Using ERS-2 SAR images for routine observation of marine pollution in European coastal waters.

PubMed

Gade, M; Alpers, W

1999-09-30

More than 660 synthetic aperture radar (SAR) images acquired over the southern Baltic Sea, the North Sea, and the Gulf of Lion in the Mediterranean Sea by the Second European Remote Sensing Satellite (ERS-2) have been analyzed since December 1996 with respect to radar signatures of marine pollution and other phenomena causing similar signatures. First results of our analysis reveal that the seas are most polluted along the main shipping routes. The sizes of the detected oil spills vary between < 0.1 km2 and > 56 km2. SAR images acquired during descending (morning) and ascending (evening) satellite passes show different percentages of oil pollution, because most of this pollution occurs during night time and is still visible on the SAR images acquired in the morning time. Moreover, we found a higher amount of oil spills on SAR images acquired during summer (April-September) than on SAR images acquired during winter (October-March). We attribute this finding to the higher mean wind speed encountered in all three test areas during winter. By using an ERS-2 SAR image of the North Sea test area we show how the reduction of the normalized radar backscattering cross section (NRCS) by an oil spill depends on wind speed.

Satellite on-board real-time SAR processor prototype

NASA Astrophysics Data System (ADS)

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 size are reviewed.

Sparsity-driven coupled imaging and autofocusing for interferometric SAR

NASA Astrophysics Data System (ADS)

Zengin, Oǧuzcan; Khwaja, Ahmed Shaharyar; ćetin, Müjdat

2018-04-01

We propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan et al. proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods.

Rock type discrimination and structural analysis with LANDSAT and Seasat data: San Rafael swell, Utah

NASA Technical Reports Server (NTRS)

Stewart, H. E.; Blom, R.; Abrams, M.; Daily, M.

1980-01-01

Satellite synthetic aperture radar (SAR) images is evaluated in terms of its geologic applications. The benchmark to which the SAR images are compared is LANDSAT, used both for structural and lithologic interpretations.

Radarsat-1 and ERS InSAR analysis over southeastern coastal Louisiana: Implications for mapping water-level changes beneath swamp forests

USGS Publications Warehouse

Lu, Z.; Kwoun, Oh-Ig

2008-01-01

Detailed analysis of C-band European Remote Sensing 1 and 2 (ERS-1/ERS-2) and Radarsat-1 interferometric synthetic aperture radar (InSAR) imagery was conducted to study water-level changes of coastal wetlands of southeastern Louisiana. Radar backscattering and InSAR coherence suggest that the dominant radar backscattering mechanism for swamp forest and saline marsh is double-bounce backscattering, implying that InSAR images can be used to estimate water-level changes with unprecedented spatial details. On the one hand, InSAR images suggest that water-level changes over the study site can be dynamic and spatially heterogeneous and cannot be represented by readings from sparsely distributed gauge stations. On the other hand, InSAR phase measurements are disconnected by structures and other barriers and require absolute water-level measurements from gauge stations or other sources to convert InSAR phase values to absolute water-level changes. ?? 2006 IEEE.

Layover and shadow detection based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Huanxin, Zou; Bin, Cai; Changzhou, Fan; Yun, Ren

2014-03-01

Distributed spaceborne single-baseline InSAR is an effective technique to get high quality Digital Elevation Model. Layover and Shadow are ubiquitous phenomenon in SAR images because of geometric relation of SAR imaging. In the signal processing of single-baseline InSAR, the phase singularity of Layover and Shadow leads to the phase difficult to filtering and unwrapping. This paper analyzed the geometric and signal model of the Layover and Shadow fields. Based on the interferometric signal autocorrelation matrix, the paper proposed the signal number estimation method based on information theoretic criteria, to distinguish Layover and Shadow from normal InSAR fields. The effectiveness and practicability of the method proposed in the paper are validated in the simulation experiments and theoretical analysis.

Classification Comparisons Between Compact Polarimetric and Quad-Pol SAR Imagery

NASA Astrophysics Data System (ADS)

Souissi, Boularbah; Doulgeris, Anthony P.; Eltoft, Torbjørn

2015-04-01

Recent interest in dual-pol SAR systems has lead to a novel approach, the so-called compact polarimetric imaging mode (CP) which attempts to reconstruct fully polarimetric information based on a few simple assumptions. In this work, the CP image is simulated from the full quad-pol (QP) image. We present here the initial comparison of polarimetric information content between QP and CP imaging modes. The analysis of multi-look polarimetric covariance matrix data uses an automated statistical clustering method based upon the expectation maximization (EM) algorithm for finite mixture modeling, using the complex Wishart probability density function. Our results showed that there are some different characteristics between the QP and CP modes. The classification is demonstrated using a E-SAR and Radarsat2 polarimetric SAR images acquired over DLR Oberpfaffenhofen in Germany and Algiers in Algeria respectively.

Reduction and coding of synthetic aperture radar data with Fourier transforms

NASA Technical Reports Server (NTRS)

Tilley, David G.

1995-01-01

Recently, aboard the Space Radar Laboratory (SRL), the two roles of Fourier Transforms for ocean image synthesis and surface wave analysis have been implemented with a dedicated radar processor to significantly reduce Synthetic Aperture Radar (SAR) ocean data before transmission to the ground. The object was to archive the SAR image spectrum, rather than the SAR image itself, to reduce data volume and capture the essential descriptors of the surface wave field. SAR signal data are usually sampled and coded in the time domain for transmission to the ground where Fourier Transforms are applied both to individual radar pulses and to long sequences of radar pulses to form two-dimensional images. High resolution images of the ocean often contain no striking features and subtle image modulations by wind generated surface waves are only apparent when large ocean regions are studied, with Fourier transforms, to reveal periodic patterns created by wind stress over the surface wave field. Major ocean currents and atmospheric instability in coastal environments are apparent as large scale modulations of SAR imagery. This paper explores the possibility of computing complex Fourier spectrum codes representing SAR images, transmitting the coded spectra to Earth for data archives and creating scenes of surface wave signatures and air-sea interactions via inverse Fourier transformations with ground station processors.

Development of a satellite SAR image spectra and altimeter wave height data assimilation system for ERS-1

NASA Technical Reports Server (NTRS)

Hasselmann, Klaus; Hasselmann, Susanne; Bauer, Eva; Bruening, Claus; Lehner, Susanne; Graber, Hans; Lionello, Piero

1988-01-01

The applicability of ERS-1 wind and wave data for wave models was studied using the WAM third generation wave model and SEASAT altimeter, scatterometer and SAR data. A series of global wave hindcasts is made for the surface stress and surface wind fields by assimilation of scatterometer data for the full 96-day SEASAT and also for two wind field analyses for shorter periods by assimilation with the higher resolution ECMWF T63 model and by subjective analysis methods. It is found that wave models respond very sensitively to inconsistencies in wind field analyses and therefore provide a valuable data validation tool. Comparisons between SEASAT SAR image spectra and theoretical SAR spectra derived from the hindcast wave spectra by Monte Carlo simulations yield good overall agreement for 32 cases representing a wide variety of wave conditions. It is concluded that SAR wave imaging is sufficiently well understood to apply SAR image spectra with confidence for wave studies if supported by realistic wave models and theoretical computations of the strongly nonlinear mapping of the wave spectrum into the SAR image spectrum. A closed nonlinear integral expression for this spectral mapping relation is derived which avoids the inherent statistical errors of Monte Carlo computations and may prove to be more efficient numerically.

Hybrid space-airborne bistatic SAR geometric resolutions

NASA Astrophysics Data System (ADS)

Moccia, Antonio; Renga, Alfredo

2009-09-01

Performance analysis of Bistatic Synthetic Aperture Radar (SAR) characterized by arbitrary geometric configurations is usually complex and time-consuming since system impulse response has to be evaluated by bistatic SAR processing. This approach does not allow derivation of general equations regulating the behaviour of image resolutions with varying the observation geometry. It is well known that for an arbitrary configuration of bistatic SAR there are not perpendicular range and azimuth directions, but the capability to produce an image is not prevented as it depends only on the possibility to generate image pixels from time delay and Doppler measurements. However, even if separately range and Doppler resolutions are good, bistatic SAR geometries can exist in which imaging capabilities are very poor when range and Doppler directions become locally parallel. The present paper aims to derive analytical tools for calculating the geometric resolutions of arbitrary configuration of bistatic SAR. The method has been applied to a hybrid bistatic Synthetic Aperture Radar formed by a spaceborne illuminator and a receiving-only airborne forward-looking Synthetic Aperture Radar (F-SAR). It can take advantage of the spaceborne illuminator to dodge the limitations of monostatic FSAR. Basic modeling and best illumination conditions have been detailed in the paper.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

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.

Wavelet Analysis of SAR Images for Coastal Monitoring

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Wu, Sunny Y.; Tseng, William Y.; Pichel, William G.

1998-01-01

The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

Analysis of Benefits and Pitfalls of Satellite SAR for Coastal Area Monitoring

NASA Astrophysics Data System (ADS)

Nunziata, F.; Buono, A.; Mgliaccio, M.; Li, X.; Wei, Y.

2016-08-01

This study aims at describing the outcomes of the Dragon-3 project no. 10689. The undertaken activities deal with coastal area monitoring and they include sea pollution and coastline extraction. The key remote sensing tool is the Synthetic Aperture Radar (SAR) that provides fine resolution images of the microwave reflectivity of the observed scene. However, the interpretation of SAR images is not at all straightforward and all the above-mentioned coastal area applications cannot be easily addressed using single-polarization SAR. Hence, the main outcome of this project is investigating the capability of multi-polarization SAR measurements to generate added-vale product in the frame of coastal area management.

Rapid Disaster Analysis based on Remote Sensing: A Case Study about the Tohoku Tsunami Disaster 2011

NASA Astrophysics Data System (ADS)

Yang, C. H.; Soergel, U.; Lanaras, Ch.; Baltsavias, E.; Cho, K.; Remondino, F.; Wakabayashi, H.

2014-09-01

In this study, we present first results of RAPIDMAP, a project funded by European Union in a framework aiming to foster the cooperation of European countries with Japan in R&D. The main objective of RAPIDMAP is to construct a Decision Support System (DSS) based on remote sensing data and WebGIS technologies, where users can easily access real-time information assisting with disaster analysis. In this paper, we present a case study of the Tohoku Tsunami Disaster 2011. We address two approaches namely change detection based on SAR data and co-registration of optical and SAR satellite images. With respect to SAR data, our efforts are subdivided into three parts: (1) initial coarse change detection for entire area, (2) flood area detection, and (3) linearfeature change detection. The investigations are based on pre- and post-event TerraSAR-X images. In (1), two pre- and post-event TerraSAR-X images are accurately co-registered and radiometrically calibrated. Data are fused in a false-color image that provides a quick and rough overview of potential changes, which is useful for initial decision making and identifying areas worthwhile to be analysed further in more depth. However, a bunch of inevitable false alarms appear within the scene caused by speckle, temporal decorrelation, co-registration inaccuracy and so on. In (2), the post-event TerraSAR-X data are used to extract the flood area by using thresholding and morphological approaches. The validated result indicates that using SAR data combining with suitable morphological approaches is a quick and effective way to detect flood area. Except for usage of SAR data, the false-color image composed of optical images are also used to detect flood area for further exploration in this part. In (3), Curvelet filtering is applied in the difference image of pre- and post-event TerraSAR-X images not only to suppress false alarms of irregular-features, but also to enhance the change signals of linear-features (e.g. buildings) in settlements. Afterwards, thresholding is exploited to extract the linear-feature changes. In rapid mapping of disasters various sensors are often employed, including optical and SAR, since they provide complementary information. Such data needs to be analyzed in an integrated fashion and the results from each dataset should be integrated in a GIS with a common coordinate reference system. Thus, if no orthoimages can be generated, the images should be co-registered employing matching of common features. We present results of co-registration between optical (FORMOSAT-2) and TerraSAR-X images based on different matching methods, and also techniques for detecting and eliminating matching errors.

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

PubMed

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.

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

PubMed Central

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 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. PMID:28792477

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

NASA Astrophysics Data System (ADS)

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.

Combined DEM Extration Method from StereoSAR and InSAR

NASA Astrophysics Data System (ADS)

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.

TerraSAR-X mission

NASA Astrophysics Data System (ADS)

Werninghaus, Rolf

2004-01-01

The TerraSAR-X is a German national SAR- satellite system for scientific and commercial applications. It is the continuation of the scientifically and technologically successful radar missions X-SAR (1994) and SRTM (2000) and will bring the national technology developments DESA and TOPAS into operational use. The space segment of TerraSAR-X is an advanced high-resolution X-Band radar satellite. The system design is based on a sound market analysis performed by Infoterra. The TerraSAR-X features an advanced high-resolution X-Band Synthetic Aperture Radar based on the active phased array technology which allows the operation in Spotlight-, Stripmap- and ScanSAR Mode with various polarizations. It combines the ability to acquire high resolution images for detailed analysis as well as wide swath images for overview applications. In addition, experimental modes like the Dual Receive Antenna Mode allow for full-polarimetric imaging as well as along track interferometry, i.e. moving target identification. The Ground Segment is optimized for flexible response to (scientific and commercial) User requests and fast image product turn-around times. The TerraSAR-X mission will serve two main goals. The first goal is to provide the strongly supportive scientific community with multi-mode X-Band SAR data. The broad spectrum of scientific application areas include Hydrology, Geology, Climatology, Oceanography, Environmental Monitoring and Disaster Monitoring as well as Cartography (DEM Generation) and Interferometry. The second goal is the establishment of a commercial EO-market in Europe which is driven by Infoterra. The commercial goal is the development of a sustainable EO-business so that the e.g. follow-on systems can be completely financed by industry from the profit. Due to its commercial potential, the TerraSAR-X project will be implemented based on a public-private partnership with the Astrium GmbH. This paper will describe first the mission objectives as well as the project organisation and major milestones. Then an overview on the satellite as well as the SAR instrument is given followed by a description of the system design. Finally the principle layout of the TerraSAR-X Ground Segment and some remarks on the European context are presented.

Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern

DOEpatents

Doerry, Armin W.

2013-04-30

Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.; Stiles, J. A.; Frost, F. S.; Shanmugam, K. S.; Smith, S. A.; Narayanan, V.; Holtzman, J. C. (Principal Investigator)

1982-01-01

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

SAR image change detection using watershed and spectral clustering

NASA Astrophysics Data System (ADS)

Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie

2011-12-01

A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.

Differential Shift Estimation in the Absence of Coherence: Performance Analysis and Benefits of Polarimetry

NASA Astrophysics Data System (ADS)

Villano, Michelangelo; Papathanassiou, Konstantinos P.

2011-03-01

The estimation of the local differential shift between synthetic aperture radar (SAR) images has proven to be an effective technique for monitoring glacier surface motion. As images acquired over glaciers by short wavelength SAR systems, such as TerraSAR-X, often suffer from a lack of coherence, image features have to be exploited for the shift estimation (feature-tracking).The present paper addresses feature-tracking with special attention to the feasibility requirements and the achievable accuracy of the shift estimation. In particular, the dependence of the performance on image characteristics, such as texture parameters, signal-to-noise ratio (SNR) and resolution, as well as on processing techniques (despeckling, normalised cross-correlation versus maximum likelihood estimation) is analysed by means of Monte-Carlo simulations. TerraSAR-X data acquired over the Helheim glacier, Greenland, and the Aletsch glacier, Switzerland, have been processed to validate the simulation results.Feature-tracking can benefit of the availability of fully-polarimetric data. As some image characteristics, in fact, are polarisation-dependent, the selection of an optimum polarisation leads to improved performance. Furthermore, fully-polarimetric SAR images can be despeckled without degrading the resolution, so that additional (smaller-scale) features can be exploited.

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

NASA Astrophysics Data System (ADS)

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.

Synthetic aperture radar image formation for the moving-target and near-field bistatic cases

NASA Astrophysics Data System (ADS)

Ding, Yu

This dissertation addresses topics in two areas of synthetic aperture radar (SAR) image formation: time-frequency based SAR imaging of moving targets and a fast backprojection (BP) algorithm for near-field bistatic SAR imaging. SAR imaging of a moving target is a challenging task due to unknown motion of the target. We approach this problem in a theoretical way, by analyzing the Wigner-Ville distribution (WVD) based SAR imaging technique. We derive approximate closed-form expressions for the point-target response of the SAR imaging system, which quantify the image resolution, and show how the blurring in conventional SAR imaging can be eliminated, while the target shift still remains. Our analyses lead to accurate prediction of the target position in the reconstructed images. The derived expressions also enable us to further study additional aspects of WVD-based SAR imaging. Bistatic SAR imaging is more involved than the monostatic SAR case, because of the separation of the transmitter and the receiver, and possibly the changing bistatic geometry. For near-field bistatic SAR imaging, we develop a novel fast BP algorithm, motivated by a newly proposed fast BP algorithm in computer tomography. First we show that the BP algorithm is the spatial-domain counterpart of the benchmark o -- k algorithm in bistatic SAR imaging, yet it avoids the frequency-domain interpolation in the o -- k algorithm, which may cause artifacts in the reconstructed image. We then derive the band-limited property for BP methods in both monostatic and bistatic SAR imaging, which is the basis for developing the fast BP algorithm. We compare our algorithm with other frequency-domain based algorithms, and show that it achieves better reconstructed image quality, while having the same computational complexity as that of the frequency-domain based algorithms.

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

NASA Astrophysics Data System (ADS)

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.

Analysis of urban area land cover using SEASAT Synthetic Aperture Radar data

NASA Technical Reports Server (NTRS)

Henderson, F. M. (Principal Investigator)

1980-01-01

Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.

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

NASA Astrophysics Data System (ADS)

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 monitoring and mapping of groundwater-related subsidence

Method for removing RFI from SAR images

DOEpatents

Doerry, Armin W.

2003-08-19

A method of removing RFI from a SAR by comparing two SAR images on a pixel by pixel basis and selecting the pixel with the lower magnitude to form a composite image. One SAR image is the conventional image produced by the SAR. The other image is created from phase-history data which has been filtered to have the frequency bands containing the RFI removed.

Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

NASA Astrophysics Data System (ADS)

Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.

2017-04-01

Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.

Playback system designed for X-Band SAR

NASA Astrophysics Data System (ADS)

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.

Ground settlement monitoring from temporarily persistent scatterers between two SAR acquisitions

USGS Publications Warehouse

Lei, Z.; Xiaoli, D.; Guangcai, F.; Zhong, L.

2009-01-01

We present an improved differential interferometric synthetic aperture radar (DInSAR) analysis method that measures motions of scatterers whose phases are stable between two SAR acquisitions. Such scatterers are referred to as temporarily persistent scatterers (TPS) for simplicity. Unlike the persistent scatterer InSAR (PS-InSAR) method that relies on a time-series of interferograms, the new algorithm needs only one interferogram. TPS are identified based on pixel offsets between two SAR images, and are specially coregistered based on their estimated offsets instead of a global polynomial for the whole image. Phase unwrapping is carried out based on an algorithm for sparse data points. The method is successfully applied to measure the settlement in the Hong Kong Airport area. The buildings surrounded by vegetation were successfully selected as TPS and the tiny deformation signal over the area was detected. ??2009 IEEE.

Rabi cropped area forecasting of parts of Banaskatha District,Gujarat using MRS RISAT-1 SAR data

NASA Astrophysics Data System (ADS)

Parekh, R. A.; Mehta, R. L.; Vyas, A.

2016-10-01

Radar sensors can be used for large-scale vegetation mapping and monitoring using backscatter coefficients in different polarisations and wavelength bands. Due to cloud and haze interference, optical images are not always available at all phonological stages important for crop discrimination. Moreover, in cloud prone areas, exclusively SAR approach would provide operational solution. This paper presents the results of classifying the cropped and non cropped areas using multi-temporal SAR images. Dual polarised C- band RISAT MRS (Medium Resolution ScanSAR mode) data were acquired on 9thDec. 2012, 28thJan. 2013 and 22nd Feb. 2013 at 18m spatial resolution. Intensity images of two polarisations (HH, HV) were extracted and converted into backscattering coefficient images. Cross polarisation ratio (CPR) images and Radar fractional vegetation density index (RFDI) were created from the temporal data and integrated with the multi-temporal images. Signatures of cropped and un-cropped areas were used for maximum likelihood supervised classification. Separability in cropped and umcropped classes using different polarisation combinations and classification accuracy analysis was carried out. FCC (False Color Composite) prepared using best three SAR polarisations in the data set was compared with LISS-III (Linear Imaging Self-Scanning System-III) image. The acreage under rabi crops was estimated. The methodology developed was for rabi cropped area, due to availability of SAR data of rabi season. Though, the approach is more relevant for acreage estimation of kharif crops when frequent cloud cover condition prevails during monsoon season and optical sensors fail to deliver good quality images.

Multistatic synthetic aperture radar image formation.

PubMed

Krishnan, V; Swoboda, J; Yarman, C E; Yazici, B

2010-05-01

In this paper, we consider a multistatic synthetic aperture radar (SAR) imaging scenario where a swarm of airborne antennas, some of which are transmitting, receiving or both, are traversing arbitrary flight trajectories and transmitting arbitrary waveforms without any form of multiplexing. The received signal at each receiving antenna may be interfered by the scattered signal due to multiple transmitters and additive thermal noise at the receiver. In this scenario, standard bistatic SAR image reconstruction algorithms result in artifacts in reconstructed images due to these interferences. In this paper, we use microlocal analysis in a statistical setting to develop a filtered-backprojection (FBP) type analytic image formation method that suppresses artifacts due to interference while preserving the location and orientation of edges of the scene in the reconstructed image. Our FBP-type algorithm exploits the second-order statistics of the target and noise to suppress the artifacts due to interference in a mean-square sense. We present numerical simulations to demonstrate the performance of our multistatic SAR image formation algorithm with the FBP-type bistatic SAR image reconstruction algorithm. While we mainly focus on radar applications, our image formation method is also applicable to other problems arising in fields such as acoustic, geophysical and medical imaging.

Controlling Data Collection to Support SAR Image Rotation

DOEpatents

Doerry, Armin W.; Cordaro, J. Thomas; Burns, Bryan L.

2008-10-14

A desired rotation of a synthetic aperture radar (SAR) image can be facilitated by adjusting a SAR data collection operation based on the desired rotation. The SAR data collected by the adjusted SAR data collection operation can be efficiently exploited to form therefrom a SAR image having the desired rotational orientation.

Methods of evaluating the effects of coding on SAR data

NASA Technical Reports Server (NTRS)

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.

Working group organizational meeting

NASA Technical Reports Server (NTRS)

1982-01-01

Scene radiation and atmospheric effects, mathematical pattern recognition and image analysis, information evaluation and utilization, and electromagnetic measurements and signal handling are considered. Research issues in sensors and signals, including radar (SAR) reflectometry, SAR processing speed, registration, including overlay of SAR and optical imagery, entire system radiance calibration, and lack of requirements for both sensors and systems, etc. were discussed.

The Advanced Rapid Imaging and Analysis (ARIA) Project's Response to the April 25, 2015 M7.8 Nepal Earthquake: Rapid Measurements and Models for Science and Situational Awareness

NASA Astrophysics Data System (ADS)

Owen, S. E.; Fielding, E. J.; Yun, S. H.; Yue, H.; Polet, J.; Riel, B. V.; Liang, C.; Huang, M. H.; Webb, F.; Simons, M.; Moore, A. W.; Agram, P. S.; Barnhart, W. D.; Hua, H.; Liu, Z.; Milillo, P.; Sacco, G. F.; Rosen, P. A.; Manipon, G.

2015-12-01

On April 25, 2015, the M7.8 Gorkha earthquake struck Nepal and the city of Kathmandu. The quake caused a significant humanitarian crisis and killed more than 8,000 due to widespread building damage and triggered landslides throughout the region. This was the strongest earthquake to occur in the region since the 1934 Nepal-Bihar magnitude 8.0 quake caused more than 10,000 fatalities. In the days following the earthquake, the JPL/Caltech ARIA project produced coseismic GPS and SAR displacements, fault slip models, and damage assessments from SAR coherence change that were helpful in both understanding the event and in the response efforts. The ARIA project produced InSAR observations from two new SAR missions - JAXA's ALOS-2 and ESA's Sentinel 1a. The GPS coseismic displacements showed ~1.8 meters of southward motion and ~1.3 meters of uplift in Kathmandu. InSAR images of the displacement field and fault models show that the rupture extended 135 km southeast of the epicenter. The SAR imagery also confirmed that the fault slip did not extend to the surface, though localized offsets formed due to liquefaction. The GPS and SAR analysis has continued to image the large M7.3 aftershock and postseismic deformation. The damage assessments from coherence change were used by several organizations guiding the response effort, including the NGA, the World Bank, and OFDA/USAID. We will present imaging, modeling, and damage assessment results from the recent April 25, 2015 M7.8 earthquake in Nepal, and its largest aftershock, a M7.3 event on May 12, 2015. We also discuss how these data were used for understanding the event, guiding the response, and for educational outreach.

Segmentation of oil spills in SAR images by using discriminant cuts

NASA Astrophysics Data System (ADS)

Ding, Xianwen; Zou, Xiaolin

2018-02-01

The discriminant cut is used to segment the oil spills in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in SAR images. The real SAR images, i.e. ALOS-1 PALSAR and Sentinel-1 SAR images were collected and used to validate the accuracy of the proposed approach for oil spill segmentation in SAR images. The accuracy of the proposed approach is higher than that of the fuzzy C-means classification method.

The use of the DInSAR method in the monitoring of road damage caused by mining activities

NASA Astrophysics Data System (ADS)

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.

Detecting Subsidence Along a High Speed Railway by Ultrashort Baseline TCP-InSAR with High Resolution Images

NASA Astrophysics Data System (ADS)

Dai, K. R.; Liu, G. X.; Yu, B.; Jia, H. G.; Ma, D. Y.; Wang, X. W.

2013-10-01

A High Speed Railway goes across Wuqing district of Tianjin, China. Historical studies showed that the land subsidence of this area was very serious, which would give rise to huge security risk to the high speed railway. For detecting the detailed subsidence related to the high speed railway, we use the multi-temporal InSAR (MT-InSAR) technique to extract regional scale subsidence of Wuqing district. Take it into consideration that Wuqing district is a suburban region with large area of low coherence farmland, we select the temporarily coherent point InSAR (TCP-InSAR) approach for MT-InSAR analysis. The TCP-InSAR is a potential approach for detecting land subsidence in low coherence areas as it can identify and analysis coherent points between just two images and can acquire a reliable solution without conventional phase unwrapping. This paper extended the TCP-InSAR with use of ultrashort spatial baseline (USB) interferograms. As thetopographic effects are negligible in the USB interferograms, an external digital elevation model (DEM) is no longer needed in interferometric processing, and the parameters needed to be estimated were simplified at the same time. With use of 17 TerraSAR-X (TSX) images acquired from 2009 to 2010 over Wuqing district, the annual subsidence rates along the high speed railway were derived by the USB-TCPInSAR approach. Two subsidence funnels were found at ShuangJie town and around Wuqing Station with subsidence rate of -17 ∼ -27 mm/year and -7 ∼ -17 mm/year, respectively. The subsidence rates derived by USB-TCPInSAR were compared with those derived by the conventional TCP-InSAR that uses an external DEM for differential interferometry. The mean and the standard deviation of the differences between two types of results at 370697 TCPs are -4.43 × 10-6 mm/year and ±1.4673 mm/year, respectively. Further comparison with the subsidence results mentioned in several other studies were made, which shows good consistencies. The results verify that even without using a DEM the USB-TCPInSAR method can detect land subsidence accurately in flat areas.

A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

PubMed Central

Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

2016-01-01

The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application. PMID:27924935

A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions.

PubMed

Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

2016-12-07

The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.

Compact time- and space-integrating SAR processor: performance analysis

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.; Christensen, Marc P.

1995-06-01

Progress made during the previous 12 months toward the fabrication and test of a flight demonstration prototype of the acousto-optic time- and space-integrating real-time SAR image formation processor is reported. Compact, rugged, and low-power analog optical signal processing techniques are used for the most computationally taxing portions of the SAR imaging problem to overcome the size and power consumption limitations of electronic approaches. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results reported for this year include tests of a laboratory version of the RAPID SAR concept on phase history data generated from real SAR high-resolution imagery; a description of the new compact 2D acousto-optic scanner that has a 2D space bandwidth product approaching 106 sports, specified and procured for NEOS Technologies during the last year; and a design and layout of the optical module portion of the flight-worthy prototype.

