellites, and additional satellites are planned for launch in the near future. A major conclusion of the present study is that InSAR technology is potentially useful for pipeline integrity monitoring. A pilot project is planned to test operational issues.

  10. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2016-08-01

    Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

  11. Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

    Science.gov (United States)

    An, Quanzhi; Pan, Zongxu; You, Hongjian

    2018-01-24

    Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

  12. Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

    Science.gov (United States)

    Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

    1991-01-01

    The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

  13. Road detection in SAR images using a tensor voting algorithm

    Science.gov (United States)

    Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

    2007-11-01

    In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

  14. Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method

    Science.gov (United States)

    Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.

    2017-09-01

    Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

  15. Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

    Directory of Open Access Journals (Sweden)

    Dongqing Peng

    2016-11-01

    Full Text Available Based on Time-Frequency (TF analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach.

  16. Radar image and data fusion for natural hazards characterisation

    Science.gov (United States)

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

    2010-01-01

    Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

  17. Modulation of Tidal Channel Signatures on SAR Images Over Gyeonggi Bay in Relation to Environmental Factors

    Directory of Open Access Journals (Sweden)

    Tae-Sung Kim

    2018-04-01

    Full Text Available In this study, variations of radar backscatter features of the tidal channel in Gyeonggi Bay in the Eastern Yellow Sea were investigated using spaceborne synthetic aperture radar (SAR images. Consistent quasi-linear bright features appeared on the SAR images. Examining the detailed local bathymetry chart, we found that the features were co-located with the major axis of the tidal channel in the region. It was also shown that modulation of the radar backscatter features changed according to the environmental conditions at the time of imaging. For the statistical analysis, the bathymetric features over the tidal channel were extracted by an objective method. In terms of shape, the extracted features had higher variability in width than in length. The analysis of the variation in intensity with the coinciding bathymetric distribution confirmed that the quasi-linear bright features on the SAR images are fundamentally imprinted due to the surface current convergence and divergence caused by the bathymetry-induced tidal current variation. Furthermore, the contribution of environmental factors to the intensity modulation was quantitatively analyzed. A comparison of the variation in normalized radar cross section (NRCS with tidal current showed a positive correlation only with the perpendicular component of tidal current (r= 0.47. This implies that the modulation in intensity of the tidal channel signatures is mainly affected by the interaction with cross-current flow. On the other hand, the modulation of the NRCS over the tidal channel tended to be degraded as wind speed increased (r= −0.65. Considering the environmental circumstances in the study area, it can be inferred that the imaging capability of SAR for the detection of tidal channel signatures mainly relies on wind speed.

  18. Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2013-01-01

    Full Text Available Parabolic-reflector antennas (PRAs, usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO, physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.

  19. The use of multifrequency and polarimetric SIR-C/X-SAR data in geologic studies of Bir Safsaf, Egypt

    Science.gov (United States)

    Schaber, G.G.; McCauley, J.F.; Breed, C.S.

    1997-01-01

    Bir Safsaf, within the hyperarid 'core' of the Sahara in the Western Desert of Egypt, was recognized following the SIR-A and SIR-B missions in the 1980s as one of the key localities in northeast Africa, where penetration of dry sand by radar signals delineates previously unknown, sand-buried paleodrainage valleys ('radar-rivers') of middle Tertiary to Quaternary age. The Bir Safsaf area was targeted as a focal point for further research in sand penetration and geologic mapping using the multifrequency and polarimetric SIR-C/X-SAR sensors. Analysis of the SIR-C/X-SAR data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and structures mostly hidden from view on the ground and on Landsat TM images by a relatively thin, but extensive blanket of blow sand. Basement rock units (granitoids and gneisses) and the fractures associated with them at Bir Safsaf are shown here for the first time to be clearly delineated using C- and L-band SAR images. The detectability of most geologic features is dependent primarily on radar frequency, as shown for wind erosion patterns in bedrock at X-band (3 cm wavelength), and for geologic units and sand and clay-filled fractures in weathered crystal-line basement rocks at C-band (6 cm) and L-band (24 cm). By contrast, Quaternary paleodrainage channels are detectable at all three radar frequencies owing, among other things, to an usually thin cover of blow sand. The SIR-C/X-SAR data investigated to date enable us to make specific recommendations about the utility of certain radar sensor configurations for geologic and paleoenvironmental reconnaissance in desert regions.Analysis of the shuttle imaging radar-C/X-synthetic aperture radar (SIR-C/X-SAR) data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and

  20. Infrastructure monitoring with spaceborne SAR sensors

    CERN Document Server

    ANGHEL, ANDREI; CACOVEANU, REMUS

    2017-01-01

    This book presents a novel non-intrusive infrastructure monitoring technique based on the detection and tracking of scattering centers in spaceborne SAR images. The methodology essentially consists of refocusing each available SAR image on an imposed 3D point cloud associated to the envisaged infrastructure element and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The methodology described in this book provides a new perspective on infrastructure monitoring with spaceborne SAR images, is based on a standalone processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and researchers working in the area of critical infrastructure monitoring by radar remote sensing.

  1. Playback system designed for X-Band SAR

    International Nuclear Information System (INIS)

    Yuquan, Liu; Changyong, Dou

    2014-01-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement

  2. Playback system designed for X-Band SAR

    Science.gov (United States)

    Yuquan, Liu; Changyong, Dou

    2014-03-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

  3. Assessing ScanSAR Interferometry for Deformation Studies

    Science.gov (United States)

    Buckley, S. M.; Gudipati, K.

    2007-12-01

    There is a trend in civil satellite SAR mission design to implement an imaging strategy that incorporates both stripmap mode and ScanSAR imaging. This represents a compromise between high resolution data collection and a desire for greater spatial coverage and more frequent revisit times. However, mixed mode imaging can greatly reduce the number of stripmap images available for measuring subtle ground deformation. Although ScanSAR-ScanSAR and ScanSAR-stripmap repeat-pass interferometry have been demonstrated, these approaches are infrequently used for single interferogram formation and nonexistent for InSAR time series analysis. For future mission design, e.g., a dedicated US InSAR mission, the effect of various ScanSAR system parameter choices on InSAR time series analysis also remains unexplored. Our objective is to determine the utility of ScanSAR differential interferometry. We will demonstrate the use of ScanSAR interferograms for several previous deformation studies: localized and broad-scale urban land subsidence, tunneling, volcanic surface movements and several examples associated with the seismic cycle. We also investigate the effect of various ScanSAR burst synchronization levels on our ability to detect and make quality measurements of deformation. To avoid the issues associated with Envisat ScanSAR burst alignment and to exploit a decade of InSAR measurements, we simulate ScanSAR data by bursting (throwing away range lines of) ERS-1/2 data. All the burst mode datasets are processed using a Modified SPECAN algorithm. To investigate the effects of burst misalignment, a number of cases with varying degrees of burst overlap are considered. In particular, we look at phase decorrelation as a function of percentage of burst overlap. Coherence clearly reduces as the percentage of overlap decreases and we find a useful threshold of 40-70% burst overlap depending on the study site. In order to get a more generalized understanding for different surface conditions

  4. Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

    Directory of Open Access Journals (Sweden)

    Qingjun Zhang

    2014-01-01

    Full Text Available This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC, and the azimuth focusing are implemented by secondary range compression (SRC and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images.

  5. Neural network-based feature point descriptors for registration of optical and SAR images

    Science.gov (United States)

    Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

    2018-04-01

    Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

  6. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Q. Zhao

    2016-06-01

    Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  7. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo

    2014-01-27

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  8. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo; Liao, Mingsheng; Wang, Teng; Zhang, Lu; Shan, Wei; Wang, Chunjiao

    2014-01-01

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  9. Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images

    Science.gov (United States)

    Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.

    2017-09-01

    Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.

  10. Evaluation of the Wishart test statistics for polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2003-01-01

    A test statistic for equality of two covariance matrices following the complex Wishart distribution has previously been used in new algorithms for change detection, edge detection and segmentation in polarimetric SAR images. Previously, the results for change detection and edge detection have been...... quantitatively evaluated. This paper deals with the evaluation of segmentation. A segmentation performance measure originally developed for single-channel SAR images has been extended to polarimetric SAR images, and used to evaluate segmentation for a merge-using-moment algorithm for polarimetric SAR data....

  11. Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2014-12-01

    Full Text Available Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR, a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.

  12. SAR Imaging of Ground Moving Targets with Non-ideal Motion Error Compensation(in English

    Directory of Open Access Journals (Sweden)

    Zhou Hui

    2015-06-01

    Full Text Available Conventional ground moving target imaging algorithms mainly focus on the range cell migration correction and the motion parameter estimation of the moving target. However, in real Synthetic Aperture Radar (SAR data processing, non-ideal motion error compensation is also a critical process, which focuses and has serious impacts on the imaging quality of moving targets. Non-ideal motion error can not be compensated by either the stationary SAR motion error compensation algorithms or the autofocus techniques. In this paper, two sorts of non-ideal motion errors that affect the Doppler centroid of the moving target is analyzed, and a novel non-ideal motion error compensation algorithm is proposed based on the Inertial Navigation System (INS data and the range walk trajectory. Simulated and real data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

  13. InSAR deformation monitoring of high risk landslides

    Science.gov (United States)

    Singhroy, V.; Li, J.

    2013-05-01

    During the past year there were at least twenty five media reports of landslides and seismic activities some fatal, occurring in various areas in Canada. These high risk geohazards sites requires high resolution monitoring both spatially and temporally for mitigation purposes, since they are near populated areas and energy, transportation and communication corridors. High resolution air photos, lidar and satellite images are quite common in areas where the landslides can be fatal. Radar interferometry (InSAR) techniques using images from several radar satellites are increasingly being used in slope stability assessment. This presentation provides examples of using high-resolution (1-3m) frequent revisits InSAR techniques from RADARSAT 2 and TerraSAR X to monitor several types of high-risk landslides affecting transportation and energy corridors and populated areas. We have analyses over 200 high resolution InSAR images over a three year period on geologically different landslides. The high-resolution InSAR images are effective in characterizing differential motion within these low velocity landslides. The low velocity landslides become high risk during the active wet spring periods. The wet soils are poor coherent targets and corner reflectors provide an effective means of InSAR monitoring the slope activities.

  14. Permanent scatterer InSAR processing: Forsmark

    International Nuclear Information System (INIS)

    Dehls, John F.

    2006-04-01

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km 2 . Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of errors

  15. Permanent scatterer InSAR processing: Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Dehls, John F [Geological Survey of Norway, Trondheim (Norway)

    2006-04-15

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km{sup 2}. Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of

  16. Urban-area extraction from polarimetric SAR image using combination of target decomposition and orientation angle

    Science.gov (United States)

    Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.

    2016-05-01

    The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.

  17. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  18. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    Science.gov (United States)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  19. Coral reef detection using SAR/RADARSAT-1 images at Costa dos Corais, PE/AL, Brazil

    Directory of Open Access Journals (Sweden)

    Frederico de Moraes Rudorff

    2008-06-01

    Full Text Available The present work aimed to examine the potentials of SAR RADARSAT-1 images to detect emergent coral reefs at the Environmental Protection Area of "Costa dos Corais". Multi-view filters were applied and tested for speckle noise reduction. A digital unsupervised classification based on image segmentation was performed and the classification accuracy was evaluated by an error matrix built between the SAR image classification and a reference map obtained from a TM Landsat-5 classification. The adaptative filters showed the best results for speckle suppression and border preservation, especially the Kuan, Gamma MAP, Lee, Frost and Enhanced Frost filters. Small similarity and area thresholds (5 and 10, respectively were used for the image segmentation due to the reduced dimensions and the narrow and elongated forms of the reefs. The classification threshold of 99% had a better user's accuracy, but a lower producer's accuracy because it is a more restrictive threshold; therefore, it may be possible that it had a greater omission on reef classification. The results indicate that SAR images have a good potential for the detection of emergent coral reefs.O presente trabalho examinou o potencial de imagens SAR do RADARSAT-1 na detecção de recifes de coral expostos na Área de Proteção Ambiental das Costa dos Corais. Filtros de multi-visada foram aplicados e testados para redução do ruído speckle. Uma classificação não supervisionada baseada em uma imagem segmentada foi realizada e a acurácia da classificação foi avaliada através de uma matriz de erro construída entre a imagem classificada e o mapa de referência. Os filtros adaptativos apresentaram os melhores desempenhos para supressão de speckle e preservação de bordas, especialmente os filtros Kuan, Gamma MAP, Lee, Frost and Enhanced Frost. Os pequenos limiares de similaridade e de área (10 e 5, respectivamente foram melhores devido à forma fina e alongada dos recifes. O limiar de

  20. Analysis of the fractal dimension of volcano geomorphology through Synthetic Aperture Radar (SAR) amplitude images acquired in C and X band.

    Science.gov (United States)

    Pepe, S.; Di Martino, G.; Iodice, A.; Manzo, M.; Pepe, A.; Riccio, D.; Ruello, G.; Sansosti, E.; Tizzani, P.; Zinno, I.

    2012-04-01

    In the last two decades several aspects relevant to volcanic activity have been analyzed in terms of fractal parameters that effectively describe natural objects geometry. More specifically, these researches have been aimed at the identification of (1) the power laws that governed the magma fragmentation processes, (2) the energy of explosive eruptions, and (3) the distribution of the associated earthquakes. In this paper, the study of volcano morphology via satellite images is dealt with; in particular, we use the complete forward model developed by some of the authors (Di Martino et al., 2012) that links the stochastic characterization of amplitude Synthetic Aperture Radar (SAR) images to the fractal dimension of the imaged surfaces, modelled via fractional Brownian motion (fBm) processes. Based on the inversion of such a model, a SAR image post-processing has been implemented (Di Martino et al., 2010), that allows retrieving the fractal dimension of the observed surfaces, dictating the distribution of the roughness over different spatial scales. The fractal dimension of volcanic structures has been related to the specific nature of materials and to the effects of active geodynamic processes. Hence, the possibility to estimate the fractal dimension from a single amplitude-only SAR image is of fundamental importance for the characterization of volcano structures and, moreover, can be very helpful for monitoring and crisis management activities in case of eruptions and other similar natural hazards. The implemented SAR image processing performs the extraction of the point-by-point fractal dimension of the scene observed by the sensor, providing - as an output product - the map of the fractal dimension of the area of interest. In this work, such an analysis is performed on Cosmo-SkyMed, ERS-1/2 and ENVISAT images relevant to active stratovolcanoes in different geodynamic contexts, such as Mt. Somma-Vesuvio, Mt. Etna, Vulcano and Stromboli in Southern Italy, Shinmoe

  1. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

    Science.gov (United States)

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-01-01

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

  2. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

    Science.gov (United States)

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-02-11

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

  3. A Constellation of CubeSat InSAR Sensors for Rapid-Revisit Surface Deformation Studies

    Science.gov (United States)

    Wye, L.; Lee, S.; Yun, S. H.; Zebker, H. A.; Stock, J. D.; Wicks, C. W., Jr.; Doe, R.

    2016-12-01

    The 2007 NRC Decadal Survey for Earth Sciences highlights three major Earth surface deformation themes: 1) solid-earth hazards and dynamics; 2) human health and security; and 3) land-use change, ecosystem dynamics and biodiversity. Space-based interferometric synthetic aperture radar (InSAR) is a key change detection tool for addressing these themes. Here, we describe the mission and radar payload design for a constellation of S-band InSAR sensors specifically designed to provide the global, high temporal resolution, sub-cm level deformation accuracy needed to address some of the major Earth system goals. InSAR observations with high temporal resolution are needed to properly monitor certain nonlinearly time-varying features (e.g., unstable volcanoes, active fault lines, and heavily-used groundwater or hydrocarbon reservoirs). Good temporal coverage is also needed to reduce atmospheric artifacts by allowing multiple acquisitions to be averaged together, since each individual SAR measurement is corrupted by up to several cm of atmospheric noise. A single InSAR platform is limited in how often it can observe a given scene without sacrificing global spatial coverage. Multiple InSAR platforms provide the spatial-temporal flexibility required to maximize the science return. However, building and launching multiple InSAR platforms is cost-prohibitive for traditional satellites. SRI International (SRI) and our collaborators are working to exploit developments in nanosatellite technology, in particular the emergence of the CubeSat standard, to provide high-cadence InSAR capabilities in an affordable package. The CubeSat Imaging Radar for Earth Science (CIRES) subsystem, a prototype SAR elec­tronics package developed by SRI with support from a 2014 NASA ESTO ACT award, is specifically scaled to be a drop-in radar solution for resource-limited delivery systems like CubeSats and small airborne vehicles. Here, we present our mission concept and flow-down requirements for a

  4. Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

    Science.gov (United States)

    Yang, C. H.; Pang, Y.; Soergel, U.

    2017-05-01

    Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.

  5. What is missing? An operational inundation mapping framework by SAR data

    Science.gov (United States)

    Shen, X.; Anagnostou, E. N.; Zeng, Z.; Kettner, A.; Hong, Y.

    2017-12-01

    Compared to optical sensors, synthetic aperture radar (SAR) works all-day all-weather. In addition, its spatial resolution does not decrease with the height of the platform and is thus applicable to a range of important studies. However, existing studies did not address the operational demands of real-time inundation mapping. The direct proof is that no water body product exists for any SAR-based satellites. Then what is missing between science and products? Automation and quality. What makes it so difficult to develop an operational inundation mapping technique based on SAR data? Spectrum-wise, unlike optical water indices such as MNDWI, AWEI etc., where a relative constant threshold may apply across acquisition of images, regions and sensors, the threshold to separate water from non-water pixels in each SAR images has to be individually chosen. The optimization of the threshold is the first obstacle to the automation of the SAR data algorithm. Morphologically, the quality and reliability of the results have been compromised by over-detection caused by smooth surface and shadowing area, the noise-like speckle and under-detection caused by strong-scatter disturbance. In this study, we propose a three-step framework that addresses all aforementioned issues of operational inundation mapping by SAR data. The framework consists of 1) optimization of Wishart distribution parameters of single/dual/fully-polarized SAR data, 2) morphological removal of over-detection, and 3) machine-learning based removal of under-detection. The framework utilizes not only the SAR data, but also the synergy of digital elevation model (DEM), and optical sensor-based products of fine resolution, including the water probability map, land cover classification map (optional), and river width. The framework has been validated throughout multiple areas in different parts of the world using different satellite SAR data and globally available ancillary data products. Therefore, it has the potential

  6. Novel Polarimetric SAR Interferometry Algorithms, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Polarimetric radar interferometry (PolInSAR) is a new SAR imaging mode that is rapidly becoming an important technique for bare earth topographic mapping, tree...

  7. Visual analytics for semantic queries of TerraSAR-X image content

    Science.gov (United States)

    Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

    2015-10-01

    With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

  8. On the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR

    Directory of Open Access Journals (Sweden)

    Matthew C. Garthwaite

    2017-06-01

    Full Text Available Trihedral corner reflectors are being increasingly used as point targets in deformation monitoring studies using interferometric synthetic aperture radar (InSAR techniques. The frequency and size dependence of the corner reflector Radar Cross Section (RCS means that no single design can perform equally in all the possible imaging modes and radar frequencies available on the currently orbiting Synthetic Aperture Radar (SAR satellites. Therefore, either a corner reflector design tailored to a specific data type or a compromise design for multiple data types is required. In this paper, I outline the practical and theoretical considerations that need to be made when designing appropriate radar targets, with a focus on supporting multi-frequency SAR data. These considerations are tested by performing field experiments on targets of different size using SAR images from TerraSAR-X, COSMO-SkyMed and RADARSAT-2. Phase noise behaviour in SAR images can be estimated by measuring the Signal-to-Clutter ratio (SCR in individual SAR images. The measured SCR of a point target is dependent on its RCS performance and the influence of clutter near to the deployed target. The SCR is used as a metric to estimate the expected InSAR displacement error incurred by the design of each target and to validate these observations against theoretical expectations. I find that triangular trihedral corner reflectors as small as 1 m in dimension can achieve a displacement error magnitude of a tenth of a millimetre or less in medium-resolution X-band data. Much larger corner reflectors (2.5 m or greater are required to achieve the same displacement error magnitude in medium-resolution C-band data. Compromise designs should aim to satisfy the requirements of the lowest SAR frequency to be used, providing that these targets will not saturate the sensor of the highest frequency to be used. Finally, accurate boresight alignment of the corner reflector can be critical to the overall

  9. New challenges for a SAR toolbox

    International Nuclear Information System (INIS)

    Loreaux, P.; Quin, G.

    2013-01-01

    High resolution multi-frequency synthetic aperture radar (SAR) imagery, available since early 2008, brings all weather capability and day/night operability in support of safeguards verification. Today, a combined approach of high resolution optical and radar imagery in monitoring exercise would enable looking at any area of interest on daily basis. One of the challenges is the co-registration of SAR images acquired with different acquisition mode and also with different optical images. We show in this paper the on-going research work to find a general co-register method and an automatic tool to detect changes. Before having an operational co-register tool, a method to find automatically tie points between SAR images acquired with different acquisition mode and with optical images has to be developed. Concerning an automatic change detection method we can conclude that the study of the Harmonic mean, Geometric mean and Arithmetic mean, enables several applications like change detection for SAR imagery. Thus, we developed the MAGMA (Method for Arithmetic and Geometric Means Analysis) change detection method. As shown in this paper, the MAGMA method improves the Maximum Likelihood techniques like GLRT, using Information-Theory concepts to detect changes between SAR amplitude images. The major improvement consists in a lower false detection rate, especially in low amplitude areas. The second improvement consists in a better location of the changes in clearly delimited areas, which enables precise interpretations. Results presented here reveal the potential of high resolution radar imagery for a baseline description of some sites, change detection based on repeat pass imagery acquisitions and site specific constraints in coherent change detection due to cover conditions. (A.C.)

  10. Research on a dem Coregistration Method Based on the SAR Imaging Geometry

    Science.gov (United States)

    Niu, Y.; Zhao, C.; Zhang, J.; Wang, L.; Li, B.; Fan, L.

    2018-04-01

    Due to the systematic error, especially the horizontal deviation that exists in the multi-source, multi-temporal DEMs (Digital Elevation Models), a method for high precision coregistration is needed. This paper presents a new fast DEM coregistration method based on a given SAR (Synthetic Aperture Radar) imaging geometry to overcome the divergence and time-consuming problem of the conventional DEM coregistration method. First, intensity images are simulated for two DEMs under the given SAR imaging geometry. 2D (Two-dimensional) offsets are estimated in the frequency domain using the intensity cross-correlation operation in the FFT (Fast Fourier Transform) tool, which can greatly accelerate the calculation process. Next, the transformation function between two DEMs is achieved via the robust least-square fitting of 2D polynomial operation. Accordingly, two DEMs can be precisely coregistered. Last, two DEMs, i.e., one high-resolution LiDAR (Light Detection and Ranging) DEM and one low-resolution SRTM (Shutter Radar Topography Mission) DEM, covering the Yangjiao landslide region of Chongqing are taken as an example to test the new method. The results indicate that, in most cases, this new method can achieve not only a result as much as 80 times faster than the minimum elevation difference (Least Z-difference, LZD) DEM registration method, but also more accurate and more reliable results.

  11. An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

    Directory of Open Access Journals (Sweden)

    Tingting Jin

    2017-04-01

    Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

  12. Generalized internal multiple imaging

    KAUST Repository

    Zuberi, Mohammad Akbar Hosain

    2014-12-04

    Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green\\'s function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green\\'s function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green\\'s function and renders the higher order internal multiple image for display on a display device.

  13. Generalized internal multiple imaging

    KAUST Repository

    Zuberi, Mohammad Akbar Hosain; Alkhalifah, Tariq

    2014-01-01

    Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green's function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green's function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green's function and renders the higher order internal multiple image for display on a display device.

  14. STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE

    Directory of Open Access Journals (Sweden)

    D. Xue

    2018-04-01

    Full Text Available In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.

  15. Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification

    DEFF Research Database (Denmark)

    Loosvelt, Lien; Peters, Jan; Skriver, Henning

    2012-01-01

    , we introduce Random Forests for the probabilistic mapping of vegetation from high-dimensional remote sensing data and present a comprehensive methodology to assess and analyze classification uncertainty based on the local probabilities of class membership. We apply this method to SAR image data...

  16. Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

    Science.gov (United States)

    Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

    2016-05-01

    Fully Polarimetric SAR (PolSAR) data is used for scattering information retrieval from single SAR resolution cell. Single SAR resolution cell may contain contribution from more than one scattering objects. Hence, single or dual polarized data does not provide all the possible scattering information. So, to overcome this problem fully Polarimetric data is used. It was observed in previous study that fully Polarimetric data of different dates provide different scattering values for same object and coefficient of determination obtained from linear regression between volume scattering and aboveground biomass (AGB) shows different values for the SAR dataset of different dates. Scattering values are important input elements for modelling of forest aboveground biomass. In this research work an approach is proposed to get reliable scattering from interferometric pair of fully Polarimetric RADARSAT-2 data. The field survey for data collection was carried out for Barkot forest during November 10th to December 5th, 2014. Stratified random sampling was used to collect field data for circumference at breast height (CBH) and tree height measurement. Field-measured AGB was compared with the volume scattering elements obtained from decomposition modelling of individual PolSAR images and PolInSAR coherency matrix. Yamaguchi 4-component decomposition was implemented to retrieve scattering elements from SAR data. PolInSAR based decomposition was the great challenge in this work and it was implemented with certain assumptions to create Hermitian coherency matrix with co-registered polarimetric interferometric pair of SAR data. Regression analysis between field-measured AGB and volume scattering element obtained from PolInSAR data showed highest (0.589) coefficient of determination. The same regression with volume scattering elements of individual SAR images showed 0.49 and 0.50 coefficients of determination for master and slave images respectively. This study recommends use of

  17. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Directory of Open Access Journals (Sweden)

    Chen Gong-bo

    2013-06-01

    Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

  18. Estimation of Bridge Height over Water from Polarimetric SAR Image Data Using Mapping and Projection Algorithm and De-Orientation Theory

    Science.gov (United States)

    Wang, Haipeng; Xu, Feng; Jin, Ya-Qiu; Ouchi, Kazuo

    An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.

  19. Generalized internal multiple imaging

    KAUST Repository

    Zuberi, M. A. H.

    2014-08-05

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling. If properly imaged, internal multiples (internally scattered energy) can enhance the seismic image. Conventionally, to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we have developed a generalized internal multiple imaging procedure that images any order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model, usually used for conventional imaging. For the first-order internal multiples, the approach consisted of three steps, in which we first back propagated the recorded surface seismic data using the background Green’s function, then crosscorrelated the back-propagated data with the recorded data, and finally crosscorrelated the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples, and it is almost free of the single-scattering recorded energy. The cost includes one additional crosscorrelation over the conventional single-scattering imaging application. We generalized this method to image internal multiples of any order separately. The resulting images can be added to the conventional single-scattering image, obtained, e.g., from Kirchhoff or reverse-time migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering (double scattering) demonstrated the effectiveness of the approach.

  20. SAR Imaging of Wave Tails: Recognition of Second Mode Internal Wave Patterns and Some Mechanisms of their Formation

    Science.gov (United States)

    da Silva, Jose C. B.; Magalhaes, J. M.; Buijsman, M. C.; Garcia, C. A. E.

    2016-08-01

    Mode-2 internal waves are usually not as energetic as larger mode-1 Internal Solitary Waves (ISWs), but they have attracted a great deal of attention in recent years because they have been identified as playing a significant role in mixing shelf waters [1]. This mixing is particularly effective for mode-2 ISWs because the location of these waves in the middle of the pycnocline plays an important role in eroding the barrier between the base of the surface mixed layer and the stratified deep layer below. An urgent problem in physical oceanography is therefore to account for the magnitude and distribution of ISW-driven mixing, including mode-2 ISWs. Several generation mechanisms of mode-2 ISWs have been identified. These include: (1) mode-1 ISWs propagating onshore (shoaling) and entering the breaking instability stage, or propagating over a steep sill; (2) a mode-1 ISW propagating offshore (antishoaling) over steep slopes of the shelf break, and undergoing modal transformation; (3) intrusion of the whole head of a gravity current into a three-layer fluid; (4) impingement of an internal tidal beam on the pycnocline, itself emanating from critical bathymetry; (5) nonlinear disintegration of internal tide modes; (6) lee wave mechanism. In this paper we provide methods to identify internal wave features denominated "Wave Tails" in SAR images of the ocean surface, which are many times associated with second mode internal waves. The SAR case studies that are presented portray evidence of the aforementioned generation mechanisms, and we further discuss possible methods to discriminate between the various types of mode-2 ISWs in SAR images, that emerge from these physical mechanisms. Some of the SAR images correspond to numerical simulations with the MITgcm in fully nonlinear and nonhydrostatic mode and in a 2D configuration with realistic stratification, bathymetry and other environmental conditions.Results of a global survey with some of these observations are presented

  1. Detecting and monitoring UCG subsidence with InSAR

    Energy Technology Data Exchange (ETDEWEB)

    Mellors, R J; Foxall, W; Yang, X

    2012-03-23

    The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidence related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness.

  2. Ground Subsidence over Beijing-Tianjin-Hebei Region during Three Periods of 1992 to 2014 Monitored by Interferometric SAR

    Directory of Open Access Journals (Sweden)

    ZHANG Yonghong

    2016-09-01

    Full Text Available The Beijing-Tianjin-Hebei region suffers the most serious ground subsidence in China, which has caused huge economic losses every year. Therefore, ground subsidence was listed as an important mission in the project of geographic conditions monitoring over Beijing-Tianjin-Hebei launched by the National Administration of Surveying, Mapping and Geoinformation in 2013. In this paper, we propose a methodology of ground subsidence monitoring over wide area, which is entitled "multiple master-image coherent target small-baseline interferometric SAR (MCTSB-InSAR". MCTSB-InSAR is an improved time series InSAR technique with some unique features. SAR datasets used for ground subsidence monitoring over the Beijing-Tianjin-Hebei region include ERS-1/2 SAR images acquired between 1992 to 2000, ENVISAT ASAR images acquired between 2003 to 2010 and RADARSAT-2 images acquired between 2012 to 2014. This research represents a first ever effort on mapping ground subsidence over Beijing-Tianjin-Hebei region and over such as a long time span in China. In comparison with more than 120 leveling measurements collected in Beijing and Tianjin, the derived subsidence velocity has the accuracy of 8.7mm/year (1992—2000, 4.7mm/year (2003—2010, and 5.4mm/year (2012—2014 respectively. The spatial-temporal characteristics of the development of ground subsidence in Beijing and Tianjin are analyzed. In general, ground subsidence in Beijing kept continuously expanding in the period of 1992 to 2014. While, ground subsidence in Tianjin had already been serious in 1990s, had dramatically expanded during 2000s, and started to alleviate in recent years. The monitoring result is of high significance for prevention and mitigation of ground subsidence disaster, for making development plan, for efficient and effective utilization of water resource, and for adjustment of economic framework of this region. The result also indicates the effectiveness and reliability of the MCTSB-InSAR

  3. MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    M. Soheili Majd

    2012-09-01

    Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.

  4. SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

    Science.gov (United States)

    Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

    2018-05-01

    Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

  5. Exploitation of Amplitude and Phase of Satellite SAR Images for Landslide Mapping: The Case of Montescaglioso (South Italy

    Directory of Open Access Journals (Sweden)

    Federico Raspini

    2015-11-01

    Full Text Available Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy. In this paper, ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry and amplitude information (through speckle tracking techniques of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide.