Automatic SAR/optical cross-matching for GCP monograph generation

NASA Astrophysics Data System (ADS)

Nutricato, Raffaele; Morea, Alberto; Nitti, Davide Oscar; La Mantia, Claudio; Agrimano, Luigi; Samarelli, Sergio; Chiaradia, Maria Teresa

2016-10-01

Ground Control Points (GCP), automatically extracted from Synthetic Aperture Radar (SAR) images through 3D stereo analysis, can be effectively exploited for an automatic orthorectification of optical imagery if they can be robustly located in the basic optical images. The present study outlines a SAR/Optical cross-matching procedure that allows a robust alignment of radar and optical images, and consequently to derive automatically the corresponding sub-pixel position of the GCPs in the optical image in input, expressed as fractional pixel/line image coordinates. The cross-matching in performed in two subsequent steps, in order to gradually gather a better precision. The first step is based on the Mutual Information (MI) maximization between optical and SAR chips while the last one uses the Normalized Cross-Correlation as similarity metric. This work outlines the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight stereo images with different beams and passes are available. The experimental analysis involves different satellite images, in order to evaluate the performances of the algorithm w.r.t. the optical spatial resolution. An assessment of the performances of the algorithm has been carried out, and errors are computed by measuring the distance between the GCP pixel/line position in the optical image, automatically estimated by the tool, and the "true" position of the GCP, visually identified by an expert user in the optical images.

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

NASA Astrophysics Data System (ADS)

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.

Applicability of interferometric SAR technology to ground movement and pipeline monitoring

NASA Astrophysics Data System (ADS)

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.

SAR imaging and hydrodynamic analysis of ocean bottom topographic waves

NASA Astrophysics Data System (ADS)

Zheng, Quanan; Li, Li; Guo, Xiaogang; Ge, Yong; Zhu, Dayong; Li, Chunyan

2006-09-01

The satellite synthetic aperture radar (SAR) images display wave-like patterns of the ocean bottom topographic features at the south outlet of Taiwan Strait (TS). Field measurements indicate that the most TS water body is vertically stratified. However, SAR imaging models available were developed for homogeneous waters. Hence explaining SAR imaging mechanisms of bottom features in a stratified ocean is beyond the scope of those models. In order to explore these mechanisms and to determine the quantitative relations between the SAR imagery and the bottom features, a two-dimensional, three-layer ocean model with sinusoidal bottom topographic features is developed. Analytical solutions and inferences of the momentum equations of the ocean model lead to the following conditions. (1) In the lower layer, the topography-induced waves (topographic waves hereafter) exist in the form of stationary waves, which satisfy a lower boundary resonance condition σ = kC0, here σ is an angular frequency of the stationary waves, k is a wavenumber of bottom topographic corrugation, and C0 is a background current speed. (2) As internal waves, the topographic waves may propagate vertically to the upper layer with an unchanged wavenumber k, if a frequency relation N3 < σ < N2 is satisfied, here N2 and N3 are the Brunt-Wäisälä frequencies of middle layer and upper layer, respectively. (3) The topographic waves are extremely amplified if an upper layer resonance condition is satisfied. The SAR image of topographic waves is derived on the basis of current-modulated small wave spectra. The results indicate that the topographic waves on SAR images have the same wavelength of bottom topographic corrugation, and the imagery brightness peaks are either inphase or antiphase with respect to the topographic corrugation, depending on a sign of a coupling factor. These theoretical predictions are verified by field observations. The results of this study provide a physical basis for quantitative interpretation of SAR images of bottom topographic waves in the stratified ocean.

Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

NASA Astrophysics Data System (ADS)

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.

Numerical Analysis of Orbital Perturbation Effects on Inclined Geosynchronous SAR

PubMed Central

Dong, Xichao; Hu, Cheng; Long, Teng; Li, Yuanhao

2016-01-01

The geosynchronous synthetic aperture radar (GEO SAR) is susceptible to orbit perturbations, leading to orbit drifts and variations. The influences behave very differently from those in low Earth orbit (LEO) SAR. In this paper, the impacts of perturbations on GEO SAR orbital elements are modelled based on the perturbed dynamic equations, and then, the focusing is analyzed theoretically and numerically by using the Systems Tool Kit (STK) software. The accurate GEO SAR slant range histories can be calculated according to the perturbed orbit positions in STK. The perturbed slant range errors are mainly the first and second derivatives, leading to image drifts and defocusing. Simulations of the point target imaging are performed to validate the aforementioned analysis. In the GEO SAR with an inclination of 53° and an argument of perigee of 90°, the Doppler parameters and the integration time are different and dependent on the geometry configurations. Thus, the influences are varying at different orbit positions: at the equator, the first-order phase errors should be mainly considered; at the perigee and apogee, the second-order phase errors should be mainly considered; at other positions, first-order and second-order exist simultaneously. PMID:27598168

Radar image and data fusion for natural hazards characterisation

USGS Publications Warehouse

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.

Simultaneous electroencephalography-functional MRI at 3 T: an analysis of safety risks imposed by performing anatomical reference scans with the EEG equipment in place.

PubMed

Nöth, Ulrike; Laufs, Helmut; Stoermer, Robert; Deichmann, Ralf

2012-03-01

To describe heating effects to be expected in simultaneous electroencephalography (EEG) and magnetic resonance imaging (MRI) when deviating from the EEG manufacturer's instructions; to test which anatomical MRI sequences have a sufficiently low specific absorption rate (SAR) to be performed with the EEG equipment in place; and to suggest precautions to reduce the risk of heating. Heating was determined in vivo below eight EEG electrodes, using both head and body coil transmission and sequences covering the whole range of SAR values. Head transmit coil: temperature increases were below 2.2°C for low SAR sequences, but reached 4.6°C (one subject, clavicle) for high SAR sequences; the equilibrium temperature T(eq) remained below 39°C. Body transmit coil: temperature increases were higher and more frequent over subjects and electrodes, with values below 2.6°C for low SAR sequences, reaching 6.9°C for high SAR sequences (T8 electrode) with T(eq) exceeding a critical level of 40°C. Anatomical imaging should be based on T1-weighted sequences (FLASH, MPRAGE, MDEFT) with an SAR below values for functional MRI sequences based on gradient echo planar imaging. Anatomical sequences with a high SAR can pose a significant risk, which is reduced by using head coil transmission. Copyright © 2011 Wiley-Liss, Inc.

Multitask saliency detection model for synthetic aperture radar (SAR) image and its application in SAR and optical image fusion

NASA Astrophysics Data System (ADS)

Liu, Chunhui; Zhang, Duona; Zhao, Xintao

2018-03-01

Saliency detection in synthetic aperture radar (SAR) images is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR images. We extract four features of the SAR image, which include the intensity, orientation, uniqueness, and global contrast, as the input of the MSD model. The saliency map is generated by the multitask sparsity pursuit, which integrates the multiple features collaboratively. Detection of different scale features is also taken into consideration. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps obtained by the MSD model, we apply the saliency map of the SAR image to the SAR and color optical image fusion. The experimental results of real data show that the saliency map obtained by the MSD model helps to improve the fusion effect, and the salient areas in the SAR image can be highlighted in the fusion results.

Using SAR Interferograms and Coherence Images for Object-Based Delineation of Unstable Slopes

NASA Astrophysics Data System (ADS)

Friedl, Barbara; Holbling, Daniel

2015-05-01

This study uses synthetic aperture radar (SAR) interferometric products for the semi-automated identification and delineation of unstable slopes and active landslides. Single-pair interferograms and coherence images are therefore segmented and classified in an object-based image analysis (OBIA) framework. The rule-based classification approach has been applied to landslide-prone areas located in Taiwan and Southern Germany. The semi-automatically obtained results were validated against landslide polygons derived from manual interpretation.

SAR-based sea traffic monitoring: a reliable approach for maritime surveillance

NASA Astrophysics Data System (ADS)

Renga, Alfredo; Graziano, Maria D.; D'Errico, M.; Moccia, A.; Cecchini, A.

2011-11-01

Maritime surveillance problems are drawing the attention of multiple institutional actors. National and international security agencies are interested in matters like maritime traffic security, maritime pollution control, monitoring migration flows and detection of illegal fishing activities. Satellite imaging is a good way to identify ships but, characterized by large swaths, it is likely that the imaged scenes contain a large number of ships, with the vast majority, hopefully, performing legal activities. Therefore, the imaging system needs a supporting system which identifies legal ships and limits the number of potential alarms to be further monitored by patrol boats or aircrafts. In this framework, spaceborne Synthetic Aperture Radar (SAR) sensors, terrestrial AIS and the ongoing satellite AIS systems can represent a great potential synergy for maritime security. Starting from this idea the paper develops different designs for an AIS constellation able to reduce the time lag between SAR image and AIS data acquisition. An analysis of SAR-based ship detection algorithms is also reported and candidate algorithms identified.

Local region power spectrum-based unfocused ship detection method in synthetic aperture radar images

NASA Astrophysics Data System (ADS)

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.

Monitoring of precursor landslide surface deformation using InSAR image in Kuchi-Sakamoto, Shizuoka Prefecture, Japan

NASA Astrophysics Data System (ADS)

Sato, H. P.; Nakajima, H.; Nakano, T.; Daimaru, H.

2014-12-01

Synthetic Aperture Radar (SAR) is the technique to obtain ground surface images using microwave that is emitted from and received on the antenna. The Kuchi-Sakamoto area, 2.2 km2 in precipitous mountains, central Japan, has suffered from frequent landslides, and slow landslide surface deformation has been monitored by on-site extensometer; however, such the monitoring method cannot detect the deformation in the whole area. Because satellite InSAR is effective tool to monitor slow landslide suface deformation, it is a promising tool for detecting precursor deformation and preparing effective measures against serious landslide disasters. In this study Advanced Land Observing Satellite (ALOS) / Phased Array type L-band SAR (PALSAR) data were used, and InSAR images were produced from the PALSAR data that were observed between 5 Sep 2008 and 21 Oct 2008 (from descending orbit) and between 20 Jul 2008 and 7 Sep 2009 (from ascending orbit). InSAR image from descending orbit was found to detect clear precursor landslide surface deformation on a slope; however, InSAR image on ascending orbit did not always detect clear precursor deformation. It is thought to be related with atmospheric moisture condition, length of observation baseline and so on. Furthermore, after phase unwrapping on InSAR images, 2.5-dimensional deformation was analized. This analysis needed both ascending and descending InSAR images and culculated quasi east-west deformation component (Figs. (a) and (b)) and quasi up-down deformation component (Figs. (c) and (d)). The resulting 2.5D calculation gave westward deformation and mixture of upward and downward deformations on the precursor landslide surface deformation slope (blue circles in Figs. (c) and (d)), where remarkable disrupted deep landslide occurred during Nov 2012 and 25 Jun 2013, judging from result of airborne LiDAR survey and field survey; the occurrence date is not precisely identified. The figure remains the issue that eliminating "real" precursor deformation from other candidate deformations. Preparation of this paper was supported by part of Individual Research Fund in College of Humanities and Sciences, Nihon University and part of Grants-in-Aid for Scientific Research, Challenging Exploratory (#25560185, Principal Investigator: Dr. Hiromu Daimaru).

Sea Surface Wakes Observed by Spaceborne SAR in the Offshore Wind Farms

NASA Astrophysics Data System (ADS)

Li, Xiaoming; Lehner, Susanne; Jacobsen, Sven

2014-11-01

In the paper, we present some X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) images acquired at the offshore wind farms in the North Sea and the East China Sea. The high spatial resolution SAR images show different sea surface wake patterns downstream of the offshore wind turbines. The analysis suggests that there are major two types of wakes among the observed cases. The wind turbine wakes generated by movement of wind around wind turbines are the most often observed cases. In contrast, due to the strong local tidal currents in the near shore wind farm sites, the tidal current wakes induced by tidal current impinging on the wind turbine piles are also observed in the high spatial resolution TS-X images. The discrimination of the two types of wakes observed in the offshore wind farms is also described in the paper.

Wave attenuation in the marginal ice zone during LIMEX

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Vachon, Paris W.; Peng, Chih Y.; Bhogal, A. S.

1992-01-01

The effect of ice cover on ocean-wave attenuation is investigated for waves under flexure in the marginal ice zone (MIZ) with SAR image spectra and the results of models. Directional wavenumber spectra are taken from the SAR image data, and the wave-attenuation rate is evaluated with SAR image spectra and by means of the model by Liu and Mollo-Christensen (1988). Eddy viscosity is described by means of dimensional analysis as a function of ice roughness and wave-induced velocity, and comparisons are made with the remotely sensed data. The model corrects the open-water model by introducing the effects of a continuous ice sheet, and turbulent eddy viscosity is shown to depend on ice thickness, floe sizes, significant wave height, and wave period. SAR and wave-buoy data support the trends described in the model results, and a characteristic rollover is noted in the model and experimental wave-attenuation rates at high wavenumbers.

Chirp Scaling Algorithms for SAR Processing

NASA Technical Reports Server (NTRS)

Jin, M.; Cheng, T.; Chen, M.

1993-01-01

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

NASA Technical Reports Server (NTRS)

Vesecky, John F.; Samadani, Ramin; Smith, Martha P.; Daida, Jason M.; Bracewell, Ronald N.

1988-01-01

The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

SAR image registration based on Susan algorithm

NASA Astrophysics Data System (ADS)

Wang, Chun-bo; Fu, Shao-hua; Wei, Zhong-yi

2011-10-01

Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Spaceborne SAR Imaging Algorithm for Coherence Optimized.

PubMed

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

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.

Spaceborne SAR Imaging Algorithm for Coherence Optimized

PubMed Central

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

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446

Ocean Remote Sensing from Chinese Spaceborne Microwave Sensors

NASA Astrophysics Data System (ADS)

Yang, J.

2017-12-01

GF-3 (GF stands for GaoFen, which means High Resolution in Chinese) is the China's first C band multi-polarization high resolution microwave remote sensing satellite. It was successfully launched on Aug. 10, 2016 in Taiyuan satellite launch center. The synthetic aperture radar (SAR) on board GF-3 works at incidence angles ranging from 20 to 50 degree with several polarization modes including single-polarization, dual-polarization and quad-polarization. GF-3 SAR is also the world's most imaging modes SAR satellite, with 12 imaging modes consisting of some traditional ones like stripmap and scanSAR modes and some new ones like spotlight, wave and global modes. GF-3 SAR is thus a multi-functional satellite for both land and ocean observation by switching the different imaging modes. TG-2 (TG stands for TianGong, which means Heavenly Palace in Chinese) is a Chinese space laboratory which was launched on 15 Sep. 2016 from Jiuquan Satellite Launch Centre aboard a Long March 2F rocket. The onboard Interferometric Imaging Radar Altimeter (InIRA) is a new generation radar altimeter developed by China and also the first on orbit wide swath imaging radar altimeter, which integrates interferometry, synthetic aperture, and height tracking techniques at small incidence angles and a swath of 30 km. The InIRA was switch on to acquire data during this mission on 22 September. This paper gives some preliminary results for the quantitative remote sensing of ocean winds and waves from the GF-3 SAR and the TG-2 InIRA. The quantitative analysis and ocean wave spectra retrieval have been given from the SAR imagery. The image spectra which contain ocean wave information are first estimated from image's modulation using fast Fourier transform. Then, the wave spectra are retrieved from image spectra based on Hasselmann's classical quasi-linear SAR-ocean wave mapping model and the estimation of three modulation transfer functions (MTFs) including tilt, hydrodynamic and velocity bunching modulation. The wind speed is retrieved from InIRA data using a Ku-band low incidence backscatter model (KuLMOD), which relates the backscattering coefficients to the wind speeds and incidence angles. The ocean wave spectra are retrieved linearly from image spectra which extracted first from InIRA data, using a similar procedure for GF-3 SAR data.

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

PubMed Central

You, Hongjian

2018-01-01

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. PMID:29364194

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

PubMed

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.

Ship Speed Retrieval From Single Channel TerraSAR-X Data

NASA Astrophysics Data System (ADS)

Soccorsi, Matteo; Lehner, Susanne

2010-04-01

A method to estimate the speed of a moving ship is presented. The technique, introduced in Kirscht (1998), is extended to marine application and validated on TerraSAR-X High-Resolution (HR) data. The generation of a sequence of single-look SAR images from a single- channel image corresponds to an image time series with reduced resolution. This allows applying change detection techniques on the time series to evaluate the velocity components in range and azimuth of the ship. The evaluation of the displacement vector of a moving target in consecutive images of the sequence allows the estimation of the azimuth velocity component. The range velocity component is estimated by evaluating the variation of the signal amplitude during the sequence. In order to apply the technique on TerraSAR-X Spot Light (SL) data a further processing step is needed. The phase has to be corrected as presented in Eineder et al. (2009) due to the SL acquisition mode; otherwise the image sequence cannot be generated. The analysis, when possible validated by the Automatic Identification System (AIS), was performed in the framework of the ESA project MARISS.

High Resolution Rapid Revisits Insar Monitoring of Surface Deformation

NASA Astrophysics Data System (ADS)

Singhroy, V.; Li, J.; Charbonneau, F.

2014-12-01

Monitoring surface deformation on strategic energy and transportation corridors requires high resolution spatial and temporal InSAR images for mitigation and safety purposes. High resolution air photos, lidar and other satellite images are very useful in areas where the landslides can be fatal. Recently, radar interferometry (InSAR) techniques using more rapid revisit images from several radar satellites are increasingly being used in active deformation monitoring. The Canadian RADARSAT Constellation (RCM) is a three-satellite mission that will provide rapid revisits of four days interferometric (InSAR) capabilities that will be very useful for complex deformation monitoring. For instance, the monitoring of surface deformation due to permafrost activity, complex rock slide motion and steam assisted oil extraction will benefit from this new rapid revisit capability. This paper provide examples of how the high resolution (1-3 m) rapid revisit InSAR capabilities will improve our monitoring of surface deformation and provide insights in understanding triggering mechanisms. We analysed over a hundred high resolution InSAR images over a two year period on three geologically different sites with various configurations of topography, geomorphology, and geology conditions. We show from our analysis that the more frequent InSAR acquisitions are providing more information in understanding the rates of movement and failure process of permafrost triggered retrogressive thaw flows; the complex motion of an asymmetrical wedge failure of an active rock slide and the identification of over pressure zones related to oil extraction using steam injection. Keywords: High resolution, InSAR, rapid revisits, triggering mechanisms, oil extraction.

Synthetic Aperture Radar (SAR) data processing

NASA Technical Reports Server (NTRS)

Beckner, F. L.; Ahr, H. A.; Ausherman, D. A.; Cutrona, L. J.; Francisco, S.; Harrison, R. E.; Heuser, J. S.; Jordan, R. L.; Justus, J.; Manning, B.

1978-01-01

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.

Rapid SAR and GPS Measurements and Models for Hazard Science and Situational Awareness

NASA Astrophysics Data System (ADS)

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 about the potential usefulness of rapid SAR and GPS-based information. We will present progress on our data system technology that enables rapid and reliable production of imagery, as well as lessons learned from our engagement with FEMA and others in the hazard response community on the important actionable information that they need.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Preliminary analysis of the sensitivity of AIRSAR images to soil moisture variations

NASA Technical Reports Server (NTRS)

Pardipuram, Rajan; Teng, William L.; Wang, James R.; Engman, Edwin T.

1993-01-01

Synthetic Aperture Radar (SAR) images acquired from various sources such as Shuttle Imaging Radar B (SIR-B) and airborne SAR (AIRSAR) have been analyzed for signatures of soil moisture. The SIR-B measurements have shown a strong correlation between measurements of surface soil moisture (0-5 cm) and the radar backscattering coefficient sigma(sup o). The AIRSAR measurements, however, indicated a lower sensitivity. In this study, an attempt has been made to investigate the causes for this reduced sensitivity.

Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping

NASA Astrophysics Data System (ADS)

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 DEM without the need of ground control points. This step includes radiometric calibration. (3) A subsequent change detection analysis generates the final map showing the extent of the flash flood on Nov. 5th 2010. The underlying algorithms are provided by three different sources: Geocoding & radiometric calibration (2) is a standard functionality from the commercial SARscape Toolbox for ArcGIS. This toolbox is extended by the filter tool (1), which is called from the SARscape modules in ENVI. The change detection analysis (3) is based on ENVI processing routines and scripted with IDL. (2) and (3) are integrated with ArcGIS using a predefined Python interface. These 3 processing steps are combined using the ArcGIS ModelBuilder to create a new model for rapid disaster mapping in ArcGIS, based on SAR data. Moreover, this model can be dissolved from its desktop environment and published to users across the ArcGIS Server enterprise. Thus disaster zones, e.g. after severe flooding, can be automatically identified and mapped to support local task forces - using an operational workflow for SAR image analysis, which can be executed by the responsible operators without SAR expert knowledge.

Analysis of Multipath Pixels in SAR Images

NASA Astrophysics Data System (ADS)

Zhao, J. W.; Wu, J. C.; Ding, X. L.; Zhang, L.; Hu, F. M.

2016-06-01

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, permittivity)which 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.

SP mountain data analysis

NASA Technical Reports Server (NTRS)

Rawson, R. F.; Hamilton, R. E.; Liskow, C. L.; Dias, A. R.; Jackson, P. L.

1981-01-01

An analysis of synthetic aperture radar data of SP Mountain was undertaken to demonstrate the use of digital image processing techniques to aid in geologic interpretation of SAR data. These data were collected with the ERIM X- and L-band airborne SAR using like- and cross-polarizations. The resulting signal films were used to produce computer compatible tapes, from which four-channel imagery was generated. Slant range-to-ground range and range-azimuth-scale corrections were made in order to facilitate image registration; intensity corrections were also made. Manual interpretation of the imagery showed that L-band represented the geology of the area better than X-band. Several differences between the various images were also noted. Further digital analysis of the corrected data was done for enhancement purposes. This analysis included application of an MSS differencing routine and development of a routine for removal of relief displacement. It was found that accurate registration of the SAR channels is critical to the effectiveness of the differencing routine. Use of the relief displacement algorithm on the SP Mountain data demonstrated the feasibility of the technique.

Brain MR imaging at ultra-low radiofrequency power.

PubMed

Sarkar, Subhendra N; Alsop, David C; Madhuranthakam, Ananth J; Busse, Reed F; Robson, Philip M; Rofsky, Neil M; Hackney, David B

2011-05-01

To explore the lower limits for radiofrequency (RF) power-induced specific absorption rate (SAR) achievable at 1.5 T for brain magnetic resonance (MR) imaging without loss of tissue signal or contrast present in high-SAR clinical imaging in order to create a potentially viable MR method at ultra-low RF power to image tissues containing implanted devices. An institutional review board-approved HIPAA-compliant prospective MR study design was used, with written informed consent from all subjects prior to MR sessions. Seven healthy subjects were imaged prospectively at 1.5 T with ultra-low-SAR optimized three-dimensional (3D) fast spin-echo (FSE) and fluid-attenuated inversion-recovery (FLAIR) T2-weighted sequences and an ultra-low-SAR 3D spoiled gradient-recalled acquisition in the steady state T1-weighted sequence. Corresponding high-SAR two-dimensional (2D) clinical sequences were also performed. In addition to qualitative comparisons, absolute signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) for multicoil, parallel imaging acquisitions were generated by using a Monte Carlo method for quantitative comparison between ultra-low-SAR and high-SAR results. There were minor to moderate differences in the absolute tissue SNR and CNR values and in qualitative appearance of brain images obtained by using ultra-low-SAR and high-SAR techniques. High-SAR 2D T2-weighted imaging produced slightly higher SNR, while ultra-low-SAR 3D technique not only produced higher SNR for T1-weighted and FLAIR images but also higher CNRs for all three sequences for most of the brain tissues. The 3D techniques adopted here led to a decrease in the absorbed RF power by two orders of magnitude at 1.5 T, and still the image quality was preserved within clinically acceptable imaging times. RSNA, 2011

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

USGS Publications Warehouse

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 structures mostly hidden from view on the ground and on Landsat images by a relatively thin, but extensive blanket of blow sand. Basement rock units and associated fractures at the Bir Safsaf are clearly delineated using C- and L-band SAR images. The detectability of most geologic features depend primarily on radar frequency. The SIR-C/X-SAR data also provide recommendations about the utility of certain radar configurations for geologic and paleoenvironmental reconnaissance in deserts.

Research on vehicle detection based on background feature analysis in SAR images

NASA Astrophysics Data System (ADS)

Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping

2017-10-01

Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.

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

PubMed Central

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

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

PubMed

Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling

2018-03-03

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.

Preliminary results of the comparative study between EO-1/Hyperion and ALOS/PALSAR

NASA Astrophysics Data System (ADS)

Koizumi, E.; Furuta, R.; Yamamoto, A.

2011-12-01

[Introduction]Hyper-spectral remote sensing images have been used for land-cover classification due to their high spectral resolutions. Synthetic Aperture Radar (SAR) remote sensing data are also useful to probe surface condition because radar image reflects surface geometry, although there are not so many reports about the land-cover detection with combination use of both hyper-spectral data and SAR data. Among SAR sensors, L-band SAR is thought to be useful tool to find physical properties because its comparatively long wave length can through small objects on surface. We are comparing the result of land cover classification and/or physical values from hyper-spectral and L-band SAR data to find the relationship between these two quite different sensors and to confirm the possibility of the combined analysis of hyper-spectral and L-band SAR data, and in this presentation we will report the preliminary result of this study. There are only few sources of both hyper-spectral and L-band SAR data from the space in this time, however, several space organizations plan to launch new satellites on which hyper-spectral or L-band SAR equipments are mounted in next few years. So, the importance of the combined analysis will increase more than ever. [Target Area]We are performing and planning analyses on the following areas in this study. (a)South of Cairo, Nile river area, Egypt, for sand, sandstone, limestone, river, crops. (b)Mount Sakurajima, Japan, for igneous rock and other related geological property. [Methods and Results]EO-1 Hyperion data are analyzed in this study as hyper-spectral data. The Hyperion equipment has 242 channels but some of them include full noise or have no data. We selected channels for analysis by checking each channel, and select about 150 channels (depend on the area). Before analysis, the atmospheric correction of ATCOR-3 was applied for the selected channels. The corrected data were analyzed by unsupervised classification or principal component analysis (PCA). We also did the unsupervised classification with the several components from PCA. According to the analysis results, several classifications can be extracted for each category (vegetation, sand and rocks, and water). One of the interesting results is that there are a few classes for sand as those of other categories, and these classes seem to reflect artificial and natural surface changes that are some result of excavation or scratching. ALOS PALSAR data are analyzed as L-band SAR data. We selected the Dual Polarization data for each target area. The data were converted to backscattered images, and then calculated some image statistic values. The topographic information also calculates with SAR interferometry technique as reference. Comparing the Hyperion classification results with the result of the calculation of statistic values from PALSAR, there are some areas where relativities seem to be confirmed. To confirm the combined analysis between hyper-spectral and L-band SAR data to detect and classify the surface material, further studies are still required. We will continue to investigate more efficient analytic methods and to examine other functions like the adopted channels, the number of class in classification, the kind of statistic information, and so on, to refine the method.

A novel multi-band SAR data technique for fully automatic oil spill detection in the ocean

NASA Astrophysics Data System (ADS)

Del Frate, Fabio; Latini, Daniele; Taravat, Alireza; Jones, Cathleen E.

2013-10-01

With the launch of the Italian constellation of small satellites for the Mediterranean basin observation COSMO-SkyMed and the German TerraSAR-X missions, the delivery of very high-resolution SAR data to observe the Earth day or night has remarkably increased. In particular, also taking into account other ongoing missions such as Radarsat or those no longer working such as ALOS PALSAR, ERS-SAR and ENVISAT the amount of information, at different bands, available for users interested in oil spill analysis has become highly massive. Moreover, future SAR missions such as Sentinel-1 are scheduled for launch in the very next years while additional support can be provided by Uninhabited Aerial Vehicle (UAV) SAR systems. Considering the opportunity represented by all these missions, the challenge is to find suitable and adequate image processing multi-band procedures able to fully exploit the huge amount of data available. In this paper we present a new fast, robust and effective automated approach for oil-spill monitoring starting from data collected at different bands, polarizations and spatial resolutions. A combination of Weibull Multiplicative Model (WMM), Pulse Coupled Neural Network (PCNN) and Multi-Layer Perceptron (MLP) techniques is proposed for achieving the aforementioned goals. One of the most innovative ideas is to separate the dark spot detection process into two main steps, WMM enhancement and PCNN segmentation. The complete processing chain has been applied to a data set containing C-band (ERS-SAR, ENVISAT ASAR), X-band images (Cosmo-SkyMed and TerraSAR-X) and L-band images (UAVSAR) for an overall number of more than 200 images considered.

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

PubMed

Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli

2009-01-01

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.

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

PubMed Central

Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli

2009-01-01

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. PMID:22399966

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

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.

Calibrating a hydraulic model using water levels derived from time series high-resolution Radarsat-2 synthetic aperture radar images and elevation data

NASA Astrophysics Data System (ADS)

Trudel, M.; Desrochers, N.; Leconte, R.

2017-12-01

Knowledge of water extent (WE) and level (WL) of rivers is necessary to calibrate and validate hydraulic models and thus to better simulate and forecast floods. Synthetic aperture radar (SAR) has demonstrated its potential for delineating water bodies, as backscattering of water is much lower than that of other natural surfaces. The ability of SAR to obtain information despite cloud cover makes it an interesting tool for temporal monitoring of water bodies. The delineation of WE combined with a high-resolution digital terrain model (DTM) allows extracting WL. However, most research using SAR data to calibrate hydraulic models has been carried out using one or two images. The objectives of this study is to use WL derived from time series high resolution Radarsat-2 SAR images for the calibration of a 1-D hydraulic model (HEC-RAS). Twenty high-resolution (5 m) Radarsat-2 images were acquired over a 40 km reach of the Athabasca River, in northern Alberta, Canada, between 2012 and 2016, covering both low and high flow regimes. A high-resolution (2m) DTM was generated combining information from LIDAR data and bathymetry acquired between 2008 and 2016 by boat surveying. The HEC-RAS model was implemented on the Athabasca River to simulate WL using cross-sections spaced by 100 m. An image histogram thresholding method was applied on each Radarsat-2 image to derive WE. WE were then compared against each cross-section to identify those were the slope of the banks is not too abrupt and therefore amenable to extract WL. 139 observations of WL at different locations along the river reach and with streamflow measurements were used to calibrate the HEC-RAS model. The RMSE between SAR-derived and simulated WL is under 0.35 m. Validation was performed using in situ observations of WL measured in 2008, 2012 and 2016. The RMSE between the simulated water levels calibrated with SAR images and in situ observations is less than 0.20 m. In addition, a critical success index (CSI) was performed to compare the WE simulated by HEC-RAS and that derived from SARs images. The CSI is higher than 0.85 for each date, which means that simulated WE is highly similar to the WE derived from SARs images. Thereby, the results of our analysis indicate that calibration of a hydraulic model can be performed from WL derived from time series of high-resolution SAR images.

Remote sensing of a dynamic sub-arctic peatland reservoir using optical and synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Larter, Jarod Lee

Stephens Lake, Manitoba is an example of a peatland reservoir that has undergone physical changes related to mineral erosion and peatland disintegration processes since its initial impoundment. In this thesis I focused on the processes of peatland upheaval, transport, and disintegration as the primary drivers of dynamic change within the reservoir. The changes related to these processes are most frequent after initial reservoir impoundment and decline over time. They continue to occur over 35 years after initial flooding. I developed a remote sensing approach that employs both optical and microwave sensors for discriminating land (Le. floating peatlands, forested land, and barren land) from open water within the reservoir. High spatial resolution visible and near-infrared (VNIR) optical data obtained from the QuickBird satellite, and synthetic aperture radar (SAR) microwave data obtained from the RADARSAT-1 satellite were implemented. The approach was facilitated with a Geographic Information System (GIS) based validation map for the extraction of optical and SAR pixel data. Each sensor's extracted data set was first analyzed separately using univariate and multivariate statistical methods to determine the discriminant ability of each sensor. The initial analyses were followed by an integrated sensor approach; the development of an image classification model; and a change detection analysis. Results showed excellent (> 95%) classification accuracy using QuickBird satellite image data. Discrimination and classification of studied land cover classes using SAR image texture data resulted in lower overall classification accuracies (˜ 60%). SAR data classification accuracy improved to > 90% when classifying only land and water, demonstrating SAR's utility as a land and water mapping tool. An integrated sensor data approach showed no considerable improvement over the use of optical satellite image data alone. An image classification model was developed that could be used to map both detailed land cover classes and the land and water interface within the reservoir. Change detection analysis over a seven year period indicated that physical changes related to mineral erosion, peatland upheaval, transport, and disintegration, and operational water level variation continue to take place in the reservoir some 35 years after initial flooding. This thesis demonstrates the ability of optical and SAR satellite image remote sensing data sets to be used in an operational context for the routine discrimination of the land and water boundaries within a dynamic peatland reservoir. Future monitoring programs would benefit most from a complementary image acquisition program in which SAR images, known for their acquisition reliability under cloud cover, are acquired along with optical images given their ability to discriminate land cover classes in greater detail.

Multisensor analysis of hydrologic features with emphasis on the Seasat SAR

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.

1981-01-01

Synthetic aperture radar (SAR) imagery of the Wind River Range area in Wyoming is compared with visible and near-infrared imagery of the same area. Data from the Seasat L-Band SAR and an aircraft X-Band SAR are compared with Landsat Return Beam Vidicon (RBV) visible data and near-infrared aerial photography and topographic maps of the same area. It is noted that visible and near-infrared data provide more information than the SAR data when conditions are the most favorable. The SAR penetrates clouds and snow, however, and data can be acquired day or night. Drainage density detail is good on SAR imagery because individual streams show up well owing to riparian vegetation; this causes higher radar reflections which result from the 'rough' surface which vegetation creates. In the winter image, the X-Band radar data show high returns because of cracks on the lake ice surfaces. High returns can also be seen in the L-Band SAR imagery of the lakes due to ripples on the surface induced by wind. It is concluded that the use of multispectral data would optimize analysis of hydrologic features.

Satellite Remote Sensing of Ocean Winds, Surface Waves and Surface Currents during the Hurricanes

NASA Astrophysics Data System (ADS)

Zhang, G.; Perrie, W. A.; Liu, G.; Zhang, L.

2017-12-01

Hurricanes over the ocean have been observed by spaceborne aperture radar (SAR) since the first SAR images were available in 1978. SAR has high spatial resolution (about 1 km), relatively large coverage and capability for observations during almost all-weather, day-and-night conditions. In this study, seven C-band RADARSAT-2 dual-polarized (VV and VH) ScanSAR wide images from the Canadian Space Agency (CSA) Hurricane Watch Program in 2017 are collected over five hurricanes: Harvey, Irma, Maria, Nate, and Ophelia. We retrieve the ocean winds by applying our C-band Cross-Polarization Coupled-Parameters Ocean (C-3PO) wind retrieval model [Zhang et al., 2017, IEEE TGRS] to the SAR images. Ocean waves are estimated by applying a relationship based on the fetch- and duration-limited nature of wave growth inside hurricanes [Hwang et al., 2016; 2017, J. Phys. Ocean.]. We estimate the ocean surface currents using the Doppler Shift extracted from VV-polarized SAR images [Kang et al., 2016, IEEE TGRS]. C-3PO model is based on theoretical analysis of ocean surface waves and SAR microwave backscatter. Based on the retrieved ocean winds, we estimate the hurricane center locations, maxima wind speeds, and radii of the five hurricanes by adopting the SHEW model (Symmetric Hurricane Estimates for Wind) by Zhang et al. [2017, IEEE TGRS]. Thus, we investigate possible relations between hurricane structures and intensities, and especially some possible effects of the asymmetrical characteristics on changes in the hurricane intensities, such as the eyewall replacement cycle. The three SAR images of Ophelia include the north coast of Ireland and east coast of Scotland allowing study of ocean surface currents respond to the hurricane. A system of methods capable of observing marine winds, surface waves, and surface currents from satellites is of value, even if these data are only available in near real-time or from SAR-related satellite images. Insight into high resolution ocean winds, waves and currents in hurricanes can be useful for intensity prediction, which has had relatively few improvements in the past 25 years. In 2018 RADARSAT Constellation Mission will be launched, increasing SAR coverage by 10×, allowing increased observations during the next hurricane season.

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

Using SAR and GPS for Hazard Management and Response: Progress and Examples from the Advanced Rapid Imaging and Analysis (ARIA) Project

NASA Astrophysics Data System (ADS)

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

2014-12-01

ARIA is a joint JPL/Caltech project to automate synthetic aperture radar (SAR) and GPS imaging capabilities for scientific understanding, hazard response, and societal benefit. We have built a prototype SAR and GPS data system that forms the foundation for hazard monitoring and response capability, as well as providing imaging capabilities important for science studies. Together, InSAR and GPS have the ability to capture surface deformation in high spatial and temporal resolution. For earthquakes, this deformation provides information that is complementary to seismic data on location, geometry and magnitude of earthquakes. Accurate location information is critical for understanding the regions affected by damaging shaking. Regular surface deformation measurements from SAR and GPS are useful for monitoring changes related to many processes that are important for hazard and resource management such as volcanic deformation, groundwater withdrawal, and landsliding. Observations of SAR coherence change have a demonstrated use for damage assessment for hazards such as earthquakes, tsunamis, hurricanes, and volcanic eruptions. These damage assessment maps can be made from imagery taken day or night and are not affected by clouds, making them valuable complements to optical imagery. The coherence change caused by the damage from hazards (building collapse, flooding, ash fall) is also detectable with intelligent algorithms, allowing for rapid generation of damage assessment maps over large areas at fine resolution, down to the spatial scale of single family homes. We will present the progress and results we have made on automating the analysis of SAR data for hazard monitoring and response using data from the Italian Space Agency's (ASI) COSMO-SkyMed constellation of X-band SAR satellites. Since the beginning of our project with ASI, our team has imaged deformation and coherence change caused by many natural hazard events around the world. We will present progress on our data system technology that enables rapid and reliable production of imagery. Lastly, we participated in the March 2014 FEMA exercise based on a repeat of the 1964 M9.2 Alaska earthquake, providing simulated data products for use in this hazards response exercise. We will present lessons learned from this and other simulation exercises.

Study on Landslide Disaster Extraction Method Based on Spaceborne SAR Remote Sensing Images - Take Alos Palsar for AN Example

NASA Astrophysics Data System (ADS)

Xue, D.; Yu, X.; Jia, S.; Chen, F.; Li, X.

2018-04-01

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.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

A Wavelet Polarization Decomposition Net Model for Polarimetric SAR Image Classification

NASA Astrophysics Data System (ADS)

He, Chu; Ou, Dan; Yang, Teng; Wu, Kun; Liao, Mingsheng; Chen, Erxue

2014-11-01

In this paper, a deep model based on wavelet texture has been proposed for Polarimetric Synthetic Aperture Radar (PolSAR) image classification inspired by recent successful deep learning method. Our model is supposed to learn powerful and informative representations to improve the generalization ability for the complex scene classification tasks. Given the influence of speckle noise in Polarimetric SAR image, wavelet polarization decomposition is applied first to obtain basic and discriminative texture features which are then embedded into a Deep Neural Network (DNN) in order to compose multi-layer higher representations. We demonstrate that the model can produce a powerful representation which can capture some untraceable information from Polarimetric SAR images and show a promising achievement in comparison with other traditional SAR image classification methods for the SAR image dataset.

Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, J. X.; Zhao, Z.; Ma, A. D.

2015-06-01

Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It's of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.

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

NASA Astrophysics Data System (ADS)

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.

Interferometric synthetic aperture radar: Building tomorrow's tools today

USGS Publications Warehouse

Lu, Zhong

2006-01-01

A synthetic aperture radar (SAR) system transmits electromagnetic (EM) waves at a wavelength that can range from a few millimeters to tens of centimeters. The radar wave propagates through the atmosphere and interacts with the Earth’s surface. Part of the energy is reflected back to the SAR system and recorded. Using a sophisticated image processing technique, called SAR processing (Curlander and McDonough, 1991), both the intensity and phase of the reflected (or backscattered) signal of each ground resolution element (a few meters to tens of meters) can be calculated in the form of a complex-valued SAR image representing the reflectivity of the ground surface. The amplitude or intensity of the SAR image is determined primarily by terrain slope, surface roughness, and dielectric constants, whereas the phase of the SAR image is determined primarily by the distance between the satellite antenna and the ground targets, slowing of the signal by the atmosphere, and the interaction of EM waves with ground surface. Interferometric SAR (InSAR) imaging, a recently developed remote sensing technique, utilizes the interaction of EM waves, referred to as interference, to measure precise distances. Very simply, InSAR involves the use of two or more SAR images of the same area to extract landscape topography and its deformation patterns.

SAR Ambiguity Study for the Cassini Radar

NASA Technical Reports Server (NTRS)

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.

The contribution of satellite SAR-derived displacement measurements in landslide risk management practices

NASA Astrophysics Data System (ADS)

Raspini, Federico; Bardi, Federica; Bianchini, Silvia; Ciampalini, Andrea; Del Ventisette, Chiara; Farina, Paolo; Ferrigno, Federica; Solari, Lorenzo; Casagli, Nicola

2017-04-01

Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern in many countries, including Italy. With 13% of the territory prone to landslides, Italy is one of the European countries with the highest landslide hazard, and on a worldwide scale, it is second only to Japan among the technologically advanced countries. Over the last 15 years, an increasing number of applications have aimed to demonstrate the applicability of images captured by space-borne Synthetic Aperture Radar (SAR) sensors in slope instability investigations. InSAR (SAR Interferometry) is currently one of the most exploited techniques for the assessment of ground displacements, and it is becoming a consolidated tool for Civil Protection institutions in addressing landslide risk. We present a subset of the results obtained in Italy within the framework of SAR-based programmes and applications intended to test the potential application of C- and X-band satellite interferometry during different Civil Protection activities (namely, prevention, prevision, emergency response and post-emergency phases) performed to manage landslide risk. In all phases, different benefits can be derived from the use of SAR-based measurements, which were demonstrated to be effective in the field of landslide analysis. Analysis of satellite-SAR data is demonstrated to play a major role in the investigation of landslide-related events at different stages, including detection, mapping, monitoring, characterization and prediction. Interferometric approaches are widely consolidated for analysis of slow-moving slope deformations in a variety of environments, and exploitation of the amplitude data in SAR images is a somewhat natural complement for rapid-moving landslides. In addition, we discuss the limitations that still exist and must be overcome in the coming years to manage the transition of satellite SAR systems towards complete operational use in landslide risk management practices.

Application of Lipschitz Regularity and Multiscale Techniques for the Automatic Detection of Oil Spills in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

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

2015-12-01

This research presents a promising new method for the detection and tracking of oil spills from Synthetic Aperture Radar (SAR) data. The method presented here combines a number of advanced image processing techniques in order to overcome some common performance limitations of SAR-based oil spill detection. Principal among these limitations are: (1) the radar cross section of the ocean surface strongly depends on wind and wave activities and is therefore highly variable; (2) the radar cross section of oil covered waters is often indistinguishable from other dark ocean features such as low wind areas or oil lookalikes, leading to ambiguities in oil spill detection. In this paper, we introduce two novel image analysis techniques to largely mitigate the aforementioned performance limitations, namely Lipschitz regularity (LR) and Wavelet transforms. We used LR, an image texture parameter akin to the slope of the local power spectrum, in our approach to mitigate these limitations. We show that the LR parameter is much less sensitive to variations of wind and waves than the original image amplitude, lending itself well for normalizing image content. Beyond its benefit for image normalization, we also show that the LR transform enhances the contrast between oil-covered and oil-free ocean surfaces and therefore improves overall spill detection performance. To calculate LR, the SAR images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), which are furthermore transformed into Holder space to measure LR. Finally, we demonstrate that the implementation of wavelet transforms provide additional benefits related to the adaptive reduction of speckle noise. We show how LR and CWT are integrated into our image analysis workflow for application to oil spill detection. To describe the performance of this approach under controlled conditions, we applied our method to simulated SAR data of wind driven oceans containing oil spills of various properties. We also show applications to several real life oil spill scenarios using a series of L-band ALOS PALSAR images and X-band TerraSAR-X images acquired during the Deep Water Horizon spill in the Gulf of Mexico in 2010. From our analysis, we concluded that the LR and CWT have distinct advantages in oil spill detection and lead to high performance spill mapping results.

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

NASA Astrophysics Data System (ADS)

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.

A discussion on the use of X-band SAR images in marine applications

NASA Astrophysics Data System (ADS)

Schiavulli, D.; Sorrentino, A.; Migliaccio, M.

2012-10-01

The Synthetic Aperture Radar (SAR) is able to generate images of the sea surface that can be exploited to extract geophysical information of environmental interest. In order to enhance the operational use of these data in the marine applications the revisit time is to be improved. This goal can be achieved by using SAR virtual or real constellations and/or exploiting new antenna technologies that allow huge swath and fine resolution. Within this framework, the presence of the Italian and German X-band SAR constellations is of special interest while the new SAR technologies are not nowadays operated. Although SAR images are considered to be independent of weather conditions, this is only partially true at higher frequencies, e.g. X-band. In fact, observations can present signature corresponding to high intensity precipitating clouds, i.e. rain cells. Further, ScanSAR images may be characterized by the presence of processing artifacts, called scalloping, that corrupt image interpretation. In this paper we review these key facts that are at the basis of an effective use of X-band SAR images for marine applications.

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

NASA Astrophysics Data System (ADS)

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 in Japan, Merapi in Indonesia. Preliminary results reveal that the fractal dimension of natural areas, being related only to the roughness of the observed surface, is very stable as the radar illumination geometry, the resolution and the wavelength change, thus holding a very unique property in SAR data inversion. Such a behavior is not verified in case of non-natural objects. As a matter of fact, when the fractal estimation is performed in the presence of either man-made objects or SAR image features depending on geometrical distortions due to the SAR system acquisition (i.e. layover, shadowing), fractal dimension (D) values outside the range of fractality of natural surfaces (2 < D < 3) are retrieved. These non-fractal characteristics show to be heavily dependent on sensor acquisition parameters (e.g. view angle, resolution). In this work, the behaviour of the maps generated starting from the C- and X- band SAR data, relevant to all the considered volcanoes, is analyzed: the distribution of the obtained fractal dimension values is investigated on different zones of the maps. In particular, it is verified that the fore-slope and back-slope areas of the image share a very similar fractal dimension distribution that is placed around the mean value of D=2.3. We conclude that, in this context, the fractal dimension could be considered as a signature of the identification of the volcano growth as a natural process. The COSMO-SkyMed data used in this study have been processed at IREA-CNR within the SAR4Volcanoes project under Italian Space Agency agreement n. I/034/11/0.

Composite SAR imaging using sequential joint sparsity

NASA Astrophysics Data System (ADS)

Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.

2017-06-01

This paper investigates accurate and efficient ℓ1 regularization methods for generating synthetic aperture radar (SAR) images. Although ℓ1 regularization algorithms are already employed in SAR imaging, practical and efficient implementation in terms of real time imaging remain a challenge. Here we demonstrate that fast numerical operators can be used to robustly implement ℓ1 regularization methods that are as or more efficient than traditional approaches such as back projection, while providing superior image quality. In particular, we develop a sequential joint sparsity model for composite SAR imaging which naturally combines the joint sparsity methodology with composite SAR. Our technique, which can be implemented using standard, fractional, or higher order total variation regularization, is able to reduce the effects of speckle and other noisy artifacts with little additional computational cost. Finally we show that generalizing total variation regularization to non-integer and higher orders provides improved flexibility and robustness for SAR imaging.

InSAR time series analysis of ALOS-2 ScanSAR data and its implications for NISAR

NASA Astrophysics Data System (ADS)

Liang, C.; Liu, Z.; Fielding, E. J.; Huang, M. H.; Burgmann, R.

2017-12-01

The JAXA's ALOS-2 mission was launched on May 24, 2014. It operates at L-band and can acquire data in multiple modes. ScanSAR is the main operational mode and has a 350 km swath, somewhat larger than the 250 km swath of the SweepSAR mode planned for the NASA-ISRO SAR (NISAR) mission. ALOS-2 has been acquiring a wealth of L-band InSAR data. These data are of particular value in areas of dense vegetation and high relief. The InSAR technical development for ALOS-2 also enables the preparation for the upcoming NISAR mission. We have been developing advanced InSAR processing techniques for ALOS-2 over the past two years. Here, we report the important issues for doing InSAR time series analysis using ALOS-2 ScanSAR data. First, we present ionospheric correction techniques for both regular ScanSAR InSAR and MAI (multiple aperture InSAR) ScanSAR InSAR. We demonstrate the large-scale ionospheric signals in the ScanSAR interferograms. They can be well mitigated by the correction techniques. Second, based on our technical development of burst-by-burst InSAR processing for ALOS-2 ScanSAR data, we find that the azimuth Frequency Modulation (FM) rate error is an important issue not only for MAI, but also for regular InSAR time series analysis. We identify phase errors caused by azimuth FM rate errors during the focusing process of ALOS-2 product. The consequence is mostly a range ramp in the InSAR time series result. This error exists in all of the time series results we have processed. We present the correction techniques for this error following a theoretical analysis. After corrections, we present high quality ALOS-2 ScanSAR InSAR time series results in a number of areas. The development for ALOS-2 can provide important implications for NISAR mission. For example, we find that in most cases the relative azimuth shift caused by ionosphere can be as large as 4 m in a large area imaged by ScanSAR. This azimuth shift is half of the 8 m azimuth resolution of the SweepSAR mode planned for NISAR, which implies that a good coregistration strategy for NISAR's SweepSAR mode is geometrical coregistration followed by MAI or spectral diversity analysis. Besides, our development also provides implications for the processing and system parameter requirements of NISAR, such as the accuracy requirement of azimuth FM rate and range timing.

An ice-motion tracking system at the Alaska SAR facility

NASA Technical Reports Server (NTRS)

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.

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

PubMed

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.

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

PubMed Central

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

Relationships between autofocus methods for SAR and self-survey techniques for SONAR. [Synthetic Aperture Radar (SAR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahl, D.E.; Jakowatz, C.V. Jr.; Ghiglia, D.C.

1991-01-01

Autofocus methods in SAR and self-survey techniques in SONAR have a common mathematical basis in that they both involve estimation and correction of phase errors introduced by sensor position uncertainties. Time delay estimation and correlation methods have been shown to be effective in solving the self-survey problem for towed SONAR arrays. Since it can be shown that platform motion errors introduce similar time-delay estimation problems in SAR imaging, the question arises as to whether such techniques could be effectively employed for autofocus of SAR imagery. With a simple mathematical model for motion errors in SAR, we will show why suchmore » correlation/time-delay techniques are not nearly as effective as established SAR autofocus algorithms such as phase gradient autofocus or sub-aperture based methods. This analysis forms an important bridge between signal processing methodologies for SAR and SONAR. 5 refs., 4 figs.« less

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

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.

Development Of Polarimetric Decomposition Techniques For Indian Forest Resource Assessment Using Radar Imaging Satellite (Risat-1) Images

NASA Astrophysics Data System (ADS)

Sridhar, J.

2015-12-01

The focus of this work is to examine polarimetric decomposition techniques primarily focussed on Pauli decomposition and Sphere Di-Plane Helix (SDH) decomposition for forest resource assessment. The data processing methods adopted are Pre-processing (Geometric correction and Radiometric calibration), Speckle Reduction, Image Decomposition and Image Classification. Initially to classify forest regions, unsupervised classification was applied to determine different unknown classes. It was observed K-means clustering method gave better results in comparison with ISO Data method.Using the algorithm developed for Radar Tools, the code for decomposition and classification techniques were applied in Interactive Data Language (IDL) and was applied to RISAT-1 image of Mysore-Mandya region of Karnataka, India. This region is chosen for studying forest vegetation and consists of agricultural lands, water and hilly regions. Polarimetric SAR data possess a high potential for classification of earth surface.After applying the decomposition techniques, classification was done by selecting region of interests andpost-classification the over-all accuracy was observed to be higher in the SDH decomposed image, as it operates on individual pixels on a coherent basis and utilises the complete intrinsic coherent nature of polarimetric SAR data. Thereby, making SDH decomposition particularly suited for analysis of high-resolution SAR data. The Pauli Decomposition represents all the polarimetric information in a single SAR image however interpretation of the resulting image is difficult. The SDH decomposition technique seems to produce better results and interpretation as compared to Pauli Decomposition however more quantification and further analysis are being done in this area of research. The comparison of Polarimetric decomposition techniques and evolutionary classification techniques will be the scope of this work.

Space Radar Image of Kilauea, Hawaii

NASA Technical Reports Server (NTRS)

1994-01-01

Data acquired on April 13, 1994 and on October 4, 1994 from the X-band Synthetic Aperture Radar on board the space shuttle Endeavour were used to generate interferometric fringes, which were overlaid on the X-SAR image of Kilauea. The volcano is centered in this image at 19.58 degrees north latitude and 155.55 degrees west longitude. The image covers about 9 kilometers by 13 kilometers (5.6 miles by 8 miles). The X-band fringes correspond clearly to the expected topographic image. The yellow line indicates the area below which was used for the three-dimensional image using altitude lines. The yellow rectangular frame fences the area for the final topographic image. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR. The Instituto Ricerca Elettromagnetismo Componenti Elettronici (IRECE) at the University of Naples was a partner in interferometry analysis.

Despeckling Polsar Images Based on Relative Total Variation Model

NASA Astrophysics Data System (ADS)

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.

Colorizing SENTINEL-1 SAR Images Using a Variational Autoencoder Conditioned on SENTINEL-2 Imagery

NASA Astrophysics Data System (ADS)

Schmitt, M.; Hughes, L. H.; Körner, M.; Zhu, X. X.

2018-05-01

In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Technical Reports Server (NTRS)

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.

Pre-Processes for Urban Areas Detection in SAR Images

NASA Astrophysics Data System (ADS)

Altay Açar, S.; Bayır, Ş.

2017-11-01

In this study, pre-processes for urban areas detection in synthetic aperture radar (SAR) images are examined. These pre-processes are image smoothing, thresholding and white coloured regions determination. Image smoothing is carried out to remove noises then thresholding is applied to obtain binary image. Finally, candidate urban areas are detected by using white coloured regions determination. All pre-processes are applied by utilizing the developed software. Two different SAR images which are acquired by TerraSAR-X are used in experimental study. Obtained results are shown visually.

Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

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

2014-12-01

Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images acquired in 2010. The comparison showed exceptional performance of our method. This method can be applied to emergency management and decision support systems with a need for real-time data, and it shows great potential for rapid data analysis in other areas, including volcano detection, flood boundaries, forest health, and wildfires.

An Improved Method of AGM for High Precision Geolocation of SAR Images

NASA Astrophysics Data System (ADS)

Zhou, G.; He, C.; Yue, T.; Huang, W.; Huang, Y.; Li, X.; Chen, Y.

2018-05-01

In order to take full advantage of SAR images, it is necessary to obtain the high precision location of the image. During the geometric correction process of images, to ensure the accuracy of image geometric correction and extract the effective mapping information from the images, precise image geolocation is important. This paper presents an improved analytical geolocation method (IAGM) that determine the high precision geolocation of each pixel in a digital SAR image. This method is based on analytical geolocation method (AGM) proposed by X. K. Yuan aiming at realizing the solution of RD model. Tests will be conducted using RADARSAT-2 SAR image. Comparing the predicted feature geolocation with the position as determined by high precision orthophoto, results indicate an accuracy of 50m is attainable with this method. Error sources will be analyzed and some recommendations about improving image location accuracy in future spaceborne SAR's will be given.

Structural Information Detection Based Filter for GF-3 SAR Images

NASA Astrophysics Data System (ADS)

Sun, Z.; Song, Y.

2018-04-01

GF-3 satellite with high resolution, large swath, multi-imaging mode, long service life and other characteristics, can achieve allweather and all day monitoring for global land and ocean. It has become the highest resolution satellite system in the world with the C-band multi-polarized synthetic aperture radar (SAR) satellite. However, due to the coherent imaging system, speckle appears in GF-3 SAR images, and it hinders the understanding and interpretation of images seriously. Therefore, the processing of SAR images has big challenges owing to the appearance of speckle. The high-resolution SAR images produced by the GF-3 satellite are rich in information and have obvious feature structures such as points, edges, lines and so on. The traditional filters such as Lee filter and Gamma MAP filter are not appropriate for the GF-3 SAR images since they ignore the structural information of images. In this paper, the structural information detection based filter is constructed, successively including the point target detection in the smallest window, the adaptive windowing method based on regional characteristics, and the most homogeneous sub-window selection. The despeckling experiments on GF-3 SAR images demonstrate that compared with the traditional filters, the proposed structural information detection based filter can well preserve the points, edges and lines as well as smooth the speckle more sufficiently.

Interferometric synthetic aperture radar (InSAR)—its past, present and future

USGS Publications Warehouse

Lu, Zhong; Kwoun, Oh-Ig; Rykhus, R.P.

2007-01-01

Very simply, interferometric synthetic aperture radar (InSAR) involves the use of two or more synthetic aperture radar (SAR) images of the same area to extract landscape topography and its deformation patterns. A SAR system transmits electromagnetic waves at a wavelength that can range from a few millimeters to tens of centimeters and therefore can operate during day and night under all-weather conditions. Using SAR processing technique (Curlander and McDonough, 1991), both the intensity and phase of the reflected (or backscattered) radar signal of each ground resolution element (a few meters to tens of meters) can be calculated in the form of a complex-valued SAR image that represents the reflectivity of the ground surface. The amplitude or intensity of the SAR image is determined primarily by terrain slope, surface roughness, and dielectric constants, whereas the phase of the SAR image is determined primarily by the distance between the satellite antenna and the ground targets. InSAR imaging utilizes the interaction of electromagnetic waves, referred to as interference, to measure precise distances between the satellite antenna and ground resolution elements to derive landscape topography and its subtle change in elevation.