  6. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  7. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    < 2m and the zero-crossing period during the satellite overpass is small (< 6s, �O�O < 60m). We therefore utilized the visit of one of the authors (Sarma) to the Southampton Oceanographic Centre, U.K., to procure two ERS-1 digital image mode SAR...-dimensional FFT as well as a computer program for downloading SAR data from CCT. Finally we owe a debt of gratitude to J C da Silva, Southampton Oceanographic Centre, U K for sharing some of his SAR data with us. References Allan T. D. (Ed) (1983...

  8. Landslide precursory deformation interpretation using ALOS-2/PALSAR-2 InSAR image along Min River in Maoxien, Sichuan Province, China

    Science.gov (United States)

    Sato, H. P.

    2017-12-01

    Maoxien area in Sichuan Province, China has many landslide. For example, landslide (rock avalanche) occurred on the slope in Xinmocun Village in Maoxeien on 24 June 2017. I produced and interpreetd InSAR image using ALOS/PALSAR data observed on 19 Jul 2007-3 Sep 2007 and on 27 Jan 2011-14 Mar 2011, and ALOS-2/PALSAR-2 data observed on 26 Jul 2015-13 Dec 2015 and on 13 Dec 2015-11 Dec 2016. These images give good coherence and it was easy to identify local landslide surface deformation. As a result, e.g., two slopes were estimated to have local landslide surface deformation; one is at 103.936587 deg E and 32.04462 deg N, another is at 103.674754 deg E and 31.852838 N. However, the slope in Xinmocun Village was not identified as landslide precursory deformation. In the poster I will present more InSAR image observed after 11 Dec 2016 and discuss the possibility of local landslide surface deformaton using InSAR image. ALOS/PALSAR and ALOS-2/PALSAR-2 data were provided by JAXA through Landslide Working Group in JAXA and through Special Research 2015-B-02 of Earthquake Research Institute/Tokyo University. This study was supported by KAKENHI (17H02973).

  9. The Advanced Rapid Imaging and Analysis (ARIA) Project: Status of SAR products for Earthquakes, Floods, Volcanoes and Groundwater-related Subsidence

    Science.gov (United States)

    Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.

    2017-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano

  10. M-Estimators of Roughness and Scale for -Modelled SAR Imagery

    Directory of Open Access Journals (Sweden)

    Frery Alejandro C

    2002-01-01

    Full Text Available The GA0 distribution is assumed as the universal model for multilook amplitude SAR imagery data under the multiplicative model. This distribution has two unknown parameters related to the roughness and the scale of the signal, that can be used in image analysis and processing. It can be seen that maximum likelihood and moment estimators for its parameters can be influenced by small percentages of "outliers"; hence, it is of outmost importance to find robust estimators for these parameters. One of the best-known classes of robust techniques is that of M-estimators, which are an extension of the maximum likelihood estimation method. In this work we derive the M-estimators for the parameters of the distribution, and compare them with maximum likelihood estimators with a Monte-Carlo experience. It is checked that this robust technique is superior to the classical approach under the presence of corner reflectors, a common source of contamination in SAR images. Numerical issues are addressed, and a practical example is provided.

  11. Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

    Science.gov (United States)

    Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

    2018-05-01

    Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

  12. A MATCHING METHOD TO REDUCE THE INFLUENCE OF SAR GEOMETRIC DEFORMATION

    Directory of Open Access Journals (Sweden)

    C. Gao

    2018-04-01

    Full Text Available There are large geometrical deformations in SAR image, including foreshortening, layover, shade,which leads to SAR Image matching with low accuracy. Especially in complex terrain area, the control points are difficult to obtain, and the matching is difficult to achieve. Considering the impact of geometric distortions in SAR image pairs, a matching algorithm with a combination of speeded up robust features (SURF and summed of normalize cross correlation (SNCC was proposed, which can avoid the influence of SAR geometric deformation. Firstly, SURF algorithm was utilized to predict the search area. Then the matching point pairs was selected based on summed of normalized cross correlation. Finally, false match points were eliminated by the bidirectional consistency. SURF algorithm can control the range of matching points, and the matching points extracted from the deformation area are eliminated, and the matching points with stable and even distribution are obtained. The experimental results demonstrated that the proposed algorithm had high precision, and can effectively avoid the effect of geometric distortion on SAR image matching. Meet accuracy requirements of the block adjustment with sparse control points.

  13. Mapping mountain meadow with high resolution and polarimetric SAR data

    International Nuclear Information System (INIS)

    Tian, Bangsen; Li, Zhen; Xu, Juan; Fu, Sitao; Liu, Jiuli

    2014-01-01

    This paper presents a method to map the large grassland in the eastern margin of the Tibetan Plateau with the high resolution polarimetric SAR (PolSAR) imagery. When PolSAR imagery is used for land cover classification, the brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. The objective of this paper is twofold: (1) we first extend the theory of SAR terrain correction to the polarimetric case, to utilize the entire available polarimetric signature, where correction is performed explicitly based on a matrix format like covariance matrix. (2) Next, the orthoectified PolSAR is applied to classify mountain meadow and investigate the potential of PolSAR in mapping grassland. In this paper, the gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product. Secondly, the impact of radiometric correction upon classification accuracy is investigated. A supervised classification is performed on the orthorectified Radarsat-2 PolSAR to map the spatial distribution of meadow and evaluate monitoring capabilities of mountain meadow

  14. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

    International Nuclear Information System (INIS)

    Mera, David; Cotos, José M.; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-01-01

    Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  15. An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

    Science.gov (United States)

    Ruan, Z.; Yan, S.; Liu, G.; LV, M.

    2017-12-01

    Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS

  16. Estimation of the Above Ground Biomass of Tropical Forests using Polarimetric and Tomographic SAR Data Acquired at P Band and 3-D Imaging Techniques

    Science.gov (United States)

    Ferro-Famil, L.; El Hajj Chehade, B.; Ho Tong Minh, D.; Tebaldini, S.; LE Toan, T.

    2016-12-01

    Developing and improving methods to monitor forest biomass in space and time is a timely challenge, especially for tropical forests, for which SAR imaging at larger wavelength presents an interesting potential. Nevertheless, directly estimating tropical forest biomass from classical 2-D SAR images may reveal a very complex and ill-conditioned problem, since a SAR echo is composed of numerous contributions, whose features and importance depend on many geophysical parameters, such has ground humidity, roughness, topography… that are not related to biomass. Recent studies showed that SAR modes of diversity, i.e. polarimetric intensity ratios or interferometric phase centers, do not fully resolve this under-determined problem, whereas Pol-InSAR tree height estimates may be related to biomass through allometric relationships, with, in general over tropical forests, significant levels of uncertainty and lack of robustness. In this context, 3-D imaging using SAR tomography represents an appealing solution at larger wavelengths, for which wave penetration properties ensures a high quality mapping of a tropical forest reflectivity in the vertical direction. This paper presents a series of studies led, in the frame of the preparation of the next ESA mission BIOMASS, on the estimation of biomass over a tropical forest in French Guiana, using Polarimetric SAR Tomographic (Pol-TomSAR) data acquired at P band by ONERA. It is then shown that Pol-TomoSAR significantly improves the retrieval of forest above ground biomass (AGB) in a high biomass forest (200 up to 500 t/ha), with an error of only 10% at 1.5-ha resolution using a reflectivity estimates sampled at a predetermined elevation. The robustness of this technique is tested by applying the same approach over another site, and results show a similar relationship between AGB and tomographic reflectivity over both sites. The excellent ability of Pol-TomSAR to retrieve both canopy top heights and ground topography with an error

  17. SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

    2010-05-22

    This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

  18. Estimating Elevation Angles From SAR Crosstalk

    Science.gov (United States)

    Freeman, Anthony

    1994-01-01

    Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

  19. Wake-based ship route estimation in high-resolution SAR images

    Science.gov (United States)

    Graziano, M. Daniela; Rufino, Giancarlo; D'Errico, Marco

    2014-10-01

    This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the images ship wake on the basis of the well known theoretical characteristics of the wakes' geometry and components, that are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic procedures, as well as speed measure accuracy.

  20. A SAR Observation and Numerical Study on Ocean Surface Imprints of Atmospheric Vortex Streets

    Directory of Open Access Journals (Sweden)

    William G. Pichel

    2008-05-01

    Full Text Available The sea surface imprints of Atmospheric Vortex Street (AVS off Aleutian Volcanic Islands, Alaska were observed in two RADARSAT-1 Synthetic Aperture Radar (SAR images separated by about 11 hours. In both images, three pairs of distinctive vortices shedding in the lee side of two volcanic mountains can be clearly seen. The length and width of the vortex street are about 60-70 km and 20 km, respectively. Although the AVS’s in the two SAR images have similar shapes, the structure of vortices within the AVS is highly asymmetrical. The sea surface wind speed is estimated from the SAR images with wind direction input from Navy NOGAPS model. In this paper we present a complete MM5 model simulation of the observed AVS. The surface wind simulated from the MM5 model is in good agreement with SAR-derived wind. The vortex shedding rate calculated from the model run is about 1 hour and 50 minutes. Other basic characteristics of the AVS including propagation speed of the vortex, Strouhal and Reynolds numbers favorable for AVS generation are also derived. The wind associated with AVS modifies the cloud structure in the marine atmospheric boundary layer. The AVS cloud pattern is also observed on a MODIS visible band image taken between the two RADARSAT SAR images. An ENVISAT advance SAR image taken 4 hours after the second RADARSAT SAR image shows that the AVS has almost vanished.

  1. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  2. Wind mapping offshore in coastal Mediterranean area using SAR images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  3. Skipping the real world: Classification of PolSAR images without explicit feature extraction

    Science.gov (United States)

    Hänsch, Ronny; Hellwich, Olaf

    2018-06-01

    The typical processing chain for pixel-wise classification from PolSAR images starts with an optional preprocessing step (e.g. speckle reduction), continues with extracting features projecting the complex-valued data into the real domain (e.g. by polarimetric decompositions) which are then used as input for a machine-learning based classifier, and ends in an optional postprocessing (e.g. label smoothing). The extracted features are usually hand-crafted as well as preselected and represent (a somewhat arbitrary) projection from the complex to the real domain in order to fit the requirements of standard machine-learning approaches such as Support Vector Machines or Artificial Neural Networks. This paper proposes to adapt the internal node tests of Random Forests to work directly on the complex-valued PolSAR data, which makes any explicit feature extraction obsolete. This approach leads to a classification framework with a significantly decreased computation time and memory footprint since no image features have to be computed and stored beforehand. The experimental results on one fully-polarimetric and one dual-polarimetric dataset show that, despite the simpler approach, accuracy can be maintained (decreased by only less than 2 % for the fully-polarimetric dataset) or even improved (increased by roughly 9 % for the dual-polarimetric dataset).

  4. Two-step single slope/SAR ADC with error correction for CMOS image sensor.

    Science.gov (United States)

    Tang, Fang; Bermak, Amine; Amira, Abbes; Amor Benammar, Mohieddine; He, Debiao; Zhao, Xiaojin

    2014-01-01

    Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μ m CMOS technology. The chip area of the proposed ADC is 7 μ m × 500 μ m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k  μ m(2) · cycles/sample.

  5. Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

    Directory of Open Access Journals (Sweden)

    Fang Tang

    2014-01-01

    Full Text Available Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μm CMOS technology. The chip area of the proposed ADC is 7 μm × 500 μm. The measurement results show that the energy efficiency figure-of-merit (FOM of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μm2·cycles/sample.

  6. URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

    Directory of Open Access Journals (Sweden)

    U. G. Sefercik

    2017-09-01

    Full Text Available In synthetic aperture radar (SAR technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX and Cosmo-SkyMed (CSK since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM acquisition for urban areas utilizing interferometric SAR (InSAR technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

  7. Near Surface Soil Moisture Estimation Using SAR Images: A Case Study in the Mediterranean Area of Catalonia

    Science.gov (United States)

    Reppucci, Antonio; Moreno, Laura

    2010-12-01

    Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.

  8. The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

    Science.gov (United States)

    Tan, Linglong; Li, Changkai; Wang, Yueqin

    2018-04-01

    SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

  9. Improved techniques to utilize remotely sensed data from multi-frequency imaging radar polarimeter; Tashuha tahenha SAR data no riyoho no kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Okada, K [Sumitomo Metal Mining Co. Ltd., Osaka (Japan); Maruyama, Y [Earth Remote Sensing Data Analysis Center, Tokyo (Japan); Tapley, I

    1997-05-27

    It was intended to serve for establishing specifications for a next generation SAR such as PALSAR through studying methods for evaluating and utilizing the multi-frequency, multi-polarized wave SAR data. Placing an emphasis on utilization of the NASA`s AIRSAR, identification was made on backscatter amount recorded on the SAR data, terrestrial constitutional substances, patterns of the ground surface, micro-topography and such terrestrial conditions as vegetation and land utilization. Their mutual relationships were also analyzed. A noise reduction method usable on multi-band data can be applied to the AIRSAR data, and can reduce noise effectively. Images with more volume of information can be acquired from multi-band images with the same polarization wave than from multi-polarization wave images with the same band. As a result of estimating terrestrial permitivity by using the method invented by Dubois and van Zyl, most of the subject area is judged to have terrestrial substances dried at the time of having acquired the images. A colluvium rich with exposed rock regions and gravels was identified as an area having higher permitivity than the former area. Images of terrestrial roughness were divided largely into smooth flat lands, sand and gravel distributed regions, exposed rock regions, and plant distributed regions along river basins. 3 refs., 2 figs., 1 tab.

  10. Methods of evaluating the effects of coding on SAR data

    Science.gov (United States)

    Dutkiewicz, Melanie; Cumming, Ian

    1993-01-01

    It is recognized that mean square error (MSE) is not a sufficient criterion for determining the acceptability of an image reconstructed from data that has been compressed and decompressed using an encoding algorithm. In the case of Synthetic Aperture Radar (SAR) data, it is also deemed to be insufficient to display the reconstructed image (and perhaps error image) alongside the original and make a (subjective) judgment as to the quality of the reconstructed data. In this paper we suggest a number of additional evaluation criteria which we feel should be included as evaluation metrics in SAR data encoding experiments. These criteria have been specifically chosen to provide a means of ensuring that the important information in the SAR data is preserved. The paper also presents the results of an investigation into the effects of coding on SAR data fidelity when the coding is applied in (1) the signal data domain, and (2) the image domain. An analysis of the results highlights the shortcomings of the MSE criterion, and shows which of the suggested additional criterion have been found to be most important.

  11. Emergency product generation for disaster management using RISAT and DMSAR quick look SAR processors

    Science.gov (United States)

    Desai, Nilesh; Sharma, Ritesh; Kumar, Saravana; Misra, Tapan; Gujraty, Virendra; Rana, SurinderSingh

    2006-12-01

    Since last few years, ISRO has embarked upon the development of two complex Synthetic Aperture Radar (SAR) missions, viz. Spaceborne Radar Imaging Satellite (RISAT) and Airborne SAR for Disaster Mangement (DMSAR), as a capacity building measure under country's Disaster Management Support (DMS) Program, for estimating the extent of damage over large areas (~75 Km) and also assess the effectiveness of the relief measures undertaken during natural disasters such as cyclones, epidemics, earthquakes, floods and landslides, forest fires, crop diseases etc. Synthetic Aperture Radar (SAR) has an unique role to play in mapping and monitoring of large areas affected by natural disasters especially floods, owing to its unique capability to see through clouds as well as all-weather imaging capability. The generation of SAR images with quick turn around time is very essential to meet the above DMS objectives. Thus the development of SAR Processors, for these two SAR systems poses considerable challenges and design efforts. Considering the growing user demand and inevitable necessity for a full-fledged high throughput processor, to process SAR data and generate image in real or near-real time, the design and development of a generic SAR Processor has been taken up and evolved, which will meet the SAR processing requirements for both Airborne and Spaceborne SAR systems. This hardware SAR processor is being built, to the extent possible, using only Commercial-Off-The-Shelf (COTS) DSP and other hardware plug-in modules on a Compact PCI (cPCI) platform. Thus, the major thrust has been on working out Multi-processor Digital Signal Processor (DSP) architecture and algorithm development and optimization rather than hardware design and fabrication. For DMSAR, this generic SAR Processor operates as a Quick Look SAR Processor (QLP) on-board the aircraft to produce real time full swath DMSAR images and as a ground based Near-Real Time high precision full swath Processor (NRTP). It will

  12. Performance Analysis for Airborne Interferometric SAR Affected by Flexible Baseline Oscillation

    Directory of Open Access Journals (Sweden)

    Liu Zhong-sheng

    2014-04-01

    Full Text Available The airborne interferometric SAR platform suffers from instability factors, such as air turbulence and mechanical vibrations during flight. Such factors cause the oscillation of the flexible baseline, which leads to significant degradation of the performance of the interferometric SAR system. This study is concerned with the baseline oscillation. First, the error of the slant range model under baseline oscillation conditions is formulated. Then, the SAR complex image signal and dual-channel correlation coefficient are modeled based on the first-order, second-order, and generic slant range error. Subsequently, the impact of the baseline oscillation on the imaging and interferometric performance of the SAR system is analyzed. Finally, simulations of the echo data are used to validate the theoretical analysis of the baseline oscillation in the airborne interferometric SAR.

  13. Detection of macroalgae blooms by complex SAR imagery

    International Nuclear Information System (INIS)

    Shen, Hui; Perrie, William; Liu, Qingrong; He, Yijun

    2014-01-01

    Highlights: • Complex SAR imagery enables better recognition of macroalgae patches. • Combination of different information in SAR matrix forms new index factors. • Proposed index factors contribute to unsupervised recognition of macroalgae. -- Abstract: Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean

  14. 3D Monitoring of Buildings Using TerraSAR-X InSAR, DInSAR and PolSAR Capacities

    Directory of Open Access Journals (Sweden)

    Flora Weissgerber

    2017-09-01

    Full Text Available The rapid expansion of cities increases the need of urban remote sensing for a large scale monitoring. This paper provides greater understanding of how TerraSAR-X (TSX high-resolution abilities enable to reach the spatial precision required to monitor individual buildings, through the use of a 4 year temporal stack of 100 images over Paris (France. Three different SAR modes are investigated for this purpose. First a method involving a whole time-series is proposed to measure realistic heights of buildings. Then, we show that the small wavelength of TSX makes the interferometric products very sensitive to the ordinary building-deformation, and that daily deformation can be measured over the entire building with a centimetric accuracy, and without any a priori on the deformation evolution, even when neglecting the impact of the atmosphere. Deformations up to 4 cm were estimated for the Eiffel Tower and up to 1 cm for other lower buildings. These deformations were analyzed and validated with weather and in situ local data. Finally, four TSX polarimetric images were used to investigate geometric and dielectric properties of buildings under the deterministic framework. Despite of the resolution loss of this mode, the possibility to estimate the structural elements of a building orientations and their relative complexity in the spatial organization are demonstrated.

  15. Early appearance of SARS on chest CT scan

    International Nuclear Information System (INIS)

    Cheng Xiaoguang; Feng Suchen; Xia Guoguang; Zhao Tao; Gu Xiang; Qu Hui

    2003-01-01

    Objective: To evaluate the early appearance of SARS on chest CT scan and its role in the early diagnosis. Methods: Forty cases of SARS in keeping with the criteria of the Ministry of Health had chest CT scans within 7 days of onset of symptoms, and CR chest X-ray films were available as well. These chest X-rays and CT images were retrospectively reviewed to determine if there were any abnormalities on the images. The lesions on the chest CT images were then further analyzed in terms of the number, location, size, and density. Results: Positive abnormalities on chest CT scans were revealed in all 40 SARS cases. Positive findings on CR chest films were showed in only 25 cases, equivocal in 6, and normal in 9 cases. The main abnormalities seen on CT and X-rays were pulmonary infiltrations varied markedly in severity. 70 % cases had 1 or 2 lesions on chest CT scan, 30 % cases had 3 or more lesions. The lesions seen on chest CT scan tended to be ground-glass opacification, sometimes with consolidation which was very faint and inhomogeneous, easily missed on chest X-rays. Typically the lesions were located in the periphery of the lung, or both central and peripheral lung, but very rare in a pure central location. They were commonly in the shape of patch or ball. Conclusions: Chest CT scan is much more sensitive in detecting the lesions of the lung in SARS. The early appearance of SARS on chest CT scan is characteristic but non-specific, indicating that chest CT scan plays a very important role in the early diagnosis and differential diagnosis of SARS

  16. Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

    Directory of Open Access Journals (Sweden)

    Sang-Hoon Hong

    2015-07-01

    Full Text Available The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-pol synthetic aperture radar (PolSAR data for classifying wetland vegetation in the Everglades. We processed quad-pol data using the Hong & Wdowinski four-component decomposition, which accounts for double bounce scattering in the cross-polarization signal. The calculated decomposition images consist of four scattering mechanisms (single, co- and cross-pol double, and volume scattering. We applied an object-oriented image analysis approach to classify vegetation types with the decomposition results. We also used a high-resolution multispectral optical RapidEye image to compare statistics and classification results with Synthetic Aperture Radar (SAR observations. The calculated classification accuracy was higher than 85%, suggesting that the TerraSAR-X quad-pol SAR signal had a high potential for distinguishing different vegetation types. Scattering components from SAR acquisition were particularly advantageous for classifying mangroves along tidal channels. We conclude that the typical scattering behaviors from model-based decomposition are useful for discriminating among different wetland vegetation types.

  17. Using SAR images to delineate ocean oil slicks with a texture-classifying neural network algorithm (TCNNA)

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pineda, O.; MacDonald, I.R. [Florida State Univ., Tallahassee, FL (United States). Dept. of Oceanography; Zimmer, B. [Texas A and M Univ., Corpus Christi, TX (United States). Dept. of Mathematics and Statistics; Howard, M. [Texas A and M Univ., College Station, TX (United States). Dept. of Oceanography; Pichel, W. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Center for Satellite Applications and Research, National Environmental Satellite, Data and Information Service; Li, X. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Systems Group, National Environmental Satellite, Data and Information

    2009-10-15

    Synthetic aperture radar (SAR) is used to detect surfactant layers produced by floating oil on the ocean surface. This study presented details of a texture-classifying neural network algorithm (TCNNA) designed to process SAR data from a wide selection of beam modes. Patterns from SAR imagery were extracted in a semi-supervised procedure using a combination of edge-detection filters; texture descriptors; collection information; and environmental data. Various natural oil seeps in the Gulf of Mexico were used as case studies. An analysis of the case studies demonstrated that the TCNNA was able to extract targets and rapidly interpret images collected under a range of environmental conditions. Results presented by the TCNNA were used to evaluate the effects of different environmental conditions on the expressions of oil slicks detected by the data. Optimal incidence angle ranges and wind speed ranges for surfactant film detection were also presented. Results obtained by the TCNNA can be stored and manipulated in geographic information system (GIS) data layers. 26 refs., 1 tab., 7 figs.

  18. ASTC-MIMO-TOPS Mode with Digital Beam-Forming in Elevation for High-Resolution Wide-Swath Imaging

    Directory of Open Access Journals (Sweden)

    Pingping Huang

    2015-03-01

    Full Text Available Future spaceborne synthetic aperture radar (SAR missions require complete and frequent coverage of the earth with a high resolution. Terrain Observation by Progressive Scans (TOPS is a novel wide swath mode but has impaired azimuth resolution. In this paper, an innovative extended TOPS mode named Alamouti Space-time Coding multiple-input multiple-output TOPS (ASTC-MIMO-TOPS mode combined with digital beam-forming (DBF in elevation and multi-aperture SAR signal reconstruction in azimuth is proposed. This innovative mode achieves wide-swath coverage with a high geometric resolution and also overcomes major drawbacks in conventional MIMO SAR systems. The data processing scheme of this imaging scheme is presented in detail. The designed system example of the proposed ASTC-MIMO-TOPS mode, which has the imaging capacity of a 400 km wide swath with an azimuth resolution of 3 m, is given. Its system performance analysis results and simulated imaging results on point targets demonstrate the potential of the proposed novel spaceborne SAR mode for high-resolution wide-swath (HRWS imaging.

  19. Analysis of the Effect of Radio Frequency Interference on Repeat Track Airborne InSAR System

    Directory of Open Access Journals (Sweden)

    Ding Bin

    2012-03-01

    Full Text Available The SAR system operating at low frequency is susceptible to Radio Frequency Interference (RFI from television station, radio station, and some other civil electronic facilities. The presence of RFI degrades the SAR image quality, and obscures the targets in the scene. Furthermore, RFI can cause interferometric phase error in repeat track InSAR system. In order to analyze the effect of RFI on interferometric phase of InSAR, real measured RFI signal are added on cone simulated SAR echoes. The imaging and interferometric processing results of both the RFI-contaminated and raw data are given. The effect of real measured RFI signal on repeat track InSAR system is analyzed. Finally, the imaging and interferometric processing results of both with and without RFI suppressed of the P band airborne repeat track InSAR real data are presented, which demonstrates the efficiency of the RFI suppression method in terms of decreasing the interferometric phase errors caused by RFI.

  20. Simulation-Based Evaluation of Light Posts and Street Signs as 3-D Geolocation Targets in SAR Images

    Science.gov (United States)

    Auer, S.; Balss, U.

    2017-05-01

    The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  1. SIMULATION-BASED EVALUATION OF LIGHT POSTS AND STREET SIGNS AS 3-D GEOLOCATION TARGETS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    S. Auer

    2017-05-01

    Full Text Available The assignment of phase center positions (in 2D or 3D derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR. For the first time, the appearance of the targets is analyzed in 2D (image plane and 3D space (world coordinates of scene model and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  2. Program Merges SAR Data on Terrain and Vegetation Heights

    Science.gov (United States)

    Siqueira, Paul; Hensley, Scott; Rodriguez, Ernesto; Simard, Marc

    2007-01-01

    X/P Merge is a computer program that estimates ground-surface elevations and vegetation heights from multiple sets of data acquired by the GeoSAR instrument [a terrain-mapping synthetic-aperture radar (SAR) system that operates in the X and bands]. X/P Merge software combines data from X- and P-band digital elevation models, SAR backscatter magnitudes, and interferometric correlation magnitudes into a simplified set of output topographical maps of ground-surface elevation and tree height.

  3. The Advanced Rapid Imaging and Analysis (ARIA) Project: Providing Standard and On-Demand SAR products for Hazard Science and Hazard Response

    Science.gov (United States)

    Owen, S. E.; Hua, H.; Rosen, P. A.; Agram, P. S.; Webb, F.; Simons, M.; Yun, S. H.; Sacco, G. F.; Liu, Z.; Fielding, E. J.; Lundgren, P.; Moore, A. W.

    2017-12-01

    A new era of geodetic imaging arrived with the launch of the ESA Sentinel-1A/B satellites in 2014 and 2016, and with the 2016 confirmation of the NISAR mission, planned for launch in 2021. These missions assure high quality, freely and openly distributed regularly sampled SAR data into the indefinite future. These unprecedented data sets are a watershed for solid earth sciences as we progress towards the goal of ubiquitous InSAR measurements. We now face the challenge of how to best address the massive volumes of data and intensive processing requirements. Should scientists individually process the same data independently themselves? Should a centralized service provider create standard products that all can use? Are there other approaches to accelerate science that are cost effective and efficient? The Advanced Rapid Imaging and Analysis (ARIA) project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. However, there are challenges in defining the optimal InSAR data products for the solid earth science community. In this presentation, we will present our experience with InSAR users, our lessons learned the advantages of on demand and standard products, and our proposal for the most effective path forward.

  4. Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistics

    NARCIS (Netherlands)

    Zhou, Y.; Stein, A.; Molenaar, M.

    2003-01-01

    Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater

  5. Spaceborne Polarimetric SAR Interferometry: Performance Analysis and Mission Concepts

    Directory of Open Access Journals (Sweden)

    Shane R. Cloude

    2005-12-01

    Full Text Available We investigate multichannel imaging radar systems employing coherent combinations of polarimetry and interferometry (Pol-InSAR. Such systems are well suited for the extraction of bio- and geophysical parameters by evaluating the combined scattering from surfaces and volumes. This combination leads to several important differences between the design of Pol-InSAR sensors and conventional single polarisation SAR interferometers. We first highlight these differences and then investigate the Pol-InSAR performance of two proposed spaceborne SAR systems (ALOS/PalSAR and TerraSAR-L operating in repeat-pass mode. For this, we introduce the novel concept of a phase tube which enables (1 a quantitative assessment of the Pol-InSAR performance, (2 a comparison between different sensor configurations, and (3 an optimization of the instrument settings for different Pol-InSAR applications. The phase tube may hence serve as an interface between system engineers and application-oriented scientists. The performance analysis reveals major limitations for even moderate levels of temporal decorrelation. Such deteriorations may be avoided in single-pass sensor configurations and we demonstrate the potential benefits from the use of future bi- and multistatic SAR interferometers.

  6. Chinese HJ-1C SAR And Its Wind Mapping Capability

    Science.gov (United States)

    Huang, Weigen; Chen, Fengfeng; Yang, Jingsong; Fu, Bin; Chen, Peng; Zhang, Chan

    2010-04-01

    Chinese Huan Jing (HJ)-1C synthetic aperture radar (SAR) satellite has been planed to be launched in 2010. HJ-1C satellite will fly in a sun-synchronous polar orbit of 500-km altitude. SAR will be the only sensor on board the satellite. It operates in S band with VV polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. There are two selectable SAR modes of operation, which are fine resolution beams and standard beams respectively. The sea surface wind mapping capability of the SAR has been examined using M4S radar imaging model developed by Romeiser. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat ASAR. It shows that HJ-1C SAR is as good as Envisat ASAR at sea surface wind mapping.

  7. A NEW SAR CLASSIFICATION SCHEME FOR SEDIMENTS ON INTERTIDAL FLATS BASED ON MULTI-FREQUENCY POLARIMETRIC SAR IMAGERY

    Directory of Open Access Journals (Sweden)

    W. Wang

    2017-11-01

    Full Text Available We present a new classification scheme for muddy and sandy sediments on exposed intertidal flats, which is based on synthetic aperture radar (SAR data, and use ALOS-2 (L-band, Radarsat-2 (C-band and TerraSAR-X (X-band fully polarimetric SAR imagery to demonstrate its effectiveness. Four test sites on the German North Sea coast were chosen, which represent typical surface compositions of different sediments, vegetation, and habitats, and of which a large amount of SAR is used for our analyses. Both Freeman-Durden and Cloude-Pottier polarimetric decomposition are utilized, and an additional descriptor called Double-Bounce Eigenvalue Relative Difference (DERD is introduced into the feature sets instead of the original polarimetric intensity channels. The classification is conducted following Random Forest theory, and the results are verified using ground truth data from field campaigns and an existing classification based on optical imagery. In addition, the use of Kennaugh elements for classification purposes is demonstrated using both fully and dual-polarization multi-frequency and multi-temporal SAR data. Our results show that the proposed classification scheme can be applied for the discrimination of muddy and sandy sediments using L-, C-, and X-band SAR images, while SAR imagery acquired at short wavelengths (C- and X-band can also be used to detect more detailed features such as bivalve beds on intertidal flats.

  8. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

    Jiankang, Ji; Thomsen, A.; Skriver, Henning

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness a...... of surface parameters with the bilinear model, the correlation coefficient between the estimated and measured soil moisture, as well as rms height, is about 0.77. To improve the result, the local incidence angles need to be taken into account......The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...