Mapping slope movements in Alpine environments using TerraSAR-X interferometric methods

NASA Astrophysics Data System (ADS)

Barboux, Chloé; Strozzi, Tazio; Delaloye, Reynald; Wegmüller, Urs; Collet, Claude

2015-11-01

Mapping slope movements in Alpine environments is an increasingly important task in the context of climate change and natural hazard management. We propose the detection, mapping and inventorying of slope movements using different interferometric methods based on TerraSAR-X satellite images. Differential SAR interferograms (DInSAR), Persistent Scatterer Interferometry (PSI), Short-Baseline Interferometry (SBAS) and a semi-automated texture image analysis are presented and compared in order to determine their contribution for the automatic detection and mapping of slope movements of various velocity rates encountered in Alpine environments. Investigations are conducted in a study region of about 6 km × 6 km located in the Western Swiss Alps using a unique large data set of 140 DInSAR scenes computed from 51 summer TerraSAR-X (TSX) acquisitions from 2008 to 2012. We found that PSI is able to precisely detect only points moving with velocities below 3.5 cm/yr in the LOS, with a root mean squared error of about 0.58 cm/yr compared to DGPS records. SBAS employed with 11 days summer interferograms increases the range of detectable movements to rates up to 35 cm/yr in the LOS with a root mean squared error of 6.36 cm/yr, but inaccurate measurements due to phase unwrapping are already possible for velocity rates larger than 20 cm/year. With the semi-automated texture image analysis the rough estimation of the velocity rates over an outlined moving zone is accurate for rates of "cm/day", "dm/month" and "cm/month", but due to the decorrelation of yearly TSX interferograms this method fails for the observation of slow movements in the "cm/yr" range.

Comparisons between wave directional spectra from SAR and pressure sensor arrays

NASA Technical Reports Server (NTRS)

Pawka, S. S.; Inman, D. L.; Hsiao, S. V.; Shemdin, O. H.

1980-01-01

Simultaneous directional wave measurements were made at Torrey Pines Beach, California, by a synthetic aperture radar (SAR) and a linear array of pressure sensors. The measurements were conducted during the West Coast Experiment in March 1977. Quantitative comparisons of the normalized directional spectra from the two systems were made for wave periods of 6.9-17.0 s. The comparison results were variable but generally showed good agreement of the primary mode of the normalized directional energy. An attempt was made to quantify the physical criteria for good wave imaging in the SAR. A frequency band analysis of wave parameters such as band energy, slope, and orbital velocity did not show good correlation with the directional comparisons. It is noted that absolute values of the wave height spectrum cannot be derived from the SAR images yet and, consequently, no comparisons of absolute energy levels with corresponding array measurements were intended.

Information extraction and transmission techniques for spaceborne synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Yurovsky, L.; Watson, E.; Townsend, K.; Gardner, S.; Boberg, D.; Watson, J.; Minden, G. J.; Shanmugan, K. S.

1984-01-01

Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.

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

NASA Astrophysics Data System (ADS)

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.

The Performance Analysis Based on SAR Sample Covariance Matrix

PubMed Central

Erten, Esra

2012-01-01

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. PMID:22736976

Performance analysis of multiple PRF technique for ambiguity resolution

NASA Technical Reports Server (NTRS)

Chang, C. Y.; Curlander, J. C.

1992-01-01

For short wavelength spaceborne synthetic aperture radar (SAR), ambiguity in Doppler centroid estimation occurs when the azimuth squint angle uncertainty is larger than the azimuth antenna beamwidth. Multiple pulse recurrence frequency (PRF) hopping is a technique developed to resolve the ambiguity by operating the radar in different PRF's in the pre-imaging sequence. Performance analysis results of the multiple PRF technique are presented, given the constraints of the attitude bound, the drift rate uncertainty, and the arbitrary numerical values of PRF's. The algorithm performance is derived in terms of the probability of correct ambiguity resolution. Examples, using the Shuttle Imaging Radar-C (SIR-C) and X-SAR parameters, demonstrate that the probability of correct ambiguity resolution obtained by the multiple PRF technique is greater than 95 percent and 80 percent for the SIR-C and X-SAR applications, respectively. The success rate is significantly higher than that achieved by the range cross correlation technique.

First Image Products from EcoSAR - Osa Peninsula, Costa Rica

NASA Technical Reports Server (NTRS)

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.

Mapping tectonic and anthropogenic processes in central California using satellite and airborne InSAR

NASA Astrophysics Data System (ADS)

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 subsidence in the SJV due to over-exploitation of groundwater. InSAR time series are compared to GPS and well-water hydraulic head in-situ time series to understand water storage processes and mass loading changes. We present model results to assess the influence of anthropogenic processes on surface deformation and fault mechanics.

Advanced InSAR imaging for dune mapping

NASA Astrophysics Data System (ADS)

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 extensively in the field. High resolution TerraSAR-X (TSX) images, covering the entire research area were acquired for the period of October 2011 to July 2012 (15 images in total). All images were co-registreted, the first image was used as the master image. A coherence index was calculated for all the images. Analysis was performed in GIS software. The results display minor changes (coherence index in range of 0.4-0.65) on dune crests depending on the dune location relative to its distance from the sea and distance from the city. In addition, field results indicate erosion / deposition of sand in a cumulatively amount of approximately 30mm annually. The results of this study confirm that it is possible to monitor subtle changes in dunes and to identify dune stability or instability, only by the use of SAR images.

Contextual descriptors and neural networks for scene analysis in VHR SAR images

NASA Astrophysics Data System (ADS)

Del Frate, Fabio; Picchiani, Matteo; Falasco, Alessia; Schiavon, Giovanni

2016-10-01

The development of SAR technology during the last decade has made it possible to collect a huge amount of data over many regions of the world. In particular, the availability of SAR images from different sensors, with metric or sub-metric spatial resolution, offers novel opportunities in different fields as land cover, urban monitoring, soil consumption etc. On the other hand, automatic approaches become crucial for the exploitation of such a huge amount of information. In such a scenario, especially if single polarization images are considered, the main issue is to select appropriate contextual descriptors, since the backscattering coefficient of a single pixel may not be sufficient to classify an object on the scene. In this paper a comparison among three different approaches for contextual features definition is presented so as to design optimum procedures for VHR SAR scene understanding. The first approach is based on Gray Level Co- Occurrence Matrix since it is widely accepted and several studies have used it for land cover classification with SAR data. The second approach is based on the Fourier spectra and it has been already proposed with positive results for this kind of problems, the third one is based on Auto-associative Neural Networks which have been already proven effective for features extraction from polarimetric SAR images. The three methods are evaluated in terms of the accuracy of the classified scene when the features extracted using each method are considered as input to a neural network classificator and applied on different Cosmo-SkyMed spotlight products.

Characterization and Mitigation of Radio Frequency Interference in PolSAR Data

NASA Astrophysics Data System (ADS)

Tao, Mingliang; Zhou, Feng; Zhang, Zijing

2017-11-01

Polarimetric synthetic aperture radar (PolSAR) is a very important instrument for active remote sensing. However, it is common to find that PolSAR echoes are often contaminated by incoherent electromagnetic interference, which is referred to as radio frequency interference (RFI). The analysis of RFI signatures and its influence on PolSAR data seems to be lacking in existing literatures, especially for PolSAR post products, such as the polarimetric decomposition parameters and clustering result. The goal of this paper is to reveal the link between RFI and polarization, as well as to analyze the impact of interference on PolSAR image and its post products. Qualitative and quantitative analyses of the adverse impact of RFI on the real measured NASA/Jet Propulsion Laboratory (JPL) Uninhabited Aerial Vehicle Synthetic Aperture Radar data set are illustrated from two perspectives, that is, evaluation of imaging quality and interpretation of scattering mechanisms. The point target response and effective number of looks are evaluated for assessing the distortion to focusing quality. Further, we discussed the characteristics of ultra wideband RFI and proposed a mitigation method using nonnegative matrix factorization along azimuth direction. The experimental results indicate the effectiveness of the proposed method.

Superresolution SAR Imaging Algorithm Based on Mvm and Weighted Norm Extrapolation

NASA Astrophysics Data System (ADS)

Zhang, P.; Chen, Q.; Li, Z.; Tang, Z.; Liu, J.; Zhao, L.

2013-08-01

In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.

Burnt area mapping from ERS-SAR time series using the principal components transformation

NASA Astrophysics Data System (ADS)

Gimeno, Meritxell; San-Miguel Ayanz, Jesus; Barbosa, Paulo M.; Schmuck, Guido

2003-03-01

Each year thousands of hectares of forest burnt across Southern Europe. To date, remote sensing assessments of this phenomenon have focused on the use of optical satellite imagery. However, the presence of clouds and smoke prevents the acquisition of this type of data in some areas. It is possible to overcome this problem by using synthetic aperture radar (SAR) data. Principal component analysis (PCA) was performed to quantify differences between pre- and post- fire images and to investigate the separability over a European Remote Sensing (ERS) SAR time series. Moreover, the transformation was carried out to determine the best conditions to acquire optimal SAR imagery according to meteorological parameters and the procedures to enhance burnt area discrimination for the identification of fire damage assessment. A comparative neural network classification was performed in order to map and to assess the burnts using a complete ERS time series or just an image before and an image after the fire according to the PCA. The results suggest that ERS is suitable to highlight areas of localized changes associated with forest fire damage in Mediterranean landcover.

A method to calibrate channel friction and bathymetry parameters of a Sub-Grid hydraulic model using SAR flood images

NASA Astrophysics Data System (ADS)

Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.; Bates, P. D.

2015-12-01

Synthetic Aperture Radar (SAR) satellites are capable of all-weather day and night observations that can discriminate between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR satellite data to improve our understanding of water processes, in particular for fluvial flood inundation mechanisms. Past studies prove that integrating SAR derived data with hydraulic models can improve simulations of flooding. However while much of this work focusses on improving model channel roughness values or inflows in ungauged catchments, improvement of model bathymetry is often overlooked. The provision of good bathymetric data is critical to the performance of hydraulic models but there are only a small number of ways to obtain bathymetry information where no direct measurements exist. Spatially distributed river depths are also rarely available. We present a methodology for calibration of model average channel depth and roughness parameters concurrently using SAR images of flood extent and a Sub-Grid model utilising hydraulic geometry concepts. The methodology uses real data from the European Space Agency's archive of ENVISAT[1] Wide Swath Mode images of the River Severn between Worcester and Tewkesbury during flood peaks between 2007 and 2010. Historic ENVISAT WSM images are currently free and easy to access from archive but the methodology can be applied with any available SAR data. The approach makes use of the SAR image processing algorithm of Giustarini[2] et al. (2013) to generate binary flood maps. A unique feature of the calibration methodology is to also use parameter 'identifiability' to locate the parameters with higher accuracy from a pre-assigned range (adopting the DYNIA method proposed by Wagener[3] et al., 2003). [1] https://gpod.eo.esa.int/services/ [2] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 4. [3] Wagener. 2003. 'Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis'. Hydrol. Process. 17, 455-476.

Ship Detection in SAR Image Based on the Alpha-stable Distribution

PubMed Central

Wang, Changcheng; Liao, Mingsheng; Li, Xiaofeng

2008-01-01

This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alpha-stable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. PMID:27873794

Schatten Matrix Norm Based Polarimetric SAR Data Regularization Application over Chamonix Mont-Blanc

NASA Astrophysics Data System (ADS)

Le, Thu Trang; Atto, Abdourrahmane M.; Trouve, Emmanuel

2013-08-01

The paper addresses the filtering of Polarimetry Synthetic Aperture Radar (PolSAR) images. The filtering strategy is based on a regularizing cost function associated with matrix norms called the Schatten p-norms. These norms apply on matrix singular values. The proposed approach is illustrated upon scattering and coherency matrices on RADARSAT-2 PolSAR images over the Chamonix Mont-Blanc site. Several p values of Schatten p-norms are surveyed and their capabilities on filtering PolSAR images is provided in comparison with conventional strategies for filtering PolSAR data.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

The Research on Dryland Crop Classification Based on the Fusion of SENTINEL-1A SAR and Optical Images

NASA Astrophysics Data System (ADS)

Liu, F.; Chen, T.; He, J.; Wen, Q.; Yu, F.; Gu, X.; Wang, Z.

2018-04-01

In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.

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

PubMed

Li, Xiaofeng; Zheng, Weizhong; Zou, Cheng-Zhi; Pichel, William G

2008-05-21

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.

Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

Clutter modeling of the Denver Airport and surrounding areas

NASA Technical Reports Server (NTRS)

Harrah, Steven D.; Delmore, Victor E.; Onstott, Robert G.

1991-01-01

To accurately simulate and evaluate an airborne Doppler radar as a wind shear detection and avoidance sensor, the ground clutter surrounding a typical airport must be quantified. To do this, an imaging airborne Synthetic Aperture Radar (SAR) was employed to investigate and map the normalized radar cross sections (NRCS) of the ground terrain surrounding the Denver Stapleton Airport during November of 1988. Images of the Stapleton ground clutter scene were obtained at a variety of aspect and elevation angles (extending to near-grazing) at both HH and VV polarizations. Presented here, in viewgraph form with commentary, are the method of data collection, the specific observations obtained of the Denver area, a summary of the quantitative analysis performed on the SAR images to date, and the statistical modeling of several of the more interesting stationary targets in the SAR database. Additionally, the accompanying moving target database, containing NRCS and velocity information, is described.

Application of Polarimetric-Interferometric Phase Coherence Optimization (PIPCO) Procedure to SIR-C/X-SAR Tien-Shan Tracks 122.20(94 Oct. 08)/154.20(94 Oct. 09) Repeat-Orbit C/L-Band Pol-D-InSAR Imag

NASA Technical Reports Server (NTRS)

Boerner, W. M.; Mott, H.; Verdi, J.; Darizhapov, D.; Dorjiev, B.; Tsybjito, T.; Korsunov, V.; Tatchkov, G.; Bashkuyev, Y.; Cloude, S.;

Large-Scale Sentinel-1 Processing for Solid Earth Science and Urgent Response using Cloud Computing and Machine Learning

NASA Astrophysics Data System (ADS)

Hua, H.; Owen, S. E.; Yun, S. H.; Agram, P. S.; Manipon, G.; Starch, M.; Sacco, G. F.; Bue, B. D.; Dang, L. B.; Linick, J. P.; Malarout, N.; Rosen, P. A.; Fielding, E. J.; Lundgren, P.; Moore, A. W.; Liu, Z.; Farr, T.; Webb, F.; Simons, M.; Gurrola, E. M.

2017-12-01

With the increased availability of open SAR data (e.g. Sentinel-1 A/B), new challenges are being faced with processing and analyzing the voluminous SAR datasets to make geodetic measurements. Upcoming SAR missions such as NISAR are expected to generate close to 100TB per day. The Advanced Rapid Imaging and Analysis (ARIA) project can now generate geocoded unwrapped phase and coherence products from Sentinel-1 TOPS mode data in an automated fashion, using the ISCE software. This capability is currently being exercised on various study sites across the United States and around the globe, including Hawaii, Central California, Iceland and South America. The automated and large-scale SAR data processing and analysis capabilities use cloud computing techniques to speed the computations and provide scalable processing power and storage. Aspects such as how to processing these voluminous SLCs and interferograms at global scales, keeping up with the large daily SAR data volumes, and how to handle the voluminous data rates are being explored. Scene-partitioning approaches in the processing pipeline help in handling global-scale processing up to unwrapped interferograms with stitching done at a late stage. We have built an advanced science data system with rapid search functions to enable access to the derived data products. Rapid image processing of Sentinel-1 data to interferograms and time series is already being applied to natural hazards including earthquakes, floods, volcanic eruptions, and land subsidence due to fluid withdrawal. We will present the status of the ARIA science data system for generating science-ready data products and challenges that arise from being able to process SAR datasets to derived time series data products at large scales. For example, how do we perform large-scale data quality screening on interferograms? What approaches can be used to minimize compute, storage, and data movement costs for time series analysis in the cloud? We will also present some of our findings from applying machine learning and data analytics on the processed SAR data streams. We will also present lessons learned on how to ease the SAR community onto interfacing with these cloud-based SAR science data systems.

Synthetic aperture design for increased SAR image rate

DOEpatents

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.

Comparison of Shuttle Imaging Radar-B ocean wave image spectra with linear model predictions based on aircraft measurements

NASA Technical Reports Server (NTRS)

Monaldo, Frank M.; Lyzenga, David R.

1988-01-01

During October 1984, coincident Shuttle Imaging Radar-B synthetic aperture radar (SAR) imagery and wave measurements from airborne instrumentation were acquired. The two-dimensional wave spectrum was measured by both a radar ocean-wave spectrometer and a surface-contour radar aboard the aircraft. In this paper, two-dimensional SAR image intensity variance spectra are compared with these independent measures of ocean wave spectra to verify previously proposed models of the relationship between such SAR image spectra and ocean wave spectra. The results illustrate both the functional relationship between SAR image spectra and ocean wave spectra and the limitations imposed on the imaging of short-wavelength, azimuth-traveling waves.

Evaluation of the Potentials and Challenges of an Airborne InSAR System for Deformation Mapping: A Case Study over the Slumgullion Landslide

NASA Astrophysics Data System (ADS)

Cao, N.; Lee, H.; Zaugg, E.; Shrestha, R. L.; Carter, W. E.; Glennie, C. L.; Wang, G.; Lu, Z.; Diaz, J. C. F.

2016-12-01

Synthetic aperture radar (SAR) interferometry (InSAR) is a technique which uses two or more SAR images of the same area to estimate landscape topography or ground surface displacement. Differential InSAR (DInSAR) is capable of measuring ground displacements at the millimeter level, but a major drawback of traditional DInSAR is that only the deformation along the line-of-sight direction can be detected. Because most of the current spaceborne SAR systems have near-polar, sun-synchronous orbits, deformation measurements in the South-North direction are limited (except for polar regions). Compared with spaceborne SAR, airborne SAR systems have the advantages of flexible scanning geometry and revisit time, high spatial resolution, and no ionospheric distortion. In this study, we present a case study of the Slumgullion landslide conducted in July 2015 to assess an airborne SAR system known as ARTEMIS SlimSAR, which is a compact, modular, and multi-frequency radar system. The Slumgullion landslide, located in the San Juan Mountains near Lake City, Colorado is a long-term slow moving landslide that moves downhill continuously. For this study, the L-band SlimSAR was installed and data were collected on July 3, 7, and 10 and processed using the time-domain backprojection algorithm. GPS surveys and spaceborne DInSAR analysis using COSMO-SkyMed images were also conducted to verify the performance of the airborne SAR system. The airborne DInSAR results showed satisfying agreement with the GPS and spaceborne DInSAR results. The root mean square of the differences between the SlimSAR, and GPS and satellite derived velocities, were 0.6 mm/day, and 0.9 mm/day, respectively. A 3-D deformation map over Slumgullion landslide was generated, which displayed distinct correlation between the landslide motion and topography. This study also indicated that the primary source of the error for the SlimSAR system is the trajectory turbulences of the aircraft. The effect of the trajectory turbulences is analyzed and several possible solutions are proposed to improve the airborne SAR performance. In the long run, an improved airborne SAR system will open avenues for differential interferometry to be used in scientific studies and commercial applications previously prohibited by orbital constraints of spaceborne SAR.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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

2016-01-01

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. PMID:27070606

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

PubMed

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.

Automatic Coregistration for Multiview SAR Images in Urban Areas

NASA Astrophysics Data System (ADS)

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.

Analysis of Wind and Sea State in SAR data of Hurricanes

NASA Astrophysics Data System (ADS)

Hoja, D.; Schulz-Stellenfleth, J.; Lehner, S.; Horstmann, J.

2003-04-01

Spaceborne synthetic aperture radar (SAR) is still the only instrument providing directional ocean wave and in addition surface wind information on a global and continuous basis. Operating in ASAR wave mode ENVISAT, launched in 2002, provides 10 km x 5 km SAR images every 100 km along the orbit. These SAR data continue and expand the SAR era of the European Remote Sensing satellites ERS-1 and ERS-2, which have acquired similar SAR data since 1991 on a global basis. To not only use the official ERS SAR wave mode product, which consists only of the SAR image power spectrum, but also the full SAR image information a subset of 27 days globally distributed ERS-2 SAR raw data were processed to single look complex SAR imagettes using the BSAR processor developed at the German Aerospace Center. These data have the same format as the official ESA product for ENVISAT ASAR wave mode data. This subset of 34,000 ERS-2 SAR imagettes was used to develop and validate algorithms for wind and wave retrieval, which are also applicable to ENVISAT ASAR wave mode data. The time frame of the dataset covers several tropical cyclones in the Atlantic Ocean of which hurricane Fran has been investigated in detail together with additional data available from scatterometers, buoys and weather centers. Hurricane Fran was active from August 23 to September 8, 1996. During this time, hurricane Fran developed near the African coast and progressed over the North Atlantic Ocean. Landfall occurred on September 5, 1996 at the coast of North Carolina, USA. Fran was part of a whole series of tropical cyclones travelling about the same course in a short time. The wind is extracted from SAR imagery and compared to results of the numerical model output provided by the European Center for Medium-Range Weather Forecast (ECMWF) and co-located ERS-2 scatterometer measurements. The Swell and wind sea systems generated by the tropical cyclones are measured using SAR cross spectra and a newly developed partitioning technique. For each component wave system (partition) spectral parameters like wavelength and wave propagation direction are calculated and compared to numerical model output provided by ECMWF. The progression of the tropical cyclones is presented and it is described, how the hurricanes are portrayed in the SAR data. The response of waves to fast turning winds is analyzed. Conclusions are drawn about the wave model forecast in hurricane situations using satellite wave mode data. Keywords: Hurricanes, SAR, ocean winds, ocean waves, wind sea and swell

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

NASA Astrophysics Data System (ADS)

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.

SAR processing using SHARC signal processing systems

NASA Astrophysics Data System (ADS)

Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.

1998-09-01

Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.

Marine Targets Detection in Pol-SAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong

2016-08-01

In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.

SAR imaging - Seeing the unseen

NASA Technical Reports Server (NTRS)

Kobrick, M.

1982-01-01

The functional abilities and operations of synthetic aperture radar (SAR) are described. SAR employs long wavelength radio waves in bursts, imaging a target by 'listening' to the small frequency changes that result from the Doppler shift due to the relative motion of the imaging craft and the motions of the target. The time delay of the signal return allows a determination of the location of the target, leading to the build up of a two-dimensional image. The uses of both Doppler shifts and time delay enable detailed imagery which is independent of distance. The synthetic aperture part of the name of SAR derives from the beaming of multiple pulses, which result in a picture that is effectively the same as using a large antenna. Mechanisms contributing to the fineness of SAR images are outlined.

Comparative Study of Speckle Filtering Methods in PolSAR Radar Images

NASA Astrophysics Data System (ADS)

Boutarfa, S.; Bouchemakh, L.; Smara, Y.

2015-04-01

Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria: smoothing homogeneous areas, preserving edges and polarimetric information.Experimental results are included to illustrate the different implemented methods.

Calibration and Validation of Airborne InSAR Geometric Model

NASA Astrophysics Data System (ADS)

Chunming, Han; huadong, Guo; Xijuan, Yue; Changyong, Dou; Mingming, Song; Yanbing, Zhang

2014-03-01

The image registration or geo-coding is a very important step for many applications of airborne interferometric Synthetic Aperture Radar (InSAR), especially for those involving Digital Surface Model (DSM) generation, which requires an accurate knowledge of the geometry of the InSAR system. While the trajectory and attitude instabilities of the aircraft introduce severe distortions in three dimensional (3-D) geometric model. The 3-D geometrical model of an airborne SAR image depends on the SAR processor itself. Working at squinted model, i.e., with an offset angle (squint angle) of the radar beam from broadside direction, the aircraft motion instabilities may produce distortions in airborne InSAR geometric relationship, which, if not properly being compensated for during SAR imaging, may damage the image registration. The determination of locations of the SAR image depends on the irradiated topography and the exact knowledge of all signal delays: range delay and chirp delay (being adjusted by the radar operator) and internal delays which are unknown a priori. Hence, in order to obtain reliable results, these parameters must be properly calibrated. An Airborne InSAR mapping system has been developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS) to acquire three-dimensional geo-spatial data with high resolution and accuracy. To test the performance of the InSAR system, the Validation/Calibration (Val/Cal) campaign has carried out in Sichun province, south-west China, whose results will be reported in this paper.

Stability Analysis of Railway Subgrade in Mining Area Based on Dinsar

NASA Astrophysics Data System (ADS)

Xu, J.; Hu, J.; Ding, J.

2018-04-01

DInSAR technology have been applied to monitor the mining subsidence and the stability of the railway subgrade. A total of 10 Sentinel-1A images acquired from 2015/9/26 to 2016/2/23 were used in DInSAR analysis. The study mining area is about 13.4 km2. Mining have induced serious land subsidence involve a large area that causing different levels of damages to infrastructures on the land. There is an important railway near the mining area, the DInSAR technology is applied to analyse the subsidence near the railway, which can warn early the possible deformation that may occur during underground mining. The DInSAR results was verified by the field measurement. The results show that the mining did not cause subsidence of railway subgrade and did not affect the stability of railway subgrade.

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

NASA Astrophysics Data System (ADS)

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.

Research on Airborne SAR Imaging Based on Esc Algorithm

NASA Astrophysics Data System (ADS)

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.

Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model

NASA Astrophysics Data System (ADS)

Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Eerdenbrugh, Katrien Van; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; Baets, Bernard De; Bates, Paul D.; Verhoest, Niko E. C.

2017-02-01

Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modelled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.

Impact of the Timing of a SAR Image Acquisition on the Calibration of a Flood Inundation Model

NASA Technical Reports Server (NTRS)

Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Van Eerdenbrugh, Katrien; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; De Baets, Bernard;

MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?

PubMed

Deledalle, Charles-Alban; Denis, Loic; Tabti, Sonia; Tupin, Florence

2017-09-01

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.

Change detection in multitemporal synthetic aperture radar images using dual-channel convolutional neural network

NASA Astrophysics Data System (ADS)

Liu, Tao; Li, Ying; Cao, Ying; Shen, Qiang

2017-10-01

This paper proposes a model of dual-channel convolutional neural network (CNN) that is designed for change detection in SAR images, in an effort to acquire higher detection accuracy and lower misclassification rate. This network model contains two parallel CNN channels, which can extract deep features from two multitemporal SAR images. For comparison and validation, the proposed method is tested along with other change detection algorithms on both simulated SAR images and real-world SAR images captured by different sensors. The experimental results demonstrate that the presented method outperforms the state-of-the-art techniques by a considerable margin.

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

NASA Astrophysics Data System (ADS)

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.

Flight path-driven mitigation of wavefront curvature effects in SAR images

DOEpatents

Doerry, Armin W [Albuquerque, NM

2009-06-23

A wavefront curvature effect associated with a complex image produced by a synthetic aperture radar (SAR) can be mitigated based on which of a plurality of possible flight paths is taken by the SAR when capturing the image. The mitigation can be performed differently for different ones of the flight paths.

SAR image classification based on CNN in real and simulation datasets

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Direct Geolocation of TerraSAR-X Spotlight Mode Image and Error Correction

NASA Astrophysics Data System (ADS)

Zhou, Xiao; Zeng, Qiming; Jiao, Jian; Zhang, Jingfa; Gong, Lixia

2013-01-01

The GERMAN TerraSAR-X mission was launched in June 2007, operating a versatile new-generation SAR sensor in X-band. Its Spotlight mode providing SAR images at very high resolution of about 1m. The product’s specified 3-D geolocation accuracy is tightened to 1m according to the official technical report. However, this accuracy is able to be achieved relies on not only robust mathematical basis of SAR geolocation, but also well knowledge of error sources and their correction. The research focuses on geolocation of TerraSAR-X spotlight image. Mathematical model and resolving algorithms have been analyzed. Several error sources have been researched and corrected especially. The effectiveness and accuracy of the research was verified by the experiment results.

Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Feng; Dong, Junyu; Li, Bo; Xu, Qizhi; Xie, Cui

2016-10-01

Change detection is of high practical value to hazard assessment, crop growth monitoring, and urban sprawl detection. A synthetic aperture radar (SAR) image is the ideal information source for performing change detection since it is independent of atmospheric and sunlight conditions. Existing SAR image change detection methods usually generate a difference image (DI) first and use clustering methods to classify the pixels of DI into changed class and unchanged class. Some useful information may get lost in the DI generation process. This paper proposed an SAR image change detection method based on neighborhood-based ratio (NR) and extreme learning machine (ELM). NR operator is utilized for obtaining some interested pixels that have high probability of being changed or unchanged. Then, image patches centered at these pixels are generated, and ELM is employed to train a model by using these patches. Finally, pixels in both original SAR images are classified by the pretrained ELM model. The preclassification result and the ELM classification result are combined to form the final change map. The experimental results obtained on three real SAR image datasets and one simulated dataset show that the proposed method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.