  9. 基于MRF的多时相SAR影像非监督变化检测%Unsupervised Change Detection in Multitemporal SAR Images Using MRF Models

    Institute of Scientific and Technical Information of China (English)

    江利明; 廖明生; 张路; 林珲

    2007-01-01

    An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.

  10. Classification of sea-ice types in SAR imagery

    International Nuclear Information System (INIS)

    Baraldi, A.; Parmiggiani, F.

    2001-01-01

    It is presented a supervised three-stage classification (labeling) scheme applied to SAR images of polar regions for detecting different sea-ice types. The three-stage labeling procedure consists of: 1) a speckle noise filtering stage, based on a sequence of contour detection, segmentation and filtering steps, which removes SAR speckle noise (and texture information as well) without losing spatial details; 2) a second stage providing Bayesian, maximum-α-posteriori, hierarchical (coarse-to-fine), adaptive (data-driven) and contextual labeling of piecewise constant intensity images featuring little useful texture information; and 3) an output stage providing a many-to-one relationship between second stage output categories (types or clusters) and desired output classes. Modules 1) and 2), which demonstrated their validity in several applications in the existing literature, are briefly recalled in the current paper. The proposed labeling scheme features some interesting functional properties when applied to sea-ice SAR images: it is easy to use, i.e., it requires minor user interaction, is robust to changes in input conditions and performs better than a non-contextual (per-pixel) classifier. Application results are presented and discussed for a pair of SAR images extracted, respectively, from an ERS-1 scene acquired on November 1992 over the Bellingshausen Sea (Antarctica) and from an ERS-2 scene of the East Greenland Sea acquired on March 1997 when a field experiment by the research vessel Jan Ma yen was conducted in the same area

  11. MRI screening on bone ischemia of hip and knee in recovered SARS patients

    International Nuclear Information System (INIS)

    Cheng Xiaoguang; Qu Hui; Liu Wei; Sun Jing; Cheng Kebin; Feng Suchen; Li Xiaosong

    2004-01-01

    Objective: To screen ischemia in the hip and knee joints of recovered SARS patients with MRI, and to investigate the prevalence rate of bone ischemia in those patients and its relationship with the use of steroid. Methods: Hip and knee MRI examinations were performed in 76 recovered SARS patients. There were 17 males and 59 females. Eight patients were treated without steroid, while 68 patients with steroid. Dose and duration of steroid usage were available in 30 out of 68 patients. The MRI images were read by senior radiologists to determine whether bone ischemia and/or osteonecrosis was present. Appropriate statistic analysis was performed to determine the significance of difference between groups. Results: (1) The MRI appearance of osteonecrosis in femoral head and condyle and bone infarct in bone marrow found in SARS patients was identical to those caused by other conditions (including steroid usage in other diseases). (2) No one of 8 SARS without steroid developed osteonecrosis, while 25 out of 68 steroid users had osteonecrosis found by MRI screening, and the difference in prevalence of osteonecrosis between these 2 groups was significant. In 25 patients with osteonecrosis, 20 of them involved more than one joints. Osteonecrosis involved 32 femoral heads, 26 femoral condyles, and 6 in femoral and tibial shafts. Thirteen patients with osteonecrosis had greater total steroid dose, greater daily dose, and longer duration than those (17 patients) without osteonecrosis, however, the differences between the two groups were not statistically significant. Sixty-four patients out of 76 complained pain in joints, 50 of them had multiple joint pains. The pain was reported in hips in 40 cases, followed by knees in 36, low backs in 10, shoulders in 7, and wrists in 4, respectively. The differences in frequency of pain between steroid users and non-steroid users, as well as between osteonecrosis and non-osteonecrosis were not significant. Conclusion: MRI is recommended for

  12. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

    Directory of Open Access Journals (Sweden)

    Hu Ke-bin

    2015-02-01

    Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

  13. Observation of pressure ridges in SAR images of sea ice: Scattering theory and comparison with observations

    Science.gov (United States)

    Vesecky, J. F.; Daida, J. M.; Shuchman, R. A.; Onstott, R. H.; Camiso, J. C.

    1993-01-01

    Ridges and keels (hummocks and bummocks) in sea ice flows are important in sea ice research for both scientific and practical reasons. Sea ice movement and deformation is driven by internal and external stresses on the ice. Ridges and keels play important roles in both cases because they determine the external wind and current stresses via drag coefficients. For example, the drag coefficient over sea ice can vary by a factor of several depending on the fluid mechanical roughness length of the surface. This roughness length is thought to be strongly dependent on the ridge structures present. Thus, variations in ridge and keel structure can cause gradients in external stresses which must be balanced by internal stresses and possibly fracture of the ice. Ridging in sea ice is also a sign of fracture. In a practical sense, large ridges form the biggest impediment to surface travel over the ice or penetration through sea ice by ice-strengthened ships. Ridges also play an important role in the damage caused by sea ice to off-shore structures. Hence, observation and measurement of sea ice ridges is an important component of sea ice remote sensing. The research reported here builds on previous work, estimating the characteristics of ridges and leads in sea ice from SAR images. Our objective is to develop methods for quantitative measurement of sea ice ridges from SAR images. To make further progress, in particular, to estimate ridge height, a scattering model for ridges is needed. Our research approach for a ridge scattering model begins with a survey of the geometrical properties of ridges and a comparison with the characteristics of the surrounding ice. For this purpose we have used airborne optical laser (AOL) data collected during the 1987 Greenland Sea Experiment. These data were used to generate a spatial wavenumber spectrum for height variance for a typical ridge - the typical ridge is the average over 10 large ridges. Our first-order model radar scattering includes

  14. Mapping and monitoring renewable resources with space SAR

    Science.gov (United States)

    Ulaby, F. T.; Brisco, B.; Dobson, M. C.; Moezzi, S.

    1983-01-01

    The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

  15. Global Rapid Flood Mapping System with Spaceborne SAR Data

    Science.gov (United States)

    Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

    2017-12-01

    As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

  16. Robust tie points selection for InSAR image coregistration

    Science.gov (United States)

    Skanderi, Takieddine; Chabira, Boulerbah; Afifa, Belkacem; Belhadj Aissa, Aichouche

    2013-10-01

    Image coregistration is an important step in SAR interferometry which is a well known method for DEM generation and surface displacement monitoring. A practical and widely used automatic coregistration algorithm is based on selecting a number of tie points in the master image and looking for the correspondence of each point in the slave image using correlation technique. The characteristics of these points, their number and their distribution have a great impact on the reliability of the estimated transformation. In this work, we present a method for automatic selection of suitable tie points that are well distributed over the common area without decreasing the desired tie points' number. First we select candidate points using Harris operator. Then from these points we select tie points depending on their cornerness measure (the highest first). Once a tie point is selected, its correspondence is searched for in the slave image, if the similarity measure maximum is less than a given threshold or it is at the border of the search window, this point is discarded and we proceed to the next Harris point, else, the cornerness of the remaining candidates Harris points are multiplied by a spatially radially increasing function centered at the selected point to disadvantage the points in a neighborhood of a radius determined from the size of the common area and the desired number of points. This is repeated until the desired number of points is selected. Results of an ERS1/2 tandem pair are presented and discussed.

  17. Automated inundation monitoring using TerraSAR-X multitemporal imagery

    Science.gov (United States)

    Gebhardt, S.; Huth, J.; Wehrmann, T.; Schettler, I.; Künzer, C.; Schmidt, M.; Dech, S.

    2009-04-01

    The Mekong Delta in Vietnam offers natural resources for several million inhabitants. However, a strong population increase, changing climatic conditions and regulatory measures at the upper reaches of the Mekong lead to severe changes in the Delta. Extreme flood events occur more frequently, drinking water availability is increasingly limited, soils show signs of salinization or acidification, species and complete habitats diminish. During the Monsoon season the river regularly overflows its banks in the lower Mekong area, usually with beneficial effects. However, extreme flood events occur more frequently causing extensive damage, on the average once every 6 to 10 years river flood levels exceed the critical beneficial level X-band SAR data are well suited for deriving inundated surface areas. The TerraSAR-X sensor with its different scanning modi allows for the derivation of spatial and temporal high resolved inundation masks. The paper presents an automated procedure for deriving inundated areas from TerraSAR-X Scansar and Stripmap image data. Within the framework of the German-Vietnamese WISDOM project, focussing the Mekong Delta region in Vietnam, images have been acquired covering the flood season from June 2008 to November 2008. Based on these images a time series of the so called watermask showing inundated areas have been derived. The product is required as intermediate to (i) calibrate 2d inundation model scenarios, (ii) estimate the extent of affected areas, and (iii) analyze the scope of prior crisis. The image processing approach is based on the assumption that water surfaces are forward scattering the radar signal resulting in low backscatter signals to the sensor. It uses multiple grey level thresholds and image morphological operations. The approach is robust in terms of automation, accuracy, robustness, and processing time. The resulting watermasks show the seasonal flooding pattern with inundations starting in July, having their peak at the end

  18. Comparing Accuracy of Airborne Laser Scanning and TerraSAR-X Radar Images in the Estimation of Plot-Level Forest Variables

    Directory of Open Access Journals (Sweden)

    Juha Hyyppä

    2010-01-01

    Full Text Available In this study we compared the accuracy of low-pulse airborne laser scanning (ALS data, multi-temporal high-resolution noninterferometric TerraSAR-X radar data and a combined feature set derived from these data in the estimation of forest variables at plot level. The TerraSAR-X data set consisted of seven dual-polarized (HH/HV or VH/VV Stripmap mode images from all seasons of the year. We were especially interested in distinguishing between the tree species. The dependent variables estimated included mean volume, basal area, mean height, mean diameter and tree species-specific mean volumes. Selection of best possible feature set was based on a genetic algorithm (GA. The nonparametric k-nearest neighbour (k-NN algorithm was applied to the estimation. The research material consisted of 124 circular plots measured at tree level and located in the vicinity of Espoo, Finland. There are large variations in the elevation and forest structure in the study area, making it demanding for image interpretation. The best feature set contained 12 features, nine of them originating from the ALS data and three from the TerraSAR-X data. The relative RMSEs for the best performing feature set were 34.7% (mean volume, 28.1% (basal area, 14.3% (mean height, 21.4% (mean diameter, 99.9% (mean volume of Scots pine, 61.6% (mean volume of Norway spruce and 91.6% (mean volume of deciduous tree species. The combined feature set outperformed an ALS-based feature set marginally; in fact, the latter was better in the case of species-specific volumes. Features from TerraSAR-X alone performed poorly. However, due to favorable temporal resolution, satellite-borne radar imaging is a promising data source for updating large-area forest inventories based on low-pulse ALS.

  19. Radionuclide bone scintigraphy in early detection of avascular osteonecrosis occurred in recovered SARS patients after hormone therapy

    International Nuclear Information System (INIS)

    Wang Qian; Huang Lili; Qin Shuling; Wang Yu; Nie Yuxin; Liang Tiejun; Zhang Caiqun; Zhao Yamei

    2005-01-01

    Objective: To analyze the characteristics of bone scintigraphy in patients who recovered from the severe acute respiratory syndrome (SARS), and to evaluate the clinical value of bone scintigraphy in the early diagnosis of avascular osteonecrosis (AVN) after hormone therapy. Methods: Bone scintigraphy was performed in 66 SARS patients. Among them 54 underwent MRI in bilateral hips and knees. Both images were compared and followed up clinically. Results: Abnormal scintigraphy was found in 30 (45.5%) of the 66 recovered SARS patients. Total 82 foci were found in hip, knee, ankle, elbow, shoulder, wrist and the middle of the tibia. Hip and knee joints were the most involved sites. 25 patients with 71 lesions were symptomatic, whereas 11 in 5 patients were asymptomatic, lesions in 8 patients were multifocal. The lesions found in scintigraphy and MRI were concordant in 92.6% of the joints. But more lesions could be detected by bone scintigraphy. Conclusions: SARS patients have a high occurrence of AVN, usually involved in multiple sites. Bone scintigraphy should be the first choice method used for early detection of AVN. (authors)

  20. Rice status and microwave characteristics: Analysis of rice paddy fields at Kojima Bay [Okayama, Japan] using multi-frequency and polarimetric Pi-SAR radar data images

    International Nuclear Information System (INIS)

    Ishitsuka, N.; Saito, G.; Ouchi, K.; Davidson, G.; Mohri, K.; Uratsuka, S.

    2003-01-01

    Abstract South-east Asia has a rainy-season at the crop growing period, and it is difficult to observe agricultural land in this season using optical remote sensing. Synthetic Aperture Radar (SAR) can observe the earth's surface without being influenced by of clouds. However, it is less useful for observing agricultural land, because satellite SAR has only one data band. Recently, SAR is able to provide multi band and multi polarimetric data. Pi-SAR, an airborne SAR developed by NASDA and CRL, can provide L and X bands and fully polarimetric data. Rice is the main crop in Asia, and we studied the characteristic microwave scatter on rice paddy fields using Pi-SAR data. Our study area was the rice paddy fields in Kojima reclaimed land in Japan. We had two fully polarimetric data sets from 13 July 1999 and 4 October 2000. First, we processed the color polarimetric composite image. Next we calibrated the phase of each polarimetric data using river area by the Kimura method. After that we performed decomposition analysis and drew polarimetric signatures for understanding the status of rice paddy fields. At the rice planting period, rice paddy fields are filled with water and rice plants are very small. The SAR microwave scatters on water surfaces like a mirror, called 'mirror (or specular) reflection'. This phenomenon makes backscatter a small value at the water-covered area. The image from July is about one month after trans-planting and rice plants are 20-40 cm in height. X-band microwave scatters on the rice surface, but L-band microwave passes through rice bodies and shows mirror refraction on water surfaces. Some strong backscatter occur on rice paddy fields especially VV polarization because of bragg scattering. The fields where bragg scattering returns strong VV scatter because the space between rice stems cause resonation in the L-band wavelength. We can easily understand bragg scatter by using polarimetric data. Using the image from October at

  1. Discrimination of Different Water Layers with TerraSAR X Images in "La Albufera de Valencia"

    Science.gov (United States)

    García Fernández, M. A.; Miguelsanz Muñoz, P.

    2009-04-01

    To analyze the capabilities of TerraSAR X Strip Map images in order to discriminate different water layers in the "Parque de la Albufera de Valencia", Spain, a test project was carried out. This place is a rice crop area under European and National Agro environmental regulation which obliges to preserve the habitat and to keep the rice plots flooded out of crop season, from October to January

  2. Geocoding of SAR Image Using the Orbit and Attitude Determination of RADARSAT

    Directory of Open Access Journals (Sweden)

    Jin Wook So

    1998-06-01

    Full Text Available The Synthetic Aperture Radar (SAR image and the Digital Elevation Model (DEM of an target area are put into use to generate three dimensional image map. An method of image map generation is explained. The orbit and attitude determination of satellite makes it possible to model signal acquisition configuration precisely, which is a key to mapping image coordinates to geographic coordinates of concerned area. An application is made to RADARSAT in the purpose of testing its validity. To determine the orbit, zero Doppler range is used. And to determine the attitude, Doppler centroid frequency, which is the frequency observed when target is in the center of antenna's view, is used. Conventional geocoding has been performed on the basis of direct method(mapping image coordinates to geographic coordinates, but in this research the inverse method (mapping from geographic coordinates to image coordinates is taken. This paper shows that precise signal acquisition modeling based on the orbit and attitude determination of satellite as a platform leads to a satellite-centered accurate geocoding process. It also shows how to model relative motion between spaceborne radar and target. And the relative motion is described in ECIC (earth-centered initial coordinates using Doppler equation and signal acquisition geometry.

  3. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

    Science.gov (United States)

    Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

    2017-01-23

    Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  4. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS

    Directory of Open Access Journals (Sweden)

    Zhongyu Li

    2017-01-01

    Full Text Available Bistatic forward-looking SAR (BFSAR is a kind of bistatic synthetic aperture radar (SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I large and unknown range cell migration (RCM (including range walk and high-order RCM; (II the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  5. An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

    Science.gov (United States)

    Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

    2018-02-12

    The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

  6. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Science.gov (United States)

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  7. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

    Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

  8. RAMP AMM-1 SAR Image Mosaic of Antarctica

    Data.gov (United States)

    National Aeronautics and Space Administration — In 1997, the Canadian RADARSAT-1 satellite was rotated in orbit so that its Synthetic Aperture Radar (SAR) antenna looked south towards Antarctica. This permitted...

  9. The Temporal and Spatial Variability of the Confined Aquifer Head and Storage Properties in the San Luis Valley, Colorado Inferred From Multiple InSAR Missions

    Science.gov (United States)

    Chen, Jingyi; Knight, Rosemary; Zebker, Howard A.

    2017-11-01

    Interferometric Synthetic Aperture Radar (InSAR) data from multiple satellite missions were combined to study the temporal and spatial variability of head and storage properties in a confined aquifer system on a decadal time scale. The area of study was a 4,500 km2 agricultural basin in the San Luis Valley (SLV), Colorado. We had available previous analyses of C-band ERS-1/2 data from June 1992 to November 2000, and L-band ALOS PALSAR data from October 2009 to March 2011. We used C-band Envisat data to fill in the time period from November 2006 to July 2010. In processing the Envisat data, we successfully employed a phase interpolation between persistent scatterer pixels to reduce the impact of vegetation decorrelation, which can significantly reduce the quality of C-band InSAR data over agricultural basins. In comparing the results from the L-band ALOS data and C-band Envisat data in a 10 month overlapping time period, we found that the shorter wavelength of C-band InSAR allowed us to preserve small deformation signals that were not detectable using L-band ALOS data. A significant result was the finding that the elastic storage properties of the SLV confined aquifer system remained stable over the 20 year time period and vary slowly in space, allowing us to combine InSAR data acquired from multiple missions to fill the temporal and spatial gaps in well data. The InSAR estimated head levels were validated with well measurements, which indicate little permanent water-storage loss over the study time period in the SLV.

  10. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas

    Directory of Open Access Journals (Sweden)

    Zhenwei Chen

    2016-09-01

    Full Text Available Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  11. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    Science.gov (United States)

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-09-17

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  12. SAR Ambiguity Study for the Cassini Radar

    Science.gov (United States)

    Hensley, Scott; Im, Eastwood; Johnson, William T. K.

    1993-01-01

    The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.

  13. 7 T body MRI: B1 shimming with simultaneous SAR reduction

    International Nuclear Information System (INIS)

    Bergen, Bob van den; Berg, Cornelis A T van den; Bartels, Lambertus W; Lagendijk, Jan J W

    2007-01-01

    The high frequency of the radiofrequency (RF) fields used in high field magnetic resonance imaging (MRI) results in electromagnetic field variations that can cause local regions to have a large specific absorption rate (SAR) and/or a low excitation. In this study, we evaluated the use of a B 1 shimming technique which can simultaneously improve the B + 1 homogeneity and reduce the SAR for whole body imaging at 7 T. Optimizations for four individual anatomies showed a reduction up to 74% of the peak SAR values with respect to a quadrature excitation and a simultaneous improvement of the B + 1 homogeneity varying between 39 and 75% for different optimization parameters. The average SAR was reduced with approximately 50% for all optimizations. The optimized phase and amplitude settings from an elliptical phantom model were applied to four realistic human anatomy models to evaluate whether a generic application without prior knowledge of the detailed human anatomy is possible. This resulted in an average improvement of the B + 1 homogeneity of 37% and an average reduction of the maximum and average SAR of 50 and 55%, respectively. It can be concluded that this generic method can be used as a simple method to improve the prospects of 7 T body imaging

  14. Evaluation of RISAT-1 SAR data for tropical forestry applications

    Science.gov (United States)

    Padalia, Hitendra; Yadav, Sadhana

    2017-01-01

    India launched C band (5.35 GHz) RISAT-1 (Radar Imaging Satellite-1) on 26th April, 2012, equipped with the capability to image the Earth at multiple-resolutions and -polarizations. In this study the potential of Fine Resolution Strip (FRS) modes of RISAT-1 was evaluated for characterization and classification forests and estimation of biomass of early growth stages. The study was carried out at the two sites located in the foothills of western Himalaya, India. The pre-processing and classification of FRS-1 SAR data was performed using PolSAR Pro ver. 5.0 software. The scattering mechanisms derived from m-chi decomposition of FRS-1 RH/RV data were found physically meaningful for the characterization of various surface features types. The forest and land use type classification of the study area was developed applying Support Vector Machine (SVM) algorithm on FRS-1 derived appropriate polarimetric features. The biomass of early growth stages of Eucalyptus (up to 60 ton/ha) was estimated developing a multi-linear regression model using C band σ0 HV and σ0 HH backscatter information. The study outcomes has promise for wider application of RISAT-1 data for forest cover monitoring, especially for the tropical regions.

  15. a Method for the Extraction of Long-Term Deformation Characteristics of Long-Span High-Speed Railway Bridges Using High-Resolution SAR Images

    Science.gov (United States)

    Jia, H. G.; Liu, L. Y.

    2016-06-01

    Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR) technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  16. A METHOD FOR THE EXTRACTION OF LONG-TERM DEFORMATION CHARACTERISTICS OF LONG-SPAN HIGH-SPEED RAILWAY BRIDGES USING HIGH-RESOLUTION SAR IMAGES

    Directory of Open Access Journals (Sweden)

    H. G. Jia

    2016-06-01

    Full Text Available Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  17. The Danish real-time SAR processor: first results

    DEFF Research Database (Denmark)

    Dall, Jørgen; Jørgensen, Jørn Hjelm; Netterstrøm, Anders

    1993-01-01

    A real-time processor (RTP) for the Danish airborne Synthetic Aperture Radar (SAR) has been designed and constructed at the Electromagnetics Institute. The implementation was completed in mid 1992, and since then the RTP has been operated successfully on several test and demonstration flights....... The processor is capable of focusing the entire swath of the raw SAR data into full resolution, and depending on the choice made by the on-board operator, either a high resolution one-look zoom image or a spatially multilooked overview image is displayed. After a brief design review, the paper addresses various...

  18. Research on the method of extracting DEM based on GBInSAR

    Science.gov (United States)

    Yue, Jianping; Yue, Shun; Qiu, Zhiwei; Wang, Xueqin; Guo, Leping

    2016-05-01

    Precise topographical information has a very important role in geology, hydrology, natural resources survey and deformation monitoring. The extracting DEM technology based on synthetic aperture radar interferometry (InSAR) obtains the three-dimensional elevation of the target area through the phase information of the radar image data. The technology has large-scale, high-precision, all-weather features. By changing track in the location of the ground radar system up and down, it can form spatial baseline. Then we can achieve the DEM of the target area by acquiring image data from different angles. Three-dimensional laser scanning technology can quickly, efficiently and accurately obtain DEM of target area, which can verify the accuracy of DEM extracted by GBInSAR. But research on GBInSAR in extracting DEM of the target area is a little. For lack of theory and lower accuracy problems in extracting DEM based on GBInSAR now, this article conducted research and analysis on its principle deeply. The article extracted the DEM of the target area, combined with GBInSAR data. Then it compared the DEM obtained by GBInSAR with the DEM obtained by three-dimensional laser scan data and made statistical analysis and normal distribution test. The results showed the DEM obtained by GBInSAR was broadly consistent with the DEM obtained by three-dimensional laser scanning. And its accuracy is high. The difference of both DEM approximately obeys normal distribution. It indicated that extracting the DEM of target area based on GBInSAR is feasible and provided the foundation for the promotion and application of GBInSAR.

  19. The Performance Analysis Based on SAR Sample Covariance Matrix

    Directory of Open Access Journals (Sweden)

    Esra Erten

    2012-03-01

    Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.

  20. UAVSAR and TerraSAR-X Based InSAR Detection of Localized Subsidence in the New Orleans Area

    Science.gov (United States)

    Blom, R. G.; An, K.; Jones, C. E.; Latini, D.

    2014-12-01

    Vulnerability of the US Gulf coast to inundation has received increased attention since hurricanes Katrina and Rita. Compounding effects of sea level rise, wetland loss, and regional and local subsidence makes flood protection a difficult challenge, and particularly for the New Orleans area. Key to flood protection is precise knowledge of elevations and elevation changes. Analysis of historical and continuing geodetic measurements show surprising complexity, including locations subsiding more rapidly than considered during planning of hurricane protection and coastal restoration projects. Combining traditional, precise geodetic data with interferometric synthetic aperture radar (InSAR) observations can provide geographically dense constraints on surface deformation. The Gulf Coast environment is challenging for InSAR techniques, especially with systems not designed for interferometry. We use two InSAR capable systems, the L- band (24 cm wavelength) airborne JPL/NASA UAVSAR, and the DLR/EADS Astrium spaceborne TerraSAR X-band (3 cm wavelength), and compare results. First, we are applying pair-wise InSAR to the longer wavelength UAVSAR data to detect localized elevation changes potentially impacting flood protection infrastructure from 2009 - 2014. We focus on areas on and near flood protection infrastructure to identify changes indicative of subsidence, structural deformation, and/or seepage. The Spaceborne TerraSAR X-band SAR system has relatively frequent observations, and dense persistent scatterers in urban areas, enabling measurement of very small displacements. We compare L-band UAVSAR results with permanent scatterer (PS-InSAR) and Short Baseline Subsets (SBAS) interferometric analyses of a stack composed by 28 TerraSAR X-band images acquired over the same period. Thus we can evaluate results from the different radar frequencies and analyses techniques. Preliminary results indicate subsidence features potentially of a variety of causes, including ground water

  1. Monitoring of Three Case Studies of Creeping Landslides in Ecuador using L-band SAR Interferometry (InSAR)

    Science.gov (United States)

    Mayorga Torres, T. M.; Mohseni Aref, M.

    2015-12-01

    Tannia Mayorga Torres1,21 Universidad Central del Ecuador. Faculty of Geology, Mining, Oil, and Environment 2 Hubert H. Humphrey Fellowship 2015-16 IntroductionLandslides lead to human and economic losses across the country, mainly in the winter season. On the other hand, satellite radar data has cost-effective benefits due to open-source software and free availability of data. With the purpose of establishing an early warning system of landslide-related surface deformation, three case studies were designed in the Coast, Sierra (Andean), and Oriente (jungle) regions. The objective of this work was to assess the capability of L-band InSAR to get phase information. For the calculation of the interferograms in Repeat Orbit Interferometry PACkage, the displacement was detected as the error and was corrected. The coherence images (Figure 1) determined that L-band is suitable for InSAR processing. Under this frame, as a first approach, the stacking DInSAR technique [1] was applied in the case studies [2]; however, due to lush vegetation and steep topography, it is necessary to apply advanced InSAR techniques [3]. The purpose of the research is to determine a pattern of data acquisition and successful results to understand the spatial and temporal ground movements associated with landslides. The further work consists of establishing landslide inventories to combine phases of SAR images to generate maps of surface deformation in Tumba-San Francisco and Guarumales to compare the results with ground-based measurements to determine the maps' accuracy. References[1] Sandwell D., Price E. (1998). Phase gradient approach to stacking interferograms. Journal of Geophysical Research, Vol. 103, N. B12, pp. 30,183-30,204. [2] Mayorga T., Platzeck G. (2014). Using DInSAR as a tool to detect unstable terrain areas in an Andes region in Ecuador. NH3.5-Blue Poster B298, Vol. 16, EGU2014-16203. Austria. [3] Wasowski J., Bovenga F. (2014). Investigating landslides and unstable slopes with

  2. Inversion Algorithms and PS Detection in SAR Tomography, Case Study of Bucharest City

    Directory of Open Access Journals (Sweden)

    C. Dănişor

    2016-06-01

    Full Text Available Synthetic Aperture Radar (SAR tomography can reconstruct the elevation profile of each pixel based on a set of co-registered complex images of a scene. Its main advantage over classical interferometric methods consists in the capability to improve the detection of single persistent scatterers as well as to enable the detection of multiple scatterers interfering within the same pixel. In this paper, three tomographic algorithms are compared and applied to a dataset of 32 images to generate the elevation map of dominant scatterers from a scene. Targets which present stable proprieties over time - Persistent Scatterers (PS are then detected based on reflectivity functions reconstructed with Capon filtering.

  3. Sea ice classification using dual polarization SAR data

    International Nuclear Information System (INIS)

    Huiying, Liu; Huadong, Guo; Lu, Zhang

    2014-01-01

    Sea ice is an indicator of climate change and also a threat to the navigation security of ships. Polarimetric SAR images are useful in the sea ice detection and classification. In this paper, backscattering coefficients and texture features derived from dual polarization SAR images are used for sea ice classification. Firstly, the HH image is recalculated based on the angular dependences of sea ice types. Then the effective gray level co-occurrence matrix (GLCM) texture features are selected for the support vector machine (SVM) classification. In the end, because sea ice concentration can provide a better separation of pancake ice from old ice, it is used to improve the SVM result. This method provides a good classification result, compared with the sea ice chart from CIS

  4. Experimental validation of hyperthermia SAR treatment planning using MR B1+ imaging

    International Nuclear Information System (INIS)

    Berg, Cornelis A T van den; Bartels, Lambertus W; Leeuw, Astrid A C De; Lagendijk, Jan J W; Kamer, Jeroen B Van de

    2004-01-01

    In this paper the concept of using B 1+ imaging as a means to validate SAR models for radiofrequency hyperthermia is presented. As in radiofrequency hyperthermia, in common clinical MR imaging which applies RF frequencies between 64 and 128 MHz, the RF field distribution inside a patient is largely determined by the dielectric distribution of the anatomy. Modern MR imaging techniques allow measurement of the RF magnetic field component B 1+ making it possible to measure at high resolution the dielectric interaction of the RF field with the patient. Given these considerations, we propose to use MR imaging to verify the validity of our dielectric patient model used for SAR models of radiofrequency hyperthermia. The aim of this study was to investigate the feasibility of this concept by performing B 1+ measurements and simulations on cylindrical split phantoms consisting of materials with dielectric properties similar to human tissue types. Important topics of investigation were the accuracy and sensitivity of B 1+ measurements and the validity of the electric model of the MR body coil. The measurements were performed on a clinical 1.5 T MR scanner with its quadrature body coil operating at 64 MHz. It was shown that even small B 1+ variations of 2 to 5% could be measured reliably in the phantom experiments. An electrical model of the transmit coil was implemented on our FDTD-based hyperthermia treatment planning platform and the RF field distributions were calculated assuming an idealized quadrature current distribution in the coil. A quantitatively good correlation between measurements and simulations was found for phantoms consisting of water and oil, while highly conductive phantoms show considerable deviations. However, assuming linear excitation for these conductive phantoms resulted in good correspondence. As an explanation it is suggested that the coil is being detuned due to the inductive nature of the conductive phantoms, breaking up the phase difference of

  5. Detection of Oil near Shorelines during the Deepwater Horizon Oil Spill Using Synthetic Aperture Radar (SAR

    Directory of Open Access Journals (Sweden)

    Oscar Garcia-Pineda

    2017-06-01

    Full Text Available During any marine oil spill, floating oil slicks that reach shorelines threaten a wide array of coastal habitats. To assess the presence of oil near shorelines during the Deepwater Horizon (DWH oil spill, we scanned the library of Synthetic Aperture Radar (SAR imagery collected during the event to determine which images intersected shorelines and appeared to contain oil. In total, 715 SAR images taken during the DWH spill were analyzed and processed, with 188 of the images clearly showing oil. Of these, 156 SAR images showed oil within 10 km of the shoreline with appropriate weather conditions for the detection of oil on SAR data. We found detectable oil in SAR images within 10 km of the shoreline from west Louisiana to west Florida, including near beaches, marshes, and islands. The high number of SAR images collected in Barataria Bay, Louisiana in 2010 allowed for the creation of a nearshore oiling persistence map. This analysis shows that, in some areas inside Barataria Bay, floating oil was detected on as many as 29 different days in 2010. The nearshore areas with persistent floating oil corresponded well with areas where ground survey crews discovered heavy shoreline oiling. We conclude that satellite-based SAR imagery can detect oil slicks near shorelines, even in sheltered areas. These data can help assess potential shoreline oil exposure without requiring boats or aircraft. This method can be particularly helpful when shoreline assessment crews are hampered by difficult access or, in the case of DWH, a particularly large spatial and temporal spill extent.

  6. Monitoring Building Deformation with InSAR: Experiments and Validation

    Science.gov (United States)

    Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

    2016-01-01

    Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403

  7. Monitoring Building Deformation with InSAR: Experiments and Validation

    Directory of Open Access Journals (Sweden)

    Kui Yang

    2016-12-01

    Full Text Available Synthetic Aperture Radar Interferometry (InSAR techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

  8. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  9. Empirical wind retrieval model based on SAR spectrum measurements

    Science.gov (United States)

    Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

    The present paper considers polarimetric SAR wind vector applications. Remote-sensing measurements of the near-surface wind over the ocean are of great importance for the understanding of atmosphere-ocean interaction. In recent years investigations for wind vector retrieval using Synthetic Aperture Radar (SAR) data have been performed. In contrast with scatterometers, a SAR has a finer spatial resolution that makes it a more suitable microwave instrument to explore wind conditions in the marginal ice zones, coastal regions and lakes. The wind speed retrieval procedure from scatterometer data matches the measured radar backscattering signal with the geophysical model function (GMF). The GMF determines the radar cross section dependence on the wind speed and direction with respect to the azimuthal angle of the radar beam. Scatterometers provide information on wind speed and direction simultaneously due to the fact that each wind vector cell (WVC) is observed at several azimuth angles. However, SAR is not designed to be used as a high resolution scatterometer. In this case, each WVC is observed at only one single azimuth angle. That is why for wind vector determination additional information such as wind streak orientation over the sea surface is required. It is shown that the wind vector can be obtained using polarimetric SAR without additional information. The main idea is to analyze the spectrum of a homogeneous SAR image area instead of the backscattering normalized radar cross section. Preliminary numerical simulations revealed that SAR image spectral maxima positions depend on the wind vector. Thus the following method for wind speed retrieval is proposed. In the first stage of the algorithm, the SAR spectrum maxima are determined. This procedure is carried out to estimate the wind speed and direction with ambiguities separated by 180 degrees due to the SAR spectrum symmetry. The second stage of the algorithm allows us to select the correct wind direction

  10. Segment-based change detection for polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2006-01-01

    that is needed compared to single polarisation SAR to provide reliable and robust detection of changes. Polarimetric SAR data will be available from satellites in the near future, e.g. the Japanese ALOS, the Canadian Radarsat-2 and the German TerraSAR-X. An appropriate way of representing multi-look fully...... be split into a number of smaller fields, a building may be removed from or added to some area, hedgerows may be removed/added or other type of vegetated areas may be partly removed or added. In this case, ambiguities may arise when segments have changed shape and extent from one image to another...

  11. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    KAUST Repository

    Feng, Guangcai

    2017-03-15

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  12. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    KAUST Repository

    Feng, Guangcai; Jonsson, Sigurjon; Klinger, Yann

    2017-01-01

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  13. Selective interferometric imaging of internal multiples

    KAUST Repository

    Zuberi, M. A H

    2013-01-01

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not reproduce such scattering in the Green’s function. If properly imaged, internal multiples (and internally-scattered energy) can enhance the seismic image and illuminate areas otherwise neglected or poorly imaged by conventional single-scattering approaches. Conventionally, in order to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we develop a three-step procedure, which images the first-order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model: We first back-propagate the recorded surface data using the background Green’s function, then cross-correlate the back-propagated data with the recorded data and finally cross-correlate the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples and is almost free of the single-scattering recorded energy. This image can be added to the conventional single-scattering image, obtained e.g. from Kirchhoff migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering only demonstrates the effectiveness of the approach.

  14. Preliminary Study of Ground Movement in Prone Landslide Area by Means of MAI InSAR A Case Study: Ciloto, West Java, Indonesia

    Science.gov (United States)

    Hayati, Noorlaila; Riedel, Björn; Niemeier, Wolfgang

    2016-04-01

    Ciloto is one of the most prone landslide hazard areas in Indonesia. Several landslides in 2012 and 2013 had been recorded in Ciloto and damaged infrastructure around the area. Investigating the history of ground movement along slope area before the landslide happened could support the hazard mitigation in the future. Considering to an efficient surveying method, space-borne SAR processing is the one appropriate way to monitor the phenomenon in past years. The purpose of this study is detecting ground movement using multi-temporal synthetic aperture radar images. We use 13 ALOS PALSAR images from 2007 to 2009 with combination Fine Beam Single (FBS) and Fine Beam Double (FBD) polarization to investigate the slow movement on slope topography. MAI (Multiple Aperture Interferometry) InSAR method is used to analyze the ground movement from both line-of-sight and along-track direction. We split the synthetic aperture into two-looking aperture so that along-track displacement could be created by the difference of forward-backward looking interferograms. With integration of both methods, we could more precisely detect the movement in prone landslide area and achieve two measurements produced by the same interferogram. However, InSAR requires smaller baseline and good temporal baseline between master and slave images to avoid decorellation. There are only several pairs that meet the condition of proper length and temporal baseline indeed the location is also on the agriculture area where is mostly covered by vegetation. The result for two years observation shows that there is insignificant slow movement along slope surface in Ciloto with -2 - -7 cm in range looks or line of sight and 9-40 cm in along track direction. Based on geometry SAR , the most visible detecting of displacement is on the north-west area due to utilization of ascending SAR images.

  15. Detection of moving humans in UHF wideband SAR

    Science.gov (United States)

    Sjögren, Thomas K.; Ulander, Lars M. H.; Frölind, Per-Olov; Gustavsson, Anders; Stenström, Gunnar; Jonsson, Tommy

    2014-06-01

    In this paper, experimental results for UHF wideband SAR imaging of humans on an open field and inside a forest is presented. The results show ability to detect the humans and suggest possible ways to improve the results. In the experiment, single channel wideband SAR mode of the UHF UWB system LORA developed by Swedish Defence Research Agency (FOI). The wideband SAR mode used in the experiment was from 220 to 450 MHz, thus with a fractional bandwidth of 0.68. Three humans walking and one stationary were available in the scene with one of the walking humans in the forest. The signature of the human in the forest appeared on the field, due to azimuth shift from the positive range speed component. One human on the field and the one in the forest had approximately the same speed and walking direction. The signatures in the SAR image were compared as a function of integration time based on focusing using the average relative speed of these given by GPS logs. A signal processing gain was obtained for the human in forest until approximately 15 s and 35 s for the human on the field. This difference is likely explained by uneven terrain and trees in the way, causing a non-straight walking path.

  16. The 2008 Wells, Nevada earthquake sequence: Source constraints using calibrated multiple event relocation and InSAR

    Science.gov (United States)

    Nealy, Jennifer; Benz, Harley M.; Hayes, Gavin; Berman, Eric; Barnhart, William

    2017-01-01

    The 2008 Wells, NV earthquake represents the largest domestic event in the conterminous U.S. outside of California since the October 1983 Borah Peak earthquake in southern Idaho. We present an improved catalog, magnitude complete to 1.6, of the foreshock-aftershock sequence, supplementing the current U.S. Geological Survey (USGS) Preliminary Determination of Epicenters (PDE) catalog with 1,928 well-located events. In order to create this catalog, both subspace and kurtosis detectors are used to obtain an initial set of earthquakes and associated locations. The latter are then calibrated through the implementation of the hypocentroidal decomposition method and relocated using the BayesLoc relocation technique. We additionally perform a finite fault slip analysis of the mainshock using InSAR observations. By combining the relocated sequence with the finite fault analysis, we show that the aftershocks occur primarily updip and along the southwestern edge of the zone of maximum slip. The aftershock locations illuminate areas of post-mainshock strain increase; aftershock depths, ranging from 5 to 16 km, are consistent with InSAR imaging, which shows that the Wells earthquake was a buried source with no observable near-surface offset.

  17. Rapid Flood Map Generation from Spaceborne SAR Observations

    Science.gov (United States)

    Yun, S. H.; Liang, C.; Manipon, G.; Jung, J.; Gurrola, E. M.; Owen, S. E.; Hua, H.; Agram, P. S.; Webb, F.; Sacco, G. F.; Rosen, P. A.; Simons, M.

    2016-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) team has responded to the January 2016 US Midwest Floods along the Mississippi River. Daily teleconferences with FEMA, NOAA, NGA, and USGS, provided information on precipitation and flood crest migration, based on which we coordinated with the Japanese Aerospace Exploration Agency (JAXA) through NASA headquarters for JAXA's ALOS-2 timely tasking over two paths. We produced flood extent maps using ALOS-2 SM3 mode Level 1.5 data that were provided through the International Charter and stored at the US Geological Survey's Hazards Data Distribution System (HDDS) archive. On January 6, the first four frames (70 km x 240 km) were acquired, which included the City of Memphis. We registered post-event SAR images to pre-event images, applied radiometric calibration, took a logarithm of the ratio of the two images. Two thresholds were applied to represent flooded areas that became open water (colored in blue) and flooded areas with tall vegetation (colored in red). The second path was acquired on January 11 further down along the Mississippi River. Seven frames (70 km x 420 km) were acquired and flood maps were created in the similar fashion. The maps were delivered to the FEMA as well as posted on ARIA's public website. The FEMA stated that SAR provides inspection priority for optical imagery and ground response. The ALOS-2 data and the products have been a very important source of information during this response as the flood crest has moved down stream. The SAR data continue to be an important resource during times when optical observations are often not useful. In close collaboration with FEMA and USGS, we also work on other flood events including June 2016 China Floods using European Space Agency's (ESA's) Sentienl-1 data, to produce flood extent maps and identify algorithmic needs and ARIA system's requirements to automate and rapidly produce and deliver flood maps for future events. With the addition of Sentinel-1B

  18. Dynamic changes of serum SARS-Coronavirus IgG, pulmonary function and radiography in patients recovering from SARS after hospital discharge

    Directory of Open Access Journals (Sweden)

    Chen Liangan

    2005-01-01

    Full Text Available Abstract Objective The intent of this study was to examine the recovery of individuals who had been hospitalized for severe acute respiratory syndrome (SARS in the year following their discharge from the hospital. Parameters studied included serum levels of SARS coronavirus (SARS-CoV IgG antibody, tests of lung function, and imaging data to evaluate changes in lung fibrosis. In addition, we explored the incidence of femoral head necrosis in some of the individuals recovering from SARS. Methods The subjects of this study were 383 clinically diagnosed SARS patients in Beijing, China. They were tested regularly for serum levels of SARS-CoV IgG antibody and lung function and were given chest X-rays and/or high resolution computerized tomography (HRCT examinations at the Chinese PLA General Hospital during the 12 months that followed their release from the hospital. Those individuals who were found to have lung diffusion abnormities (transfer coefficient for carbon monoxide [DLCO] Findings Of all the subjects, 81.2% (311 of 383 patients tested positive for serum SARS-CoV IgG. Of those testing positive, 27.3% (85 of 311 patients were suffering from lung diffusion abnormities (DLCO Interpretation The lack of sero-positive SARS-CoV in some individuals suggests that there may have been some misdiagnosed cases among the subjects included in this study. Of those testing positive, the serum levels of SARS-CoV IgG antibody decreased significantly during the 12 months after hospital discharge. Additionally, we found that the individuals who had lung fibrosis showed some spontaneous recovery. Finally, some of the subjects developed femoral head necrosis.

  19. POST-DISASTER DAMAGE ASSESSMENT THROUGH COHERENT CHANGE DETECTION ON SAR IMAGERY

    Directory of Open Access Journals (Sweden)

    L. Guida

    2018-04-01

    Full Text Available Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS. A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

  20. Post-Disaster Damage Assessment Through Coherent Change Detection on SAR Imagery

    Science.gov (United States)

    Guida, L.; Boccardo, P.; Donevski, I.; Lo Schiavo, L.; Molinari, M. E.; Monti-Guarnieri, A.; Oxoli, D.; Brovelli, M. A.

    2018-04-01

    Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

  1. Resolution Enhancement Algorithm for Spaceborn SAR Based on Hanning Function Weighted Sidelobe Suppression

    Science.gov (United States)

    Li, C.; Zhou, X.; Tang, D.; Zhu, Z.

    2018-04-01

    Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.

  2. Satellite sar detection of hurricane helene (2006)

    DEFF Research Database (Denmark)

    Ju, Lian; Cheng, Yongcun; Xu, Qing

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined. ...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

  3. Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

    Science.gov (United States)

    Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

    1991-01-01

    The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

  4. Ultra Wide X-Band Microwave Imaging of Concealed Weapons and Explosives Using 3D-SAR Technique

    Directory of Open Access Journals (Sweden)

    P. Millot

    2015-01-01

    Full Text Available In order to detect and image concealed weapons and explosives, an electromagnetic imaging tool with its related signal processing is presented. The aim is to penetrate clothes and to find personal-born weapons and explosives under clothes. The chosen UWB frequency range covers the whole X-band. The frequency range is justified after transmission measurements of numerous clothes that are dry or slightly wet. The apparatus and the 3D near-field SAR processor are described. A strategy for contour identification is presented with results of some simulants of weapon and explosive. A conclusion is drawn on the possible future of this technique.

  5. The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

    Directory of Open Access Journals (Sweden)

    Stefano Perna

    2016-01-01

    Full Text Available We present in this work a first assessment of the imaging and topographic mapping capabilities of the InSAeS4 system, which is a single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR. In particular, we first provide a brief description of the InSAeS4 sensor. Then, we discuss the results of our analysis on the SAR and interferometric SAR products relevant to the first flight-test campaign. More specifically, we have exploited as reference the GPS measurements relevant to nine Corner Reflectors (CRs deployed over the illuminated area during the campaign and a laser scanner Digital Elevation Model (DEM. From the analysis carried out on the CRs we achieved a mean geometric resolution, for the SAR products, of about 0.14 m in azimuth and 0.49 m in range, a positioning misalignment with standard deviation of 0.07 m in range and 0.08 m in azimuth, and a height error with standard deviation of 0.51 m. From the comparison with the laser scanner DEM we estimated a height error with standard deviation of 1.57 m.

  6. Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

    Directory of Open Access Journals (Sweden)

    Julie Betbeder

    2014-04-01

    Full Text Available Whilst most hedgerow functions depend upon hedgerow structure and hedgerow network patterns, in many ecological studies information on the fragmentation of hedgerows network and canopy structure is often retrieved in the field in small areas using accurate ground surveys and estimated over landscapes in a semi-quantitative manner. This paper explores the use of radar SAR imagery to (i detect hedgerow networks; and (ii describe the hedgerow canopy heterogeneity using TerraSAR-X imagery. The extraction of hedgerow networks was achieved using an object-oriented method using two polarimetric parameters: the Single Bounce and the Shannon Entropy derived from one TerraSAR-X image. The hedgerow canopy heterogeneity estimated from field measurements was compared with two backscattering coefficients and three polarimetric parameters derived from the same image. The results show that the hedgerow network and its fragmentation can be identified with a very good accuracy (Kappa index: 0.92. This study also reveals the high correlation between one polarimetric parameter, the Shannon entropy, and the canopy fragmentation measured in the field. Therefore, VHSR radar images can both precisely detect the presence of wooded hedgerow networks and characterize their structure, which cannot be achieved with optical images.

  7. Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2

    Science.gov (United States)

    McNairn, H.; Kross, A.; Lapen, D.; Caves, R.; Shang, J.

    2014-05-01

    Early and on-going crop production forecasts are important to facilitate food price stability for regions at risk, and for agriculture exporters, to set market value. Most regional and global efforts in forecasting rely on multiple sources of information from the field. With increased access to data from spaceborne Synthetic Aperture Radar (SAR), these sensors could contribute information on crop acreage. But these acreage estimates must be available early in the season to assist with production forecasts. This study acquired TerraSAR-X and RADARSAT-2 data over a region in eastern Canada dominated by economically important corn and soybean production. Using a supervised decision tree classifier, results determined that either sensor was capable of delivering highly accurate maps of corn and soybeans at the end of the growing season. Accuracies far exceeded 90%. Spatial and multi-temporal filtering approaches were compared and small improvements in accuracies were found by applying the multi-temporal filter to the RADARSAT-2 data. Of significant interest, this study determined that by using only three TerraSAR-X images corn could be accurately identified by the end of June, a mere six weeks after planting and at a vegetative growth stage (V6 - sixth leaf collar developed). However, soybeans required additional acquisitions given the variance in planting densities and planting dates in this region of Canada. In this case, accurate soybean classification required TerraSAR-X images until early August at the start of the reproductive stage (R5 - seed development is beginning). Also important, by applying a multi-temporal filter accurate mapping (close to 90%) of corn and soybeans from RADARSAT-2 could occur five weeks earlier (by August 19) than if a spatial filter was used. Thus application of this filtering approach could accelerate delivery of a crop inventory for this region of Canada. Corn and soybeans are important commodities both globally and within Canada. This

  8. Ship Classification with High Resolution TerraSAR-X Imagery Based on Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Zhi Zhao

    2013-01-01

    Full Text Available Ship surveillance using space-borne synthetic aperture radar (SAR, taking advantages of high resolution over wide swaths and all-weather working capability, has attracted worldwide attention. Recent activity in this field has concentrated mainly on the study of ship detection, but the classification is largely still open. In this paper, we propose a novel ship classification scheme based on analytic hierarchy process (AHP in order to achieve better performance. The main idea is to apply AHP on both feature selection and classification decision. On one hand, the AHP based feature selection constructs a selection decision problem based on several feature evaluation measures (e.g., discriminability, stability, and information measure and provides objective criteria to make comprehensive decisions for their combinations quantitatively. On the other hand, we take the selected feature sets as the input of KNN classifiers and fuse the multiple classification results based on AHP, in which the feature sets’ confidence is taken into account when the AHP based classification decision is made. We analyze the proposed classification scheme and demonstrate its results on a ship dataset that comes from TerraSAR-X SAR images.

  9. Different scale land subsidence and ground fissure monitoring with multiple InSAR techniques over Fenwei basin, China

    Directory of Open Access Journals (Sweden)

    C. Zhao

    2015-11-01

    Full Text Available Fenwei basin, China, composed by several sub-basins, has been suffering severe geo-hazards in last 60 years, including large scale land subsidence and small scale ground fissure, which caused serious infrastructure damages and property losses. In this paper, we apply different InSAR techniques with different SAR data to monitor these hazards. Firstly, combined small baseline subset (SBAS InSAR method and persistent scatterers (PS InSAR method is used to multi-track Envisat ASAR data to retrieve the large scale land subsidence covering entire Fenwei basin, from which different land subsidence magnitudes are analyzed of different sub-basins. Secondly, PS-InSAR method is used to monitor the small scale ground fissure deformation in Yuncheng basin, where different spatial deformation gradient can be clearly discovered. Lastly, different track SAR data are contributed to retrieve two-dimensional deformation in both land subsidence and ground fissure region, Xi'an, China, which can be benefitial to explain the occurrence of ground fissure and the correlation between land subsidence and ground fissure.

  10. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  11. SAR processing in the cloud for oil detection in the Arctic

    Science.gov (United States)

    Garron, J.; Stoner, C.; Meyer, F. J.

    2016-12-01

    A new world of opportunity is being thawed from the ice of the Arctic, driven by decreased persistent Arctic sea-ice cover, increases in shipping, tourism, natural resource development. Tools that can automatically monitor key sea ice characteristics and potential oil spills are essential for safe passage in these changing waters. Synthetic aperture radar (SAR) data can be used to discriminate sea ice types and oil on the ocean surface and also for feature tracking. Additionally, SAR can image the earth through the night and most weather conditions. SAR data is volumetrically large and requires significant computing power to manipulate. Algorithms designed to identify key environmental features, like oil spills, in SAR imagery require secondary processing, and are computationally intensive, which can functionally limit their application in a real-time setting. Cloud processing is designed to manage big data and big data processing jobs by means of small cycles of off-site computations, eliminating up-front hardware costs. Pairing SAR data with cloud processing has allowed us to create and solidify a processing pipeline for SAR data products in the cloud to compare operational algorithms efficiency and effectiveness when run using an Alaska Satellite Facility (ASF) defined Amazon Machine Image (AMI). The products created from this secondary processing, were compared to determine which algorithm was most accurate in Arctic feature identification, and what operational conditions were required to produce the results on the ASF defined AMI. Results will be used to inform a series of recommendations to oil-spill response data managers and SAR users interested in expanding their analytical computing power.

  12. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks...

  13. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including...

  14. High-Level Performance Modeling of SAR Systems

    Science.gov (United States)

    Chen, Curtis

    2006-01-01

    SAUSAGE (Still Another Utility for SAR Analysis that s General and Extensible) is a computer program for modeling (see figure) the performance of synthetic- aperture radar (SAR) or interferometric synthetic-aperture radar (InSAR or IFSAR) systems. The user is assumed to be familiar with the basic principles of SAR imaging and interferometry. Given design parameters (e.g., altitude, power, and bandwidth) that characterize a radar system, the software predicts various performance metrics (e.g., signal-to-noise ratio and resolution). SAUSAGE is intended to be a general software tool for quick, high-level evaluation of radar designs; it is not meant to capture all the subtleties, nuances, and particulars of specific systems. SAUSAGE was written to facilitate the exploration of engineering tradeoffs within the multidimensional space of design parameters. Typically, this space is examined through an iterative process of adjusting the values of the design parameters and examining the effects of the adjustments on the overall performance of the system at each iteration. The software is designed to be modular and extensible to enable consideration of a variety of operating modes and antenna beam patterns, including, for example, strip-map and spotlight SAR acquisitions, polarimetry, burst modes, and squinted geometries.

  15. InSAR Deformation Time Series Processed On-Demand in the Cloud

    Science.gov (United States)

    Horn, W. B.; Weeden, R.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

    2017-12-01

    During this past year, ASF has developed a cloud-based on-demand processing system known as HyP3 (http://hyp3.asf.alaska.edu/), the Hybrid Pluggable Processing Pipeline, for Synthetic Aperture Radar (SAR) data. The system makes it easy for a user who doesn't have the time or inclination to install and use complex SAR processing software to leverage SAR data in their research or operations. One such processing algorithm is generation of a deformation time series product, which is a series of images representing ground displacements over time, which can be computed using a time series of interferometric SAR (InSAR) products. The set of software tools necessary to generate this useful product are difficult to install, configure, and use. Moreover, for a long time series with many images, the processing of just the interferograms can take days. Principally built by three undergraduate students at the ASF DAAC, the deformation time series processing relies the new Amazon Batch service, which enables processing of jobs with complex interconnected dependencies in a straightforward and efficient manner. In the case of generating a deformation time series product from a stack of single-look complex SAR images, the system uses Batch to serialize the up-front processing, interferogram generation, optional tropospheric correction, and deformation time series generation. The most time consuming portion is the interferogram generation, because even for a fairly small stack of images many interferograms need to be processed. By using AWS Batch, the interferograms are all generated in parallel; the entire process completes in hours rather than days. Additionally, the individual interferograms are saved in Amazon's cloud storage, so that when new data is acquired in the stack, an updated time series product can be generated with minimal addiitonal processing. This presentation will focus on the development techniques and enabling technologies that were used in developing the time

  16. Use of ERS-2 Sar and Landsat TM Images for Geological Mapping and Mineral Exploration Of Sol Hamid Area, South Eastern Desert, Egypt

    International Nuclear Information System (INIS)

    Ramadan, T.M.

    2003-01-01

    Sol hamid area is chiefy occupied by neo proterozoic rocks, partly covered by miocene sediments and recent sand sheets and dunes. The neo proterozoic rocks include ophiolitic ultramafic to mafic rocks, meta volcano-sedimentary rocks, meta volcanics, gabbros-diorite rocks, granodiorites, biotite granites and alkali granites. Magnesite, chromite, iron ores, manganese and barite ore deposits are hosted in different at the study area. ERS-2 SAR data enabled to obtain an image that reveals some buried fluvial features beneath the surface cover of desert sand. These features are not observable in Landsat TM image of similar resolution. In this work, Principal Component Analysis (PCA) technique was used for merging ERS-2 SAR and Landsat TM images to make use of the potential of data fusion technique of image processing in the interpretation of geological features. This procedure has resulted in enhancing subsurface structure such as faults that control distribution of several deposits in the study area. This study represents an example to demonstrate the utility of merging various remote sensing data for exploring mineral deposits in arid region

  17. NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    G. Máttyus

    2013-05-01

    Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  18. Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

    Science.gov (United States)

    Máttyus, G.

    2013-05-01

    Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  19. An analytical solution for improved HIFU SAR estimation

    International Nuclear Information System (INIS)

    Dillon, C R; Vyas, U; Christensen, D A; Roemer, R B; Payne, A

    2012-01-01

    Accurate determination of the specific absorption rates (SARs) present during high intensity focused ultrasound (HIFU) experiments and treatments provides a solid physical basis for scientific comparison of results among HIFU studies and is necessary to validate and improve SAR predictive software, which will improve patient treatment planning, control and evaluation. This study develops and tests an analytical solution that significantly improves the accuracy of SAR values obtained from HIFU temperature data. SAR estimates are obtained by fitting the analytical temperature solution for a one-dimensional radial Gaussian heating pattern to the temperature versus time data following a step in applied power and evaluating the initial slope of the analytical solution. The analytical method is evaluated in multiple parametric simulations for which it consistently (except at high perfusions) yields maximum errors of less than 10% at the center of the focal zone compared with errors up to 90% and 55% for the commonly used linear method and an exponential method, respectively. For high perfusion, an extension of the analytical method estimates SAR with less than 10% error. The analytical method is validated experimentally by showing that the temperature elevations predicted using the analytical method's SAR values determined for the entire 3D focal region agree well with the experimental temperature elevations in a HIFU-heated tissue-mimicking phantom. (paper)

  20. Satellite SAR inventory of Gulf of Mexico oil seeps and shallow gas hydrates

    Science.gov (United States)

    Garcia, O.; MacDonald, I. R.; Zimmer, B.; Shedd, W.; Frye, M.

    2009-04-01

    Satellite synthetic aperture radar (SAR) images from the RADARSAT platform were used to detect and inventory persistent layers of oil released from natural seeps in the Gulf of Mexico. Previously published inventories of natural oil seeps in the Gulf have been limited in scope and have relied on manual interpretation of satellite images (Mitchell et al. 1999; De Beukelaer et al. 2003). We developed a texture classifying neural network algorithm (TCNNA) to rapidly identify floating oil-layers in a semi-supervised operation. Oil layers, known as slicks, were recognized as long (10 km), narrow (100 m), often curvilinear streaks with distinct points of origin where oil reaches the ocean surface. After training the TCNNA over known seep areas and under a range of environmental and viewing conditions, the procedure was applied to 426 separate images that covered ocean areas of 100x100 km (Standard Beam Mode), 102 images that covered ocean areas of 450x450 km(ScanSAR Wide Beam Mode), and 84 images that covered ocean areas of 300x300 km (ScanSAR Narrow Beam Mode). This image data-set was collected between 1994 and 2007. It covered the entire Gulf of Mexico with a repeat rate of 4 to109, with the highest concentration over the continental slope. This effort identified a total of 4957 slicks among all the images. Of these, 287 appeared a single time in isolated locations and may therefore be false targets. The remaining slicks appeared in groups of up to 9 separate features, clustered in areas of 1 to 6.5 km across. When slicks appear within the same area in repeated images, they are judged to have a persistent source—a bubbling vent on the seafloor (MacDonald et al. 2002). Persistent sources represent geologic formations defined by migrating hydrocarbons that may include multiple separate vents. A total of 559 formations were defined by repeated imaging; these comprised a maximum of 1995 and a minimum of 1263 individual vents. This total was distributed between U

  1. METH-33 - Performance assessment for the high resolution and wide swath (HRWS) post-Sentinel-1 SAR system

    DEFF Research Database (Denmark)

    Zonno, Mariantonietta; Maria J., Sanjuan-Ferrer,; Lopez-Dekker, Paco

    The next generation, post-Sentinel-1, ESA’s C-band synthetic aperture radar (SAR) system is conceived to provide simultaneously high azimuth resolution and wide swath width (HRWS).There are different ways in which the imaging capabilities of the HRWS SAR system can be exploited, which translate...... or numerical models and, if these are not available, real SAR images as well as numerical algorithms and some explicit simulations of the data and of the inversion process are employed. The tool uses as input the HRWS SAR instrument performance for the different applicable modes and produces as output results...

  2. Superresolution Imaging Using Resonant Multiples

    KAUST Repository

    Guo, Bowen

    2017-12-22

    A resonant multiple is defined as a multiple reflection that revisits the same subsurface location along coincident reflection raypaths. We show that resonant first-order multiples can be migrated with either Kirchhoff or wave-equation migration methods to give images with approximately twice the spatial resolution compared to post-stack primary-reflection images. A moveout-correction stacking method is proposed to enhance the signal-to-noise ratios (SNRs) of the resonant multiples before superresolution migration. The effectiveness of this procedure is validated by synthetic and field data tests.

  3. Superresolution Imaging Using Resonant Multiples

    KAUST Repository

    Guo, Bowen; Schuster, Gerard T.

    2017-01-01

    A resonant multiple is defined as a multiple reflection that revisits the same subsurface location along coincident reflection raypaths. We show that resonant first-order multiples can be migrated with either Kirchhoff or wave-equation migration methods to give images with approximately twice the spatial resolution compared to post-stack primary-reflection images. A moveout-correction stacking method is proposed to enhance the signal-to-noise ratios (SNRs) of the resonant multiples before superresolution migration. The effectiveness of this procedure is validated by synthetic and field data tests.