Coastline detection with time series of SAR images

NASA Astrophysics Data System (ADS)

Ao, Dongyang; Dumitru, Octavian; Schwarz, Gottfried; Datcu, Mihai

2017-10-01

For maritime remote sensing, coastline detection is a vital task. With continuous coastline detection results from satellite image time series, the actual shoreline, the sea level, and environmental parameters can be observed to support coastal management and disaster warning. Established coastline detection methods are often based on SAR images and wellknown image processing approaches. These methods involve a lot of complicated data processing, which is a big challenge for remote sensing time series. Additionally, a number of SAR satellites operating with polarimetric capabilities have been launched in recent years, and many investigations of target characteristics in radar polarization have been performed. In this paper, a fast and efficient coastline detection method is proposed which comprises three steps. First, we calculate a modified correlation coefficient of two SAR images of different polarization. This coefficient differs from the traditional computation where normalization is needed. Through this modified approach, the separation between sea and land becomes more prominent. Second, we set a histogram-based threshold to distinguish between sea and land within the given image. The histogram is derived from the statistical distribution of the polarized SAR image pixel amplitudes. Third, we extract continuous coastlines using a Canny image edge detector that is rather immune to speckle noise. Finally, the individual coastlines derived from time series of .SAR images can be checked for changes.

First demonstration of in vivo mapping for regional brain monoacylglycerol lipase using PET with [11C]SAR127303.

PubMed

Yamasaki, Tomoteru; Mori, Wakana; Zhang, Yiding; Hatori, Akiko; Fujinaga, Masayuki; Wakizaka, Hidekatsu; Kurihara, Yusuke; Wang, Lu; Nengaki, Nobuki; Ohya, Tomoyuki; Liang, Steven H; Zhang, Ming-Rong

2018-08-01

Monoacylglycerol lipase (MAGL) is a main regulator of the endocannabinoid system within the central nervous system (CNS). Recently, [ 11 C]SAR127303 was developed as a promising radioligand for MAGL imaging. In this study, we aimed to quantify regional MAGL concentrations in the rat brain using positron emission tomography (PET) with [ 11 C]SAR127303. An irreversible two-tissue compartment model (2-TCMi, k 4  = 0) analysis was conducted to estimate quantitative parameters (k 3 , K i 2-TCMi , and λk 3 ). These parameters were successfully obtained with high identifiability (<10 %COV) for the following regions ranked in order from highest to lowest: cingulate cortex > striatum > hippocampus > thalamus > cerebellum > hypothalamus ≈ pons. In vitro autoradiographs using [ 11 C]SAR127303 showed a heterogeneous distribution of radioactivity, as seen in the PET images. The K i 2-TCMi and λk 3 values correlated relatively highly with in vitro binding (r > 0.4, P < 0.005). The K i 2-TCMi values showed high correlation and low underestimation (<10%) compared with the slope of a Patlak plot analysis with linear regression (K i Patlak ). In conclusion, we successfully estimated regional net uptake value of [ 11 C]SAR127303 reflecting MAGL concentrations in rat brain regions for the first time. Copyright © 2018 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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 generate full-swath (6 to 75 Kms) DMSAR images in 1m / 3m / 5m / 10m / 30m resolution SAR operating modes. For RISAT mission, this generic Quick Look SAR Processor will be mainly used for browse product generation at NRSA-Shadnagar (SAN) ground receive station. RISAT QLP/NRTP is also proposed to provide an alternative emergency SAR product generation chain. For this, the S/C aux data appended in Onboard SAR Frame Format (x, y, z, x', y', z', roll, pitch, yaw) and predicted orbit from previous days Orbit Determination data will be used. The QLP / NRTP will produce ground range images in real / near real time. For emergency data product generation, additional Off-line tasks like geo-tagging, masking, QC etc needs to be performed on the processed image. The QLP / NRTP would generate geo-tagged images from the annotation data available from the SAR P/L data itself. Since the orbit & attitude information are taken as it is, the location accuracy will be poorer compared to the product generated using ADIF, where smoothened attitude and orbit are made available. Additional tasks like masking, output formatting and Quality checking of the data product will be carried out at Balanagar, NRSA after the image annotated data from QLP / NRTP is sent to Balanagar. The necessary interfaces to the QLP/NRTP for Emergency product generation are also being worked out. As is widely acknowledged, QLP/NRTP for RISAT and DMSAR is an ambitious effort and the technology of future. It is expected that by the middle of next decade, the next generation SAR missions worldwide will have onboard SAR Processors of varying capabilities and generate SAR Data products and Information products onboard instead of SAR raw data. Thus, it is also envisaged that these activities related to QLP/NRTP implementation for RISAT ground segment and DMSAR will be a significant step which will directly feed into the development of onboard real time processing systems for ISRO's future space borne SAR missions. This paper describes the design requirements, configuration details and salient features, apart from highlighting the utility of these Quick Look SAR processors for RISAT and DMSAR, for generation of emergency products for Disaster management.

On the Character and Mitigation of Atmospheric Noise in InSAR Time Series Analysis (Invited)

NASA Astrophysics Data System (ADS)

Barnhart, W. D.; Fielding, E. J.; Fishbein, E.

2013-12-01

Time series analysis of interferometric synthetic aperture radar (InSAR) data, with its broad spatial coverage and ability to image regions that are sometimes very difficult to access, is a powerful tool for characterizing continental surface deformation and its temporal variations. With the impending launch of dedicated SAR missions such as Sentinel-1, ALOS-2, and the planned NASA L-band SAR mission, large volume data sets will allow researchers to further probe ground displacement processes with increased fidelity. Unfortunately, the precision of measurements in individual interferograms is impacted by several sources of noise, notably spatially correlated signals caused by path delays through the stratified and turbulent atmosphere and ionosphere. Spatial and temporal variations in atmospheric water vapor often introduce several to tens of centimeters of apparent deformation in the radar line-of-sight, correlated over short spatial scales (<10 km). Signals resulting from atmospheric path delays are particularly problematic because, like the subsidence and uplift signals associated with tectonic deformation, they are often spatially correlated with topography. In this talk, we provide an overview of the effects of spatially correlated tropospheric noise in individual interferograms and InSAR time series analysis, and we highlight where common assumptions of the temporal and spatial characteristics of tropospheric noise fail. Next, we discuss two classes of methods for mitigating the effects of tropospheric water vapor noise in InSAR time series analysis and single interferograms: noise estimation and characterization with independent observations from multispectral sensors such as MODIS and MERIS; and noise estimation and removal with weather models, multispectral sensor observations, and GPS. Each of these techniques can provide independent assessments of the contribution of water vapor in interferograms, but each technique also suffers from several pitfalls that we outline. The multispectral near-infrared (NIR) sensors provide high spatial resolution (~1 km) estimates of total column tropospheric water vapor by measuring the absorption of reflected solar illumination and provide may excellent estimates of wet delay. The Online Services for Correcting Atmosphere in Radar (OSCAR) project currently provides water vapor products through web services (http://oscar.jpl.nasa.gov). Unfortunately, such sensors require daytime and cloudless observations. Global and regional numerical weather models can provide an additional estimate of both the dry and atmospheric delays with spatial resolution of (3-100 km) and time scales of 1-3 hours, though these models are of lower accuracy than imaging observations and are benefited by independent observations from independent observations of atmospheric water vapor. Despite these issues, the integration of these techniques for InSAR correction and uncertainty estimation may contribute substantially to the reduction and rigorous characterization of uncertainty in InSAR time series analysis - helping to expand the range of tectonic displacements imaged with InSAR, to robustly constrain geophysical models, and to generate a-priori assessments of satellite acquisitions goals.

Spotlight SAR interferometry for terrain elevation mapping and interferometric change detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eichel, P.H.; Ghiglia, D.C.; Jakowatz, C.V. Jr.

1996-02-01

In this report, we employ an approach quite different from any previous work; we show that a new methodology leads to a simpler and clearer understanding of the fundamental principles of SAR interferometry. This methodology also allows implementation of an important collection mode that has not been demonstrated to date. Specifically, we introduce the following six new concepts for the processing of interferometric SAR (INSAR) data: (1) processing using spotlight mode SAR imaging (allowing ultra-high resolution), as opposed to conventional strip-mapping techniques; (2) derivation of the collection geometry constraints required to avoid decorrelation effects in two-pass INSAR; (3) derivation ofmore » maximum likelihood estimators for phase difference and the change parameter employed in interferometric change detection (ICD); (4) processing for the two-pass case wherein the platform ground tracks make a large crossing angle; (5) a robust least-squares method for two-dimensional phase unwrapping formulated as a solution to Poisson`s equation, instead of using traditional path-following techniques; and (6) the existence of a simple linear scale factor that relates phase differences between two SAR images to terrain height. We show both theoretical analysis, as well as numerous examples that employ real SAR collections to demonstrate the innovations listed above.« less

SAR studies in the Yuma Desert, Arizona: Sand penetration, geology, and the detection of military ordnance debris

USGS Publications Warehouse

Schaber, G.G.

1999-01-01

Synthetic Aperture Radar (SAR) images acquired over part of the Yuma Desert in southwestern Arizona demonstrate the ability of C-band (5.7-cm wavelength), L-band (24.5 cm), and P-band (68 cm) AIRSAR signals to backscatter from increasingly greater depths reaching several meters in blow sand and sandy alluvium. AIRSAR images obtained within the Barry M. Goldwater Bombing and Gunnery Range near Yuma, Arizona, show a total reversal of C- and P-band backscatter contrast (image tone) for three distinct geologic units. This phenomenon results from an increasingly greater depth of radar imaging with increasing radar wavelength. In the case of sandy- and small pebble-alluvium surfaces mantled by up to several meters of blow sand, backscatter increases directly with SAR wavelength as a result of volume scattering from a calcic soil horizon at shallow depth and by volume scattering from the root mounds of healthy desert vegetation that locally stabilize blow sand. AIRSAR images obtained within the military range are also shown to be useful for detecting metallic military ordnance debris that is located either at the surface or covered by tens of centimeters to several meters of blow sand. The degree of detectability of this ordnance increases with SAR wavelength and is clearly maximized on P-band images that are processed in the cross-polarized mode (HV). This effect is attributed to maximum signal penetration at P-band and the enhanced PHV image contrast between the radar-bright ordnance debris and the radar-dark sandy desert. This article focuses on the interpretation of high resolution AIRSAR images but also Compares these airborne SAR images with those acquired from spacecraft sensors such as ERS-SAR and Space Radar Laboratory (SIR-C/X-SAR).Synthetic Aperture Radar (SAR) images acquired over part of the Yuma Desert in southwestern Arizona demonstrate the ability of C-band (5.7-cm wavelength), L-band (24.5 cm), and P-band (68 cm) AIRSAR signals to backscatter from increasingly greater depths reaching several meters in blow sand and sandy alluvium. AIRSAR images obtained within the Barry M. Goldwater Bombing and Gunnery Range near Yuma, Arizona, show a total reversal of C- and P-band backscatter contrast (image tone) for three distinct geologic units. This phenomenon results from an increasingly greater depth of radar imaging with increasing radar wavelength. In the case of sandy- and small pebble-alluvium surfaces mantled by up to several meters of blow sand, backscatter increases directly with SAR wavelength as a result of volume scattering from a calcic soil horizon at shallow depth and by volume scattering from the root mounds of healthy desert vegetation that locally stabilize blow sand. AIRSAR images obtained within the military range are also shown to be useful for detecting metallic military ordnance debris that is located either at the surface or covered by tens of centimeters to several meters of blow sand. The degree of detectability of this ordnance increases with SAR wavelength and is clearly maximized on P-band images that are processed in the cross-polarized mode (HV). This effect is attributed to maximum signal penetration at P-band and the enhanced PHV image contrast between the radar-bright ordnance debris and the radar-dark sandy desert. This article focuses on the interpretation of high resolution AIRSAR images but also compares these airborne SAR images with those acquired from spacecraft sensors such as ERS-SAR and Space Radar Laboratory (SIR-C/X-SAR).

Characterization of the range effect in synthetic aperture radar images of concrete specimens for width estimation

NASA Astrophysics Data System (ADS)

Alzeyadi, Ahmed; Yu, Tzuyang

2018-03-01

Nondestructive evaluation (NDE) is an indispensable approach for the sustainability of critical civil infrastructure systems such as bridges and buildings. Recently, microwave/radar sensors are widely used for assessing the condition of concrete structures. Among existing imaging techniques in microwave/radar sensors, synthetic aperture radar (SAR) imaging enables researchers to conduct surface and subsurface inspection of concrete structures in the range-cross-range representation of SAR images. The objective of this paper is to investigate the range effect of concrete specimens in SAR images at various ranges (15 cm, 50 cm, 75 cm, 100 cm, and 200 cm). One concrete panel specimen (water-to-cement ratio = 0.45) of 30-cm-by-30-cm-by-5-cm was manufactured and scanned by a 10 GHz SAR imaging radar sensor inside an anechoic chamber. Scatterers in SAR images representing two corners of the concrete panel were used to estimate the width of the panel. It was found that the range-dependent pattern of corner scatters can be used to predict the width of concrete panels. Also, the maximum SAR amplitude decreases when the range increases. An empirical model was also proposed for width estimation of concrete panels.

Pseudo-color coding method for high-dynamic single-polarization SAR images

NASA Astrophysics Data System (ADS)

Feng, Zicheng; Liu, Xiaolin; Pei, Bingzhi

2018-04-01

A raw synthetic aperture radar (SAR) image usually has a 16-bit or higher bit depth, which cannot be directly visualized on 8-bit displays. In this study, we propose a pseudo-color coding method for high-dynamic singlepolarization SAR images. The method considers the characteristics of both SAR images and human perception. In HSI (hue, saturation and intensity) color space, the method carries out high-dynamic range tone mapping and pseudo-color processing simultaneously in order to avoid loss of details and to improve object identifiability. It is a highly efficient global algorithm.

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

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

PubMed

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

2016-07-14

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.

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

PubMed Central

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

The InSAR Scientific Computing Environment (ISCE): An Earth Science SAR Processing Framework, Toolbox, and Foundry

NASA Astrophysics Data System (ADS)

Agram, P. S.; Gurrola, E. M.; Lavalle, M.; Sacco, G. F.; Rosen, P. A.

2016-12-01

The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.

Azimuthal resolution degradation due to ocean surface motion in focused arrays and SARS

NASA Astrophysics Data System (ADS)

1990-06-01

During the meeting at WHOI (5-18-90), a discussion arose of the ability of the focused array to simulate the R/v ratios typical of airborne and/or spaceborne SARs. In particular, the ability was questioned of the focused array to yield the same azimuthal resolution, rho, as the SAR. Although the focused array can be sampled to yield the same azimuthal resolution as the SAR, it is likely that the images generated by the focused array will not be identical to those produced by a SAR with the same azimuth resolution. For a true SAR, biases in the Doppler history of azimuthally traveling waves due to their along-track motion will cause shifts in their apparent position. This will cause waves which are physically at one location to shift over several pixel widths in the image. The limited swath width of the focused array will prevent if from observing scattered power from waves falling outside the swath, thus such waves will not affect the image formed within the swath, as would happen in the SAR. Thus, it is likely that the focused array will not yield the same image as a SAR having the same resolution.

Fast Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode

PubMed Central

Liu, Lei; Qiu, Xiaolan; Lei, Bin

2017-01-01

This study aims to detect vessels with lengths ranging from about 70 to 300 m, in Gaofen-3 (GF-3) SAR images with ultrafine strip-map (UFS) mode as fast as possible. Based on the analysis of the characteristics of vessels in GF-3 SAR imagery, an effective vessel detection method is proposed in this paper. Firstly, the iterative constant false alarm rate (CFAR) method is employed to detect the potential ship pixels. Secondly, the mean-shift operation is applied on each potential ship pixel to identify the candidate target region. During the mean-shift process, we maintain a selection matrix recording which pixels can be taken, and these pixels are called as the valid points of the candidate target. The l1 norm regression is used to extract the principal axis and detect the valid points. Finally, two kinds of false alarms, the bright line and the azimuth ambiguity, are removed by comparing the valid area of the candidate target with a pre-defined value and computing the displacement between the true target and the corresponding replicas respectively. Experimental results on three GF-3 SAR images with UFS mode demonstrate the effectiveness and efficiency of the proposed method. PMID:28678197

Integrating polarimetric synthetic aperture radar and imaging spectrometry for wildland fuel mapping in southern California

Treesearch

P.E. Dennison; D.A. Roberts; J. Regelbrugge; S.L. Ustin

2000-01-01

Polarimetric synthetic aperture radar (SAR) and imaging spectrometry exemplify advanced technologies for mapping wildland fuels in chaparral ecosystems. In this study, we explore the potential of integrating polarimetric SAR and imaging spectrometry for mapping wildland fuels. P-band SAR and ratios containing P-band polarizations are sensitive to variations in stand...

Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

NASA Astrophysics Data System (ADS)

Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

2016-07-01

Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

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

NASA Astrophysics Data System (ADS)

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.

Scattering angle resolved optical coherence tomography for in vivo murine retinal imaging

NASA Astrophysics Data System (ADS)

Gardner, Michael R.; Katta, Nitesh; McElroy, Austin; Baruah, Vikram; Rylander, H. G.; Milner, Thomas E.

2017-02-01

Optical coherence tomography (OCT) retinal imaging contributes to understanding central nervous system (CNS) diseases because the eye is an anatomical "window to the brain" with direct optical access to nonmylenated retinal ganglion cells. However, many CNS diseases are associated with neuronal changes beyond the resolution of standard OCT retinal imaging systems. Though studies have shown the utility of scattering angle resolved (SAR) OCT for particle sizing and detecting disease states ex vivo, a compact SAR-OCT system for in vivo rodent retinal imaging has not previously been reported. We report a fiber-based SAR-OCT system (swept source at 1310 nm +/- 65 nm, 100 kHz scan rate) for mouse retinal imaging with a partial glass window (center aperture) for angular discrimination of backscattered light. This design incorporates a dual-axis MEMS mirror conjugate to the ocular pupil plane and a high collection efficiency objective. A muring retina is imaged during euthanasia, and the proposed SAR-index is examined versus time. Results show a positive correlation between the SAR-index and the sub-cellular hypoxic response of neurons to isoflurane overdose during euthanasia. The proposed SAR-OCT design and image process technique offer a contrast mechanism able to detect sub-resolution neuronal changes for murine retinal imaging.

Integrating Remote Sensing Data, Hybrid-Cloud Computing, and Event Notifications for Advanced Rapid Imaging & Analysis (Invited)

NASA Astrophysics Data System (ADS)

Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Fielding, E. J.; Agram, P.; Manipon, G.; Stough, T. M.; Simons, M.; Rosen, P. A.; Wilson, B. D.; Poland, M. P.; Cervelli, P. F.; Cruz, J.

2013-12-01

Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Continuous Global Positioning System (CGPS) are now important elements in our toolset for monitoring earthquake-generating faults, volcanic eruptions, hurricane damage, landslides, reservoir subsidence, and other natural and man-made hazards. Geodetic imaging's unique ability to capture surface deformation with high spatial and temporal resolution has revolutionized both earthquake science and volcanology. Continuous monitoring of surface deformation and surface change before, during, and after natural hazards improves decision-making from better forecasts, increased situational awareness, and more informed recovery. However, analyses of InSAR and GPS data sets are currently handcrafted following events and are not generated rapidly and reliably enough for use in operational response to natural disasters. Additionally, the sheer data volumes needed to handle a continuous stream of InSAR data sets also presents a bottleneck. It has been estimated that continuous processing of InSAR coverage of California alone over 3-years would reach PB-scale data volumes. Our Advanced Rapid Imaging and Analysis for Monitoring Hazards (ARIA-MH) science data system enables both science and decision-making communities to monitor areas of interest with derived geodetic data products via seamless data preparation, processing, discovery, and access. We will present our findings on the use of hybrid-cloud computing to improve the timely processing and delivery of geodetic data products, integrating event notifications from USGS to improve the timely processing for response, as well as providing browse results for quick looks with other tools for integrative analysis.

Integration of SAR and AIS for ship detection and identification

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho

2012-06-01

This abstract describes the preliminary design concept for an integration system of SAR and AIS data. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Once both data reports are obtained, one need to match the timings of AIS data acquisition over the SAR image acquisition time with consideration of local time & boundary to extract the closest time signal from AIS report in order to know the AIS based ship positions, but still one cannot be able to distinguish which ships have the AIS transponder after projection of AIS based position onto the SAR image acquisition boundary. As far as integration is concerned, the ship dead-reckoning concept is most important forecasted position which provides the AIS based ship position at the time of SAR image acquisition and also provides the hints for azimuth shift which occurred in SAR image for the case of moving ships which moves in the direction perpendicular to the direction of flight path. Unknown ship's DR estimation is to be carried out based on the initial positions, speed and course over ground, which has already been shorted out from AIS reports, during the step of time matching. This DR based ship's position will be the candidate element for searching the SAR based ship targets for the purpose of identification & matching within the certain boundary around DR. The searching method is performed by means of estimation of minimum distance from ship's DR to SAR based ship position, and once it determines, so the candidate element will look for matching like ship size match of DR based ship's dimension wrt SAR based ship's edge, there may be some error during the matching with SAR based ship edges with actual ship's hull design as per the longitudinal and transverse axis size information obtained from the AIS reports due to blurring effect in SAR based ship signatures, once the conditions are satisfied, candidate element will move & shift over the SAR based ship signature target with the minimum displacement and it is known to be the azimuth shift compensation and this overall methodology are known to be integration of AIS report data over the SAR image acquisition boundary with assessment of time matching. The expected result may provide the good accuracy of the SAR and AIS contact position along with dimension and classification of ships over SAR image. There may be possibilities of matching speed and course from candidate element with SAR based ship signature, but still the challenges are presents in front of us that to estimation of speed and course by means of SAR data, if it may be possible so the expected final result may be more accurate as due to extra matching effects and the results may be used for the near real time performance for ship identification with help of integrated system design based on SAR and AIS data reports.

Geologic Map of the Sif Mons Quadrangle (V-31), Venus

USGS Publications Warehouse

Copp, Duncan L.; Guest, John E.

2007-01-01

The Magellan spacecraft orbited Venus from August 10, 1990, until it plunged into the Venusian atmosphere on October 12, 1994. Magellan Mission objectives included (1) improving the knowledge of the geological processes, surface properties, and geologic history of Venus by analysis of surface radar characteristics, topography, and morphology and (2) improving the knowledge of the geophysics of Venus by analysis of Venusian gravity. The Sif Mons quadrangle of Venus includes lat 0? to 25? N. and long 330? to 0? E.; it covers an area of about 8.10 x 106 km2 (fig. 1). The data used to construct the geologic map were from the National Aeronautics and Space Administration (NASA) Magellan Mission. The area is also covered by Arecibo images, which were also consulted (Campbell and Campbell, 1990; Campbell and others, 1989). Data from the Soviet Venera orbiters do not cover this area. All of the SAR products were employed for geologic mapping. C1-MIDRs were used for general recognition of units and structures; F-MIDRs and F-MAPs were used for more specific examination of surface characteristics and structures. Where the highest resolution was required or some image processing was necessary to solve a particular mapping problem, the images were examined using the digital data on CD-ROMs. In cycle 1, the SAR incidence angles for images obtained for the Sif Mons quadrangle ranged from 44? to 46?; in cycle 3, they were between 25? and 26?. We use the term 'high backscatter' of a material unit to imply a rough surface texture at the wavelength scale used by Magellan SAR. Conversely, 'low backscatter' implies a smooth surface. In addition, altimetric, radiometric, and rms slope data were superposed on SAR images. Figure 2 shows altimetry data; figure 3 shows images of ancillary data for the quadrangle; and figure 4 shows backscatter coefficient for selected units. The interpretation of these data was discussed by Ford and others (1989, 1993). For corrected backscatter and numerical ancillary data see tables 1 and 2; these data allow comparison with units at different latitudes on the planet, where the visual appearance may differ because of a different incidence angle. Synthetic stereo images, produced by overlaying SAR images and altimetric data, were of great value in interpreting structures and stratigraphic relations.

SBAS-InSAR analysis of surface deformation at Mauna Loa and Kilauea volcanoes in Hawaii

USGS Publications Warehouse

Casu, F.; Lanari, Riccardo; Sansosti, E.; Solaro, G.; Tizzani, Pietro; Poland, M.; Miklius, Asta

2009-01-01

We investigate the deformation of Mauna Loa and K??lauea volcanoes, Hawai'i, by exploiting the advanced differential Synthetic Aperture Radar Interferometry (InSAR) technique referred to as the Small BAseline Subset (SBAS) algorithm. In particular, we present time series of line-of-sight (LOS) displacements derived from SAR data acquired by the ASAR instrument, on board the ENVISAT satellite, from the ascending (track 93) and descending (track 429) orbits between 2003 and 2008. For each coherent pixel of the radar images we compute time-dependent surface displacements as well as the average LOS deformation rate. Our results quantify, in space and time, the complex deformation of Mauna Loa and K??lauea volcanoes. The derived InSAR measurements are compared to continuous GPS data to asses the quality of the SBAS-InSAR products. ??2009 IEEE.

InSAR data for monitoring land subsidence: time to think big

NASA Astrophysics Data System (ADS)

Ferretti, A.; Colombo, D.; Fumagalli, A.; Novali, F.; Rucci, A.

2015-11-01

Satellite interferometric synthetic aperture radar (InSAR) data have proven effective and valuable in the analysis of urban subsidence phenomena based on multi-temporal radar images. Results obtained by processing data acquired by different radar sensors, have shown the potential of InSAR and highlighted the key points for an operational use of this technology, namely: (1) regular acquisition over large areas of interferometric data stacks; (2) use of advanced processing algorithms, capable of estimating and removing atmospheric disturbances; (3) access to significant processing power for a regular update of the information over large areas. In this paper, we show how the operational potential of InSAR has been realized thanks to the recent advances in InSAR processing algorithms, the advent of cloud computing and the launch of new satellite platforms, specifically designed for InSAR analyses (e.g. Sentinel-1a operated by the ESA and ALOS2 operated by JAXA). The processing of thousands of SAR scenes to cover an entire nation has been performed successfully in Italy in a project financed by the Italian Ministry of the Environment. The challenge for the future is to pass from the historical analysis of SAR scenes already acquired in digital archives to a near real-time monitoring program where up to date deformation data are routinely provided to final users and decision makers.

Unsupervised DInSAR processing chain for multi-scale displacement analysis

NASA Astrophysics Data System (ADS)

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, thus leading to the generation of Interferometric products for both global and local scale displacement analysis. Among several examples, we will show a wide displacement SBAS processing, carried out over the southern California, during which the whole ascending ENVISAT data set of more than 740 images has been fully processed on a Cloud Computing environment in less than 9 hours, leading to the generation of a displacement map of about 150,000 square kilometres. The P-SBAS characteristics allowed also us to integrate the algorithm within the ESA Geohazard Exploitation Platform (GEP), which is based on the use of GRID and Cloud Computing facilities, thus making freely available to the EO community a web tool for massive and systematic interferometric displacement time series generation. This work has been partially supported by: the Italian MIUR under the RITMARE project; the CNR-DPC agreement and the ESA GEP project.

Registering coherent change detection products associated with large image sets and long capture intervals

DOEpatents

Perkins, David Nikolaus; Gonzales, Antonio I

2014-04-08

A set of co-registered coherent change detection (CCD) products is produced from a set of temporally separated synthetic aperture radar (SAR) images of a target scene. A plurality of transformations are determined, which transformations are respectively for transforming a plurality of the SAR images to a predetermined image coordinate system. The transformations are used to create, from a set of CCD products produced from the set of SAR images, a corresponding set of co-registered CCD products.

Hardware Development and Error Characterization for the AFIT RAIL SAR System

DTIC Science & Technology

This research is focused on updating the Air Force Institute of Technology (AFIT) Radar Instrumentation Lab (RAIL)Synthetic Aperture Radar ( SAR ...collections from a receiver in motion. Secondly, orthogonal frequency-division multiplexing (OFDM) signals are used to form ( SAR ) images in multiple...experimental and simulation configurations. This research analyses, characterizes and attempts compensation of relevant SAR image error sources, such as Doppler

Developing an interactive teleradiology system for SARS diagnosis

NASA Astrophysics Data System (ADS)

Sun, Jianyong; Zhang, Jianguo; Zhuang, Jun; Chen, Xiaomeng; Yong, Yuanyuan; Tan, Yongqiang; Chen, Liu; Lian, Ping; Meng, Lili; Huang, H. K.

2004-04-01

Severe acute respiratory syndrome (SARS) is a respiratory illness that had been reported in Asia, North America, and Europe in last spring. Most of the China cases of SARS have occurred by infection in hospitals or among travelers. To protect the physicians, experts and nurses from the SARS during the diagnosis and treatment procedures, the infection control mechanisms were built in SARS hospitals. We built a Web-based interactive teleradiology system to assist the radiologists and physicians both in side and out side control area to make image diagnosis. The system consists of three major components: DICOM gateway (GW), Web-based image repository server (Server), and Web-based DICOM viewer (Viewer). This system was installed and integrated with CR, CT and the hospital information system (HIS) in Shanghai Xinhua hospital to provide image-based ePR functions for SARS consultation between the radiologists, physicians and experts inside and out side control area. The both users inside and out side the control area can use the system to process and manipulate the DICOM images interactively, and the system provide the remote control mechanism to synchronize their operations on images and display.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

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.

Foldbelt exploration with synthetic aperture radar (SAR) in Papua New Guinea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, J.M.; Pruett, F.D.

1987-05-01

Synthetic aperture radar (SAR) is being successfully used within the southern fold and thrust belt of Papua New Guinea to map surface structure and stratigraphy and to help plan a hydrocarbon exploration program. The airborne SAR imagery, along with other surface data, is used as a primary exploration tool because acquisition of acceptable seismic data is extremely costly due to extensive outcrops of Tertiary Darai Limestone which develops rugged karst topography. Most anticlines in the licenses are capped with this deeply karstified limestone. The region is ideally suited to geologic analysis using remote sensing technology. The area is seldom cloudmore » free and is covered with tropical rain forest, and geologic field studies are limited. The widespread karst terrain is exceedingly dangerous, if not impossible, to traverse on the ground. SAR is used to guide ongoing field work, modeling of subsurface structure, and selection of well locations. SAR provides their explorationists with an excellent data base because (1) structure is enhanced with low illumination, (2) resolution is 6 x 12 m, (3) digital reprocessing is possible, (4) clouds are penetrated by the SAR, and (5) the survey was designed for stereoscopic photogeology. Landsat images and vertical aerial photographs complement SAR but provide subdued structural information because of minimal shadowing (due to high sun angles) and the jungle cover. SAR imagery reveals large-scale mass wasting that has led to a reevaluation of previously acquired field data. Lithologies can be recognized by textural and tonal changes on the SAR images despite near-continuous canopy of jungle. Reprocessing and contrast stretching of the digital radar imagery provide additional geologic information.« less

Visual analytics for semantic queries of TerraSAR-X image content

NASA Astrophysics Data System (ADS)

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 the image content using semantic terms and the relations between them answering questions such as what is the percentage of urban area in a region? or what is the distribution of water bodies in a city?

Comparison of JPL-AIRSAR and DLR E-SAR images from the MAC Europe 1991 campaign over testsite Oberpfaffenhofen: Frequency and polarization dependent backscatter variations from agricultural fields

NASA Technical Reports Server (NTRS)

Schmullius, C.; Nithack, J.

1992-01-01

On July 12, the MAC Europe '91 (Multi-Sensor Airborne Campaign) took place over test site Oberpfaffenhofen. The DLR Institute of Radio-Frequency Technology participated with its C-VV, X-VV, and X-HH Experimental Synthetic Aperture Radar (E-SAR). The high resolution E-SAR images with a pixel size between 1 and 2 m and the polarimetric AIRSAR images were analyzed. Using both sensors in combination is a unique opportunity to evaluate SAR images in a frequency range from P- to X-band and to investigate polarimetric information.

Bistatic SAR: Signal Processing and Image Formation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahl, Daniel E.; Yocky, David A.

This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013more » on Kirtland Air Force Base, New Mexico.« less

Auroral LSTIDs and SAR Arc Occurrences in Northern California During Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Bhatt, A.; Kendall, E. A.

2015-12-01

A 630nm allsky imager has been operated for two years in northern California at the Hat Creek Radio Observatory. F-region airglow data captured by the imager ranges from approximately L=1.7 -2.7. Since installation of the imager several geomagnetic storms have occurred with varying intensities. Two main manifestations of the geomagnetic storms are observed in the 630 nm airglow data: large-scale traveling ionospheric disturbances that are launched from the auroral zone and Stable Auroral Red (SAR) arcs during more intense geomagnetic storms. We will present a statistical analysis of these storm-time phenomena in northern California for the past eighteen months. This imager is part of a larger all-sky imaging network across the continental United States, termed MANGO (Midlatitude All-sky-imaging Network for Geophysical Observations). Where available, we will add data from networked imagers located at similar L-shell in other states as well.

Microvibrations in a 20 M Long Ka-Band SAR Interferometer

NASA Astrophysics Data System (ADS)

Rodriques, G.; Ludwig, M.; Santiago-Prowald, J.

2014-06-01

Interferometric SAR operating at Ka-band has the potential for offering high-resolution 3D images of the surface of the Earth taken from a single-platform.The stability of the mechanical baseline of such an instrument has been considered as a key critical area for the feasibility of the concept.This paper is devoted to the analysis of the micro- vibrations in a 20-m long Ka-band SAR interferometer arising during typical attitude changing manoeuvers and the mechanical noise transmitted from reaction wheels. It is preliminarily concluded that the expected microvibration levels are within the requirements of the instrument.

Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico

NASA Technical Reports Server (NTRS)

Rebillard, PH.; Dixon, T.

1984-01-01

A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area

An Accurate Co-registration Method for Airborne Repeat-pass InSAR

NASA Astrophysics Data System (ADS)

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

2017-10-01

Interferometric Synthetic Aperture Radar (InSAR) technology plays a significant role in topographic mapping and surface deformation detection. Comparing with spaceborne repeat-pass InSAR, airborne repeat-pass InSAR solves the problems of long revisit time and low-resolution images. Due to the advantages of flexible, accurate, and fast obtaining abundant information, airborne repeat-pass InSAR is significant in deformation monitoring of shallow ground. In order to getting precise ground elevation information and interferometric coherence of deformation monitoring from master and slave images, accurate co-registration must be promised. Because of side looking, repeat observing path and long baseline, there are very different initial slant ranges and flight heights between repeat flight paths. The differences of initial slant ranges and flight height lead to the pixels, located identical coordinates on master and slave images, correspond to different size of ground resolution cells. The mismatching phenomenon performs very obvious on the long slant range parts of master image and slave image. In order to resolving the different sizes of pixels and getting accurate co-registration results, a new method is proposed based on Range-Doppler (RD) imaging model. VV-Polarization C-band airborne repeat-pass InSAR images were used in experiment. The experiment result shows that the proposed method leads to superior co-registration accuracy.

Extraction of Extended Small-Scale Objects in Digital Images

NASA Astrophysics Data System (ADS)

Volkov, V. Y.

2015-05-01

Detection and localization problem of extended small-scale objects with different shapes appears in radio observation systems which use SAR, infra-red, lidar and television camera. Intensive non-stationary background is the main difficulty for processing. Other challenge is low quality of images, blobs, blurred boundaries; in addition SAR images suffer from a serious intrinsic speckle noise. Statistics of background is not normal, it has evident skewness and heavy tails in probability density, so it is hard to identify it. The problem of extraction small-scale objects is solved here on the basis of directional filtering, adaptive thresholding and morthological analysis. New kind of masks is used which are open-ended at one side so it is possible to extract ends of line segments with unknown length. An advanced method of dynamical adaptive threshold setting is investigated which is based on isolated fragments extraction after thresholding. Hierarchy of isolated fragments on binary image is proposed for the analysis of segmentation results. It includes small-scale objects with different shape, size and orientation. The method uses extraction of isolated fragments in binary image and counting points in these fragments. Number of points in extracted fragments is normalized to the total number of points for given threshold and is used as effectiveness of extraction for these fragments. New method for adaptive threshold setting and control maximises effectiveness of extraction. It has optimality properties for objects extraction in normal noise field and shows effective results for real SAR images.

Monitoring dam structural health from space: Insights from novel InSAR techniques and multi-parametric modeling applied to the Pertusillo dam Basilicata, Italy

NASA Astrophysics Data System (ADS)

Milillo, Pietro; Perissin, Daniele; Salzer, Jacqueline T.; Lundgren, Paul; Lacava, Giusy; Milillo, Giovanni; Serio, Carmine

2016-10-01

The availability of new constellations of synthetic aperture radar (SAR) sensors is leading to important advances in infrastructure monitoring. These constellations offer the advantage of reduced revisit times, providing low-latency data that enable analysis that can identify infrastructure instability and dynamic deformation processes. In this paper we use COSMO-SkyMed (CSK) and TerraSAR-X (TSX) data to monitor seasonal induced deformation at the Pertusillo dam (Basilicata, Italy) using multi-temporal SAR data analysis. We analyzed 198 images spanning 2010-2015 using a coherent and incoherent PS approach to merge COSMO-SkyMed adjacent tracks and TerraSAR-X acquisitions, respectively. We used hydrostatic-seasonal-temporal (HST) and hydrostatic-temperature-temporal (HTT) models to interpret the non-linear deformation at the dam wall using ground measurements together with SAR time-series analysis. Different look geometries allowed us to characterize the horizontal deformation field typically observed at dams. Within the limits of our models and the SAR acquisition sampling we found that most of the deformation at the Pertusillo dam can be explained by taking into account only thermal seasonal dilation and hydrostatic pressure. The different models show slightly different results when interpreting the aging term at the dam wall. The results highlight how short-revisit SAR satellites in combination with models widely used in the literature for interpreting pendulum and GPS data can be used for supporting structural health monitoring and provide valuable information to ground users directly involved in field measurements.

Global Rapid Flood Mapping System with Spaceborne SAR Data

NASA Astrophysics Data System (ADS)

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 ground, air, and space will provide reliable snapshot extent of many flooding events. SAR missions with easy data access, such as the Sentinel-1 and NASA's upcoming NISAR mission, combined with the ARIA system, will enable forming a library of flood extent maps, which can soon support flood modeling community, by providing observation-based constraints.

The observation of ocean surface phenomena using imagery from the SEASAT synthetic aperture radar: An assessment

NASA Astrophysics Data System (ADS)

Vesecky, John F.; Stewart, Robert H.

1982-04-01

Over the period July 4 to October 10, 1978, the SEASAT synthetic aperture radar (SAR) gathered 23 cm wavelength radar images of some 108 km2 of the earth's surface, mainly of ocean areas, at 25-40 m resolution. Our assessment is in terms of oceanographic and ocean monitoring objectives and is directed toward discovering the proper role of SAR imagery in these areas of interest. In general, SAR appears to have two major and somewhat overlapping roles: first, quantitative measurement of ocean phenomena, like long gravity waves and wind fields, as well as measurement of ships; second, exploratory observations of large-scale ocean phenomena, such as the Gulf Stream and its eddies, internal waves, and ocean fronts. These roles are greatly enhanced by the ability of 23 cm SAR to operate day or night and through clouds. To begin we review some basics of synthetic aperture radar and its implementation on the SEASAT spacecraft. SEASAT SAR imagery of the ocean is fundamentally a map of the radar scattering characteristics of ˜30 cm wavelength ocean waves, distorted in some cases by ocean surface motion. We discuss how wind stress, surface currents, long gravity waves, and surface films modulate the scattering properties of these resonant waves with particular emphasis on the mechanisms that could produce images of long gravity waves. Doppler effects by ocean motion are also briefly described. Measurements of long (wavelength ≳100 m) gravity waves, using SEASAT SAR imagery, are compared with surface measurements during several experiments. Combining these results we find that dominant wavelength and direction are measured by SEASAT SAR within ±12% and ±15°, respectively. However, we note that ocean waves are not always visible in SAR images and discuss detection criteria in terms of wave height, length, and direction. SAR estimates of omnidirectional wave height spectra made by assuming that SAR image intensity is proportional to surface height fluctuations are more similar to corresponding surface measurements of wave height spectra than to wave slope spectra. Because SEASAT SAR images show the radar cross section σ° of ˜30 cm waves (neglecting doppler effects), and because these waves are raised by wind stress on the ocean surface, wind measurements are possible. Comparison between wind speeds estimated from SEASAT SAR imagery and from the SEASAT satellite scatterometer (SASS) agreed to within ±0.7 m s- over a 350-km comparison track and for wind speeds from 2 to 15 m s-. The great potential of SAR wind measurements lies in studying the spatial structure of the wind field over a range of spatial scales of from ≲1 km to ≳100 km. At present, the spatial and temporal structure of ocean wind fields is largely unknown. Because SAR responds to short waves whose energy density is a function of wind stress at the surface rather than wind speed at some distance above the surface, variations in image intensity may also reflect changes in air-sea temperature difference (thus complicating wind measurements by SAR). Because SAR images show the effects of surface current shear, air-sea temperature difference, and surface films through their modulation of the ˜30 cm waves, SEASAT images can be used to locate and study the Gulf Stream and related warm water rings, tidal flows at inlets, internal waves, and slicks resulting from surface films. In many of these applications, SAR provides a remote sensing capability that is complementary to infrared imagery because the two techniques sense largely different properties, namely, surface roughness and temperature. Both stationary ships and moving ships with their attendant wakes are often seen in SAR images. Ship images can be used to estimate ship size, heading, and speed. However, ships known to be in areas imaged by SAR are not always detectable. Clearly, a variety of factors, such as image resolution, ship size, sea state, and winds could affect ship detection. Overall, the role of SAR imagery in oceanography is definitely evolving at this time, but its ultimate role is unclear. We have assessed the ability of SEASAT SAR to measure a variety of ocean phenomena and have commented briefly on applications. In the end, oceanographers and others will have to judge from these capabilities the proper place for SAR in oceanography and remote sensing of the ocean.

Condition assessment of corroded steel rebar in free space using synthetic aperture radar images

NASA Astrophysics Data System (ADS)

Ingemi, Christopher M.; Owusu Twumasi, Jones; Litt, Swinderjit; Yu, Tzuyang

2017-04-01

Synthetic aperture radar (SAR) imaging of construction materials offers civil engineers an opportunity to better assess the condition of aging civil infrastructures such as reinforced concrete (RC) structures. Corrosion of steel rebar in RC structures is a major problem responsible for their premature failure and unexpected collapse. In this paper, SAR imaging is applied to the quantitative assessment of corroded steel rebar in free space as the first step toward the use of SAR imaging for subsurface sensing of aging RC structures. A 10 GHz stripmap SAR system was used inside an anechoic chamber. The bandwidth of the radar system was 1.5 GHz. Steel rebar specimens were artificially corroded to different levels by regularly applying a mist of 5% NaCl solution for different durations of time in order to simulate the condition of natural corrosion. Two sizes (No. 3 and No. 4) of steel rebar were used in this research. Different orientations of steel rebar were considered. Corrosion level was determined by measuring the mass loss of corroded steel rebar specimens. From our results, feasibility of SAR images for the condition assessment of corroded steel rebar was experimentally demonstrated. It was found that the presence of surface rust on corroded steel rebar reduces the amplitude in SAR images. The SAR image of corroded steel rebar also exhibited a distribution of SAR amplitudes different from the one of intact steel rebar. In addition, it was also found that there is an optimal range for the condition assessment of corroded steel rebar in free space. In our experiment, the optimal range was determined to be 30.4 cm.

Generalized interpretation scheme for arbitrary HR InSAR image pairs

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten

2013-10-01

Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

Software For Tie-Point Registration Of SAR Data

NASA Technical Reports Server (NTRS)

Rignot, Eric; Dubois, Pascale; Okonek, Sharon; Van Zyl, Jacob; Burnette, Fred; Borgeaud, Maurice

1995-01-01

SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.

Dynamics of Kilauea's Magmatic System Imaged Using a Joint Analysis of Geodetic and Seismic Data

NASA Astrophysics Data System (ADS)

Wauthier, C.; Roman, D. C.; Poland, M. P.; Fukushima, Y.; Hooper, A. J.

2012-12-01

Nowadays, Interferometric Synthetic Aperture Radar (InSAR) is commonly used to study a wide range of active volcanic areas. InSAR provides high-spatial-resolution measurements of surface deformation with centimeter-scale accuracy. At Kilauea Volcano, Hawai'i, InSAR shows complex processes that are not well constrained by GPS data (which have relatively poor spatial resolution). However, GPS data have higher temporal resolution than InSAR data. Both datasets are thus complementary. To overcome some of the limitations of conventional InSAR, which are mainly induced by temporal decorrelation, topographic, orbital and atmospheric delays, a Multi-Temporal InSAR (MT-InSAR) approach can be used. MT-InSAR techniques involve the processing of multiple SAR acquisitions over the same area. Two classes of MT-InSAR algorithms are defined: the persistent scatterers (PS) and small baseline (SBAS) methods. Each method is designed for a specific type of scattering mechanism. A PS pixel is a pixel in which a single scatterer dominates, while the contributions from other scatterers are negligible. A SBAS pixel is a pixel that includes distributed scatterers, which have a phase with little decorrelation over short time periods. Here, we apply the "StaMPS" ("Stanford Method for Permanent Scatterers") technique, which incorporates both a PS and SBAS approach, on ENVISAT and ALOS datasets acquired from 2003 to 2010 at Kilauea. In particular, we focus our InSAR analysis on the time period before the June 2007 "Father's Day" dike intrusion and eruption, and also incorporate seismic and GPS data in our models. Our goal is to identify any precursors to the Father's Day event within Kilauea's summit magma system, east rift zone, and/or southwest rift zone.

A perspective of synthetic aperture radar for remote sensing

NASA Technical Reports Server (NTRS)

Skolnik, M. I.

1978-01-01

The characteristics and capabilities of synthetic aperture radar are discussed so as to identify those features particularly unique to SAR. The SAR and Optical images were compared. The SAR is an example of radar that provides more information about a target than simply its location. It is the spatial resolution and imaging capability of SAR that has made its application of interest, especially from spaceborne platforms. However, for maximum utility to remote sensing, it was proposed that other information be extracted from SAR data, such as the cross section with frequency and polarization.

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

NASA Astrophysics Data System (ADS)

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 %.

Calibration of a polarimetric imaging SAR

NASA Technical Reports Server (NTRS)

Sarabandi, K.; Pierce, L. E.; Ulaby, F. T.

1991-01-01

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

A Modified Subpulse SAR Processing Procedure Based on the Range-Doppler Algorithm for Synthetic Wideband Waveforms

PubMed Central

Lim, Byoung-Gyun; Woo, Jea-Choon; Lee, Hee-Young; Kim, Young-Soo

2008-01-01

Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is used to acquire the SAR images for synthetic wideband signals, errors occur due to approximations, so the images may not show the best possible result. This paper proposes a modified subpulse SAR processing algorithm for synthetic wideband signals which is based on RDA. An experiment with an automobile-based SAR system showed that the proposed algorithm is quite accurate with a considerable improvement in resolution and quality of the obtained SAR image. PMID:27873984

Science Results from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR): Progress Report

NASA Technical Reports Server (NTRS)

Evans, Diane L. (Editor); Plaut, Jeffrey (Editor)

1996-01-01

The Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) is the most advanced imaging radar system to fly in Earth orbit. Carried in the cargo bay of the Space Shuttle Endeavour in April and October of 1994, SIR-C/X-SAR simultaneously recorded SAR data at three wavelengths (L-, C-, and X-bands; 23.5, 5.8, and 3.1 cm, respectively). The SIR-C/X-SAR Science Team consists of 53 investigator teams from more than a dozen countries. Science investigations were undertaken in the fields of ecology, hydrology, ecology, and oceanography. This report contains 44 investigator team reports and several additional reports from coinvestigators and other researchers.

Synergy of Optical and SAR Data for Mapping and Monitoring Mangroves

NASA Astrophysics Data System (ADS)

Monzon, A. K.; Reyes, S. R.; Veridiano, R. K.; Tumaneng, R.; De Alban, J. D.

2016-06-01

Quantitative information on mangrove cover extents is essential in producing relevant resource management plans and conservation strategies. In the Philippines, mangrove rehabilitation was made a priority in relation to disaster risk response and mitigation following the calamities in the coastal communities during typhoon Haiyan/Yolanda; hence, baseline information on the extent of remaining mangrove cover was essential for effective site interventions. Although mangrove cover maps for the country already exists, analysis of mangrove cover changes were limited to the application of fixed annual deforestation rates due to the challenge of acquiring consistent temporal cloud-free optical satellite data over large landscapes. This study presents an initial analysis of SAR and optical imagery combined with field-based observations for detecting mangrove cover extent and changes through a straightforward graphical approach. The analysis is part of a larger study evaluating the synergistic use of time-series L-band SAR and optical data for mapping and monitoring of mangroves. Image segmentation was implemented on the 25-meter ALOS/PALSAR image mosaics, in which the generated objects were subjected to statistical analysis using the software R. In combination with selected Landsat bands, the class statistics from the image bands were used to generate decision trees and thresholds for the hierarchical image classification. The results were compared with global mangrove cover dataset and validated using collected ground truth data. This study developed an integrated replicable approach for analyzing future radar and optical datasets, essential in national level mangrove cover change monitoring and assessment for long-term conservation targets and strategies.

Comparison of multiple methods for detecting changes in urban areas in TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hammer, Horst; Dubois, Clémence; Boldt, Markus; Kuny, Silvia; Cadario, Erich; Thiele, Antje

2016-10-01

The current generation of SAR satellites such as TerraSAR-X, TanDEM-X and COSMO-SkyMed provide resolutions below one meter, permitting the detailed analysis of urban areas while covering large zones. Furthermore, as they are deployable independently of daylight and weather, such remote sensing SAR data are particularly popular for purposes such as rapid damage assessment at building level after a natural disaster. The purpose of our study is the investigation of techniques for the detection of changes based on one pre-event and one post-event SAR amplitude image. We provide a comparison of several methods for detecting changes in urban areas. Especially, changes at building locations are looked for. We analyzed two areas affected differently in detail. First, a suburban area of Paris, France, was considered due to changes caused by an urbanization project. Here, we have two TanDEM-X acquisitions available, before (November 4, 2012) and after (May 10, 2013) the changes. Second, we investigated changes that happened in Kathmandu, Nepal, after the April 25, 2015 earthquake. For this analysis, we have two TerraSAR-X acquisitions, one before (October 13, 2013) and one immediately after (April 27, 2015) the earthquake. Both areas differ by the building types, the image resolution and the available reference, which makes it an interesting challenge. In this paper, we compare six different methods for change detection. The investigated methods contain both standard criteria such as Log Ratio, Kullback-Leibler and the Difference of Entropies detector, and methods developed by the authors such as a Log Ratio combined with an Alternating Sequential Filter. All change detection results are presented and discussed by considering the available ground truth.

Damage extraction of buildings in the 2015 Gorkha, Nepal earthquake from high-resolution SAR data

NASA Astrophysics Data System (ADS)

Yamazaki, Fumio; Bahri, Rendy; Liu, Wen; Sasagawa, Tadashi

2016-05-01

Satellite remote sensing is recognized as one of the effective tools for detecting and monitoring affected areas due to natural disasters. Since SAR sensors can capture images not only at daytime but also at nighttime and under cloud-cover conditions, they are especially useful at an emergency response period. In this study, multi-temporal high-resolution TerraSAR-X images were used for damage inspection of the Kathmandu area, which was severely affected by the April 25, 2015 Gorkha Earthquake. The SAR images obtained before and after the earthquake were utilized for calculating the difference and correlation coefficient of backscatter. The affected areas were identified by high values of the absolute difference and low values of the correlation coefficient. The post-event high-resolution optical satellite images were employed as ground truth data to verify our results. Although it was difficult to estimate the damage levels for individual buildings, the high resolution SAR images could illustrate their capability in detecting collapsed buildings at emergency response times.

Synthetic aperture radar/LANDSAT MSS image registration

NASA Technical Reports Server (NTRS)

Maurer, H. E. (Editor); Oberholtzer, J. D. (Editor); Anuta, P. E. (Editor)

1979-01-01

Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint.

Impulse Response Shaping for Ultra Wide Band SAR in a Circular Flight Path

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1996-01-01

An ultra wide band SAR (synthetic aperture radar) has potential applications on imaging underground objects. Flying this SAR in a circular flight path is an efficient way to acquire high resolution images from a localized area. This paper characterizes the impulse response of sucha system. The results indicate that to achieve an image with a more uniformed resolution over the entire imaged area, proper weighting coeficients should be applied to both the principle aperture and the complimentary aperture.

Nature, distribution, and origin of Titan’s Undifferentiated Plains

USGS Publications Warehouse

Lopes, Rosaly; Malaska, M. J.; Solomonidou, A.; Le, Gall A.; Janssen, M.A.; Neish, Catherine D.; Turtle, E.P.; Birch, S. P. D.; Hayes, A.G.; Radebaugh, J.; Coustenis, A.; Schoenfeld, A.; Stiles, B.W.; Kirk, Randolph L.; Mitchell, K.L.; Stofan, E.R.; Lawrence, K. J.; ,

2016-01-01

The Undifferentiated Plains on Titan, first mapped by Lopes et al. (Lopes, R.M.C. et al., 2010. Icarus, 205, 540–588), are vast expanses of terrains that appear radar-dark and fairly uniform in Cassini Synthetic Aperture Radar (SAR) images. As a result, these terrains are often referred to as “blandlands”. While the interpretation of several other geologic units on Titan – such as dunes, lakes, and well-preserved impact craters – has been relatively straightforward, the origin of the Undifferentiated Plains has remained elusive. SAR images show that these “blandlands” are mostly found at mid-latitudes and appear relatively featureless at radar wavelengths, with no major topographic features. Their gradational boundaries and paucity of recognizable features in SAR data make geologic interpretation particularly challenging. We have mapped the distribution of these terrains using SAR swaths up to flyby T92 (July 2013), which cover >50% of Titan’s surface. We compared SAR images with other data sets where available, including topography derived from the SARTopo method and stereo DEMs, the response from RADAR radiometry, hyperspectral imaging data from Cassini’s Visual and Infrared Mapping Spectrometer (VIMS), and near infrared imaging from the Imaging Science Subsystem (ISS). We examined and evaluated different formation mechanisms, including (i) cryovolcanic origin, consisting of overlapping flows of low relief or (ii) sedimentary origins, resulting from fluvial/lacustrine or aeolian deposition, or accumulation of photolysis products created in the atmosphere. Our analysis indicates that the Undifferentiated Plains unit is consistent with a composition predominantly containing organic rather than icy materials and formed by depositional and/or sedimentary processes. We conclude that aeolian processes played a major part in the formation of the Undifferentiated Plains; however, other processes (fluvial, deposition of photolysis products) are likely to have contributed, possibly in differing proportions depending on location.

Oil Spill Map for Indian Sea Region based on Bhuvan- Geographic Information System using Satellite Images

NASA Astrophysics Data System (ADS)

Vijaya kumar, L. J.; Kishore, J. K.; Kesava Rao, P.; Annadurai, M.; Dutt, C. B. S.; Hanumantha Rao, K.; Sasamal, S. K.; Arulraj, M.; Prasad, A. V. V.; Kumari, E. V. S. Sita; Satyanarayana, S. N.; Shenoy, H. P.

2014-11-01

Oil spills in the ocean are a serious marine disaster that needs regular monitoring for environmental risk assessment and mitigation. Recent use of Polarimetric SAR imagery in near real time oil spill detection systems is associated with attempts towards automatic and unambiguous oil spill detection based on decomposition methods. Such systems integrate remote sensing technology, geo information, communication system, hardware and software systems to provide key information for analysis and decision making. Geographic information systems (GIS) like BHUVAN can significantly contribute to oil spill management based on Synthetic Aperture Radar (SAR) images. India has long coast line from Gujarat to Bengal and hundreds of ports. The increase in shipping also increases the risk of oil spills in our maritime zone. The availability of RISAT-1 SAR images enhances the scope to monitor oil spills and develop GIS on Bhuvan which can be accessed by all the users, such as ships, coast guard, environmentalists etc., The GIS enables realization of oil spill maps based on integration of the geographical, remote sensing, oil & gas production/infrastructure data and slick signatures detected by SAR. SAR and GIS technologies can significantly improve the realization of oil spill footprint distribution maps. Preliminary assessment shows that the Bhuvan promises to be an ideal solution to understand spatial, temporal occurrence of oil spills in the marine atlas of India. The oil spill maps on Bhuvan based GIS facility will help the ONGC and Coast Guard organization.

Registration of interferometric SAR images

NASA Technical Reports Server (NTRS)

Lin, Qian; Vesecky, John F.; Zebker, Howard A.

1992-01-01

Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

Ground Displacement Measurement of the 2013 Balochistan Earthquake with interferometric TerraSAR-X ScanSAR data

NASA Astrophysics Data System (ADS)

Yague-Martinez, N.; Fielding, E. J.; Haghshenas-Haghighi, M.; Cong, X.; Motagh, M.

2014-12-01

This presentation will address the 24 September 2013 Mw 7.7 Balochistan Earthquake in western Pakistan from the point of view of interferometric processing algorithms of wide-swath TerraSAR-X ScanSAR images. The algorithms are also valid for TOPS acquisition mode, the operational mode of the Sentinel-1A ESA satellite that was successfully launched in April 2014. Spectral properties of burst-mode data and an overview of the interferometric processing steps of burst-mode acquisitions, emphasizing the importance of the co-registration stage, will be provided. A co-registration approach based on incoherent cross-correlation will be presented and applied to seismic scenarios. Moreover geodynamic corrections due to differential atmospheric path delay and differential solid Earth tides are considered to achieve accuracy in the order of several centimeters. We previously derived a 3D displacement map using cross-correlation techniques applied to optical images from Landsat-8 satellite and TerraSAR-X ScanSAR amplitude images. The Landsat-8 cross-correlation measurements cover two horizontal directions, and the TerraSAR-X displacements include both horizontal along-track and slant-range (radar line-of-sight) measurements that are sensitive to vertical and horizontal deformation. It will be justified that the co-seismic displacement map from TerraSAR-X ScanSAR data may be contaminated by postseismic deformation due to the fact that the post-seismic acquisition took place one month after the main shock, confirmed in part by a TerraSAR-X stripmap interferogram (processed with conventional InSAR) covering part of the area starting on 27 September 2013. We have arranged the acquisition of a burst-synchronized stack of TerraSAR-X ScanSAR images over the affected area after the earthquake. It will be possible to apply interferometry to these data to measure the lower magnitude of the expected postseismic displacements. The processing of single interferograms will be discussed. A quicklook of the wrapped differential TerraSAR-X ScanSAR co-seismic interferogram is provided in the attachment (range coverage is 100 km by using 4 subswaths).