  4. Rapid Mapping Of Floods Using SAR Data: Opportunities And Critical Aspects

    Science.gov (United States)

    Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco

    2013-04-01

    The potentiality of spaceborne Synthetic Aperture Radar (SAR) for flood mapping was demonstrated by several past investigations. The synoptic view, the capability to operate in almost all-weather conditions and during both day time and night time and the sensitivity of the microwave band to water are the key features that make SAR data useful for monitoring inundation events. In addition, their high spatial resolution, which can reach 1m with the new generation of X-band instruments such as TerraSAR-X and COSMO-SkyMed (CSK), allows emergency managers to use flood maps at very high spatial resolution. CSK gives also the possibility of performing frequent observations of regions hit by floods, thanks to the four-satellite constellation. Current research on flood mapping using SAR is focused on the development of automatic algorithms to be used in near real time applications. The approaches are generally based on the low radar return from smooth open water bodies that behave as specular reflectors and appear dark in SAR images. The major advantage of automatic algorithms is the computational efficiency that makes them suitable for rapid mapping purposes. The choice of the threshold value that, in this kind of algorithms, separates flooded from non-flooded areas is a critical aspect because it depends on the characteristics of the observed scenario and on system parameters. To deal with this aspect an algorithm for automatic detection of the regions of low backscatter has been developed. It basically accomplishes three steps: 1) division of the SAR image in a set of non-overlapping sub-images or splits; 2) selection of inhomogeneous sub-images that contain (at least) two populations of pixels, one of which is formed by dark pixels; 3) the application in sequence of an automatic thresholding algorithm and a region growing algorithm in order to produce a homogeneous map of flooded areas. Besides the aforementioned choice of the threshold, rapid mapping of floods may

  5. Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping

    Science.gov (United States)

    Bahr, Thomas

    2014-05-01

    The use of SAR data has become increasingly popular in recent years and in a wide array of industries. Having access to SAR can be highly important and critical especially for public safety. Updating a GIS with contemporary information from SAR data allows to deliver a reliable set of geospatial information to advance civilian operations, e.g. search and rescue missions. SAR imaging offers the great advantage, over its optical counterparts, of not being affected by darkness, meteorological conditions such as clouds, fog, etc., or smoke and dust, frequently associated with disaster zones. In this paper we present the operational processing of SAR data within a GIS environment for rapid disaster mapping. For this technique we integrated the SARscape modules for ENVI with ArcGIS®, eliminating the need to switch between software packages. Thereby the premier algorithms for SAR image analysis can be directly accessed from ArcGIS desktop and server environments. They allow processing and analyzing SAR data in almost real time and with minimum user interaction. This is exemplified by the November 2010 flash flood in the Veneto region, Italy. The Bacchiglione River burst its banks on Nov. 2nd after two days of heavy rainfall throughout the northern Italian region. The community of Bovolenta, 22 km SSE of Padova, was covered by several meters of water. People were requested to stay in their homes; several roads, highways sections and railroads had to be closed. The extent of this flooding is documented by a series of Cosmo-SkyMed acquisitions with a GSD of 2.5 m (StripMap mode). Cosmo-SkyMed is a constellation of four Earth observation satellites, allowing a very frequent coverage, which enables monitoring using a very high temporal resolution. This data is processed in ArcGIS using a single-sensor, multi-mode, multi-temporal approach consisting of 3 steps: (1) The single images are filtered with a Gamma DE-MAP filter. (2) The filtered images are geocoded using a reference

  6. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  7. RESOLUTION ENHANCEMENT ALGORITHM FOR SPACEBORN SAR BASED ON HANNING FUNCTION WEIGHTED SIDELOBE SUPPRESSION

    Directory of Open Access Journals (Sweden)

    C. Li

    2018-04-01

    Full Text Available Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is −30dB.

  8. Simultaneous Genomic Detection of Multiple Enteric Bacterial and Viral Pathogens, Including Sars-CoV and RVFV

    National Research Council Canada - National Science Library

    Payne, S; Peters, C. J. (Clarence James), 1940; Makino, S; Oliver, K; Weiss, C; Kornguth, S; Carruthers, L; Chin, R

    2004-01-01

    ...) associated with the SARS-associated coronavirus (SARS-CoV) and Rift Valley Fever Virus (RVFV) has been developed. This system is based upon the Luminex xMAP" System, a multiplexed assay platform that combines high sample throughput...

  9. SAR data for the analysis of forest features: current Brazilian experiences

    Directory of Open Access Journals (Sweden)

    Fábio Guimarães Gonçalves

    2007-06-01

    Full Text Available This article presents some applications of airborne polarimetric and/or interferometric microwave data to improve the knowledge of forest structures. Three airborne SAR (Synthetic Aperture Radar experiments were done in the Amazon tropical forest: (a to study the spatial distribution of very large trees (VLTs in the primary forest using local maximum filtering and a series of Markov processes; (b to model the estimation of biomass variations in primary and secondary forests; (c to analyze the retrieval timber volume over selective logging areas. Another experiment (d was to investigate the relation among SAR data and the volumetric configuration in stands of Eucalyptus sp done by an airborne SAR imaging mission in SE-Brazil. To perform the objectives (b, (c and (d we carry out regression techniques, using variables got from multipolarimetric and/or interferometric SAR attributes and biophysical parameters from the forest cover. All data from the experiments were calibrated radiometrically to extract information during digital processing, besides an exhaustive field survey which was done simultaneously to SAR imaging, to know the physiognomy/structure of forest typology and to support the models produced for each case. The results of this series of experiments show advances at the techniques to treat SAR data, focusing on models of stand architecture and forest stock density. This will be helpful to increase the regional inventory and surveying procedures of forest conversion in the Brazilian territory in the near future.

  10. SAR data for the analysis of forest features: current Brazilian experiences

    Directory of Open Access Journals (Sweden)

    Fábio Guimarães Gonçalves

    2006-12-01

    Full Text Available This article presents some applications of airborne polarimetric and/or interferometric microwave data to improve the knowledge of forest structures. Three airborne SAR (Synthetic Aperture Radar experiments were done in the Amazon tropical forest: (a to study the spatial distribution of very large trees (VLTs in the primary forest using local maximum filtering and a series of Markov processes; (b to model the estimation of biomass variations in primary and secondary forests; (c to analyze the retrieval of timber volume over selective logging areas. Another experiment (d was to investigate the relation among SAR data and the volumetric configuration in stands of Eucalyptus sp. done by an airborne SAR imaging mission in SE-Brazil. To perform the objectives (b, (c and (d we carry out regression techniques, using variables got from multipolarimetric and/or interferometric SAR attributes and biophysical parameters from the forest cover. All data from the experiments were calibrated radiometrically to extract information during digital processing, besides an exhaustive field survey which was done simultaneously to SAR imaging, to know the physiognomy/structure of forest typology and to support the models produced for each case. The results of this series of experiments show advances at the techniques to treat SAR data, focusing on models of stand architecture and forest stock density. This will be helpful to increase the regional inventory and surveying procedures of forest conversion in the Brazilian territory in the near future.

  11. Assessment of radargrammetric DSMs from TerraSAR-X Stripmap images in a mountainous relief area of the Amazon region

    Science.gov (United States)

    de Oliveira, Cleber Gonzales; Paradella, Waldir Renato; da Silva, Arnaldo de Queiroz

    The Brazilian Amazon is a vast territory with an enormous need for mapping and monitoring of renewable and non-renewable resources. Due to the adverse environmental condition (rain, cloud, dense vegetation) and difficult access, topographic information is still poor, and when available needs to be updated or re-mapped. In this paper, the feasibility of using Digital Surface Models (DSMs) extracted from TerraSAR-X Stripmap stereo-pair images for detailed topographic mapping was investigated for a mountainous area in the Carajás Mineral Province, located on the easternmost border of the Brazilian Amazon. The quality of the radargrammetric DSMs was evaluated regarding field altimetric measurements. Precise topographic field information acquired from a Global Positioning System (GPS) was used as Ground Control Points (GCPs) for the modeling of the stereoscopic DSMs and as Independent Check Points (ICPs) for the calculation of elevation accuracies. The analysis was performed following two ways: (1) the use of Root Mean Square Error (RMSE) and (2) calculations of systematic error (bias) and precision. The test for significant systematic error was based on the Student's-t distribution and the test of precision was based on the Chi-squared distribution. The investigation has shown that the accuracy of the TerraSAR-X Stripmap DSMs met the requirements for 1:50,000 map (Class A) as requested by the Brazilian Standard for Cartographic Accuracy. Thus, the use of TerraSAR-X Stripmap images can be considered a promising alternative for detailed topographic mapping in similar environments of the Amazon region, where available topographic information is rare or presents low quality.

  12. Generalized internal multiple imaging

    KAUST Repository

    Zuberi, M. A. H.; Alkhalifah, Tariq Ali

    2014-01-01

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling

  13. SAR China Land Mapping Project: Development, Production and Potential Applications

    International Nuclear Information System (INIS)

    Zhang, Lu; Guo, Huadong; Liu, Guang; Fu, Wenxue; Yan, Shiyong; Song, Rui; Ji, Peng; Wang, Xinyuan

    2014-01-01

    Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change

  14. Measurement of Subsidence in the Yangbajain Geothermal Fields from TerraSAR-X

    Science.gov (United States)

    Li, Yongsheng; Zhang, Jingfa; Li, Zhenhong

    2016-08-01

    Yangbajain contains the largest geothermal energy power station in China. Geothermal explorations in Yangbajain first started in 1976, and two plants were subsequently built in 1981 and 1986. A large amount of geothermal fluids have been extracted since then, leading to considerable surface subsidence around the geothermal fields. In this paper, InSAR time series analysis is applied to map the subsidence of the Yangbajain geothermal fields during the period from December 2011 to November 2012 using 16 senses of TerraSAR-X stripmap SAR images. Due to its high resolution and short repeat cycle, TerraSAR-X provides detailed surface deformation information at the Yangbajain geothermal fields.

  15. Parametric estimation of time varying baselines in airborne interferometric SAR

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    1996-01-01

    A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...

  16. Unsupervised DInSAR processing chain for multi-scale displacement analysis

    Science.gov (United States)

    Casu, Francesco; Manunta, Michele

    2016-04-01

    Earth Observation techniques can be very helpful for the estimation of several sources of ground deformation due to their characteristics of large spatial coverage, high resolution and cost effectiveness. In this scenario, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most effective methodologies for its capability to generate spatially dense deformation maps at both global and local spatial scale, with centimeter to millimeter accuracy. DInSAR exploits the phase difference (interferogram) between SAR image pairs relevant to acquisitions gathered at different times, but with the same illumination geometry and from sufficiently close flight tracks, whose separation is typically referred to as baseline. Among several, the SBAS algorithm is one of the most used DInSAR approaches and it is aimed at generating displacement time series at a multi-scale level by exploiting a set of small baseline interferograms. SBAS, and generally DInSAR, has taken benefit from the large availability of spaceborne SAR data collected along years by several satellite systems, with particular regard to the European ERS and ENVISAT sensors, which have acquired SAR images worldwide during approximately 20 years. Moreover, since 2014 the new generation of Copernicus Sentinel satellites has started to acquire data with a short revisit time (12 days) and a global coverage policy, thus flooding the scientific EO community with an unprecedent amount of data. To efficiently manage such amount of data, proper processing facilities (as those coming from the emerging Cloud Computing technologies) have to be used, as well as novel algorithms aimed at their efficient exploitation have to be developed. In this work we present a set of results achieved by exploiting a recently proposed implementation of the SBAS algorithm, namely Parallel-SBAS (P-SBAS), which allows us to effectively process, in an unsupervised way and in a limited time frame, a huge number of SAR images

  17. Improved spatial mapping of rainfall events with spaceborne SAR imagery

    Science.gov (United States)

    Ulaby, F. T.; Brisco, B.; Dobson, C.

    1983-01-01

    The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

  18. Pareto-depth for multiple-query image retrieval.

    Science.gov (United States)

    Hsiao, Ko-Jen; Calder, Jeff; Hero, Alfred O

    2015-02-01

    Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

  19. Multifrequency OFDM SAR in Presence of Deception Jamming

    Directory of Open Access Journals (Sweden)

    Schuerger Jonathan

    2010-01-01

    Full Text Available Orthogonal frequency division multiplexing (OFDM is considered in this paper from the perspective of usage in imaging radar scenarios with deception jamming. OFDM radar signals are inherently multifrequency waveforms, composed of a number of subbands which are orthogonal to each other. While being employed extensively in communications, OFDM has not found comparatively wide use in radar, and, particularly, in synthetic aperture radar (SAR applications. In this paper, we aim to show the advantages of OFDM-coded radar signals with random subband composition when used in deception jamming scenarios. Two approaches to create a radar signal by the jammer are considered: instantaneous frequency (IF estimator and digital-RF-memory- (DRFM- based reproducer. In both cases, the jammer aims to create a copy of a valid target image via resending the radar signal at prescribed time intervals. Jammer signals are derived and used in SAR simulations with three types of signal models: OFDM, linear frequency modulated (LFM, and frequency-hopped (FH. Presented results include simulated peak side lobe (PSL and peak cross-correlation values for random OFDM signals, as well as simulated SAR imagery with IF and DRFM jammers'-induced false targets.

  20. TerraSAR-X InSAR multipass analysis on Venice, Italy)

    Science.gov (United States)

    Nitti, D. O.; Nutricato, R.; Bovenga, F.; Refice, A.; Chiaradia, M. T.; Guerriero, L.

    2009-09-01

    The TerraSAR-X (copyright) mission, launched in 2007, carries a new X-band Synthetic Aperture Radar (SAR) sensor optimally suited for SAR interferometry (InSAR), thus allowing very promising application of InSAR techniques for the risk assessment on areas with hydrogeological instability and especially for multi-temporal analysis, such as Persistent Scatterer Interferometry (PSI) techniques, originally developed at Politecnico di Milano. The SPINUA (Stable Point INterferometry over Unurbanised Areas) technique is a PSI processing methodology which has originally been developed with the aim of detection and monitoring of coherent PS targets in non or scarcely-urbanized areas. The main goal of the present work is to describe successful applications of the SPINUA PSI technique in processing X-band data. Venice has been selected as test site since it is in favorable settings for PSI investigations (urban area containing many potential coherent targets such as buildings) and in view of the availability of a long temporal series of TerraSAR-X stripmap acquisitions (27 scenes in all). The Venice Lagoon is affected by land sinking phenomena, whose origins are both natural and man-induced. The subsidence of Venice has been intensively studied for decades by determining land displacements through traditional monitoring techniques (leveling and GPS) and, recently, by processing stacks of ERS/ENVISAT SAR data. The present work is focused on an independent assessment of application of PSI techniques to TerraSAR-X stripmap data for monitoring the stability of the Venice area. Thanks to its orbital repeat cycle of only 11 days, less than a third of ERS/ENVISAT C-band missions, the maximum displacement rate that can be unambiguously detected along the Line-of-Sight (LOS) with TerraSAR-X SAR data through PSI techniques is expected to be about twice the corresponding value of ESA C-band missions, being directly proportional to the sensor wavelength and inversely proportional to the

  1. Detection of oil spills near offshore installations using synthetic aperture radar (SAR)

    International Nuclear Information System (INIS)

    Espedal, H.A.; Johannessen, O.M.

    2000-01-01

    Remote sensing using synthetic aperture radar (SAR) is attracting increasing interest for the detection of oil spills from offshore oil installations. Three systems are already operating and three more are planned. SAR can provide high spatial resolution and is not affected by the time of day or cloud conditions. Examples of images obtained from UK and Norwegian offshore installations are shown and their interpretation are explained. SAR image analysis is used by a satellite-based oil spill monitoring service covering the Norwegian sector of the North Sea and part of the North Sea, the Norwegian Sea and the Baltic Sea. An algorithm has been developed at the Nansen Environmental and Remote Sensing Centre (NERSC) in Norway to help distinguish between oil spills, natural films, current shear zones and rain cells

  2. Convolutional neural network using generated data for SAR ATR with limited samples

    Science.gov (United States)

    Cong, Longjian; Gao, Lei; Zhang, Hui; Sun, Peng

    2018-03-01

    Being able to adapt all weather at all times, it has been a hot research topic that using Synthetic Aperture Radar(SAR) for remote sensing. Despite all the well-known advantages of SAR, it is hard to extract features because of its unique imaging methodology, and this challenge attracts the research interest of traditional Automatic Target Recognition(ATR) methods. With the development of deep learning technologies, convolutional neural networks(CNNs) give us another way out to detect and recognize targets, when a huge number of samples are available, but this premise is often not hold, when it comes to monitoring a specific type of ships. In this paper, we propose a method to enhance the performance of Faster R-CNN with limited samples to detect and recognize ships in SAR images.

  3. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    Science.gov (United States)

    Changyong, Dou; Huadong, Guo; Chunming, Han; yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-03-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc.

  4. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    International Nuclear Information System (INIS)

    Changyong, Dou; Huadong, Guo; Chunming, Han; Yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-01-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc

  5. FUSION OF OPTICAL DATA AND SAR DATA FOR THE ESTIMATION OF NITROGEN CONCENTRATION IN PEARL RIVER ESTUARY HONG KONG SEAS, CHINA

    Directory of Open Access Journals (Sweden)

    X. Liu

    2012-08-01

    Full Text Available The knowledge of nitrogen concentration in the ocean is fundamental for the study of oceanic biogeochemical processes. The objective of this research is to estimate total inorganic nitrogen (TIN by integrating optical parameters from HJ-1 CCD image and polarization parameters from RADARSAT-2 quad-polarization image. The situ data and HJ-1 CCD, RADARSAT-2 image were acquired from Pearl River Estuary Hong Kong Seas, China in August, 2010. The four sensitive parameters, reflectance of Band 4, NDSI (Normalized Difference Spectral Index, the backscattering coefficient of HV and VH were derived as input variables to assess the TIN. A multiple regression model was established between four input variables and TIN. The result showed that the fusion of optical data and SAR data was proved to be successful in estimating TIN in sea surface, with the correlation coefficient (R2 between measured TIN and predicated TIN of 0.774, and the root mean square error (RMSE of 0.063. The optical data in combination with SAR data is promising for detecting biochemical component in sea surface.

  6. The physical basis for estimating wave energy spectra from SAR imagery

    Science.gov (United States)

    Lyzenga, David R.

    1987-01-01

    Ocean surface waves are imaged by synthetic aperture radar (SAR) through a combination of the effects of changes in the surface slope, surface roughness, and surface motion. Over a limited range of conditions, each of these effects can be described in terms of a linear modulation-transfer function. In such cases, the wave-height spectrum can be estimated in a straightforward manner from the SAR image-intensity spectrum. The range of conditions over which this assumption of linearity is valid is investigated using a numerical simulation model, and the implications of various departures from linearity are discussed.

  7. Satellite SAR interferometric techniques applied to emergency mapping

    Science.gov (United States)

    Stefanova Vassileva, Magdalena; Riccardi, Paolo; Lecci, Daniele; Giulio Tonolo, Fabio; Boccardo Boccardo, Piero; Chiesa, Giuliana; Angeluccetti, Irene

    2017-04-01

    monitoring maps for risk prevention and mitigation purposes. Nevertheless, multi-temporal techniques require large SAR temporal datasets, i.e. 20 and more images. Being the Sentinel-1 missions operational only since April 2014, multi-mission SAR datasets should be therefore exploited to carry out historical analysis.

  8. Pasture Monitoring Using SAR with COSMO-SkyMed, ENVISAT ASAR, and ALOS PALSAR in Otway, Australia

    Directory of Open Access Journals (Sweden)

    Xiaojing Li

    2013-07-01

    Full Text Available Because of all-weather working ability, sensitivity to biomass and moisture, and high spatial resolution, Synthetic aperture radar (SAR satellite images can perfectly complement optical images for pasture monitoring. This paper aims to examine the potential of the integration of COnstellation of small Satellites for the Mediterranean basin Observasion (COSMO-SkyMed, Environmental Satellite Advanced Synthetic Aperture Radar (ENVISAT ASAR, and Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR radar signals at horizontally emitted and received polarization (HH for pasture monitoring at the paddock scale in order to guide farmers for better management. The pasture site is selected, in Otway, Victoria, Australia. The biomass, water content of grass, and soil moisture over this site were analyzed with these three bands of SAR images, through linear relationship between SAR backscattering coefficient, and vegetation indices Normalized Differential Vegetation Index (NDVI, Normalized Difference Water Index (NDWI, Enhanced Vegetation Index (EVI, together with soil moisture index (MI. NDVI, NDWI, and MI are considered as proxy of pasture biomass, plant water content, and soil moisture, respectively, and computed from optical images and climate data. SAR backscattering coefficient and vegetation indices are computed within a grass zone, defined by classification with MODIS data. The grass condition and grazing activities for specific paddocks are detectable, based on SAR backscatter, with all three wavelengths datasets. Both temporal and spatial analysis results show that the X-band SAR has the highest correlation to the vegetation indices. However, its accuracy can be affected by wet weather due to its sensitivity to the water on leaves. The C-band HH backscattering coefficient showed moderate reliability to evaluate biomass and water content of grass, with limited influence from rainfall in the dry season

  9. SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

    Science.gov (United States)

    Wassermann, Anne Mai; Haebel, Peter; Weskamp, Nils; Bajorath, Jürgen

    2012-07-23

    We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

  10. A new scheme for urban impervious surface classification from SAR images

    Science.gov (United States)

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  11. A SAR-ADC using unit bridge capacitor and with calibration for the front-end electronics of PET imaging

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Wei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Wei, Tingcun, E-mail: weitc@nwpu.edu.cn [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Li, Bo; Yang, Lifeng; Xue, Feifei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Hu, Yongcai [Institut Pluridisciplinaire Hubert CURIEN, Strasbourg (France)

    2016-05-11

    This paper presents a 12-bit 1 MS/s successive approximation register-analog to digital converter (SAR-ADC) for the 32-channel front-end electronics of CZT-based PET imaging system. To reduce the capacitance mismatch, instead of the fractional capacitor, the unit capacitor is used as the bridge capacitor in the split-capacitor digital to analog converter (DAC) circuit. In addition, in order to eliminate the periodical DNL errors of −1 LSB which often exists in the SAR-ADC using the charge-redistributed DAC, a calibration algorithm is proposed and verified by the experiments. The proposed 12-bit 1 MS/s SAR-ADC is designed and implemented using a 0.35 μm CMOS technology, it occupies only an active area of 986×956 μm{sup 2}. The measurement results show that, at the power supply of 3.3/5.0 V and the sampling rate of 1 MS/s, the ADC with calibration has a signal-to-noise-and-distortion ratio (SINAD) of 67.98 dB, the power dissipation of 5 mW, and a figure of merit (FOM) of 2.44 pJ/conv.-step. This ADC is with the features of high accuracy, low power and small layout area, it is especially suitable to the one-chip integration of the front-end readout electronics.

  12. Local SAR in High Pass Birdcage and TEM Body Coils for Multiple Human Body Models in Clinical Landmark Positions at 3T

    Science.gov (United States)

    Yeo, Desmond TB; Wang, Zhangwei; Loew, Wolfgang; Vogel, Mika W; Hancu, Ileana

    2011-01-01

    Purpose To use EM simulations to study the effects of body type, landmark position, and RF body coil type on peak local SAR in 3T MRI. Materials and Methods Numerically computed peak local SAR for four human body models (HBMs) in three landmark positions (head, heart, pelvic) were compared for a high-pass birdcage and a transverse electromagnetic 3T body coil. Local SAR values were normalized to the IEC whole-body average SAR limit of 2.0 W/kg for normal scan mode. Results Local SAR distributions were highly variable. Consistent with previous reports, the peak local SAR values generally occurred in the neck-shoulder area, near rungs, or between tissues of greatly differing electrical properties. The HBM type significantly influenced the peak local SAR, with stockier HBMs, extending extremities towards rungs, displaying the highest SAR. There was also a trend for higher peak SAR in the head-centric and heart-centric positions. The impact of the coil-types studied was not statistically significant. Conclusion The large variability in peak local SAR indicates the need to include more than one HBM or landmark position when evaluating safety of body coils. It is recommended that a HBM with arms near the rungs be included, to create physically realizable high-SAR scenarios. PMID:21509880

  13. An ice-motion tracking system at the Alaska SAR facility

    Science.gov (United States)

    Kwok, Ronald; Curlander, John C.; Pang, Shirley S.; Mcconnell, Ross

    1990-01-01

    An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.

  14. Multiple Image Radiography With Diffraction Enhanced Imaging For Breast Specimen

    International Nuclear Information System (INIS)

    Oltulu, Oral; Zhong Zhong; Hasnah, Moumen; Chapman, Dean

    2007-01-01

    Biological samples are of great interest for many imaging techniques. The samples usually contain small structures and weak absorption properties. The combinations of weak signals with overlying structures make feature recognition difficult in many cases. In the x-ray regime, a relatively new imaging technique Diffraction Enhanced Imaging (DEI) has superior tissue contrast over conventional radiography and is proven to be very sensitive method. Multiple images taken by DEI are called Multiple Image Radiography (MIR). The purpose of this study is to validate the potential application of the method and to show that MIR-DEI method may give more information about the sample

  15. Generation and assessment of turntable SAR data for the support of ATR development

    Science.gov (United States)

    Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

    1998-10-01

    Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

  16. Urban remote sensing in areas of conflict: TerraSAR-X and Sentinel-1 change detection in the Middle East

    Science.gov (United States)

    Tapete, Deodato; Cigna, Francesca

    2016-08-01

    Timely availability of images of suitable spatial resolution, temporal frequency and coverage is currently one of the major technical constraints on the application of satellite SAR remote sensing for the conservation of heritage assets in urban environments that are impacted by human-induced transformation. TerraSAR-X and Sentinel-1A, in this regard, are two different models of SAR data provision: very high resolution on-demand imagery with end user-selected acquisition parameters, on one side, and freely accessible GIS-ready products with intended regular temporal coverage, on the other. What this means for change detection analyses in urban areas is demonstrated in this paper via the experiment over Homs, the third largest city of Syria with an history of settlement since 2300 BCE, where the impacts of the recent civil war combine with pre- and post-conflict urban transformation . The potential performance of Sentinel-1A StripMap scenes acquired in an emergency context is simulated via the matching StripMap beam mode offered by TerraSAR-X. Benefits and limitations of the different radar frequency band, spatial resolution and single/multi-channel polarization are discussed, as a proof-of-concept of regular monitoring currently achievable with space-borne SAR in historic urban settings. Urban transformation observed across Homs in 2009, 2014 and 2015 shows the impact of the Syrian conflict on the cityscape and proves that operator-driven interpretation is required to understand the complexity of multiple and overlapping urban changes.

  17. Basic to Advanced InSAR Processing: GMTSAR

    Science.gov (United States)

    Sandwell, D. T.; Xu, X.; Baker, S.; Hogrelius, A.; Mellors, R. J.; Tong, X.; Wei, M.; Wessel, P.

    2017-12-01

    Monitoring crustal deformation using InSAR is becoming a standard technique for the science and application communities. Optimal use of the new data streams from Sentinel-1 and NISAR will require open software tools as well as education on the strengths and limitations of the InSAR methods. Over the past decade we have developed freely available, open-source software for processing InSAR data. The software relies on the Generic Mapping Tools (GMT) for the back-end data analysis and display and is thus called GMTSAR. With startup funding from NSF, we accelerated the development of GMTSAR to include more satellite data sources and provide better integration and distribution with GMT. In addition, with support from UNAVCO we have offered 6 GMTSAR short courses to educate mostly novice InSAR users. Currently, the software is used by hundreds of scientists and engineers around the world to study deformation at more than 4300 different sites. The most challenging aspect of the recent software development was the transition from image alignment using the cross-correlation method to a completely new alignment algorithm that uses only the precise orbital information to geometrically align images to an accuracy of better than 7 cm. This development was needed to process a new data type that is being acquired by the Sentinel-1A/B satellites. This combination of software and open data is transforming radar interferometry from a research tool into a fully operational time series analysis tool. Over the next 5 years we are planning to continue to broaden the user base through: improved software delivery methods; code hardening; better integration with data archives; support for high level products being developed for NISAR; and continued education and outreach.

  18. Detecting Landscape Disturbance at the Nasca Lines Using SAR Data Collected from Airborne and Satellite Platforms

    Directory of Open Access Journals (Sweden)

    Douglas C. Comer

    2017-10-01

    Full Text Available We used synthetic aperture radar (SAR data collected over Peru’s Lines and Geoglyphs of the Nasca and Palpa World Heritage Site to detect and measure landscape disturbance threatening world-renowned archaeological features and ecosystems. We employed algorithms to calculate correlations between pairs of SAR returns, collected at different times, and generate correlation images. Landscape disturbances even on the scale of pedestrian travel are discernible in correlation images generated from airborne, L-band SAR. Correlation images derived from C-band SAR data collected by the European Space Agency’s Sentinel-1 satellites also provide detailed landscape change information. Because the two Sentinel-1 satellites together have a repeat pass interval that can be as short as six days, products derived from their data can not only provide information on the location and degree of ground disturbance, but also identify a time window of about one to three weeks during which disturbance must have occurred. For Sentinel-1, this does not depend on collecting data in fine-beam modes, which generally sacrifice the size of the area covered for a higher spatial resolution. We also report on pixel value stretching for a visual analysis of SAR data, quantitative assessment of landscape disturbance, and statistical testing for significant landscape change.

  19. SARS - Diagnosis

    Indian Academy of Sciences (India)

    SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

  20. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  1. Attenuation of multiples in image space

    Science.gov (United States)

    Alvarez, Gabriel F.

    In complex subsurface areas, attenuation of 3D specular and diffracted multiples in data space is difficult and inaccurate. In those areas, image space is an attractive alternative. There are several reasons: (1) migration increases the signal-to-noise ratio of the data; (2) primaries are mapped to coherent events in Subsurface Offset Domain Common Image Gathers (SODCIGs) or Angle Domain Common Image Gathers (ADCIGs); (3) image space is regular and smaller; (4) attenuating the multiples in data space leaves holes in the frequency-Wavenumber space that generate artifacts after migration. I develop a new equation for the residual moveout of specular multiples in ADCIGs and use it for the kernel of an apex-shifted Radon transform to focus and separate the primaries from specular and diffracted multiples. Because of small amplitude, phase and kinematic errors in the multiple estimate, we need adaptive matching and subtraction to estimate the primaries. I pose this problem as an iterative least-squares inversion that simultaneously matches the estimates of primaries and multiples to the data. Standard methods match only the estimate of the multiples. I demonstrate with real and synthetic data that the method produces primaries and multiples with little cross-talk. In 3D, the multiples exhibit residual moveout in SODCIGs in in-line and cross-line offsets. They map away from zero subsurface offsets when migrated with the faster velocity of the primaries. In ADCIGs the residual moveout of the primaries as a function of the aperture angle, for a given azimuth, is flat for those angles that illuminate the reflector. The multiples have residual moveout towards increasing depth for increasing aperture angles at all azimuths. As a function of azimuth, the primaries have better azimuth resolution than the multiples at larger aperture angles. I show, with a real 3D dataset, that even below salt, where illumination is poor, the multiples are well attenuated in ADCIGs with the new

  2. Far-field super-resolution imaging of resonant multiples

    KAUST Repository

    Guo, Bowen

    2016-05-20

    We demonstrate for the first time that seismic resonant multiples, usually considered as noise, can be used for super-resolution imaging in the far-field region of sources and receivers. Tests with both synthetic data and field data show that resonant multiples can image reflector boundaries with resolutions more than twice the classical resolution limit. Resolution increases with the order of the resonant multiples. This procedure has important applications in earthquake and exploration seismology, radar, sonar, LIDAR (light detection and ranging), and ultrasound imaging, where the multiples can be used to make high-resolution images.

  3. Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

    Science.gov (United States)

    Tan, Zhen-ya; He, Feng

    2018-04-01

    With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

  4. COSMO-skymed, TerraSAR-X, and RADARSAT-2 geolocation accuracy after compensation for earth-system effects

    OpenAIRE

    Schubert, Adrian; Small, David; Jehle, Michael; Meier, Erich

    2012-01-01

    A Synthetic Aperture Radar (SAR) sensor with high geolocation accuracy greatly simplifies the task of combining multiple data takes within a common geodetic reference system or Geographic Information System (GIS), and is a critical enabler for many applications such as near-real-time disaster mapping. In this study, the geolocation accuracy was estimated using the same methodology for products from three SAR sensors: TerraSAR-X (two identical satellites), COSMO-SkyMed (four identical satellit...