Observing the Microseism Source Regions from Space

NASA Astrophysics Data System (ADS)

Simard, M.; Kedar, S.; Rodriguez, E.; Webb, F. H.

2005-12-01

Correlations of this ambient seismic signal between seismic stations has recently emerged as a powerful technique for tomography of the Earth's crust, allowing continuous global monitoring of the crust to seismogenic depths without relying on the occurrence of earthquakes. The technique has the potential for resolving changes in the crust during periods of little or no earthquake activity. Since ambient seismic noise is predominantly generated by ocean wave-wave interactions known to originate in narrowly defined geographical source areas that vary according to ocean swell state and season, it may be possible to derive physical constraints of the source characteristics by globallyly observing candidate source regions from space. At present, such observations have been confined to point measurements such as directional buoys and ocean-bottom seismometers. Using a technique formulated by Engen and Jonsen [1995], a 'field view' of the generating region can be obtained by deriving ocean directional spectra from Synthetic Aperature Radar (SAR) images by analysis of cross correlation of single-look SAR images. In November 2004, the Jet Propulsion Laboratory's (JPL) air-borne SAR instrument, has collected data off the Alaska coast, while a large storm with wave heights of ~8m was pounding the coast. This was contemporaneous with the recording of strong microseismic activity by the Canadian National Seismic (CNSN). The AirSAR collected over a 100km long, 10km wide swath offshore, the region most likely to involve wave-wave interaction between the incoming swell and coast-reflected waves. JPL has implemented the cross correlation spectral technique, and applied it to the 2004 data-set. We will present results of the analysis of the SAR data in conjunction with analysis of the CNSN broadband seismic data.

Ship dynamics for maritime ISAR imaging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter

2008-02-01

Demand is increasing for imaging ships at sea. Conventional SAR fails because the ships are usually in motion, both with a forward velocity, and other linear and angular motions that accompany sea travel. Because the target itself is moving, this becomes an Inverse- SAR, or ISAR problem. Developing useful ISAR techniques and algorithms is considerably aided by first understanding the nature and characteristics of ship motion. Consequently, a brief study of some principles of naval architecture sheds useful light on this problem. We attempt to do so here. Ship motions are analyzed for their impact on range-Doppler imaging using Inversemore » Synthetic Aperture Radar (ISAR). A framework for analysis is developed, and limitations of simple ISAR systems are discussed.« less

Decreasing range resolution of a SAR image to permit correction of motion measurement errors beyond the SAR range resolution

DOEpatents

Doerry, Armin W.; Heard, Freddie E.; Cordaro, J. Thomas

2010-07-20

Motion measurement errors that extend beyond the range resolution of a synthetic aperture radar (SAR) can be corrected by effectively decreasing the range resolution of the SAR in order to permit measurement of the error. Range profiles can be compared across the slow-time dimension of the input data in order to estimate the error. Once the error has been determined, appropriate frequency and phase correction can be applied to the uncompressed input data, after which range and azimuth compression can be performed to produce a desired SAR image.

COSMO-SkyMed measurements in precipitation over the sea: analysis of Louisiana summer thunderstorms by simultaneous weather radar observations

NASA Astrophysics Data System (ADS)

Roberto, N.; Baldini, L.; Gorgucci, E.; Facheris, L.; Chandrasekar, V.

2012-04-01

Radar signatures of rain cells are investigated using X-band synthetic aperture radar (X-SAR) images acquired from COSMO-SkyMed constellation over oceans off the coast of Louisiana in summer 2010 provided by ASI archive. COSMO-SkyMed (CSK) monitoring of Deepwater Horizon oil spill provided a big amount of data during the period April-September 2010 and in July-August when several thunderstorms occurred in that area. In X-SAR images, radar signatures of rain cells over the sea usually consist of irregularly shaped bright and dark patches. These signatures originate from 1) the scattering and attenuation of radiation by hydrometers in the rain cells and 2) the modification of the sea roughness induced by the impact of raindrops and by wind gusts associated with rain cell. However, the interpretation of precipitation signatures in X-SAR images is not completely straightforward, especially over sea. Coincident measurements from ground based radars and an electromagnetic (EM) model predicting radar returns from the sea surface corrugated by rainfall are used to support the analysis. A dataset consisting of 4 CSK images has been collected over Gulf of Mexico while a WSR-88D NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the nearby portion of ocean. Terrestrial measurements have been used to reconstruct the component of X-SAR returns due to precipitation by modifying the known technique applied on measurements over land (Fritz et al. 2010, Baldini et al. 2011). Results confirm that the attenuation signature in X-SAR images collected over land, particularly pronounced in the presence of heavy precipitation cells, can be related to the S-band radar reflectivity integrated along the same path. The Normalized Radar Cross Section (NRCS) of land is considered to vary usually up to a few dBs in case of rain but with strong dependency on the specific type and conditions of land cover. While the NRCS of sea surface in clear weather condition can be considered as constant, in case of rain, at X-SAR incidence angles, it exhibits a dependence to precipitation event due the combined effects of corrugation due to the impinging raindrops and to the surface wind. Therefore, when retrieving of X-SAR NRCS in precipitation over the sea, this effect must be accounted for and can be quantified based on the precipitation event using a simple NRCS surface model. In this work, an EM model based on Bahar's Full Wave Model is used for evaluating such NRCS depending on polarization, frequency and incidence angle for different values of wind velocity and the root mean square height of the corrugation induced by rainfall. The reconstruction of X-SAR returns in precipitation is finally obtained by joint utilization of volume reflectivity and attenuation estimated from KLIX and the sea NRCS model.

Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

NASA Astrophysics Data System (ADS)

Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

2016-11-01

For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

Space Radar Image of Kilauea Volcano, Hawaii

NASA Technical Reports Server (NTRS)

1994-01-01

This three-dimensional image of the volcano Kilauea was generated based on interferometric fringes derived from two X-band Synthetic Aperture Radar data takes on April 13, 1994 and October 4, 1994. The altitude lines are based on quantitative interpolation of the topographic fringes. The level difference between neighboring altitude lines is 20 meters (66 feet). The ground area covers 12 kilometers by 4 kilometers (7.5 miles by 2.5 miles). The altitude difference in the image is about 500 meters (1,640 feet). The volcano is located around 19.58 degrees north latitude and 155.55 degrees west longitude. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR. The Instituto Ricerca Elettromagnetismo Componenti Elettronici (IRECE) at the University of Naples was a partner in the interferometry analysis.

Space Radar Image of Kilauea, Hawaii - interferometry 1

NASA Technical Reports Server (NTRS)

1994-01-01

This X-band image of the volcano Kilauea was taken on October 4, 1994, by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar. The area shown is about 9 kilometers by 13 kilometers (5.5 miles by 8 miles) and is centered at about 19.58 degrees north latitude and 155.55 degrees west longitude. This image and a similar image taken during the first flight of the radar instrument on April 13, 1994 were combined to produce the topographic information by means of an interferometric process. This is a process by which radar data acquired on different passes of the space shuttle is overlaid to obtain elevation information. Three additional images are provided showing an overlay of radar data with interferometric fringes; a three-dimensional image based on altitude lines; and, finally, a topographic view of the region. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR. The Instituto Ricerca Elettromagnetismo Componenti Elettronici (IRECE) at the University of Naples was a partner in interferometry analysis.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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 varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically, and studied extensively in the field. High resolution TerraSAR-X (TSX) images covering the entire research area were acquired for the period of 2011 to 2012. Analysis was performed in imaging processing and GIS software. The coherence results display minor changes on the dune crest (0.42-0.49), compared to bigger changes in windward slope (0.31-0.37). The level of change depends on the dune location relative to its distance from the sea. Furthermore, the coherence results show decreasing over time. Field results indicate erosion/deposition of sand ranging from -99 to 137 mm/year. The results of this study confirm that it is possible to monitor subtle changes in sand dunes and to identify dune stability or instability, only by the use of SAR images, even in areas characterized by low coherence.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Synthetic aperture radar images of ocean waves, theories of imaging physics and experimental tests

NASA Technical Reports Server (NTRS)

Vesecky, J. F.; Durden, S. L.; Smith, M. P.; Napolitano, D. A.

1984-01-01

The physical mechanism for the synthetic Aperture Radar (SAR) imaging of ocean waves is investigated through the use of analytical models. The models are tested by comparison with data sets from the SEASAT mission and airborne SAR's. Dominant ocean wavelengths from SAR estimates are biased towards longer wavelengths. The quasispecular scattering mechanism agrees with experimental data. The Doppler shift for ship wakes is that of the mean sea surface.

Speckle-reducing scale-invariant feature transform match for synthetic aperture radar image registration

NASA Astrophysics Data System (ADS)

Wang, Xianmin; Li, Bo; Xu, Qizhi

2016-07-01

The anisotropic scale space (ASS) is often used to enhance the performance of a scale-invariant feature transform (SIFT) algorithm in the registration of synthetic aperture radar (SAR) images. The existing ASS-based methods usually suffer from unstable keypoints and false matches, since the anisotropic diffusion filtering has limitations in reducing the speckle noise from SAR images while building the ASS image representation. We proposed a speckle reducing SIFT match method to obtain stable keypoints and acquire precise matches for the SAR image registration. First, the keypoints are detected in a speckle reducing anisotropic scale space constructed by the speckle reducing anisotropic diffusion, so that speckle noise is greatly reduced and prominent structures of the images are preserved, consequently the stable keypoints can be derived. Next, the probabilistic relaxation labeling approach is employed to establish the matches of the keypoints then the correct match rate of the keypoints is significantly increased. Experiments conducted on simulated speckled images and real SAR images demonstrate the effectiveness of the proposed method.

A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

NASA Astrophysics Data System (ADS)

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, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

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

NASA Astrophysics Data System (ADS)

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 tomograms (imaging), their 3D positions and motion parameters (deformation). A progress report will be shown on these different aspects.This work is partially supported by the CSC and UCL MAPS Dean prize through a PhD studentship at UCL-MSSL.

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

PubMed Central

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 by OKTAL-SE. PMID:27447635

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

PubMed

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

2016-07-19

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 by OKTAL-SE.

Apodized RFI filtering of synthetic aperture radar images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter

2014-02-01

Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFImore » Filtering (ARF).« less

Radar transponder apparatus and signal processing technique

DOEpatents

Axline, Jr., Robert M.; Sloan, George R.; Spalding, Richard E.

1996-01-01

An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder's echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

Radar transponder apparatus and signal processing technique

DOEpatents

Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

1996-01-23

An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR. 4 figs.

Ionospheric Specifications for SAR Interferometry (ISSI)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Chapman, Bruce D; Freeman, Anthony; Szeliga, Walter; Buckley, Sean M.; Rosen, Paul A.; Lavalle, Marco

2013-01-01

The ISSI software package is designed to image the ionosphere from space by calibrating and processing polarimetric synthetic aperture radar (PolSAR) data collected from low Earth orbit satellites. Signals transmitted and received by a PolSAR are subject to the Faraday rotation effect as they traverse the magnetized ionosphere. The ISSI algorithms combine the horizontally and vertically polarized (with respect to the radar system) SAR signals to estimate Faraday rotation and ionospheric total electron content (TEC) with spatial resolutions of sub-kilometers to kilometers, and to derive radar system calibration parameters. The ISSI software package has been designed and developed to integrate the algorithms, process PolSAR data, and image as well as visualize the ionospheric measurements. A number of tests have been conducted using ISSI with PolSAR data collected from various latitude regions using the phase array-type L-band synthetic aperture radar (PALSAR) onboard Japan Aerospace Exploration Agency's Advanced Land Observing Satellite mission, and also with Global Positioning System data. These tests have demonstrated and validated SAR-derived ionospheric images and data correction algorithms.

Extracting built-up areas from TerraSAR-X data using object-oriented classification method

NASA Astrophysics Data System (ADS)

Wang, SuYun; Sun, Z. C.

2017-02-01

Based on single-polarized TerraSAR-X, the approach generates homogeneous segments on an arbitrary number of scale levels by applying a region-growing algorithm which takes the intensity of backscatter and shape-related properties into account. The object-oriented procedure consists of three main steps: firstly, the analysis of the local speckle behavior in the SAR intensity data, leading to the generation of a texture image; secondly, a segmentation based on the intensity image; thirdly, the classification of each segment using the derived texture file and intensity information in order to identify and extract build-up areas. In our research, the distribution of BAs in Dongying City is derived from single-polarized TSX SM image (acquired on 17th June 2013) with average ground resolution of 3m using our proposed approach. By cross-validating the random selected validation points with geo-referenced field sites, Quick Bird high-resolution imagery, confusion matrices with statistical indicators are calculated and used for assessing the classification results. The results demonstrate that an overall accuracy 92.89 and a kappa coefficient of 0.85 could be achieved. We have shown that connect texture information with the analysis of the local speckle divergence, combining texture and intensity of construction extraction is feasible, efficient and rapid.

Space Radar Image of West Texas - SAR scan

NASA Technical Reports Server (NTRS)

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 forthcoming Canadian RADARSAT satellite. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.v.(DLR), the major partner in science, operations, and data processing of X-SAR.

Reducing Speckle In One-Look SAR Images

NASA Technical Reports Server (NTRS)

Nathan, K. S.; Curlander, J. C.

1990-01-01

Local-adaptive-filter algorithm incorporated into digital processing of synthetic-aperture-radar (SAR) echo data to reduce speckle in resulting imagery. Involves use of image statistics in vicinity of each picture element, in conjunction with original intensity of element, to estimate brightness more nearly proportional to true radar reflectance of corresponding target. Increases ratio of signal to speckle noise without substantial degradation of resolution common to multilook SAR images. Adapts to local variations of statistics within scene, preserving subtle details. Computationally simple. Lends itself to parallel processing of different segments of image, making possible increased throughput.

Estimating IMU heading error from SAR images.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter

Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

SAR Speckle Noise Reduction Using Wiener Filter

NASA Technical Reports Server (NTRS)

Joo, T. H.; Held, D. N.

1983-01-01

Synthetic aperture radar (SAR) images are degraded by speckle. A multiplicative speckle noise model for SAR images is presented. Using this model, a Wiener filter is derived by minimizing the mean-squared error using the known speckle statistics. Implementation of the Wiener filter is discussed and experimental results are presented. Finally, possible improvements to this method are explored.

Monitoring of land subsidence in Ravenna Municipality using two different DInSAR techniques: comparison and discussion of the results.

NASA Astrophysics Data System (ADS)

Fiaschi, Simone; Di Martire, Diego; Tessitore, Serena; Achilli, Vladimiro; Ahmed, Ahmed; Borgstrom, Sven; Calcaterra, Domenico; Fabris, Massimo; Ramondini, Massimo; Serpelloni, Enrico; Siniscalchi, Valeria; Floris, Mario

2015-04-01

Land subsidence affecting the Ravenna Municipality (Emilia Romagna Region, NE Italy) is one of the best example on how the exploitation of natural resources can affect the environment and the territory. In fact, the pumping of groundwater and the extraction of gas from both on and off-shore reservoirs, started in the 1950s, have caused a strong land subsidence affecting most of the Emilia Romagna territory but in particular the Adriatic Sea coastline near Ravenna. In such area the current subsidence rate, even if lower than in the past, can reach the -2cm/y. Local Authorities have monitored this phenomenon over the years with different techniques: spirit levelling, GPS surveys and, more recently, Interferometric Synthetic Aperture Radar (InSAR) techniques, confirming the critical situation of land subsidence risk. In this work, we present the comparison between the results obtained with two different DInSAR techniques applied to the study of the land subsidence in the Ravenna territory: the Small Baseline Subset (SBAS) and the Coherent Pixel Technique (CPT) techniques. The SBAS works on SARscape software and is based on the Berardino et al., 2002 algorithm. This technique relies on the combination of differential interferograms created from stacks of SAR image pairs that have small temporal and perpendicular baselines. Thanks to the application of several interferograms for every single image, it is possible to obtain high spatial coherence, high data density and more effective error reduction. This allows us to obtain mean velocity maps with good data density even over non-urbanized territories. For the CPT we used the SUBsoft processor based on the algorithm implemented by Mora et al., 2003. CPT is able to extract from a stack of differential interferograms the deformation evolution over wide areas during large time spans. The processing scheme is composed of three main steps: a) the generation of the best interferogram set among all the available images of the zone under study; b) the selection of the pixels with reliable phase within the employed interferograms and, c) their phase analysis to calculate, as the main result, their deformation time series within the observation period. For this study, different SAR images have been used: 25 meters ground resolution ERS 1/2 (1992-2000) and ENVISAT (2003-2010), and 3 meters ground resolution TerraSAR-X (2012-2014). The results obtained for each stack of images with the two techniques are validated and compared with the C-GPS time series of more than three benchmarks stations. The aim is to test the two InSAR techniques in the monitoring of ground settlements in low urbanized territories. Furthermore, we have investigated the advantages (data accuracy and density) of using SAR images with higher ground resolution.

Allan Variance Computed in Space Domain: Definition and Application to InSAR Data to Characterize Noise and Geophysical Signal.

PubMed

Cavalié, Olivier; Vernotte, François

2016-04-01

The Allan variance was introduced 50 years ago for analyzing the stability of frequency standards. In addition to its metrological interest, it may be also considered as an estimator of the large trends of the power spectral density (PSD) of frequency deviation. For instance, the Allan variance is able to discriminate different types of noise characterized by different power laws in the PSD. The Allan variance was also used in other fields than time and frequency metrology: for more than 20 years, it has been used in accelerometry, geophysics, geodesy, astrophysics, and even finances. However, it seems that up to now, it has been exclusively applied for time series analysis. We propose here to use the Allan variance on spatial data. Interferometric synthetic aperture radar (InSAR) is used in geophysics to image ground displacements in space [over the synthetic aperture radar (SAR) image spatial coverage] and in time thanks to the regular SAR image acquisitions by dedicated satellites. The main limitation of the technique is the atmospheric disturbances that affect the radar signal while traveling from the sensor to the ground and back. In this paper, we propose to use the Allan variance for analyzing spatial data from InSAR measurements. The Allan variance was computed in XY mode as well as in radial mode for detecting different types of behavior for different space-scales, in the same way as the different types of noise versus the integration time in the classical time and frequency application. We found that radial Allan variance is the more appropriate way to have an estimator insensitive to the spatial axis and we applied it on SAR data acquired over eastern Turkey for the period 2003-2011. Spatial Allan variance allowed us to well characterize noise features, classically found in InSAR such as phase decorrelation producing white noise or atmospheric delays, behaving like a random walk signal. We finally applied the spatial Allan variance to an InSAR time series to detect when the geophysical signal, here the ground motion, emerges from the noise.

Ship Detection from Ocean SAR Image Based on Local Contrast Variance Weighted Information Entropy

PubMed Central

Huang, Yulin; Pei, Jifang; Zhang, Qian; Gu, Qin; Yang, Jianyu

2018-01-01

Ship detection from synthetic aperture radar (SAR) images is one of the crucial issues in maritime surveillance. However, due to the varying ocean waves and the strong echo of the sea surface, it is very difficult to detect ships from heterogeneous and strong clutter backgrounds. In this paper, an innovative ship detection method is proposed to effectively distinguish the vessels from complex backgrounds from a SAR image. First, the input SAR image is pre-screened by the maximally-stable extremal region (MSER) method, which can obtain the ship candidate regions with low computational complexity. Then, the proposed local contrast variance weighted information entropy (LCVWIE) is adopted to evaluate the complexity of those candidate regions and the dissimilarity between the candidate regions with their neighborhoods. Finally, the LCVWIE values of the candidate regions are compared with an adaptive threshold to obtain the final detection result. Experimental results based on measured ocean SAR images have shown that the proposed method can obtain stable detection performance both in strong clutter and heterogeneous backgrounds. Meanwhile, it has a low computational complexity compared with some existing detection methods. PMID:29652863

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

NASA Astrophysics Data System (ADS)

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.

Application of SEASAT-1 Synthetic Aperture Radar (SAR) data to enhance and detect geological lineaments and to assist LANDSAT landcover classification mapping. [Appalachian Region, West Virginia

NASA Technical Reports Server (NTRS)

Sekhon, R.

1981-01-01

Digital SEASAT-1 synthetic aperture radar (SAR) data were used to enhance linear features to extract geologically significant lineaments in the Appalachian region. Comparison of Lineaments thus mapped with an existing lineament map based on LANDSAT MSS images shows that appropriately processed SEASAT-1 SAR data can significantly improve the detection of lineaments. Merge MSS and SAR data sets were more useful fo lineament detection and landcover classification than LANDSAT or SEASAT data alone. About 20 percent of the lineaments plotted from the SEASAT SAR image did not appear on the LANDSAT image. About 6 percent of minor lineaments or parts of lineaments present in the LANDSAT map were missing from the SEASAT map. Improvement in the landcover classification (acreage and spatial estimation accuracy) was attained by using MSS-SAR merged data. The aerial estimation of residential/built-up and forest categories was improved. Accuracy in estimating the agricultural and water categories was slightly reduced.

Mathematical modeling and SAR simulation multifunction SAR technology efforts

NASA Technical Reports Server (NTRS)

Griffin, C. R.; Estes, J. M.

1981-01-01

The orbital SAR (synthetic aperture radar) simulation data was used in several simulation efforts directed toward advanced SAR development. Efforts toward simulating an operational radar, simulation of antenna polarization effects, and simulation of SAR images at serveral different wavelengths are discussed. Avenues for improvements in the orbital SAR simulation and its application to the development of advanced digital radar data processing schemes are indicated.

Determination of Classification Accuracy for Land Use/cover Types Using Landsat-Tm Spot-Mss and Multipolarized and Multi-Channel Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Dondurur, Mehmet

The primary objective of this study was to determine the degree to which modern SAR systems can be used to obtain information about the Earth's vegetative resources. Information obtainable from microwave synthetic aperture radar (SAR) data was compared with that obtainable from LANDSAT-TM and SPOT data. Three hypotheses were tested: (a) Classification of land cover/use from SAR data can be accomplished on a pixel-by-pixel basis with the same overall accuracy as from LANDSAT-TM and SPOT data. (b) Classification accuracy for individual land cover/use classes will differ between sensors. (c) Combining information derived from optical and SAR data into an integrated monitoring system will improve overall and individual land cover/use class accuracies. The study was conducted with three data sets for the Sleeping Bear Dunes test site in the northwestern part of Michigan's lower peninsula, including an October 1982 LANDSAT-TM scene, a June 1989 SPOT scene and C-, L- and P-Band radar data from the Jet Propulsion Laboratory AIRSAR. Reference data were derived from the Michigan Resource Information System (MIRIS) and available color infrared aerial photos. Classification and rectification of data sets were done using ERDAS Image Processing Programs. Classification algorithms included Maximum Likelihood, Mahalanobis Distance, Minimum Spectral Distance, ISODATA, Parallelepiped, and Sequential Cluster Analysis. Classified images were rectified as necessary so that all were at the same scale and oriented north-up. Results were analyzed with contingency tables and percent correctly classified (PCC) and Cohen's Kappa (CK) as accuracy indices using CSLANT and ImagePro programs developed for this study. Accuracy analyses were based upon a 1.4 by 6.5 km area with its long axis east-west. Reference data for this subscene total 55,770 15 by 15 m pixels with sixteen cover types, including seven level III forest classes, three level III urban classes, two level II range classes, two water classes, one wetland class and one agriculture class. An initial analysis was made without correcting the 1978 MIRIS reference data to the different dates of the TM, SPOT and SAR data sets. In this analysis, highest overall classification accuracy (PCC) was 87% with the TM data set, with both SPOT and C-Band SAR at 85%, a difference statistically significant at the 0.05 level. When the reference data were corrected for land cover change between 1978 and 1991, classification accuracy with the C-Band SAR data increased to 87%. Classification accuracy differed from sensor to sensor for individual land cover classes, Combining sensors into hypothetical multi-sensor systems resulted in higher accuracies than for any single sensor. Combining LANDSAT -TM and C-Band SAR yielded an overall classification accuracy (PCC) of 92%. The results of this study indicate that C-Band SAR data provide an acceptable substitute for LANDSAT-TM or SPOT data when land cover information is desired of areas where cloud cover obscures the terrain. Even better results can be obtained by integrating TM and C-Band SAR data into a multi-sensor system.

Digital SAR processing using a fast polynomial transform

NASA Technical Reports Server (NTRS)

Butman, S.; Lipes, R.; Rubin, A.; Truong, T. K.

1981-01-01

A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network.

SAR/LANDSAT image registration study

NASA Technical Reports Server (NTRS)

Murphrey, S. W. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.

Visualizing characteristics of ocean data collected during the Shuttle Imaging Radar-B experiment

NASA Technical Reports Server (NTRS)

Tilley, David G.

1991-01-01

Topographic measurements of sea surface elevation collected by the Surface Contour Radar (SCR) during NASA's Shuttle Imaging Radar (SIR-B) experiment are plotted as three dimensional surface plots to observe wave height variance along the track of a P-3 aircraft. Ocean wave spectra were computed from rotating altimeter measurements acquired by the Radar Ocean Wave Spectrometer (ROWS). Fourier power spectra computed from SIR-B synthetic aperture radar (SAR) images of the ocean are compared to ROWS surface wave spectra. Fourier inversion of SAR spectra, after subtraction of spectral noise and modeling of wave height modulation, yields topography similar to direct measurements made by SCR. Visual perspectives on the SCR and SAR ocean data are compared. Threshold distinctions between surface elevation and texture modulations of SAR data are considered within the context of a dynamic statistical model of rough surface scattering. The result of these endeavors is insight as to the physical mechanism governing the imaging of ocean waves with SAR.

Acousto-optic time- and space-integrating spotlight-mode SAR processor

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.

1993-09-01

The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.

GF-3 SAR Image Despeckling Based on the Improved Non-Local Means Using Non-Subsampled Shearlet Transform

NASA Astrophysics Data System (ADS)

Shi, R.; Sun, Z.

2018-04-01

GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously. Recently, Shearlet is applied to the image processing with its best sparse representation. A new Shearlet-transform-based method is proposed in this paper based on the improved non-local means. Firstly, the logarithmic operation and the non-subsampled Shearlet transformation are applied to the GF-3 SAR image. Secondly, in order to solve the problems that the image details are smoothed overly and the weight distribution is affected by the speckle, a new non-local means is used for the transformed high frequency coefficient. Thirdly, the Shearlet reconstruction is carried out. Finally, the final filtered image is obtained by an exponential operation. Experimental results demonstrate that, compared with other despeckling methods, the proposed method can suppress the speckle effectively in homogeneous regions and has better capability of edge preserving.

Spatiotemporal deformation patterns of the Lake Urmia Causeway as characterized by multisensor InSAR analysis.

PubMed

Karimzadeh, Sadra; Matsuoka, Masashi; Ogushi, Fumitaka

2018-04-03

We present deformation patterns in the Lake Urmia Causeway (LUC) in NW Iran based on data collected from four SAR sensors in the form of interferometric synthetic aperture radar (InSAR) time series. Sixty-eight images from Envisat (2004-2008), ALOS-1 (2006-2010), TerraSAR-X (2012-2013) and Sentinel-1 (2015-2017) were acquired, and 227 filtered interferograms were generated using the small baseline subset (SBAS) technique. The rate of line-of-sight (LOS) subsidence of the LUC peaked at 90 mm/year between 2012 and 2013, mainly due to the loss of most of the water in Lake Urmia. Principal component analysis (PCA) was conducted on 200 randomly selected time series of the LUC, and the results are presented in the form of the three major components. The InSAR scores obtained from the PCA were used in a hydro-thermal model to investigate the dynamics of consolidation settlement along the LUC based on detrended water level and temperature data. The results can be used to establish a geodetic network around the LUC to identify more detailed deformation patterns and to help plan future efforts to reduce the possible costs of damage.

The InSAR Scientific Computing Environment

NASA Technical Reports Server (NTRS)

Rosen, Paul A.; Gurrola, Eric; Sacco, Gian Franco; Zebker, Howard

2012-01-01

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

Extraction of Coastlines with Fuzzy Approach Using SENTINEL-1 SAR Image

NASA Astrophysics Data System (ADS)

Demir, N.; Kaynarca, M.; Oy, S.

2016-06-01

Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS) Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the LIDAR points of coastline with the extracted coastline. The statistics of the distances are calculated as following; the mean is 5.82m, standard deviation is 5.83m and the median value is 4.08 m. Secondly, the extracted coastline is also evaluated with manually created lines on SAR image. Both lines are converted to dense points with 1 m interval. Then the closest distances are calculated between the points from extracted coastline and manually created coastline. The mean is 5.23m, standard deviation is 4.52m. and the median value is 4.13m for the calculated distances. The evaluation values are within the accuracy of used SAR data for both quality assessment approaches.