  5. Study on Zero-Doppler Centroid Control for GEO SAR Ground Observation

    Directory of Open Access Journals (Sweden)

    Yicheng Jiang

    2014-01-01

    Full Text Available In geosynchronous Earth orbit SAR (GEO SAR, Doppler centroid compensation is a key step for imaging process, which could be performed by the attitude steering of a satellite platform. However, this zero-Doppler centroid control method does not work well when the look angle of radar is out of an expected range. This paper primarily analyzes the Doppler properties of GEO SAR in the Earth rectangular coordinate. Then, according to the actual conditions of the GEO SAR ground observation, the effective range is presented by the minimum and maximum possible look angles which are directly related to the orbital parameters. Based on the vector analysis, a new approach for zero-Doppler centroid control in GEO SAR, performing the attitude steering by a combination of pitch and roll rotation, is put forward. This approach, considering the Earth’s rotation and elliptical orbit effects, can accurately reduce the residual Doppler centroid. All the simulation results verify the correctness of the range of look angle and the proposed steering method.

  6. Synthetic aperture radar imaging simulator for pulse envelope evaluation

    Science.gov (United States)

    Balster, Eric J.; Scarpino, Frank A.; Kordik, Andrew M.; Hill, Kerry L.

    2017-10-01

    A simulator for spotlight synthetic aperture radar (SAR) image formation is presented. The simulator produces radar returns from a virtual radar positioned at an arbitrary distance and altitude. The radar returns are produced from a source image, where the return is a weighted summation of linear frequency-modulated (LFM) pulse signals delayed by the distance of each pixel in the image to the radar. The imagery is resampled into polar format to ensure consistent range profiles to the position of the radar. The SAR simulator provides a capability enabling the objective analysis of formed SAR imagery, comparing it to an original source image. This capability allows for analysis of various SAR signal processing techniques previously determined by impulse response function (IPF) analysis. The results suggest that IPF analysis provides results that may not be directly related to formed SAR image quality. Instead, the SAR simulator uses image quality metrics, such as peak signal-to-noise ratio (PSNR) and structured similarity index (SSIM), for formed SAR image quality analysis. To showcase the capability of the SAR simulator, it is used to investigate the performance of various envelopes applied to LFM pulses. A power-raised cosine window with a power p=0.35 and roll-off factor of β=0.15 is shown to maximize the quality of the formed SAR images by improving PSNR by 0.84 dB and SSIM by 0.06 from images formed utilizing a rectangular pulse, on average.

  7. Free Surface Downgoing VSP Multiple Imaging

    Science.gov (United States)

    Maula, Fahdi; Dac, Nguyen

    2018-03-01

    The common usage of a vertical seismic profile is to capture the reflection wavefield (upgoing wavefield) so that it can be used for further well tie or other interpretations. Borehole Seismic (VSP) receivers capture the reflection from below the well trajectory, traditionally no seismic image information above trajectory. The non-traditional way of processing the VSP multiple can be used to expand the imaging above the well trajectory. This paper presents the case study of using VSP downgoing multiples for further non-traditional imaging applications. In general, VSP processing, upgoing and downgoing arrivals are separated during processing. The up-going wavefield is used for subsurface illumination, whereas the downgoing wavefield and multiples are normally excluded from the processing. In a situation where the downgoing wavefield passes the reflectors several times (multiple), the downgoing wavefield carries reflection information. Its benefit is that it can be used for seismic tie up to seabed, and possibility for shallow hazards identifications. One of the concepts of downgoing imaging is widely known as mirror-imaging technique. This paper presents a case study from deep water offshore Vietnam. The case study is presented to demonstrate the robustness of the technique, and the limitations encountered during its processing.

  8. 2002/2003 IfSAR data for Southern California: Radar Reflectance Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the collection and processing of topographic elevation point data derived from Interferometric Synthetic Aperture Radar (IfSAR)...

  9. Superpixel Segmentation for Polsar Images with Local Iterative Clustering and Heterogeneous Statistical Model

    Science.gov (United States)

    Xiang, D.; Ni, W.; Zhang, H.; Wu, J.; Yan, W.; Su, Y.

    2017-09-01

    Superpixel segmentation has an advantage that can well preserve the target shape and details. In this research, an adaptive polarimetric SLIC (Pol-ASLIC) superpixel segmentation method is proposed. First, the spherically invariant random vector (SIRV) product model is adopted to estimate the normalized covariance matrix and texture for each pixel. A new edge detector is then utilized to extract PolSAR image edges for the initialization of central seeds. In the local iterative clustering, multiple cues including polarimetric, texture, and spatial information are considered to define the similarity measure. Moreover, a polarimetric homogeneity measurement is used to automatically determine the tradeoff factor, which can vary from homogeneous areas to heterogeneous areas. Finally, the SLIC superpixel segmentation scheme is applied to the airborne Experimental SAR and PiSAR L-band PolSAR data to demonstrate the effectiveness of this proposed segmentation approach. This proposed algorithm produces compact superpixels which can well adhere to image boundaries in both natural and urban areas. The detail information in heterogeneous areas can be well preserved.

  10. SUPERPIXEL SEGMENTATION FOR POLSAR IMAGES WITH LOCAL ITERATIVE CLUSTERING AND HETEROGENEOUS STATISTICAL MODEL

    Directory of Open Access Journals (Sweden)

    D. Xiang

    2017-09-01

    Full Text Available Superpixel segmentation has an advantage that can well preserve the target shape and details. In this research, an adaptive polarimetric SLIC (Pol-ASLIC superpixel segmentation method is proposed. First, the spherically invariant random vector (SIRV product model is adopted to estimate the normalized covariance matrix and texture for each pixel. A new edge detector is then utilized to extract PolSAR image edges for the initialization of central seeds. In the local iterative clustering, multiple cues including polarimetric, texture, and spatial information are considered to define the similarity measure. Moreover, a polarimetric homogeneity measurement is used to automatically determine the tradeoff factor, which can vary from homogeneous areas to heterogeneous areas. Finally, the SLIC superpixel segmentation scheme is applied to the airborne Experimental SAR and PiSAR L-band PolSAR data to demonstrate the effectiveness of this proposed segmentation approach. This proposed algorithm produces compact superpixels which can well adhere to image boundaries in both natural and urban areas. The detail information in heterogeneous areas can be well preserved.

  11. Integrated Data Processing Methodology for Airborne Repeat-pass Differential SAR Interferometry

    Science.gov (United States)

    Dou, C.; Guo, H.; Han, C.; Yue, X.; Zhao, Y.

    2014-11-01

    Short temporal baseline and multiple ground deformation information can be derived from the airborne differential synthetic aperture radar Interforemetry (D-InSAR). However, affected by the turbulence of the air, the aircraft would deviate from the designed flight path with high frequent vibrations and changes both in the flight trajectory and attitude. Restricted by the accuracy of the position and orientation system (POS), these high frequent deviations can not be accurately reported, which would pose great challenges in motion compensation and interferometric process. Thus, these challenges constrain its wider applications. The objective of this paper is to investigate the accurate estimation and compensation of the residual motion errors in the airborne SAR imagery and time-varying baseline errors between the diffirent data acquirations, furthermore, to explore the integration data processing theory for the airborne D-InSAR system, and thus help to accomplish the correct derivation of the ground deformation by using the airborne D-InSAR measurements.

  12. Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods of m...

  13. Investigation on the separability of slums by multi-aspect TerraSAR-X dual-co-polarized high resolution spotlight images based on the multi-scale evaluation of local distributions

    Science.gov (United States)

    Schmitt, Andreas; Sieg, Tobias; Wurm, Michael; Taubenböck, Hannes

    2018-02-01

    Following recent advances in distinguishing settlements vs. non-settlement areas from latest SAR data, the question arises whether a further automatic intra-urban delineation and characterization of different structural types is possible. This paper studies the appearance of the structural type ;slums; in high resolution SAR images. Geocoded Kennaugh elements are used as backscatter information and Schmittlet indices as descriptor of local texture. Three cities with a significant share of slums (Cape Town, Manila, Mumbai) are chosen as test sites. These are imaged by TerraSAR-X in the dual-co-polarized high resolution spotlight mode in any available aspect angle. Representative distributions are estimated and fused by a robust approach. Our observations identify a high similarity of slums throughout all three test sites. The derived similarity maps are validated with reference data sets from visual interpretation and ground truth. The final validation strategy is based on completeness and correctness versus other classes in relation to the similarity. High accuracies (up to 87%) in identifying morphologic slums are reached for Cape Town. For Manila (up to 60%) and Mumbai (up to 54%), the distinction is more difficult due to their complex structural configuration. Concluding, high resolution SAR data can be suitable to automatically trace potential locations of slums. Polarimetric information and the incidence angle seem to have a negligible impact on the results whereas the intensity patterns and the passing direction of the satellite are playing a key role. Hence, the combination of intensity images (brightness) acquired from ascending and descending orbits together with Schmittlet indices (spatial pattern) promises best results. The transfer from the automatically recognized physical similarity to the semantic interpretation remains challenging.

  14. SAR-Based Wind Resource Statistics in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    Alfredo Peña

    2011-01-01

    Full Text Available Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

  15. Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery

    Science.gov (United States)

    Yang, L.; Jiang, L.; Lin, H.; Liao, M.

    2009-01-01

    In this study, we explored the potential to improve urban impervious surface modeling and mapping with the synergistic use of optical and Interferometric Synthetic Aperture Radar (InSAR) imagery. We used a Classification and Regression Tree (CART)-based approach to test the feasibility and accuracy of quantifying Impervious Surface Percentage (ISP) using four spectral bands of SPOT 5 high-resolution geometric (HRG) imagery and three parameters derived from the European Remote Sensing (ERS)-2 Single Look Complex (SLC) SAR image pair. Validated by an independent ISP reference dataset derived from the 33 cm-resolution digital aerial photographs, results show that the addition of InSAR data reduced the ISP modeling error rate from 15.5% to 12.9% and increased the correlation coefficient from 0.71 to 0.77. Spatially, the improvement is especially noted in areas of vacant land and bare ground, which were incorrectly mapped as urban impervious surfaces when using the optical remote sensing data. In addition, the accuracy of ISP prediction using InSAR images alone is only marginally less than that obtained by using SPOT imagery. The finding indicates the potential of using InSAR data for frequent monitoring of urban settings located in cloud-prone areas.

  16. Application of spaceborne SAR data to uranium metallogenetic environment, condition and prognosis

    International Nuclear Information System (INIS)

    Huang Xianfang; Huang Shutao; Dong Wenming; Pan Wei; Fang Maolong; Xuan Yanxiu

    2001-01-01

    JERS-1 SAR data processing and data fusion with TM, airborne radioactive and magnetic survey data have been elaborated and image effects have been described in the paper. By means of the analysis of the processed images, the stratigraphy, structures (including faults and folds) and ore-controlling factors in the study area have successfully been interpreted; the underground water mobile characteristics have been discussed; and the metallogenetic environment and condition have been summarized. Based on above research results, the prospecting criteria have been provided and favorable sections have been suggested. The practice has indicated that the application of spaceborne SAR data to uranium reconnaissance and exploration has potential prospects

  17. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  18. Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

    Directory of Open Access Journals (Sweden)

    K. Andrea Scott

    2015-09-01

    Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

  19. Multiple Segmentation of Image Stacks

    DEFF Research Database (Denmark)

    Smets, Jonathan; Jaeger, Manfred

    2014-01-01

    We propose a method for the simultaneous construction of multiple image segmentations by combining a recently proposed “convolution of mixtures of Gaussians” model with a multi-layer hidden Markov random field structure. The resulting method constructs for a single image several, alternative...

  20. COMBINATION OF GENETIC ALGORITHM AND DEMPSTER-SHAFER THEORY OF EVIDENCE FOR LAND COVER CLASSIFICATION USING INTEGRATION OF SAR AND OPTICAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    H. T. Chu

    2012-07-01

    Full Text Available The integration of different kinds of remotely sensed data, in particular Synthetic Aperture Radar (SAR and optical satellite imagery, is considered a promising approach for land cover classification because of the complimentary properties of each data source. However, the challenges are: how to fully exploit the capabilities of these multiple data sources, which combined datasets should be used and which data processing and classification techniques are most appropriate in order to achieve the best results. In this paper an approach, in which synergistic use of a feature selection (FS methods with Genetic Algorithm (GA and multiple classifiers combination based on Dempster-Shafer Theory of Evidence, is proposed and evaluated for classifying land cover features in New South Wales, Australia. Multi-date SAR data, including ALOS/PALSAR, ENVISAT/ASAR and optical (Landsat 5 TM+ images, were used for this study. Textural information were also derived and integrated with the original images. Various combined datasets were generated for classification. Three classifiers, namely Artificial Neural Network (ANN, Support Vector Machines (SVMs and Self-Organizing Map (SOM were employed. Firstly, feature selection using GA was applied for each classifier and dataset to determine the optimal input features and parameters. Then the results of three classifiers on particular datasets were combined using the Dempster-Shafer theory of Evidence. Results of this study demonstrate the advantages of the proposed method for land cover mapping using complex datasets. It is revealed that the use of GA in conjunction with the Dempster-Shafer Theory of Evidence can significantly improve the classification accuracy. Furthermore, integration of SAR and optical data often outperform single-type datasets.

  1. Helmand river hydrologic studies using ALOS PALSAR InSAR and ENVISAT altimetry

    Science.gov (United States)

    Lu, Zhong; Kim, J.-W.; Lee, H.; Shum, C.K.; Duan, J.; Ibaraki, M.; Akyilmaz, O.; Read, C.-H.

    2009-01-01

    The Helmand River wetland represents the only fresh-water resource in southern Afghanistan and one of the least mapped water basins in the world. The relatively narrow wetland consists of mostly marshes surrounded by dry lands. In this study, we demonstrate the use of the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Interferometric SAR (InSAR) to detect the changes of the Helmand River wetland water level. InSAR images are combined with the geocentric water level measurements from the retracked high-rate (18-Hz) Environmental Satellite (Envisat) radar altimetry to construct absolute water level changes over the marshes. It is demonstrated that the integration of the altimeter and InSAR can provide spatio-temporal measurements of water level variation over the Helmand River marshes where in situ measurements are absent. ?? Taylor & Francis Group, LLC.

  2. Keynote presentation : SAR systems

    NARCIS (Netherlands)

    Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

    2011-01-01

    Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

  3. Bioinformatics analysis of SARS coronavirus genome polymorphism

    Directory of Open Access Journals (Sweden)

    Pavlović-Lažetić Gordana M

    2004-05-01

    Full Text Available Abstract Background We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP, insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs. Results The nucleotide structure of all 38 isolates is presented. Based on insertions and deletions and dissimilarity due to SNPs, the dataset of all the isolates has been qualitatively classified into three groups each having their own subgroups. These are the A-group with "regular" isolates (no insertions / deletions except for 5' and 3' ends, the B-group of isolates with "long insertions", and the C-group of isolates with "many individual" insertions and deletions. The isolate with the smallest average number of SNPs, compared to other isolates, has been identified (TWH. The density distribution of SNPs, insertions and deletions for each group or subgroup, as well as cumulatively for all the isolates is also presented, along with the gene map for TWH. Since individual SNPs may have occurred at random, positions corresponding to multiple SNPs (occurring in two or more isolates are identified and presented. This result revises some previous results of a similar type. Amino acid changes caused by multiple SNPs are also identified (for the annotated sequences, as well as presupposed amino acid changes for non-annotated ones. Exact SNP positions for the isolates in each group or subgroup are presented. Finally, a phylogenetic tree for the SARS-CoV isolates has been produced using the CLUSTALW program, showing high compatibility with former qualitative classification. Conclusions The comparative study of SARS-CoV isolates provides essential information for genome

  4. Stellwagen Bank National Marine Sanctuary - Synthetic Aperture Radar (SAR) Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geodatabase contains Synthetic Aperture Radar images (SAR), which consist of a fine resolution (12.5-50m), two-dimensional radar backscatter map of the...

  5. Operational SAR-based sea ice drift monitoring over the Baltic Sea

    Directory of Open Access Journals (Sweden)

    J. Karvonen

    2012-07-01

    Full Text Available An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

  6. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Science.gov (United States)

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  7. An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Weizeng Shao

    2017-07-01

    Full Text Available In this study, we proposed an empirical algorithm for significant wave height (SWH retrieval from TerraSAR-X/TanDEM (TS-X/TD-X X-band synthetic aperture radar (SAR co-polarization (vertical-vertical (VV and horizontal-horizontal (HH images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF reanalysis field at a 0.125° grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA National Data Buoy Center (NDBC buoys. It is found that the algorithm performs well with a SWH stander deviation (STD of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6–7 m, we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information.

  8. Flood Extent Mapping for Namibia Using Change Detection and Thresholding with SAR

    Science.gov (United States)

    Long, Stephanie; Fatoyinbo, Temilola E.; Policelli, Frederick

    2014-01-01

    A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km2, 720 km2, and 673 km2 respectively. Pixels determined to be flooded in vegetation were typically flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes.

  9. Despeckling Polsar Images Based on Relative Total Variation Model

    Science.gov (United States)

    Jiang, C.; He, X. F.; Yang, L. J.; Jiang, J.; Wang, D. Y.; Yuan, Y.

    2018-04-01

    Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

  10. Understanding the Future Market for NovaSAR-S Flood Mapping Products Using Data Mining and Simulation

    Science.gov (United States)

    Lavender, Samantha; Haria, Kajal; Cooksley, Geraint; Farman, Alex; Beaton, Thomas

    2016-08-01

    The aim was to understand a future market for NovaSAR-S, with a particular focus on flood mapping, through developing a simple Synthetic Aperture Radar (SAR) simulator that can be used in advance of NovaSAR-S data becoming available.The return signal was determined from a combination of a terrain or elevation model, Envisat S-Band Radar Altimeter (RA)-2, Landsat and CORINE land cover information; allowing for a simulation of a SAR image that's influenced by both the geometry and surface type. The test sites correspond to data from the 2014 AirSAR campaign, and validation is performed by using AirSAR together with Envisat Advanced (ASAR) and Advanced Land Observing Satellite "Daichi" (ALOS) Phased Array type L-Band Synthetic Aperture Radar (PALSAR) data.It's envisaged that the resulting simulated data, and the simulator, will not only aid early understanding of NovaSAR-S, but will also aid the development of flood mapping applications.

  11. Chandrayaan-2 dual-frequency SAR: Further investigation into lunar water and regolith

    Science.gov (United States)

    Putrevu, Deepak; Das, Anup; Vachhani, J. G.; Trivedi, Sanjay; Misra, Tapan

    2016-01-01

    The Space Applications Centre (SAC), one of the major centers of the Indian Space Research Organization (ISRO), is developing a high resolution, dual-frequency Synthetic Aperture Radar as a science payload on Chandrayaan-2, ISRO's second moon mission. With this instrument, ISRO aims to further the ongoing studies of the data from S-band MiniSAR onboard Chandrayaan-1 (India) and the MiniRF of Lunar Reconnaissance Orbiter (USA). The SAR instrument has been configured to operate with both L- and S-bands, sharing a common antenna. The S-band SAR will provide continuity to the MiniSAR data, whereas L-band is expected to provide deeper penetration of the lunar regolith. The system will have a selectable slant-range resolution from 2 m to 75 m, along with standalone (L or S) and simultaneous (L and S) modes of imaging. Various features of the instrument like hybrid and full-polarimetry, a wide range of imaging incidence angles (∼10° to ∼35°) and the high spatial resolution will greatly enhance our understanding of surface properties especially in the polar regions of the Moon. The system will also help in resolving some of the ambiguities in interpreting high values of Circular Polarization Ratio (CPR) observed in MiniSAR data. The added information from full-polarimetric data will allow greater confidence in the results derived particularly in detecting the presence (and estimating the quantity) of water-ice in the polar craters. Being a planetary mission, the L&S-band SAR for Chandrayaan-2 faced stringent limits on mass, power and data rate (15 kg, 100 W and 160 Mbps respectively), irrespective of any of the planned modes of operation. This necessitated large-scale miniaturization, extensive use of on-board processing, and devices and techniques to conserve power. This paper discusses the scientific objectives which drive the requirement of a lunar SAR mission and presents the configuration of the instrument, along with a description of a number of features of the

  12. The Seamless SAR Archive (SSARA) Project and Other SAR Activities at UNAVCO

    Science.gov (United States)

    Baker, S.; Crosby, C. J.; Meertens, C. M.; Fielding, E. J.; Bryson, G.; Buechler, B.; Nicoll, J.; Baru, C.

    2014-12-01

    The seamless synthetic aperture radar archive (SSARA) implements a seamless distributed access system for SAR data and derived data products (i.e. interferograms). SSARA provides a unified application programming interface (API) for SAR data search and results at the Alaska Satellite Facility and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives. Interest from the international community has prompted an effort to incorporate ESA's Virtual Archive 4 Geohazard Supersites and Natural Laboratories (GSNL) collections and other archives into the federated query service. SSARA also provides Digital Elevation Model access for topographic correction via a simple web service through OpenTopography and tropospheric correction products through JPL's OSCAR service. Additionally, UNAVCO provides data storage capabilities for WInSAR PIs with approved TerraSAR-X and ALOS-2 proposals which allows easier distribution to US collaborators on associated proposals and facilitates data access through the SSARA web services. Further work is underway to incorporate federated data discovery for GSNL across SAR, GPS, and seismic datasets provided by web services from SSARA, GSAC, and COOPEUS.

  13. Receptor binding radiotracers for the angiotensin II receptor: radioiodinated [Sar1, Ile8]angiotensin II

    International Nuclear Information System (INIS)

    Gibson, R.E.; Beauchamp, H.T.; Fioravanti, C.; Brenner, N.; Burns, H.D.

    1994-01-01

    The potential for imaging the angiotensin II receptor was evaluated using the radioiodinated peptide antagonist [ 125 I][Sar 1 , Ile 8 ]angiotensin II. The radioligand provides a receptor-mediated signal in several tissues in rat (kidneys, adrenal and liver). The receptor-mediated signal of 3% ID/g kidney cortex should be sufficient to permit imaging, at least via SPECT. The radiotracer is sensitive to reductions in receptor concentration and can be used to define in vivo dose-occupancy curves of angiotensin II receptor ligands. Receptor-mediated images of [ 123 I][Sar 1 , Ile 8 ]angiotensin II were obtained in the rat kidney and Rhesus monkey liver. (author)

  14. Benefits and limitations of imaging multiples: Mirror migration

    KAUST Repository

    Hanafy, Sherif M.; Huang, Yunsong; Schuster, Gerard T.

    2015-01-01

    The benefits and limitations of imaging multiples are reviewed for mirror migration. Synthetic and field data examples are used to characterize the effectiveness of migrating multiples relative to primary imaging.

  15. Benefits and limitations of imaging multiples: Mirror migration

    KAUST Repository

    Hanafy, Sherif M.

    2015-07-01

    The benefits and limitations of imaging multiples are reviewed for mirror migration. Synthetic and field data examples are used to characterize the effectiveness of migrating multiples relative to primary imaging.

  16. Structured diagnostic imaging in patients with multiple trauma

    International Nuclear Information System (INIS)

    Linsenmaier, U.; Rieger, J.; Rock, C.; Pfeifer, K.J.; Reiser, M.; Kanz, K.G.

    2002-01-01

    Purpose. Development of a concept for structured diagnostic imaging in patients with multiple trauma.Material and methods. Evaluation of data from a prospective trial with over 2400 documented patients with multiple trauma. All diagnostic and therapeutic steps, primary and secondary death and the 90 days lethality were documented.Structured diagnostic imaging of multiple injured patients requires the integration of an experienced radiologist in an interdisciplinary trauma team consisting of anesthesia, radiology and trauma surgery. Radiology itself deserves standardized concepts for equipment, personnel and logistics to perform diagnostic imaging for a 24-h-coverage with constant quality.Results. This paper describes criteria for initiation of a shock room or emergency room treatment, strategies for documentation and interdisciplinary algorithms for the early clinical care coordinating diagnostic imaging and therapeutic procedures following standardized guidelines. Diagnostic imaging consists of basic diagnosis, radiological ABC-rule, radiological follow-up and structured organ diagnosis using CT. Radiological trauma scoring allows improved quality control of diagnosis and therapy of multiple injured patients.Conclusion. Structured diagnostic imaging of multiple injured patients leads to a standardization of diagnosis and therapy and ensures constant process quality. (orig.) [de

  17. Coupling SAR X-band and optical data for NDVI retrieval: model calibration and validation on two test areas

    Science.gov (United States)

    Capodici, Fulvio; D'Urso, Guido; Maltese, Antonino; Ciraolo, Giuseppe

    2013-10-01

    Sustainability of modern agro-hydrology requires the knowledge of spatial and temporal variability of vegetation biomass to optimize management of land and water resources. Diversely from optical imaging, temporal resolution of active sensors, such as SAR, is not limited by sky cloudiness; thus, they may be combined with optical imageries to provide a more continuous monitoring of land surfaces. Several new SAR missions (e.g., ALOS-PALSAR, COSMO-SkyMed 1 and 2, TerraSAR-X, TerraSAR-X2, Sentinel 1) acquiring at X-, C- and L-bands and dual polarization capability, are characterized by a short revisit time (from 12 h to ~10 days) and high spatial resolution (COSMOSkyMed images and 2 Landsat 7 SLC-off images were acquired in the southwestern part of Sicily (Italy) between 8 and 25 August 2011. Determination coefficients of the validation set were similar to those of the calibration set. Results confirm that VISAR obtained using the combined model is a suitable surrogate of VIopt if estimated at parcel scale.

  18. Secure image retrieval with multiple keys

    Science.gov (United States)

    Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

    2018-03-01

    This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

  19. Severe acute respiratory syndrome (SARS)

    Science.gov (United States)

    SARS; Respiratory failure - SARS ... Complications may include: Respiratory failure Liver failure Heart failure ... 366. McIntosh K, Perlman S. Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). ...

  20. SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

    OpenAIRE

    Zhang, Fan; Hu, Chen; Yin, Qiang; Li, Wei; Li, Hengchao; Hong, Wen

    2017-01-01

    The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a limitation in current deep learning based ATR solution that each learning process only handle one SAR image, namely learning the static scattering information, while missing the space-varying information. It is obvious that multi-aspect joint recognition introduced space-varying scattering information should improve ...

  1. Mapping tectonic and anthropogenic processes in central California using satellite and airborne InSAR

    Science.gov (United States)

    Liu, Z.; Lundgren, P.; Liang, C.; Farr, T. G.; Fielding, E. J.

    2017-12-01

    The improved spatiotemporal resolution of surface deformation from recent satellite and airborne InSAR measurements provides a great opportunity to improve our understanding of both tectonic and non-tectonic processes. In central California the primary plate boundary fault system (San Andreas fault) lies adjacent to the San Joaquin Valley (SJV), a vast structural trough that accounts for about one-sixth of the United Sates' irrigated land and one-fifth of its extracted groundwater. The central San Andreas fault (CSAF) displays a range of fault slip behavior with creeping in its central segment that decreases towards its northwest and southeast ends, where it transitions to being fully locked. Despite much progress, many questions regarding fault and anthropogenic processes in the region still remain. In this study, we combine satellite InSAR and NASA airborne UAVSAR data to image fault and anthropogenic deformation. The UAVSAR data cover fault perpendicular swaths imaged from opposing look directions and fault parallel swaths since 2009. The much finer spatial resolution and optimized viewing geometry provide important constraints on near fault deformation and fault slip at very shallow depth. We performed a synoptic InSAR time series analysis using Sentinel-1, ALOS, and UAVSAR interferograms. We estimate azimuth mis-registration between single look complex (SLC) images of Sentinel-1 in a stack sense to achieve accurate azimuth co-registration between SLC images for low coherence and/or long interval interferometric pairs. We show that it is important to correct large-scale ionosphere features in ALOS-2 ScanSAR data for accurate deformation measurements. Joint analysis of UAVSAR and ALOS interferometry measurements show clear variability in deformation along the fault strike, suggesting variable fault creep and locking at depth and along strike. In addition to fault creep, the L-band ALOS, and especially ALOS-2 ScanSAR interferometry, show large-scale ground

  2. Change Detection with Polarimetric SAR Imagery for Nuclear Verification

    International Nuclear Information System (INIS)

    Canty, M.

    2015-01-01

    This paper investigates the application of multivariate statistical change detection with high-resolution polarimetric SAR imagery acquired from commercial satellite platforms for observation and verification of nuclear activities. A prototype software tool comprising a processing chain starting from single look complex (SLC) multitemporal data through to change detection maps is presented. Multivariate change detection algorithms applied to polarimetric SAR data are not common. This is because, up until recently, not many researchers or practitioners have had access to polarimetric data. However with the advent of several spaceborne polarimetric SAR instruments such as the Japanese ALOS, the Canadian Radarsat-2, the German TerraSAR-X, the Italian COSMO-SkyMed missions and the European Sentinal SAR platform, the situation has greatly improved. There is now a rich source of weather-independent satellite radar data which can be exploited for Nuclear Safeguards purposes. The method will also work for univariate data, that is, it is also applicable to scalar or single polarimetric SAR data. The change detection procedure investigated here exploits the complex Wishart distribution of dual and quad polarimetric imagery in look-averaged covariance matrix format in order to define a per-pixel change/no-change hypothesis test. It includes approximations for the probability distribution of the test statistic, and so permits quantitative significance levels to be quoted for change pixels. The method has been demonstrated previously with polarimetric images from the airborne EMISAR sensor, but is applied here for the first time to satellite platforms. In addition, an improved multivariate method is used to estimate the so-called equivalent number of looks (ENL), which is a critical parameter of the hypothesis test. (author)

  3. A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    A. Castillo Atoche

    2013-01-01

    Full Text Available A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU, achieving considerable speedups compared to the serial version of the same techniques implemented in C language.

  4. Design and characterization of a 12-bit 10MS/s 10mW pipelined SAR ADC for CZT-based hard X-ray imager

    Science.gov (United States)

    Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.

    2018-02-01

    This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.

  5. Covariance estimation for dInSAR surface deformation measurements in the presence of anisotropic atmospheric noise

    KAUST Repository

    Knospe, Steffen H G

    2010-04-01

    We study anisotropic spatial autocorrelation in differential synthetic aperture radar interferometric (dInSAR) measurements and its impact on geophysical parameter estimations. The dInSAR phase acquired by the satellite sensor is a superposition of different contributions, and when studying geophysical processes, we are usually only interested in the surface deformation part of the signal. Therefore, to obtain high-quality results, we would like to characterize and/or remove other phase components. A stochastic model has been found to be appropriate to describe atmospheric phase delay in dInSAR images. However, these phase delays are usually modeled as being isotropic, which is a simplification, because InSAR images often show directional atmospheric anomalies. Here, we analyze anisotropic structures and show validation results using both real and simulated data. We calculate experimental semivariograms of the dInSAR phase in several European Remote Sensing satellite-1/2 tandem interferograms. Based on the theory of random functions (RFs), we then fit anisotropic variogram models in the spatial domain, employing Matérn-and Bessel-family correlation functions in nested models to represent complex dInSAR covariance structures. The presented covariance function types, in the statistical framework of stationary RFs, are consistent with tropospheric delay models. We find that by using anisotropic data covariance information to weight dInSAR measurements, we can significantly improve both the precision and accuracy of geophysical parameter estimations. Furthermore, the improvement is dependent on how similar the deformation pattern is to the dominant structure of the anisotropic atmospheric signals. © 2009 IEEE.

  6. A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

    Science.gov (United States)

    Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

    2013-04-01

    There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood

  7. Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

    Science.gov (United States)

    Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

    2017-12-01

    Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

  8. Local region power spectrum-based unfocused ship detection method in synthetic aperture radar images

    Science.gov (United States)

    Wei, Xiangfei; Wang, Xiaoqing; Chong, Jinsong

    2018-01-01

    Ships on synthetic aperture radar (SAR) images will be severely defocused and their energy will disperse into numerous resolution cells under long SAR integration time. Therefore, the image intensity of ships is weak and sometimes even overwhelmed by sea clutter on SAR image. Consequently, it is hard to detect the ships from SAR intensity images. A ship detection method based on local region power spectrum of SAR complex image is proposed. Although the energies of the ships are dispersed on SAR intensity images, their spectral energies are rather concentrated or will cause the power spectra of local areas of SAR images to deviate from that of sea surface background. Therefore, the key idea of the proposed method is to detect ships via the power spectra distortion of local areas of SAR images. The local region power spectrum of a moving target on SAR image is analyzed and the way to obtain the detection threshold through the probability density function (pdf) of the power spectrum is illustrated. Numerical P- and L-band airborne SAR ocean data are utilized and the detection results are also illustrated. Results show that the proposed method can well detect the unfocused ships, with a detection rate of 93.6% and a false-alarm rate of 8.6%. Moreover, by comparing with some other algorithms, it indicates that the proposed method performs better under long SAR integration time. Finally, the applicability of the proposed method and the way of parameters selection are also discussed.

  9. Shortcomings of InSAR for studying megathrust earthquakes: The case of the M w 9.0 Tohoku-Oki earthquake

    KAUST Repository

    Feng, Guangcai; Jonsson, Sigurjon

    2012-01-01

    .0) and test InSAR-derived fault-slip models against models constrained by GPS data from the extensive nationwide network in Japan. The coseismic deformation field was mapped using InSAR data acquired from multiple ascending and descending passes of the ALOS

  10. The linearized inversion of the generalized interferometric multiple imaging

    KAUST Repository

    Aldawood, Ali

    2016-09-06

    The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.

  11. A Multi-Polarization Study on Ship Detection over X-Band Full-Resolution COSMO SkyMed SAR Data

    Science.gov (United States)

    Migliaccio, Maurizio; Nunziata, Ferdinando; Sorrentio, Antonio; Ferrara, Giuseppe

    2011-03-01

    Ship detection over marine Synthetic Aperture Radar (SAR) images is a key application for global monitoring for environment and security. In this paper, a physically-based filter which exploits a proper combination of GK parameters is conceived to unambiguously observe ships over sea surface in HV-polarized Single Look Complex (SLC) SAR data. Experiments accomplished over a meaningful set of X-band SLC CosmoSkyMed StripMap SAR data confirm the physical soundness of the proposed approach.

  12. VenSAR on EnVision: Taking earth observation radar to Venus

    Science.gov (United States)

    Ghail, Richard C.; Hall, David; Mason, Philippa J.; Herrick, Robert R.; Carter, Lynn M.; Williams, Ed

    2018-02-01

    Venus should be the most Earth-like of all our planetary neighbours: its size, bulk composition and distance from the Sun are very similar to those of Earth. How and why did it all go wrong for Venus? What lessons can be learned about the life story of terrestrial planets in general, in this era of discovery of Earth-like exoplanets? Were the radically different evolutionary paths of Earth and Venus driven solely by distance from the Sun, or do internal dynamics, geological activity, volcanic outgassing and weathering also play an important part? EnVision is a proposed ESA Medium class mission designed to take Earth Observation technology to Venus to measure its current rate of geological activity, determine its geological history, and the origin and maintenance of its hostile atmosphere, to understand how Venus and Earth could have evolved so differently. EnVision will carry three instruments: the Venus Emission Mapper (VEM); the Subsurface Radar Sounder (SRS); and VenSAR, a world-leading European phased array synthetic aperture radar that is the subject of this article. VenSAR will obtain images at a range of spatial resolutions from 30 m regional coverage to 1 m images of selected areas; an improvement of two orders of magnitude on Magellan images; measure topography at 15 m resolution vertical and 60 m spatially from stereo and InSAR data; detect cm-scale change through differential InSAR, to characterise volcanic and tectonic activity, and estimate rates of weathering and surface alteration; and characterise of surface mechanical properties and weathering through multi-polar radar data. These data will be directly comparable with Earth Observation radar data, giving geoscientists unique access to an Earth-sized planet that has evolved on a radically different path to our own, offering new insights on the Earth-sized exoplanets across the galaxy.

  13. Effects of Target Positioning Error on Motion Compensation for Airborne Interferometric SAR

    Directory of Open Access Journals (Sweden)

    Li Yin-wei

    2013-12-01

    Full Text Available The measurement inaccuracies of Inertial Measurement Unit/Global Positioning System (IMU/GPS as well as the positioning error of the target may contribute to the residual uncompensated motion errors in the MOtion COmpensation (MOCO approach based on the measurement of IMU/GPS. Aiming at the effects of target positioning error on MOCO for airborne interferometric SAR, the paper firstly deduces a mathematical model of residual motion error bring out by target positioning error under the condition of squint. And the paper analyzes the effects on the residual motion error caused by system sampling delay error, the Doppler center frequency error and reference DEM error which result in target positioning error based on the model. Then, the paper discusses the effects of the reference DEM error on the interferometric SAR image quality, the interferometric phase and the coherent coefficient. The research provides theoretical bases for the MOCO precision in signal processing of airborne high precision SAR and airborne repeat-pass interferometric SAR.

  14. GROUND SUBSIDENCE ALONG SHANGHAI METRO LINE 6 BY PS-InSAR METHOD

    Directory of Open Access Journals (Sweden)

    J. Wu

    2018-04-01

    Full Text Available With the rapid development of urban economy, convenient, safe, and efficient urban rail transit has become the preferred method for people to travel. In order to ensure the safety and sustainable development of urban rail transit, the PS-InSAR technology with millimeter deformation measurement accuracy has been widely applied to monitor the deformation of urban rail transit. In this paper, 32 scenes of COSMO-SkyMed descending images and 23 scenes of Envisat ASAR images covering the Shanghai Metro Line 6 acquired from 2008 to 2010 are used to estimate the average deformation rate along line-of-sight (LOS direction by PS-InSAR method. The experimental results show that there are two main subsidence areas along the Shanghai Metro Line 6, which are located between Wuzhou Avenue Station to Wulian Road Station and West Gaoke Road Station to Gaoqing Road Station. Between Wuzhou Avenue Station and Wulian Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is −9.92 mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is −8.53 mm/year. From the West Gaoke Road Station to the Gaoqing Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is −15.53 mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is −17.9 mm/year. The results show that the ground deformation rates obtained by two SAR platforms with different wavelengths, different sensors and different incident angles have good consistence with each other, and also that of spirit leveling.

  15. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

    Science.gov (United States)

    Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

    2017-11-07

    This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  16. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

    Directory of Open Access Journals (Sweden)

    Tianzhu Yi

    2017-11-01

    Full Text Available This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR data processing. Several nonlinear chirp scaling (NLCS algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC. However, the azimuth depth of focusing (ADOF is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS algorithm that is proposed in this paper uses the method of series reverse (MSR to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  17. On the interpretation of SAR imagery from the Sea Empress oil spill

    International Nuclear Information System (INIS)

    Jones, B.; Mitchelson-Jacob, E.G.

    1998-01-01

    A method for monitoring oil spills using SAR imagery is suggested, based on the simulation of the wave spectrum using modelled surface winds. A first order separation of the purely wind-driven backscatter distribution and its modifications due to surfactant was made by parametrizing the effect of surfactant on the wave growth rate and on the reflective properties of the sea surface. The technique was applied to an SAR image showing the Sea Empress oil spill, in south-west Wales, UK. (author)

  18. Oil seepage polarimetric contrast analysis in a time series of TerraSAR-X images

    OpenAIRE

    de Macedo, Carina Regina; Nunziata, Ferdinando; Velotto, Domenico; Migliaccio, Maurizio

    2017-01-01

    Natural hydrocarbon seeps are broadly distributed across the Gulf of Mexico. Such seeps emit oil and gas into the water column, increasing the phytoplankton biomass and impacting regionally the productivity, carbon and nutrient cycling [1]. A fraction of this oil reaches to the sea surface and can be detected by SAR data. Although the ability of SAR data to detect oil features present in ocean's surface is wide exploited in the literature, it is known that the detection of those features is a...

  19. Observations and Mitigation of RFI in ALOS PALSAR SAR Data; Implications for the Desdyni Mission

    Science.gov (United States)

    Rosen, Paul A.; Hensley, Scott; Le, Charles

    2008-01-01

    Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystems, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems as well. Therefore the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands is of considerable interest. RFI is observed in ALOS PALSAR in California, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straightforward spectral normalization to time-domain, multi-phase filtering techniques are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

  20. Report on workshop "Study of the Antarctic ice sheet and glacier using ERS-1/JERS-1 SAR data"

    Directory of Open Access Journals (Sweden)

    Naohiko Hirasawa

    1996-07-01

    Full Text Available The main purpose of the workshop is to discuss recent results of Antarctic research using SAR data. It was held on February 6,1996 at the National Institute of Polar Research (NIPR, the number of participants being about 30. The contents of the workshop are demonstration of various SAR images, comparison with pictures from an airplane and visible images, comparison with observational data on ice conditions and demonstration of problems in interferometry.

  1. Tracking lava flow emplacement on the east rift zone of Kilauea, Hawai’i with synthetic aperture radar (SAR) coherence

    Science.gov (United States)

    Dietterich, Hannah R.; Poland, Michael P.; Schmidt, David; Cashman, Katharine V.; Sherrod, David R.; Espinosa, Arkin Tapia

    2012-01-01

    Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu‘u ‘Ō‘ō-Kupaianaha eruption at Kīlauea, Hawai‘i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post-emplacement flow subsidence.

  2. Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

    Directory of Open Access Journals (Sweden)

    Manabu Watanabe

    2010-01-01

    Full Text Available We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR σ∘ under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the σ∘ difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that σ∘ and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

  3. Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

    Directory of Open Access Journals (Sweden)

    Shimada Masanobu

    2010-01-01

    Full Text Available Abstract We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

  4. Speckle Filtering of GF-3 Polarimetric SAR Data with Joint Restriction Principle.

    Science.gov (United States)

    Xie, Jinwei; Li, Zhenfang; Zhou, Chaowei; Fang, Yuyuan; Zhang, Qingjun

    2018-05-12

    Polarimetric SAR (PolSAR) scattering characteristics of imagery are always obtained from the second order moments estimation of multi-polarization data, that is, the estimation of covariance or coherency matrices. Due to the extra-paths that signal reflected from separate scatterers within the resolution cell has to travel, speckle noise always exists in SAR images and has a severe impact on the scattering performance, especially on single look complex images. In order to achieve high accuracy in estimating covariance or coherency matrices, three aspects are taken into consideration: (1) the edges and texture of the scene are distinct after speckle filtering; (2) the statistical characteristic should be similar to the object pixel; and (3) the polarimetric scattering signature should be preserved, in addition to speckle reduction. In this paper, a joint restriction principle is proposed to meet the requirement. Three different restriction principles are introduced to the processing of speckle filtering. First, a new template, which is more suitable for the point or line targets, is designed to ensure the morphological consistency. Then, the extent sigma filter is used to restrict the pixels in the template aforementioned to have an identical statistic characteristic. At last, a polarimetric similarity factor is applied to the same pixels above, to guarantee the similar polarimetric features amongst the optional pixels. This processing procedure is named as speckle filtering with joint restriction principle and the approach is applied to GF-3 polarimetric SAR data acquired in San Francisco, CA, USA. Its effectiveness of keeping the image sharpness and preserving the scattering mechanism as well as speckle reduction is validated by the comparison with boxcar filters and refined Lee filter.

  5. MM wave SAR sensor design: Concept for an airborne low level reconnaissance system

    Science.gov (United States)

    Boesswetter, C.

    1986-07-01

    The basic system design considerations for a high resolution SAR system operating at 35 GHz or 94 GHz are given. First it is shown that only the focussed SAR concept in the side looking configuration matches the requirements and constraints. After definition of illumination geometry and airborne modes the fundamental SAR parameters in range and azimuth direction are derived. A review of the performance parameters of some critical mm wave components (coherent pulsed transmitters, front ends, antennas) establish the basis for further analysis. The power and contrast budget in the processed SAR image shows the feasibility of a 35/94 GHz SAR sensor design. The discussion of the resulting system parameters points out that this unusual system design implies both benefits and new risk areas. One of the benefits besides the compactness of sensor hardware turns out to be the short synthetic aperture length simplifying the design of the digital SAR processor, preferably operating in real time. A possible architecture based on current state-of-the-art correlator hardware is shown. One of the potential risk areas in achieving high resolution SAR imagery in the mm wave frequency band is motion compensation. However, it is shown that the short range and short synthetic aperture lengths ease the problem so that correction of motion induced phase errors and thus focussed synthetic aperture processing should be possible.

  6. Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

    Directory of Open Access Journals (Sweden)

    Fan Yang

    2015-07-01

    Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

  7. SAR Imagery Simulation of Ship Based on Electromagnetic Calculations and Sea Clutter Modelling for Classification Applications

    International Nuclear Information System (INIS)

    Ji, K F; Zhao, Z; Xing, X W; Zou, H X; Zhou, S L

    2014-01-01

    Ship detection and classification with space-borne SAR has many potential applications within the maritime surveillance, fishery activity management, monitoring ship traffic, and military security. While ship detection techniques with SAR imagery are well established, ship classification is still an open issue. One of the main reasons may be ascribed to the difficulties on acquiring the required quantities of real data of vessels under different observation and environmental conditions with precise ground truth. Therefore, simulation of SAR images with high scenario flexibility and reasonable computation costs is compulsory for ship classification algorithms development. However, the simulation of SAR imagery of ship over sea surface is challenging. Though great efforts have been devoted to tackle this difficult problem, it is far from being conquered. This paper proposes a novel scheme for SAR imagery simulation of ship over sea surface. The simulation is implemented based on high frequency electromagnetic calculations methods of PO, MEC, PTD and GO. SAR imagery of sea clutter is modelled by the representative K-distribution clutter model. Then, the simulated SAR imagery of ship can be produced by inserting the simulated SAR imagery chips of ship into the SAR imagery of sea clutter. The proposed scheme has been validated with canonical and complex ship targets over a typical sea scene

  8. ARBRES: Light-Weight CW/FM SAR Sensors for Small UAVs

    Directory of Open Access Journals (Sweden)

    Xavier Fabregas

    2013-03-01

    Full Text Available This paper describes a pair of compact CW/FM airborne SAR systems for small UAV-based operation (wingspan of 3.5 m for low-cost testing of innovative SAR concepts. Two different SAR instruments, using the C and X bands, have been developed in the context of the ARBRES project, each of them achieving a payload weight below 5 Kg and a volume of 13.5 dm3 (sensor and controller. Every system has a dual receiving channel which allows operation in interferometric or polarimetric modes. Planar printed array antennas are used in both sensors for easy system integration and better isolation between transmitter and receiver subsystems. First experimental tests on board a 3.2 m wingspan commercial radio-controlled aircraft are presented. The SAR images of a field close to an urban area have been focused using a back-projection algorithm. Using the dual channel capability, a single pass interferogram and Digital Elevation Model (DEM has been obtained which agrees with the scene topography. A simple Motion Compensation (MoCo module, based on the information from an Inertial+GPS unit, has been included to compensate platform motion errors with respect to the nominal straight trajectory.

  9. Satellite SAR data assessment for Silk Road archaeological prospection

    Science.gov (United States)

    Chen, Fulong; Lasaponara, Rosa; Masini, Nicola; Yang, Ruixia

    2015-04-01

    The development of Synthetic Aperture Radar (SAR) in terms of multi-band, multi-polarization and high-resolution data, favored the application of this technology also in archaeology [1]. Different approaches based on both single and multitemporal data analysis, exploiting the backscattering and the penetration of radar data, have been used for a number of archaeological sites and landscapes [2-5]. Nevertheless, the capability of this technology in archaeological applications has so far not been fully assessed. It lacks a contribution aimed at evaluating the potential of SAR technology for the same study area by using different bands, spatial resolutions and data processing solutions. In the framework of the Chinese-Italian bilateral project "Smart management of cultural heritage sites in Italy and China: Earth Observation and pilot projects", we addressed some pioneering investigations to assess multi-mode (multi-band, temporal, resolution) satellite SAR data (including X-band TerraSAR, C-band Envisat and L-band ALOS PALSAR) in archaeological prospection of the Silk road [6]. The Silk Road, a series of trade and cultural transmission routes connecting China to Europe, is the witness of civilization and friendship between the East and West dated back to 2000 years ago, that left us various relics (e.g. lost cities) to be uncovered and investigated.. In particular, the assessment has been performed in the Xinjiang and Gansu section pf the Silk Road focusing on : i) the subsurface penetration capability of SAR data in the arid and semi-arid region ii) and sensitivity of SAR imaging geometry for the detection of relics As regards the point i) , apart from the soil moisture, the penetration is seriously restricted by the soil porosity. For instance, negligible penetration signs were detected in Yumen Frontier Pass either using X- or L-band SAR data due to the occurrence of Yardang landscape. As regards the point ii), the flight path of SAR images in parallel with the

  10. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  11. Curvelet-based compressive sensing for InSAR raw data

    Science.gov (United States)

    Costa, Marcello G.; da Silva Pinho, Marcelo; Fernandes, David

    2015-10-01

    The aim of this work is to evaluate the compression performance of SAR raw data for interferometry applications collected by airborne from BRADAR (Brazilian SAR System operating in X and P bands) using the new approach based on compressive sensing (CS) to achieve an effective recovery with a good phase preserving. For this framework is desirable a real-time capability, where the collected data can be compressed to reduce onboard storage and bandwidth required for transmission. In the CS theory, a sparse unknown signals can be recovered from a small number of random or pseudo-random measurements by sparsity-promoting nonlinear recovery algorithms. Therefore, the original signal can be significantly reduced. To achieve the sparse representation of SAR signal, was done a curvelet transform. The curvelets constitute a directional frame, which allows an optimal sparse representation of objects with discontinuities along smooth curves as observed in raw data and provides an advanced denoising optimization. For the tests were made available a scene of 8192 x 2048 samples in range and azimuth in X-band with 2 m of resolution. The sparse representation was compressed using low dimension measurements matrices in each curvelet subband. Thus, an iterative CS reconstruction method based on IST (iterative soft/shrinkage threshold) was adjusted to recover the curvelets coefficients and then the original signal. To evaluate the compression performance were computed the compression ratio (CR), signal to noise ratio (SNR), and because the interferometry applications require more reconstruction accuracy the phase parameters like the standard deviation of the phase (PSD) and the mean phase error (MPE) were also computed. Moreover, in the image domain, a single-look complex image was generated to evaluate the compression effects. All results were computed in terms of sparsity analysis to provides an efficient compression and quality recovering appropriated for inSAR applications

  12. Seismic reflection imaging, accounting for primary and multiple reflections

    Science.gov (United States)

    Wapenaar, Kees; van der Neut, Joost; Thorbecke, Jan; Broggini, Filippo; Slob, Evert; Snieder, Roel

    2015-04-01

    Imaging of seismic reflection data is usually based on the assumption that the seismic response consists of primary reflections only. Multiple reflections, i.e. waves that have reflected more than once, are treated as primaries and are imaged at wrong positions. There are two classes of multiple reflections, which we will call surface-related multiples and internal multiples. Surface-related multiples are those multiples that contain at least one reflection at the earth's surface, whereas internal multiples consist of waves that have reflected only at subsurface interfaces. Surface-related multiples are the strongest, but also relatively easy to deal with because the reflecting boundary (the earth's surface) is known. Internal multiples constitute a much more difficult problem for seismic imaging, because the positions and properties of the reflecting interfaces are not known. We are developing reflection imaging methodology which deals with internal multiples. Starting with the Marchenko equation for 1D inverse scattering problems, we derived 3D Marchenko-type equations, which relate reflection data at the surface to Green's functions between virtual sources anywhere in the subsurface and receivers at the surface. Based on these equations, we derived an iterative scheme by which these Green's functions can be retrieved from the reflection data at the surface. This iterative scheme requires an estimate of the direct wave of the Green's functions in a background medium. Note that this is precisely the same information that is also required by standard reflection imaging schemes. However, unlike in standard imaging, our iterative Marchenko scheme retrieves the multiple reflections of the Green's functions from the reflection data at the surface. For this, no knowledge of the positions and properties of the reflecting interfaces is required. Once the full Green's functions are retrieved, reflection imaging can be carried out by which the primaries and multiples are

  13. The use of the DInSAR method in the monitoring of road damage caused by mining activities

    Science.gov (United States)

    Murdzek, Radosław; Malik, Hubert; Leśniak, Andrzej

    2018-04-01

    This paper reviews existing remote sensing methods of road damage detection and demonstrates the possibility of using DInSAR (Differential Interferometry SAR) method to identify endangered road sections. In this study two radar images collected by Sentinel-1 satellite have been used. Images were acquired with 24 days interval in 2015. The analysis allowed to estimate the scale of the post-mining deformation that occurred in Upper Silesia and to indicate areas where road infrastructure is particularly vulnerable to damage.

  14. A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation.

    Science.gov (United States)

    Wen, Xuejiao; Qiu, Xiaolan; Han, Bing; Ding, Chibiao; Lei, Bin; Chen, Qi

    2018-05-07

    Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

  15. 3D OBJECT COORDINATES EXTRACTION BY RADARGRAMMETRY AND MULTI STEP IMAGE MATCHING

    Directory of Open Access Journals (Sweden)

    A. Eftekhari

    2013-09-01

    Full Text Available Nowadays by high resolution SAR imaging systems as Radarsat-2, TerraSAR-X and COSMO-skyMed, three-dimensional terrain data extraction using SAR images is growing. InSAR and Radargrammetry are two most common approaches for removing 3D object coordinate from SAR images. Research has shown that extraction of terrain elevation data using satellite repeat pass interferometry SAR technique due to atmospheric factors and the lack of coherence between the images in areas with dense vegetation cover is a problematic. So the use of Radargrammetry technique can be effective. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-stage algorithm founded on the combination of feature based and area based image matching. Then the RPCs that calculate for each images use for extracting 3D coordinate in matched points. At the end, the coordinates calculating that compare with coordinates extracted from 1 meters DEM. The results show root mean square errors for 360 points are 3.09 meters. We use a pair of spotlight TerraSAR-X images from JAM (IRAN in this article.

  16. Exploring cloud and big data components for SAR archiving and analysis

    Science.gov (United States)

    Baker, S.; Crosby, C. J.; Meertens, C.; Phillips, D.

    2017-12-01

    Under the Geodesy Advancing Geoscience and EarthScope (GAGE) NSF Cooperative Agreement, UNAVCO has seen the volume of the SAR Data Archive grow at a substantial rate, from 2 TB in Y1 and 5 TB in Y2 to 41 TB in Y3 primarily due to WInSAR PI proposal management of ALOS-­2/JAXA (Japan Aerospace Exploration Agency) data and to a lesser extent Supersites and other data collections. JAXA provides a fixed number of scenes per year for each PI, and some data files are 50­-60GB each, which accounts for the large volume of data. In total, over 100TB of SAR data are in the WInSAR/UNAVCO archive and a large portion of these are available unrestricted for WInSAR members. In addition to the existing data, newer data streams from the Sentinel-1 and NISAR missions will require efficient processing pipelines and easily scalable infrastructure to handle processed results. With these growing data sizes and space concerns, the SAR archive operations migrated to the Texas Advanced Computing Center (TACC) via an NSF XSEDE proposal in spring 2017. Data are stored on an HPC system while data operations are running on Jetstream virtual machines within the same datacenter. In addition to the production data operations, testing was done in early 2017 with container based InSAR processing analysis using JupyterHub and Docker images deployed on a VM cluster on Jetstream. The JupyterHub environment is well suited for short courses and other training opportunities for the community such as labs for university courses on InSAR. UNAVCO is also exploring new processing methodologies using DC/OS (the datacenter operating system) for batch and stream processing workflows and time series analysis with Big Data open source components like the Spark, Mesos, Akka, Cassandra, Kafka (SMACK) stack. The comparison of the different methodologies will provide insight into the pros and cons for each and help the SAR community with decisions about infrastructure and software requirements to meet their research

  17. Rapid SAR and GPS Measurements and Models for Hazard Science and Situational Awareness

    Science.gov (United States)

    Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Moore, A. W.; Rosen, P. A.; Simons, M.; Webb, F.; Linick, J.; Fielding, E. J.; Lundgren, P.; Sacco, G. F.; Polet, J.; Manipon, G.

    2016-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR), Differential Global Positioning System (DGPS), SAR-based change detection, and image pixel tracking have recently become critical additions to our toolset for understanding and mapping the damage caused by earthquakes, volcanic eruptions, landslides, and floods. Analyses of these data sets are still largely handcrafted following each event and are not generated rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition, the ARIA project is developing the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the imminent increase in raw data from geodetic imaging missions planned for launch by NASA, as well as international space agencies. We will present the progress we have made on automating the analysis of SAR data for hazard monitoring and response using data from Sentinel 1a/b as well as continuous GPS stations. Since the beginning of our project, our team has imaged events and generated response products for events around the world. These response products have enabled many conversations with those in the disaster response community

  18. Crop Classification by Polarimetric SAR

    DEFF Research Database (Denmark)

    Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming

    1999-01-01

    Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...

  19. Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

    Science.gov (United States)

    Deidda, Roberto; Mascaro, Giuseppe; Hellies, Matteo; Baldini, Luca; Roberto, Nicoletta

    2013-04-01

    COSMO Sky-Med (CSK) is an important programme of the Italian Space Agency aiming at supporting environmental monitoring and management of exogenous, endogenous and anthropogenic risks through X-band Synthetic Aperture Radar (X-SAR) on board of 4 satellites forming a constellation. Most of typical SAR applications are focused on land or ocean observation. However, X-band SAR can be detect precipitation that results in a specific signature caused by the combination of attenuation of surface returns induced by precipitation and enhancement of backscattering determined by the hydrometeors in the SAR resolution volume. Within CSK programme, we conducted an intercomparison between the statistical properties of precipitation fields derived by CSK SARs and those derived by the CNR Polar 55C (C-band) ground based weather radar located in Rome (Italy). This contribution presents main results of this research which was aimed at the robust characterisation of rainfall statistical properties across different scales by means of scale-invariance analysis and multifractal theory. The analysis was performed on a dataset of more two years of precipitation observations collected by the CNR Polar 55C radar and rainfall fields derived from available images collected by the CSK satellites during intense rainfall events. Scale-invariance laws and multifractal properties were detected on the most intense rainfall events derived from the CNR Polar 55C radar for spatial scales from 4 km to 64 km. The analysis on X-SAR retrieved rainfall fields, although based on few images, leaded to similar results and confirmed the existence of scale-invariance and multifractal properties for scales larger than 4 km. These outcomes encourage investigating SAR methodologies for future development of meteo-hydrological forecasting models based on multifractal theory.

  20. Image Alignment for Multiple Camera High Dynamic Range Microscopy

    OpenAIRE

    Eastwood, Brian S.; Childs, Elisabeth C.

    2012-01-01

    This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability fo...

  1. A strategy for Local Surface Stability Monitoring Using SAR Imagery

    Science.gov (United States)

    Kim, J.; Lan, C. W.; Lin, S. Y.; vanGasselt, S.; Yun, H.

    2017-12-01

    In order to provide sufficient facilities to satisfy a growing number of residents, nowadays there are many constructions and maintenance of infrastructures or buildings undergoing above and below the surface of urban area. In some cases we have learned that disasters might happen if the developments were conducted on unknown or geologically unstable ground or in over-developed areas. To avoid damages caused by such settings, it is essential to perform a regular monitoring scheme to understand the ground stability over the whole urban area. Through long-term monitoring, we firstly aim to observe surface stability over the construction sites. Secondly, we propose to implement an automatic extraction and tracking of suspicious unstable area. To achieve this, we used 12-days-interval C-band Sentinel-1A Synthetic Aperture Radar (SAR) images as the main source to perform regular monitoring. Differential Interferometric SAR (D-InSAR) technique was applied to generate interferograms. Together with the accumulation of updated Sentinel-1A SAR images, time series interferograms were formed accordingly. For the purpose of observing surface stability over known construction sites, the interferograms and the unwrapped products could be used to identify the surface displacement occurring before and after specific events. In addition, Small Baseline Subset (SBAS) and Permanent Scatterers (PS) approaches combining a set of unwrapped D-InSAR interferograms were also applied to derive displacement velocities over long-term periods. For some cases, we conducted the ascending and descending mode time series analysis to decompose three surface migration vectors and to precisely identify the risk pattern. Regarding the extraction of suspicious unstable areas, we propose to develop an automatic pattern recognition algorithm for the identification of specific fringe patterns involving various potential risks. The detected fringes were tracked in the time series interferograms and

  2. Multimodality imaging features of hereditary multiple exostoses

    OpenAIRE

    Kok, H K; Fitzgerald, L; Campbell, N; Lyburn, I D; Munk, P L; Buckley, O; Torreggiani, W C

    2013-01-01

    Hereditary multiple exostoses (HME) or diaphyseal aclasis is an inherited disorder characterised by the formation of multiple osteochondromas, which are cartilage-capped osseous outgrowths, and the development of associated osseous deformities. Individuals with HME may be asymptomatic or develop clinical symptoms, which prompt imaging studies. Different modalities ranging from plain radiographs to cross-sectional and nuclear medicine imaging studies can be helpful in the diagnosis and detecti...

  3. Polarimetric scattering and SAR information retrieval

    CERN Document Server

    Jin, Ya-Qiu

    2013-01-01

    Taking an innovative look at Synthetic Aperture Radar (SAR), this practical reference fully covers new developments in SAR and its various methodologies and enables readers to interpret SAR imagery An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics. It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface. The book includes quantitative app

  4. Long term landslide monitoring with Ground Based SAR

    Science.gov (United States)

    Monserrat, Oriol; Crosetto, Michele; Luzi, Guido; Gili, Josep; Moya, Jose; Corominas, Jordi

    2014-05-01

    In the last decade, Ground-Based (GBSAR) has proven to be a reliable microwave Remote Sensing technique in several application fields, especially for unstable slopes monitoring. GBSAR can provide displacement measurements over few squared kilometres areas and with a very high spatial and temporal resolution. This work is focused on the use of GBSAR technique for long term landslide monitoring based on a particular data acquisition configuration, which is called discontinuous GBSAR (D-GBSAR). In the most commonly used GBSAR configuration, the radar is left installed in situ, acquiring data periodically, e.g. every few minutes. Deformations are estimated by processing sets of GBSAR images acquired during several weeks or months, without moving the system. By contrast, in the D-GBSAR the radar is installed and dismounted at each measurement campaign, revisiting a given site periodically. This configuration is useful to monitor slow deformation phenomena. In this work, two alternative ways for exploiting the D-GBSAR technique will be presented: the DInSAR technique and the Amplitude based Technique. The former is based on the exploitation of the phase component of the acquired SAR images and it allows providing millimetric precision on the deformation estimates. However, this technique presents several limitations like the reduction of measurable points with an increase in the period of observation, the ambiguous nature of the phase measurements, and the influence of the atmospheric phase component that can make it non applicable in some cases, specially when working in natural environments. The second approach, that is based on the use of the amplitude component of GB-SAR images combined with a image matching technique, will allow the estimation of the displacements over specific targets avoiding two of the limitations commented above: the phase unwrapping and atmosphere contribution but reducing the deformation measurement precision. Two successful examples of D

  5. A study on rational function model generation for TerraSAR-X imagery.

    Science.gov (United States)

    Eftekhari, Akram; Saadatseresht, Mohammad; Motagh, Mahdi

    2013-09-09

    The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10-3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

  6. A Study on Rational Function Model Generation for TerraSAR-X Imagery

    Directory of Open Access Journals (Sweden)

    Mahdi Motagh

    2013-09-01

    Full Text Available The Rational Function Model (RFM has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10−3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

  7. Using InSAR to Observe Sinkhole Activity in Central Florida

    Science.gov (United States)

    Oliver-Cabrera, T.; Wdowinski, S.; Kruse, S.; Kiflu, H. G.

    2017-12-01

    Sinkhole collapse in Florida is a major geologic hazard, threatening human life and causing substantial damage to property. Detecting sinkhole deformation before a collapse is an important but difficult task; most techniques used to monitor sinkholes are spatially constrained to relatively small areas (tens to hundred meters). To overcome this limitation, we use Interferometric Synthetic Aperture Radar (InSAR), which is a very useful technique for detecting localized deformation while covering vast areas. InSAR results show localized deformation at several houses and commercial buildings in different locations along the study sites. We use a subsurface imaging technique, ground penetrating radar, to verify sinkhole existence beneath the observed deforming areas.

  8. Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2016-11-01

    Full Text Available Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS and 18 descending images from the Environmental Satellite (ENVISAT have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface–parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

  9. Flood extent mapping for Namibia using change detection and thresholding with SAR

    International Nuclear Information System (INIS)

    Long, Stephanie; Fatoyinbo, Temilola E; Policelli, Frederick

    2014-01-01

    A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision-based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km 2 , 720 km 2 , and 673 km 2 respectively. Pixels determined to be flooded in vegetation were typically <0.5% of the entire scene, with the exception of 2009 where the detection of flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes. (paper)

  10. Multiplicative calculus in biomedical image analysis

    NARCIS (Netherlands)

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  11. Ocean Wave Parameters Retrieval from Sentinel-1 SAR Imagery

    Directory of Open Access Journals (Sweden)

    Weizeng Shao

    2016-08-01

    Full Text Available In this paper, a semi-empirical algorithm for significant wave height (Hs and mean wave period (Tmw retrieval from C-band VV-polarization Sentinel-1 synthetic aperture radar (SAR imagery is presented. We develop a semi-empirical function for Hs retrieval, which describes the relation between Hs and cutoff wavelength, radar incidence angle, and wave propagation direction relative to radar look direction. Additionally, Tmw can be also calculated through Hs and cutoff wavelength by using another empirical function. We collected 106 C-band stripmap mode Sentinel-1 SAR images in VV-polarization and wave measurements from in situ buoys. There are a total of 150 matchup points. We used 93 matchups to tune the coefficients of the semi-empirical algorithm and the rest 57 matchups for validation. The comparison shows a 0.69 m root mean square error (RMSE of Hs with a 18.6% of scatter index (SI and 1.98 s RMSE of Tmw with a 24.8% of SI. Results indicate that the algorithm is suitable for wave parameters retrieval from Sentinel-1 SAR data.

  12. Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

    Science.gov (United States)

    Saatchi, Sassan; Moghaddam, Mahta

    1995-01-01

    In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

  13. The best of a BAD situation: Optimising an algorithm to match course resolution SAR vessel detections to sparse AIS data

    CSIR Research Space (South Africa)

    Meyer, Rory GV

    2017-07-01

    Full Text Available The detection and classification of SAR imaged vessels at sea is a valuable ability for organisations interested in the marine environment or marine vessels. Matching the SAR detected vessels to their AIS messages allows vessels to be identified...

  14. Magnetic resonance imaging of the spine in multiple myeloma

    International Nuclear Information System (INIS)

    Tanaka, Masato; Nakahara, Shinnosuke; Koura, Hiroshi; Kai, Nobuo; Asaumi, Koji; Tanaka, Shunsuke; Sezaki, Tatsuo; Fukuda, Shunichi; Sunami, Kazutaka

    2000-01-01

    The characteristics of diagnostic imaging of the spine in multiple myeloma were examined. Twenty-one patients with stage II-III multiple myeloma (male=12, female=9, mean age=64) underwent MRI of the spine. Other diagnostic imaging modalities used in these patients included, CT bone scintigraphy, and radiography. All images of the spine were assessed and compared with the MRI images. The type of progression was evaluated based on the tumor distribution classification established by Sezaki. T1-weighted images of all 21 patients showed low signals in vertebral bodies, including 14 cases with a focal low signal intensity and 7 cases with diffuse low signal intensity. On the T2-weighted images, 15 of the 21 cases (71%) showed equivalent signals, while T2*-weighted images obtained by the field-echo method yielded high signals in 10 out of 11 cases. It was difficult to differentiate between senile osteoporosis and multiple myeloma by MRI, but CT images clearly distinguished between them. The results suggested that fat-suppressive T1-contrast images and T2*-weighted images are useful in detecting lesions, especially focal low signal intensity lesions. Patients with the multiple-lesion-tumor type of disease were more likely to develop paralysis more than those with the diffuse myeloproliferative type. Thus, the tumor distribution classification established by Sezaki was useful in considering radiotherapy for the treatment of patients at risk of paralysis. Bone scintigraphy revealed accumulation only in spinal lesions caused by compression fractures, while CT appeared to be useful in localizing the diffuse myeloproliferative type of lesions. The problems associated with diagnosis by MRI are differentiation of multiple myeloma from senile osteoporosis and metastatic bone tumors of the spine. There are few specific findings in multiple myeloma. (K.H.)

  15. On the use of Cloud Computing and Machine Learning for Large-Scale SAR Science Data Processing and Quality Assessment Analysi

    Science.gov (United States)

    Hua, H.

    2016-12-01

    Geodetic imaging is revolutionizing geophysics, but the scope of discovery has been limited by labor-intensive technological implementation of the analyses. The Advanced Rapid Imaging and Analysis (ARIA) project has proven capability to automate SAR data processing and analysis. Existing and upcoming SAR missions such as Sentinel-1A/B and NISAR are also expected to generate massive amounts of SAR data. This has brought to the forefront the need for analytical tools for SAR quality assessment (QA) on the large volumes of SAR data-a critical step before higher-level time series and velocity products can be reliably generated. Initially leveraging an advanced hybrid-cloud computing science data system for performing large-scale processing, machine learning approaches were augmented for automated analysis of various quality metrics. Machine learning-based user-training of features, cross-validation, prediction models were integrated into our cloud-based science data processing flow to enable large-scale and high-throughput QA analytics for enabling improvements to the production quality of geodetic data products.

  16. Significant Wave Height under Hurricane Irma derived from SAR Sentinel-1 Data

    Science.gov (United States)

    Lehner, S.; Pleskachevsky, A.; Soloviev, A.; Fujimura, A.

    2017-12-01

    The 2017 Atlantic hurricane season was with three major hurricanes a particular active one. The Category 4 hurricane Irma made landfall on the Florida Keys on September 10th 2017 and was imaged several times by ESAs Sentinel-1 satellites in C-band and the TerraSAR-X satellite in X-band. The high resolution TerraSAR-X imagery showed the footprint of individual tornadoes on the sea surface together with their turbulent wake imaged as a dark line due to increased turbulence. The water-cloud structures of the tornadoes are analyzed and their sea surface structure is compared to optical and IR cloud imagery. An estimate of the wind field using standard XMOD algorithms is provided, although saturating under the strong rain and high wind speed conditions. Imaging the hurricanes by space radar gives the opportunity to observe the sea surface and thus measure the wind field and the sea state under hurricane conditions through the clouds even in this severe weather, although rain features, which are usually not observed in SAR become visible due to damping effects. The Copernicus Sentinel-1 A and B satellites, which are operating in C-band provided several images of the sea surface under hurricane Irma, Jose and Maria. The data were acquired daily and converted into measurements of sea surface wind field u10 and significant wave height Hs over a swath width of 280km about 1000 km along the orbit. The wind field of the hurricanes as derived by CMOD is provided by NOAA operationally on their web server. In the hurricane cases though the wind speed saturates at 20 m/sec and is thus too low in the area of hurricane wind speed. The technique to derive significant wave height is new though and does not show any calibration issues. This technique provides for the first time measurements of the areal coverage and distribution of the ocean wave height as caused by a hurricane on SAR wide swath images. Wave heights up to 10 m were measured under the forward quadrant of the hurricane

  17. A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation

    Directory of Open Access Journals (Sweden)

    Xuejiao Wen

    2018-05-01

    Full Text Available Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

  18. Multi-dimensional SAR tomography for monitoring the deformation of newly built concrete buildings

    Science.gov (United States)

    Ma, Peifeng; Lin, Hui; Lan, Hengxing; Chen, Fulong

    2015-08-01

    Deformation often occurs in buildings at early ages, and the constant inspection of deformation is of significant importance to discover possible cracking and avoid wall failure. This paper exploits the multi-dimensional SAR tomography technique to monitor the deformation performances of two newly built buildings (B1 and B2) with a special focus on the effects of concrete creep and shrinkage. To separate the nonlinear thermal expansion from total deformations, the extended 4-D SAR technique is exploited. The thermal map estimated from 44 TerraSAR-X images demonstrates that the derived thermal amplitude is highly related to the building height due to the upward accumulative effect of thermal expansion. The linear deformation velocity map reveals that B1 is subject to settlement during the construction period, in addition, the creep and shrinkage of B1 lead to wall shortening that is a height-dependent movement in the downward direction, and the asymmetrical creep of B2 triggers wall deflection that is a height-dependent movement in the deflection direction. It is also validated that the extended 4-D SAR can rectify the bias of estimated wall shortening and wall deflection by 4-D SAR.

  19. Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

    Science.gov (United States)

    Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

    2016-08-01

    Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

  20. Suitability Assessment of X-Band Satellite SAR Data for Geotechnical Monitoring of Site Scale Slow Moving Landslides

    Directory of Open Access Journals (Sweden)

    Guadalupe Bru

    2018-06-01

    Full Text Available This work addresses the suitability of using X-band Synthetic Aperture Radar (SAR data for operational geotechnical monitoring of site scale slow moving landslides, affecting urban areas and infrastructures. The scale of these studies requires high resolution data. We propose a procedure for the practical use of SAR data in geotechnical landslides campaigns, that includes an appropriate dataset selection taking into account the scenario characteristics, a visibility analysis, and considerations when comparing advanced differential SAR interferometry (A-DInSAR results with other monitoring techniques. We have determined that Sentinel-2 satellite optical images are suited for performing high resolution land cover classifications, which results in the achievement of qualitative visibility maps. We also concluded that A-DInSAR is a very powerful and versatile tool for detailed scale landslide monitoring, although in combination with other instrumentation techniques.

  1. A typical MR imaging of multiple sclerosis

    International Nuclear Information System (INIS)

    Katagiri, Shinako; Kan, Shinichi; Ikeda, Toshiaki; Nishiyama, Syougo; Nishimaki, Hiroshi; Matsubayashi, Takashi; Hata, Takashi

    1995-01-01

    MR imaging is very useful in detecting the intracranial lesion of multiple sclerosis (MS). We present six patients of MS with atypical MR imaging findings. Six patients aged 27-56 years (mean 36 years), and sexuality of six patients were 2 men and 4 females. Three patient's clinical course had episodes of optic neuritis. The plaque's size of the predominant lesion of the patients ranged from 3.0 to 9.0 cm in diameter. The plaques were oval, elliptically and other shaped. At acute stage, MR imaging detected perfocal edema and focal mass effect in three cases of our study. Two out of six cases showed multiple irregularly enhancing lesion with Gadolinium-DTPA. Plaques of all cases did not disappear completely in final MR imaging study. (author)

  2. Peptide Mimicrying Between SARS Coronavirus Spike Protein and Human Proteins Reacts with SARS Patient Serum

    Directory of Open Access Journals (Sweden)

    K.-Y. Hwa

    2008-01-01

    Full Text Available Molecular mimicry, defined as similar structures shared by molecules from dissimilar genes or proteins, is a general strategy used by pathogens to infect host cells. Severe acute respiratory syndrome (SARS is a new human respiratory infectious disease caused by SARS coronavirus (SARS-CoV. The spike (S protein of SARS-CoV plays an important role in the virus entry into a cell. In this study, eleven synthetic peptides from the S protein were selected based on its sequence homology with human proteins. Two of the peptides D07 (residues 927–937 and D08 (residues 942–951 were recognized by the sera of SARS patients. Murine hyperimmune sera against these peptides bound to proteins of human lung epithelial cells A549. Another peptide D10 (residues 490–502 stimulated A549 to proliferate and secrete IL-8. The present results suggest that the selected S protein regions, which share sequence homology with human proteins, may play important roles in SARS-CoV infection.

  3. Automated Registration Of Images From Multiple Sensors

    Science.gov (United States)

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.; Pang, Shirley S. N.

    1994-01-01

    Images of terrain scanned in common by multiple Earth-orbiting remote sensors registered automatically with each other and, where possible, on geographic coordinate grid. Simulated image of terrain viewed by sensor computed from ancillary data, viewing geometry, and mathematical model of physics of imaging. In proposed registration algorithm, simulated and actual sensor images matched by area-correlation technique.

  4. Impact of the Regulators SigB, Rot, SarA and sarS on the Toxic Shock Tst Promoter and TSST-1 Expression in Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Diego O Andrey

    Full Text Available Staphylococcus aureus is an important pathogen manifesting virulence through diverse disease forms, ranging from acute skin infections to life-threatening bacteremia or systemic toxic shock syndromes. In the latter case, the prototypical superantigen is TSST-1 (Toxic Shock Syndrome Toxin 1, encoded by tst(H, and carried on a mobile genetic element that is not present in all S. aureus strains. Transcriptional regulation of tst is only partially understood. In this study, we dissected the role of sarA, sarS (sarH1, RNAIII, rot, and the alternative stress sigma factor sigB (σB. By examining tst promoter regulation predominantly in the context of its native sequence within the SaPI1 pathogenicity island of strain RN4282, we discovered that σB emerged as a particularly important tst regulator. We did not detect a consensus σB site within the tst promoter, and thus the effect of σB is likely indirect. We found that σB strongly repressed the expression of the toxin via at least two distinct regulatory pathways dependent upon sarA and agr. Furthermore rot, a member of SarA family, was shown to repress tst expression when overexpressed, although its deletion had no consistent measurable effect. We could not find any detectable effect of sarS, either by deletion or overexpression, suggesting that this regulator plays a minimal role in TSST-1 expression except when combined with disruption of sarA. Collectively, our results extend our understanding of complex multifactorial regulation of tst, revealing several layers of negative regulation. In addition to environmental stimuli thought to impact TSST-1 production, these findings support a model whereby sporadic mutation in a few key negative regulators can profoundly affect and enhance TSST-1 expression.

  5. C/X-band SAR interferometry applied to ground monitoring: examples and new potential

    Science.gov (United States)

    Nutricato, Raffaele; Nitti, Davide O.; Bovenga, Fabio; Refice, Alberto; Wasowski, Janusz; Chiaradia, Maria T.

    2013-10-01

    Classical applications of the MTInSAR techniques have been carried out in the past on medium resolution data acquired by the ERS, Envisat (ENV) and Radarsat sensors. The new generation of high-resolution X-Band SAR sensors, such as TerraSAR-X (TSX) and the COSMO-SkyMed (CSK) constellation allows acquiring data with spatial resolution reaching metric/submetric values. Thanks to the finer spatial resolution with respect to C-band data, X-band InSAR applications result very promising for monitoring single man-made structures (buildings, bridges, railways and highways), as well as landslides. This is particularly relevant where C-band data show low density of coherent scatterers. Moreover, thanks again to the higher resolution, it is possible to infer reliable estimates of the displacement rates with a number of SAR scenes significantly lower than in C-band within the same time span or by using more images acquired in a narrower time span. We present examples of the application of a Persistent Scatterers Interferometry technique, namely the SPINUA algorithm, to data acquired by ENV, TSX and CSK on selected number of sites. Different cases are considered concerning monitoring of both instable slopes and infrastructure. Results are compared and commented with particular attention paid to the advantages provided by the new generation of X-band high resolution space-borne SAR sensors.

  6. Low cost realization of space-borne synthectic aperture radar - MicroSAR

    Science.gov (United States)

    Carter, D.; Hall, C.

    Spaceborne Earth Observation data has been used for decades in the areas of meteorology and optical imaging. The systems and satellites have, in the main, been owned and operated by a few government institutions and agencies. More recently industrial organizations in North America have joined the list. Few of these, however, include Synthetic Aperture Radar (SAR)., although the additional utility in terms of all weather, 24 hour measurement capability over the Earth's surface is well recognized. Three major factors explain this:1) Relationships between the SAR measurements of radar backscatter and images to the specific information needs have not been seen as sufficiently well understood or robust2) Availability of suitable sources, at the relevant performance and data quality have been inadequate to provide service assurance that is necessary to sustain commercial businesses3) Costs associated with building, launching and operating spaceborne SAR have not been low enough as to achieve an acceptable return of investment. A significant amount of research and development has been undertaken throughout the World to establish reliable and robust algorithms for information extraction from SAR data. Much of this work has been carried out utilizing airborne systems over localized and carefully controlled regions. In addition, an increasing number of pilot services have been offered by geo-information providers. This has allowed customer confidence to grow. With the status of spaceborne SAR being effectively in the development phase, commercial funding has been scarce, and there has been need to rely on government and institutional budgets. Today the increasing maturity of the technology of SAR and its applications is beginning to attract the commercial sector. This is the funding necessary to realize sufficient assets to be able to provide a robust supply of SAR data to the geo-information providers and subsequently a reliable service to customers. Reducing the costs

  7. Utility of Characterizing and Monitoring Suspected Underground Nuclear Sites with VideoSAR

    Science.gov (United States)

    Dauphin, S. M.; Yocky, D. A.; Riley, R.; Calloway, T. M.; Wahl, D. E.

    2016-12-01

    Sandia National Laboratories proposed using airborne synthetic aperture RADAR (SAR) collected in VideoSAR mode to characterize the Underground Nuclear Explosion Signature Experiment (UNESE) test bed site at the Nevada National Security Site (NNSS). The SNL SAR collected airborne, Ku-band (16.8 GHz center frequency), 0.2032 meter ground resolution over NNSS in August 2014 and X-band (9.6 GHz), 0.1016 meter ground resolution fully-polarimetric SAR in April 2015. This paper reports the findings of processing and exploiting VideoSAR for creating digital elevation maps, detecting cultural artifacts and exploiting full-circle polarimetric signatures. VideoSAR collects a continuous circle of phase history data, therefore, imagery can be formed over the 360-degrees of the site. Since the Ku-band VideoSAR had two antennas suitable for interferometric digital elevation mapping (DEM), DEMs could be generated over numerous aspect angles, filling in holes created by targets with height by imaging from all sides. Also, since the X-band VideoSAR was fully-polarimetric, scattering signatures could be gleaned from all angles also. Both of these collections can be used to find man-made objects and changes in elevation that might indicate testing activities. VideoSAR provides a unique, coherent measure of ground objects allowing one to create accurate DEMS, locate man-made objects, and identify scattering signatures via polarimetric exploitation. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. The authors would like to thank the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development, for sponsoring this work. We would also like to thank the Underground Nuclear Explosion Signatures Experiment team, a multi

  8. Automated Waterline Detection in the Wadden Sea Using High-Resolution TerraSAR-X Images

    Directory of Open Access Journals (Sweden)

    Stefan Wiehle

    2015-01-01

    Full Text Available We present an algorithm for automatic detection of the land-water-line from TerraSAR-X images acquired over the Wadden Sea. In this coastal region of the southeastern North Sea, a strip of up to 20 km of seabed falls dry during low tide, revealing mudflats and tidal creeks. The tidal currents transport sediments and can change the coastal shape with erosion rates of several meters per month. This rate can be strongly increased by storm surges which also cause flooding of usually dry areas. Due to the high number of ships traveling through the Wadden Sea to the largest ports of Germany, frequent monitoring of the bathymetry is also an important task for maritime security. For such an extended area and the required short intervals of a few months, only remote sensing methods can perform this task efficiently. Automating the waterline detection in weather-independent radar images provides a fast and reliable way to spot changes in the coastal topography. The presented algorithm first performs smoothing, brightness thresholding, and edge detection. In the second step, edge drawing and flood filling are iteratively performed to determine optimal thresholds for the edge drawing. In the last step, small misdetections are removed.

  9. Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

    Science.gov (United States)

    Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

    2018-03-01

    Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

  10. Tracking morphological changes and slope instability using spaceborne and ground-based SAR data

    Science.gov (United States)

    Di Traglia, Federico; Nolesini, Teresa; Ciampalini, Andrea; Solari, Lorenzo; Frodella, William; Bellotti, Fernando; Fumagalli, Alfio; De Rosa, Giuseppe; Casagli, Nicola

    2018-01-01

    Stromboli (Aeolian Archipelago, Italy) is an active volcano that is frequently affected by moderate to large mass wasting, which has occasionally triggered tsunamis. With the aim of understanding the relationship between the geomorphologic evolution and slope instability of Stromboli, remote sensing information from space-born Synthetic Aperture Radar (SAR) change detection and interferometry (InSAR) () and Ground Based InSAR (GBInSAR) was compared with field observations and morphological analyses. Ground reflectivity and SqueeSAR™ (an InSAR algorithm for surface deformation monitoring) displacement measurements from X-band COSMO-SkyMed satellites (CSK) were analysed together with displacement measurements from a permanent-sited, Ku-band GBInSAR system. Remote sensing results were compared with a preliminary morphological analysis of the Sciara del Fuoco (SdF) steep volcanic flank, which was carried out using a high-resolution Digital Elevation Model (DEM). Finally, field observations, supported by infrared thermographic surveys (IRT), allowed the interpretation and validation of remote sensing data. The analysis of the entire dataset (collected between January 2010 and December 2014) covers a period characterized by a low intensity of Strombolian activity. This period was punctuated by the occurrence of lava overflows, occurring from the crater terrace evolving downslope toward SdF, and flank eruptions, such as the 2014 event. The amplitude of the CSK images collected between February 22nd, 2010, and December 18th, 2014, highlights that during periods characterized by low-intensity Strombolian activity, the production of materials ejected from the crater terrace towards the SdF is generally low, and erosion is the prevailing process mainly affecting the central sector of the SdF. CSK-SqueeSAR™ and GBInSAR data allowed the identification of low displacements in the SdF, except for high displacement rates (up to 1.5 mm/h) that were measured following both lava

  11. A typical MR imaging of multiple sclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Katagiri, Shinako; Kan, Shinichi; Ikeda, Toshiaki; Nishiyama, Syougo; Nishimaki, Hiroshi; Matsubayashi, Takashi; Hata, Takashi [Kitasato Univ., Sagamihara, Kanagawa (Japan). School of Medicine

    1995-06-01

    MR imaging is very useful in detecting the intracranial lesion of multiple sclerosis (MS). We present six patients of MS with atypical MR imaging findings. Six patients aged 27-56 years (mean 36 years), and sexuality of six patients were 2 men and 4 females. Three patient`s clinical course had episodes of optic neuritis. The plaque`s size of the predominant lesion of the patients ranged from 3.0 to 9.0 cm in diameter. The plaques were oval, elliptically and other shaped. At acute stage, MR imaging detected perfocal edema and focal mass effect in three cases of our study. Two out of six cases showed multiple irregularly enhancing lesion with Gadolinium-DTPA. Plaques of all cases did not disappear completely in final MR imaging study. (author).

  12. Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

    Science.gov (United States)

    Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

    2009-11-01

    In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

  13. Spectral Properties of Homogeneous and Nonhomogeneous Radar Images

    DEFF Research Database (Denmark)

    Madsen, Søren Nørvang

    1987-01-01

    On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown that the sp......On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown...... that the spectrum of the intensityimage is in general related to the radar scene spectrum by a linearintegral equation, a Fredholm's integral equation of the third kind.Under simplifying assumptions, a closed-form equation giving theradar scene spectrum as a function of the SAR image spectrum canbe derived....

  14. Application of Satellite SAR for Discovery and Quantification of Natural Marine Oil Seeps

    Science.gov (United States)

    Amos, J.; Lai, R.; Zimmer, B.; Leiva, A.; MacDonald, I.

    2006-12-01

    Natural marine oil seeps discharge gassy drops from the seafloor. Oil drops and gas bubbles reach the surface from water depths as great as 3000m. The oil spreads rapidly, forming an invisible layer that drifts down-wind and down-current in long, linear streaks called slicks. Oil slicks are visible in SAR data because the surfactant dampens capillary waves and reduces backscatter. Application of SAR as an exploration tool in energy prospecting is well-established. We have applied this technique for discovering the chemosynthetic communities that colonize the seafloor in the vicinity of deep-water seeps on the continental margin of the Gulf of Mexico. The management goal for this effort is to prevent harmful impact to these communities resulting from exploration or production activities. The scientific goals are to delineate the zoogeography of the chemosynthetic fauna, which is widespread on continental margins, and to establish study sites where their life history can be investigated. In the course of an ongoing, multidisciplinary study in the spring and summer of 2006, we explored 20 possible sites where SAR and geophysical data indicated seeps might occur. SAR was only partly diagnostic: all sites with SAR-detected slicks were found to have biologic communities, but communities were also found at geophysical anomalies that did not produce slicks. We acquired over 60 RADARSAT SAR images from the northern Gulf of Mexico in cooperation with the Alaska Satellite Facility. The ship RV ATLANTIS was at sea during the acquisition and collected synoptic weather and oceanographic data. To automate interpretation of large image dataset we have employed texture recognition with use of a library of textons applied iteratively to the images. This treatment shows promise in distinguishing floating oil from false targets generated by rain fronts and other phenomena. One goal of the analysis is to delineate bounding boxes to quantify the ocean area covered by the thin oil layer

  15. Classification of PolSAR Images Using Multilayer Autoencoders and a Self-Paced Learning Approach

    Directory of Open Access Journals (Sweden)

    Wenshuai Chen

    2018-01-01

    Full Text Available In this paper, a novel polarimetric synthetic aperture radar (PolSAR image classification method based on multilayer autoencoders and self-paced learning (SPL is proposed. The multilayer autoencoders network is used to learn the features, which convert raw data into more abstract expressions. Then, softmax regression is applied to produce the predicted probability distributions over all the classes of each pixel. When we optimize the multilayer autoencoders network, self-paced learning is used to accelerate the learning convergence and achieve a stronger generalization capability. Under this learning paradigm, the network learns the easier samples first and gradually involves more difficult samples in the training process. The proposed method achieves the overall classification accuracies of 94.73%, 94.82% and 78.12% on the Flevoland dataset from AIRSAR, Flevoland dataset from RADARSAT-2 and Yellow River delta dataset, respectively. Such results are comparable with other state-of-the-art methods.

  16. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    Science.gov (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  17. Observation of high-resolution wind fields and offshore wind turbine wakes using TerraSAR-X imagery

    Science.gov (United States)

    Gies, Tobias; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey

    2014-05-01

    1. Introduction Numerous large-scale offshore wind farms have been built in European waters and play an important role in providing renewable energy. Therefore, knowledge of behavior of wakes, induced by large wind turbines and their impact on wind power output is important. The spatial variation of offshore wind turbine wake is very complex, depending on wind speed, wind direction, ambient atmospheric turbulence and atmospheric stability. In this study we demonstrate the application of X-band TerraSAR-X (TS-X) data with high spatial resolution for studies on wind turbine wakes in the near and far field of the offshore wind farm Alpha Ventus, located in the North Sea. Two cases which different weather conditions and different wake pattern as observed in the TS-X image are presented. 2. Methods The space-borne synthetic aperture radar (SAR) is a unique sensor that provides two-dimensional information on the ocean surface. Due to their high resolution, daylight and weather independency and global coverage, SARs are particularly suitable for many ocean and coastal applications. SAR images reveal wind variations on small scales and thus represent a valuable means in detailed wind-field analysis. The general principle of imaging turbine wakes is that the reduced wind speed downstream of offshore wind farms modulates the sea surface roughness, which in turn changes the Normalized Radar Cross Section (NRCS, denoted by σ0) in the SAR image and makes the wake visible. In this study we present two cases at the offshore wind farm Alpha Ventus to investigate turbine-induced wakes and the retrieved sea surface wind field. Using the wind streaks, visible in the TS-X image and the shadow behind the offshore wind farm, induced by turbine wake, the sea surface wind direction is derived and subsequently the sea surface wind speed is calculated using the latest generation of wind field algorithm XMOD2. 3. Case study alpha ventus Alpha Ventus is located approximately 45 km from the

  18. Application of SAR remote sensing and crop modeling for operational rice crop monitoring in South and South East Asian Countries

    Science.gov (United States)

    Setiyono, T. D.; Holecz, F.; Khan, N. I.; Barbieri, M.; Maunahan, A. A.; Gatti, L.; Quicho, E. D.; Pazhanivelan, S.; Campos-Taberner, M.; Collivignarelli, F.; Haro, J. G.; Intrman, A.; Phuong, D.; Boschetti, M.; Prasadini, P.; Busetto, L.; Minh, V. Q.; Tuan, V. Q.

    2017-12-01

    This study uses multi-temporal SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations in South and South Asian countries and assimilate the information into ORYZA Crop Growth Simulation Model (CGSM) to monitor rice yield. The study demonstrates examples of operational application of this rice monitoring system in: (1) detecting drought impact on rice planting in Central Thailand and Tamil Nadu, India, (2) mapping heat stress impact on rice yield in Andhra Pradesh, India, and (3) generating historical rice yield data for districts in Red River Delta, Vietnam.

  19. Improved inland water levels from SAR altimetry using novel empirical and physical retrackers

    DEFF Research Database (Denmark)

    Villadsen, Heidi; Deng, Xiaoli; Andersen, Ole Baltazar

    2016-01-01

    with in situdata in Lake Vänern and Lake Okeechobee are in the order of 2–5 cm for well-behaved waveforms. Combining the physical and empirical retrackers did not offer significantly improved mean track standarddeviations or RMSEs. Based on these studies, it is suggested that future SAR derived water levels......Satellite altimetry has proven a valuable resource of information on river and lake levels where in situ data are sparse or non-existent. In this study several new methods for obtaining stable inland water levels from CryoSat-2 Synthetic Aperture Radar (SAR) altimetry are presented and evaluated....... In addition, the possible benefits from combining physical and empirical retrackers are investigated.The retracking methods evaluated in this paper include the physical SAR Altimetry MOde Studies andApplications (SAMOSA3) model, a traditional subwaveform threshold retracker, the proposed Multiple...

  20. SARS-related perceptions in Hong Kong.

    Science.gov (United States)

    Lau, Joseph T F; Yang, Xilin; Pang, Ellie; Tsui, H Y; Wong, Eric; Wing, Yun Kwok

    2005-03-01

    To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means of prevention; 40.4% believed that SARS would resurge in Hong Kong; and approximately equals 70% would then wear masks in public places. High percentages of respondents felt helpless, horrified, and apprehensive because of SARS. Approximately 16% showed signs of posttraumatic symptoms, and approximately equals 40% perceived increased stress in family or work settings. The general public in Hong Kong has been very vigilant about SARS but needs to be more psychologically prepared to face a resurgence of the epidemic.