Earthquake-Induced Building Damage Assessment Based on SAR Correlation and Texture

NASA Astrophysics Data System (ADS)

Gong, Lixia; Li, Qiang; Zhang, Jingfa

2016-08-01

Comparing with optical Remote Sensing, the Synthetic Aperture Radar (SAR) has unique advantages as applied to seismic hazard monitoring and evaluation. SAR can be helpful in the whole process of after an earthquake, which can be divided into three stages. On the first stage, pre-disaster imagery provides history information of the attacked area. On the mid-term stage, up-to-date thematic maps are provided for disaster relief. On the later stage, information is provided to assist secondary disaster monitoring, post- disaster assessment and reconstruction second stage. In recent years, SAR has become an important data source of earthquake damage analysis and evaluation.Correlation between pre- and post-event SAR images is considered to be related with building damage. There will be a correlation decrease when the building collapsed in a shock. Whereas correlation decrease does not definitely indicate building changes. Correlation is also affected by perpendicular baseline, the ground coverage type, atmospheric change and other natural conditions, data processing and other factors. Building samples in the earthquake are used to discriminate the relation between damage degree and SAR correlation.

Earthquake damage mapping by using remotely sensed data: the Haiti case study

NASA Astrophysics Data System (ADS)

Romaniello, Vito; Piscini, Alessandro; Bignami, Christian; Anniballe, Roberta; Stramondo, Salvatore

2017-01-01

This work proposes methodologies aimed at evaluating the sensitivity of optical and synthetic aperture radar (SAR) change features obtained from satellite images with respect to the damage grade due to an earthquake. The test case is the Mw 7.0 earthquake that hit Haiti on January 12, 2010, located 25 km west-south-west of the city of Port-au-Prince. The disastrous shock caused the collapse of a huge number of buildings and widespread damage. The objective is to investigate possible parameters that can affect the robustness and sensitivity of the proposed methods derived from the literature. It is worth noting how the proposed analysis concerns the estimation of derived features at object scale. For this purpose, a segmentation of the study area into several regions has been done by considering a set of polygons, over the city of Port-au-Prince, extracted from the open source open street map geo-database. The analysis of change detection indicators is based on ground truth information collected during a postearthquake survey and is available from a Joint Research Centre database. The resulting damage map is expressed in terms of collapse ratio, thus indicating the areas with a greater number of collapsed buildings. The available satellite dataset is composed of optical and SAR images, collected before and after the seismic event. In particular, we used two GeoEye-1 optical images (one preseismic and one postseismic) and three TerraSAR-X SAR images (two preseismic and one postseismic). Previous studies allowed us to identify some features having a good sensitivity with damage at the object scale. Regarding the optical data, we selected the normalized difference index and two quantities coming from the information theory, namely the Kullback-Libler divergence (KLD) and the mutual information (MI). In addition, for the SAR data, we picked out the intensity correlation difference and the KLD parameter. In order to analyze the capability of these parameters to correctly detect damaged areas, two different classifiers were used: the Naive Bayes and the support vector machine classifiers. The classification results demonstrate that the simultaneous use of several change features from Earth observations can improve the damage estimation at object scale.

Classification of the Gabon SAR Mosaic Using a Wavelet Based Rule Classifier

NASA Technical Reports Server (NTRS)

Simard, Marc; Saatchi, Sasan; DeGrandi, Gianfranco

2000-01-01

A method is developed for semi-automated classification of SAR images of the tropical forest. Information is extracted using the wavelet transform (WT). The transform allows for extraction of structural information in the image as a function of scale. In order to classify the SAR image, a Desicion Tree Classifier is used. The method of pruning is used to optimize classification rate versus tree size. The results give explicit insight on the type of information useful for a given class.

FIREX mission requirements document for nonrenewable resources

NASA Technical Reports Server (NTRS)

Dixon, T.; Carsey, F.

1982-01-01

The proposed mission requirements and a proposed experimental program for satellite synthetic aperture radar (SAR) system named FIREX (Free-Flying Imaging Radar Experiment) for nonrenewable resources is described. The recommended spacecraft minimum SAR system is a C-band imager operating in four modes: (1) low look angle HH-polarized; (2) intermediate look angle, HH-polarized; (3) intermediate look angle, IIV-polarized; and (4) high look angle HH-polarized. This SAR system is complementary to other future spaceborne imagers such as the Thematic Mapper on LANDSAT-D. A near term aircraft SAR based research program is outlined which addresses specific mission design issues such as preferred incidence angles or polarizations for geologic targets of interest.

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

NASA Astrophysics Data System (ADS)

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.

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

Development of Wind Speed Retrieval from Cross-Polarization Chinese Gaofen-3 Synthetic Aperture Radar in Typhoons

PubMed Central

Yuan, Xinzhe; Sun, Jian; Zhou, Wei; Zhang, Qingjun

2018-01-01

The purpose of our work is to determine the feasibility and effectiveness of retrieving sea surface wind speeds from C-band cross-polarization (herein vertical-horizontal, VH) Chinese Gaofen-3 (GF-3) SAR images in typhoons. In this study, we have collected three GF-3 SAR images acquired in Global Observation (GLO) and Wide ScanSAR (WSC) mode during the summer of 2017 from the China Sea, which includes the typhoons Noru, Doksuri and Talim. These images were collocated with wind simulations at 0.12° grids from a numeric model, called the Regional Assimilation and Prediction System-Typhoon model (GRAPES-TYM). Recent research shows that GRAPES-TYM has a good performance for typhoon simulation in the China Sea. Based on the dataset, the dependence of wind speed and of radar incidence angle on normalized radar cross (NRCS) of VH-polarization GF-3 SAR have been investigated, after which an empirical algorithm for wind speed retrieval from VH-polarization GF-3 SAR was tuned. An additional four VH-polarization GF-3 SAR images in three typhoons, Noru, Hato and Talim, were investigated in order to validate the proposed algorithm. SAR-derived winds were compared with measurements from Windsat winds at 0.25° grids with wind speeds up to 40 m/s, showing a 5.5 m/s root mean square error (RMSE) of wind speed and an improved RMSE of 5.1 m/s wind speed was achieved compared with the retrieval results validated against GRAPES-TYM winds. It is concluded that the proposed algorithm is a promising potential technique for strong wind retrieval from cross-polarization GF-3 SAR images without encountering a signal saturation problem. PMID:29385068

Subsidence monitoring and prediction of high-speed railway in Beijing with multitemporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Fan, Zelin; Zhang, Yonghong; Wu, Hong'an; Kang, Yonghui; Jiang, Decai

2018-02-01

The uneven settlement of high-speed railway (HSR) brings about great threat to the safe operation of trains. Therefore, the subsidence monitoring and prediction of HSR has important significance. In this paper, an improved multitemporal InSAR method combing PS-InSAR and SBAS-InSAR, Multiple-master Coherent Target Small-Baseline InSAR (MCTSB-InSAR), is used to monitor the subsidence of partial section of the Beijing-Tianjin HSR (BTHSR) and the Beijing-Shanghai HSR (BSHSR) in Beijing area. Thirty-one TerraSAR-X images from June 2011 to December 2016 are processed with the MCTSB-InSAR, and the subsidence information of the region covering 56km*32km in Beijing is dug out. Moreover, the monitoring results is validated by the leveling measurements in this area, with the accuracy of 4.4 mm/year. On the basis of above work, we extract the subsidence information of partial section of BTHSR and BSHSR in the research area. Finally, we adopt the idea of timing analysis, and employ the back-propagation (BP) neural network to simulate the relationship between former settlement and current settlement. Training data sets and test data sets are constructed respectively based on the monitoring results. The experimental results show that the prediction model has good prediction accuracy and applicability.

Observations with the ROWS instrument during the Grand Banks calibration/validation experiments

NASA Technical Reports Server (NTRS)

Vandemark, D.; Chapron, B.

1994-01-01

As part of a global program to validate the ocean surface sensors on board ERS-1, a joint experiment on the Grand Banks of Newfoundland was carried out in Nov. 1991. The principal objective was to provide a field validation of ERS-1 Synthetic Aperture Radar (SAR) measurement of ocean surface structure. The NASA-P3 aircraft measurements made during this experiment provide independent measurements of the ocean surface along the validation swath. The Radar Ocean Wave Spectrometer (ROWS) is a radar sensor designed to measure direction of the long wave components using spectral analysis of the tilt induced radar backscatter modulation. This technique greatly differs from SAR and thus, provides a unique set of measurements for use in evaluating SAR performance. Also, an altimeter channel in the ROWS gives simultaneous information on the surface wave height and radar mean square slope parameter. The sets of geophysical parameters (wind speed, significant wave height, directional spectrum) are used to study the SAR's ability to accurately measure ocean gravity waves. The known distortion imposed on the true directional spectrum by the SAR imaging mechanism is discussed in light of the direct comparisons between ERS-1 SAR, airborne Canadian Center for Remote Sensing (CCRS) SAR, and ROWS spectra and the use of the nonlinear ocean SAR transform.

Analysis, comparison, and modeling of radar interferometry, date of surface deformation signals associated with underground explosions, mine collapses and earthquakes. Phase I: underground explosions, Nevada Test Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foxall, W; Vincent, P; Walter, W

1999-07-23

We have previously presented simple elastic deformation modeling results for three classes of seismic events of concern in monitoring the CTBT--underground explosions, mine collapses and earthquakes. Those results explored the theoretical detectability of each event type using synthetic aperture radar interferometry (InSAR) based on commercially available satellite data. In those studies we identified and compared the characteristics of synthetic interferograms that distinguish each event type, as well the ability of the interferograms to constrain source parameters. These idealized modeling results, together with preliminary analysis of InSAR data for the 1995 mb 5.2 Solvay mine collapse in southwestern Wyoming, suggested thatmore » InSAR data used in conjunction with regional seismic monitoring holds great potential for CTBT discrimination and seismic source analysis, as well as providing accurate ground truth parameters for regional calibration events. In this paper we further examine the detectability and ''discriminating'' power of InSAR by presenting results from InSAR data processing, analysis and modeling of the surface deformation signals associated with underground explosions. Specifically, we present results of a detailed study of coseismic and postseismic surface deformation signals associated with underground nuclear and chemical explosion tests at the Nevada Test Site (NTS). Several interferograms were formed from raw ERS-1/2 radar data covering different time spans and epochs beginning just prior to the last U.S. nuclear tests in 1992 and ending in 1996. These interferograms have yielded information about the nature and duration of the source processes that produced the surface deformations associated with these events. A critical result of this study is that significant post-event surface deformation associated with underground nuclear explosions detonated at depths in excess of 600 meters can be detected using differential radar interferometry. An immediate implication of this finding is that underground nuclear explosions may not need to be captured coseismically by radar images acquired before and after an event in order to be detectable. This has obvious advantages in CTBT monitoring since suspect seismic events--which usually can be located within a 100 km by 100 km area of an ERS-1/2 satellite frame by established seismic methods-can be imaged after the event has been identified and located by existing regional seismic networks. Key Words: InSAR, SLC images, interferogram, synthetic interferogram, ERS-1/2 frame, phase unwrapping, DEM, coseismic, postseismic, source parameters.« less

Exploitation of Digital Surface Models Generated from WORLDVIEW-2 Data for SAR Simulation Techniques

NASA Astrophysics Data System (ADS)

Ilehag, R.; Auer, S.; d'Angelo, P.

2017-05-01

GeoRaySAR, an automated SAR simulator developed at DLR, identifies buildings in high resolution SAR data by utilizing geometric knowledge extracted from digital surface models (DSMs). Hitherto, the simulator has utilized DSMs generated from LiDAR data from airborne sensors with pre-filtered vegetation. Discarding the need for pre-optimized model input, DSMs generated from high resolution optical data (acquired with WorldView-2) are used for the extraction of building-related SAR image parts in this work. An automatic preprocessing of the DSMs has been developed for separating buildings from elevated vegetation (trees, bushes) and reducing the noise level. Based on that, automated simulations are triggered considering the properties of real SAR images. Locations in three cities, Munich, London and Istanbul, were chosen as study areas to determine advantages and limitations related to WorldView-2 DSMs as input for GeoRaySAR. Beyond, the impact of the quality of the DSM in terms of building extraction is evaluated as well as evaluation of building DSM, a DSM only containing buildings. The results indicate that building extents can be detected with DSMs from optical satellite data with various success, dependent on the quality of the DSM as well as on the SAR imaging perspective.

Imaging Complex Fault Slip of the 2016 MeiNong and Kumamoto Earthquakes with Sentinel-1 InSAR and Other Geodetic and Seismic Data

NASA Astrophysics Data System (ADS)

Fielding, E. J.; Huang, M. H.; Liang, C.; Yue, H.; Agram, P. S.; Simons, M.; Fattahi, H.; Tung, H.; Hu, J. C.; Huang, C.

2016-12-01

We map complex fault ruptures of the February 2016 MeiNong earthquake in Taiwan and the April 2016 Kumamoto earthquake sequence in Japan by analysis of Synthetic Aperture Radar (SAR) data from the Copernicus Sentinel-1A (S1A) satellite operated by the European Space Agency and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japanese Aerospace Exploration Agency (JAXA). Our analysis shows that the MeiNong main rupture at lower crustal depth triggered slip on another fault at upper crustal depth and shallow slip on several faults in the upper few km. The Kumamoto earthquake sequence ruptured two major fault systems over two days and triggered shallow slip on a large number of shallow faults. We combine less precise analysis of large scale displacements from the SAR images of the two satellites by pixel offset tracking or sub-pixel correlation, including the along-track component of surface motion, with the more precise SAR interferometry (InSAR) measurements in the radar line-of-sight direction to estimate all three components of the surface displacement for the events. Data was processed with customized workflows based on modules in the InSAR Scientific Computing Environment (ISCE). Joint inversion of S1A and ALOS-2 InSAR, GPS, and strong motion seismograms for the Mw6.4 MeiNong earthquake shows that the main thrust rupture with N61°W strike and 15° dip at 15-20 km depth explains nearly all of the seismic waveforms but leaves a substantial uplift residual in the InSAR and GPS offsets estimated 4 hours after the earthquake. We model this residual with slip on a N8°E-trending thrust fault dipping 30° at depths between 5-10 km. This fault strike is parallel to surface faults and we interpret it as fault slip within a mid-crustal duplex that was triggered by the main rupture within 4 hours of the mainshock. In addition, InSAR shows sharp discontinuities at many locations that are likely due to shallow triggered slip, but the timing of these is uncertain. The Kumamoto earthquake sequence in Japan started with Mw 6.2 and 6.0 earthquakes on 14 April (UTC) followed on 15 April by the Mw 7.0 mainshock. JAXA acquired one ALOS-2 scene between the foreshocks and mainshock that enables some separation of the surface deformation. InSAR shows M6 foreshocks were deeper, while M7 mainshock ruptured surface in many places.

A Novel Strategy of Ambiguity Correction for the Improved Faraday Rotation Estimator in Linearly Full-Polarimetric SAR Data.

PubMed

Li, Jinhui; Ji, Yifei; Zhang, Yongsheng; Zhang, Qilei; Huang, Haifeng; Dong, Zhen

2018-04-10

Spaceborne synthetic aperture radar (SAR) missions operating at low frequencies, such as L-band or P-band, are significantly influenced by the ionosphere. As one of the serious ionosphere effects, Faraday rotation (FR) is a remarkable distortion source for the polarimetric SAR (PolSAR) application. Various published FR estimators along with an improved one have been introduced to solve this issue, all of which are implemented by processing a set of PolSAR real data. The improved estimator exhibits optimal robustness based on performance analysis, especially in term of the system noise. However, all published estimators, including the improved estimator, suffer from a potential FR angle (FRA) ambiguity. A novel strategy of the ambiguity correction for those FR estimators is proposed and shown as a flow process, which is divided into pixel-level and image-level correction. The former is not yet recognized and thus is considered in particular. Finally, the validation experiments show a prominent performance of the proposed strategy.

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

NASA Astrophysics Data System (ADS)

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.

Analysis of Radarsat-2 Full Polarimetric Data for Forest Mapping

NASA Astrophysics Data System (ADS)

Maghsoudi, Yasser

Forests are a major natural resource of the Earth and control a wide range of environmental processes. Forests comprise a major part of the planet's plant biodiversity and have an important role in the global hydrological and biochemical cycles. Among the numerous potential applications of remote sensing in forestry, forest mapping plays a vital role for characterization of the forest in terms of species. Particularly, in Canada where forests occupy 45% of the territory, representing more than 400 million hectares of the total Canadian continental area. In this thesis, the potential of polarimetric SAR (PolSAR) Radarsat-2 data for forest mapping is investigated. This thesis has two principle objectives. First is to propose algorithms for analyzing the PolSAR image data for forest mapping. There are a wide range of SAR parameters that can be derived from PolSAR data. In order to make full use of the discriminative power offered by all these parameters, two categories of methods are proposed. The methods are based on the concept of feature selection and classifier ensemble. First, a nonparametric definition of the evaluation function is proposed and hence the methods NFS and CBFS. Second, a fast wrapper algorithm is proposed for the evaluation function in feature selection and hence the methods FWFS and FWCBFS. Finally, to incorporate the neighboring pixels information in classification an extension of the FWCBFS method i.e. CCBFS is proposed. The second objective of this thesis is to provide a comparison between leaf-on (summer) and leaf-off (fall) season images for forest mapping. Two Radarsat-2 images acquired in fine quad-polarized mode were chosen for this study. The images were collected in leaf-on and leaf-off seasons. We also test the hypothesis whether combining the SAR parameters obtained from both images can provide better results than either individual datasets. The rationale for this combination is that every dataset has some parameters which may be useful for forest mapping. To assess the potential of the proposed methods their performance have been compared with each other and with the baseline classifiers. The baseline methods include the Wishart classifier, which is a commonly used classification method in PolSAR community, as well as an SVM classifier with the full set of parameters. Experimental results showed a better performance of the leaf-off image compared to that of leaf-on image for forest mapping. It is also shown that combining leaf-off parameters with leaf-on parameters can significantly improve the classification accuracy. Also, the classification results (in terms of the overall accuracy) compared to the baseline classifiers demonstrate the effectiveness of the proposed nonparametric scheme for forest mapping.

Process for combining multiple passes of interferometric SAR data

DOEpatents

Bickel, Douglas L.; Yocky, David A.; Hensley, Jr., William H.

2000-11-21

Interferometric synthetic aperture radar (IFSAR) is a promising technology for a wide variety of military and civilian elevation modeling requirements. IFSAR extends traditional two dimensional SAR processing to three dimensions by utilizing the phase difference between two SAR images taken from different elevation positions to determine an angle of arrival for each pixel in the scene. This angle, together with the two-dimensional location information in the traditional SAR image, can be transformed into geographic coordinates if the position and motion parameters of the antennas are known accurately.

Polarimetric SAR calibration experiment using active radar calibrators

NASA Astrophysics Data System (ADS)

Freeman, Anthony; Shen, Yuhsyen; Werner, Charles L.

1990-03-01

Active radar calibrators are used to derive both the amplitude and phase characteristics of a multichannel polarimetric SAR from the complex image data. Results are presented from an experiment carried out using the NASA/JPL DC-8 aircraft SAR over a calibration site at Goldstone, California. As part of the experiment, polarimetric active radar calibrators (PARCs) with adjustable polarization signatures were deployed. Experimental results demonstrate that the PARCs can be used to calibrate polarimetric SAR images successfully. Restrictions on the application of the PARC calibration procedure are discussed.

Polarimetric SAR calibration experiment using active radar calibrators

NASA Technical Reports Server (NTRS)

Freeman, Anthony; Shen, Yuhsyen; Werner, Charles L.

1990-01-01

Active radar calibrators are used to derive both the amplitude and phase characteristics of a multichannel polarimetric SAR from the complex image data. Results are presented from an experiment carried out using the NASA/JPL DC-8 aircraft SAR over a calibration site at Goldstone, California. As part of the experiment, polarimetric active radar calibrators (PARCs) with adjustable polarization signatures were deployed. Experimental results demonstrate that the PARCs can be used to calibrate polarimetric SAR images successfully. Restrictions on the application of the PARC calibration procedure are discussed.

A Novel Range Compression Algorithm for Resolution Enhancement in GNSS-SARs.

PubMed

Zheng, Yu; Yang, Yang; Chen, Wu

2017-06-25

In this paper, a novel range compression algorithm for enhancing range resolutions of a passive Global Navigation Satellite System-based Synthetic Aperture Radar (GNSS-SAR) is proposed. In the proposed algorithm, within each azimuth bin, firstly range compression is carried out by correlating a reflected GNSS intermediate frequency (IF) signal with a synchronized direct GNSS base-band signal in the range domain. Thereafter, spectrum equalization is applied to the compressed results for suppressing side lobes to obtain a final range-compressed signal. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR images can be achieved by the proposed range compression algorithm, compared to the conventional range compression algorithm.

Radarsat Antarctic Mapping Project: Antarctic Imaging Campaign 2

NASA Technical Reports Server (NTRS)

2001-01-01

The Radarsat Antarctic Mapping Project is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first, high-resolution SAR image map of Antarctica. The limited amount of data suitable for interferometric analysis have also been used to produce remarkably detailed maps of surface velocity for a few selected regions. Most importantly, the results from AMM-1 are now available to the general science community in the form of various resolution, radiometrically calibrated and geometrically accurate image mosaics. The second Antarctic imaging campaign occurred during the fall of 2000. Modified from AMM-1, the satellite remained in north looking mode during AMM-2 restricting coverage to regions north of about -80 degrees latitude. But AMM-2 utilized for the first time RADARSAT-1 fine beams providing an unprecedented opportunity to image many of Antarctica's fast glaciers whose extent was revealed through AMM-1 data. AMM-2 also captured extensive data suitable for interferometric analysis of the surface velocity field. This report summarizes the science goals, mission objectives, and project status through the acquisition phase and the start of the processing phase. The reports describes the efforts of team members including Alaska SAR Facility, Jet Propulsion Laboratory, Vexcel Corporation, Goddard Space Flight Center, Wallops Flight Facility, Ohio State University, Environmental Research Institute of Michigan, White Sands Facility, Canadian Space Agency Mission Planning and Operations Groups, and the Antarctic Mapping Planning Group.

Deep feature extraction and combination for synthetic aperture radar target classification

NASA Astrophysics Data System (ADS)

Amrani, Moussa; Jiang, Feng

2017-10-01

Feature extraction has always been a difficult problem in the classification performance of synthetic aperture radar automatic target recognition (SAR-ATR). It is very important to select discriminative features to train a classifier, which is a prerequisite. Inspired by the great success of convolutional neural network (CNN), we address the problem of SAR target classification by proposing a feature extraction method, which takes advantage of exploiting the extracted deep features from CNNs on SAR images to introduce more powerful discriminative features and robust representation ability for them. First, the pretrained VGG-S net is fine-tuned on moving and stationary target acquisition and recognition (MSTAR) public release database. Second, after a simple preprocessing is performed, the fine-tuned network is used as a fixed feature extractor to extract deep features from the processed SAR images. Third, the extracted deep features are fused by using a traditional concatenation and a discriminant correlation analysis algorithm. Finally, for target classification, K-nearest neighbors algorithm based on LogDet divergence-based metric learning triplet constraints is adopted as a baseline classifier. Experiments on MSTAR are conducted, and the classification accuracy results demonstrate that the proposed method outperforms the state-of-the-art methods.

Global Boreal Forest Mapping with JERS-1: North America

NASA Technical Reports Server (NTRS)

Williams, Cynthia L.; McDonald, Kyle; Chapman, Bruce

2000-01-01

Collaborative effort is underway to map boreal forests worldwide using L-band, single polarization Synthetic Aperture Radar (SAR) imagery from the Japanese Earth Resources (JERS-1) satellite. Final products of the North American Boreal Forest Mapping Project will include two continental scale radar mosaics and supplementary multitemporal mosaics for Alaska, central Canada, and eastern Canada. For selected sites, we are also producing local scale (100 km x 100 km) and regional scale maps (1000 km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web. Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR Facility.

Remote sensing of frozen lakes on the North Slope of Alaska

USGS Publications Warehouse

French, N.; Savage, S.; Shuchman, R.; Edson, R.; Payne, J.; Josberger, E.

2004-01-01

We used synthetic aperture radar (SAR) images from the ERS-2 remote sensing satellite to map the freeze condition of lakes on Alaska's North Slope, the geographic region to the north of the Brooks Range. An mage from March 1997, to coincide with the period of maximum freeze depth, was used for the frozen lake mapping. Emphasis was placed on distinguishing between lakes frozen to the lakebed and lakes with some portion unfrozen to the bed (a binary classification). The result of the analysis is a map identifying lakes as frozen to the lakebed and lakes not frozen to the lakebed. This analysis of one SAR image has shown the feasibility of a simple technique for mapping frozen lake condition for supporting decision making and understanding impacts of climate change on the North Slope.

Digital SAR processing using a fast polynomial transform

NASA Technical Reports Server (NTRS)

Truong, T. K.; Lipes, R. G.; Butman, S. A.; Reed, I. S.; Rubin, A. L.

1984-01-01

A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network. Previously announced in STAR as N82-11295

A novel framework for change detection in bi-temporal polarimetric SAR images

NASA Astrophysics Data System (ADS)

Pirrone, Davide; Bovolo, Francesca; Bruzzone, Lorenzo

2016-10-01

Last years have seen relevant increase of polarimetric Synthetic Aperture Radar (SAR) data availability, thanks to satellite sensors like Sentinel-1 or ALOS-2 PALSAR-2. The augmented information lying in the additional polarimetric channels represents a possibility for better discriminate different classes of changes in change detection (CD) applications. This work aims at proposing a framework for CD in multi-temporal multi-polarization SAR data. The framework includes both a tool for an effective visual representation of the change information and a method for extracting the multiple-change information. Both components are designed to effectively handle the multi-dimensionality of polarimetric data. In the novel representation, multi-temporal intensity SAR data are employed to compute a polarimetric log-ratio. The multitemporal information of the polarimetric log-ratio image is represented in a multi-dimensional features space, where changes are highlighted in terms of magnitude and direction. This representation is employed to design a novel unsupervised multi-class CD approach. This approach considers a sequential two-step analysis of the magnitude and the direction information for separating non-changed and changed samples. The proposed approach has been validated on a pair of Sentinel-1 data acquired before and after the flood in Tamil-Nadu in 2015. Preliminary results demonstrate that the representation tool is effective and that the use of polarimetric SAR data is promising in multi-class change detection applications.

Analysis of the local worst-case SAR exposure caused by an MRI multi-transmit body coil in anatomical models of the human body.

PubMed

Neufeld, Esra; Gosselin, Marie-Christine; Murbach, Manuel; Christ, Andreas; Cabot, Eugenia; Kuster, Niels

2011-08-07

Multi-transmit coils are increasingly being employed in high-field magnetic resonance imaging, along with a growing interest in multi-transmit body coils. However, they can lead to an increase in whole-body and local specific absorption rate (SAR) compared to conventional body coils excited in circular polarization for the same total incident input power. In this study, the maximum increase of SAR for three significantly different human anatomies is investigated for a large 3 T (128 MHz) multi-transmit body coil using numerical simulations and a (generalized) eigenvalue-based approach. The results demonstrate that the increase of SAR strongly depends on the anatomy. For the three models and normalization to the sum of the rung currents squared, the whole-body averaged SAR increases by up to a factor of 1.6 compared to conventional excitation and the peak spatial SAR (averaged over any 10 cm(3) of tissue) by up to 13.4. For some locations the local averaged SAR goes up as much as 800 times (130 when looking only at regions where it is above 1% of the peak spatial SAR). The ratio of the peak spatial SAR to the whole-body SAR increases by a factor of up to 47 and can reach values above 800. Due to the potentially much larger power deposition, additional, preferably patient-specific, considerations are necessary to avoid injuries by such systems.

Processor architecture for airborne SAR systems

NASA Technical Reports Server (NTRS)

Glass, C. M.

1983-01-01

Digital processors for spaceborne imaging radars and application of the technology developed for airborne SAR systems are considered. Transferring algorithms and implementation techniques from airborne to spaceborne SAR processors offers obvious advantages. The following topics are discussed: (1) a quantification of the differences in processing algorithms for airborne and spaceborne SARs; and (2) an overview of three processors for airborne SAR systems.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Earth resources shuttle imaging radar. [systems analysis and design analysis of pulse radar for earth resources information system

NASA Technical Reports Server (NTRS)

1975-01-01

A report is presented on a preliminary design of a Synthetic Array Radar (SAR) intended for experimental use with the space shuttle program. The radar is called Earth Resources Shuttle Imaging Radar (ERSIR). Its primary purpose is to determine the usefulness of SAR in monitoring and managing earth resources. The design of the ERSIR, along with tradeoffs made during its evolution is discussed. The ERSIR consists of a flight sensor for collecting the raw radar data and a ground sensor used both for reducing these radar data to images and for extracting earth resources information from the data. The flight sensor consists of two high powered coherent, pulse radars, one that operates at L and the other at X-band. Radar data, recorded on tape can be either transmitted via a digital data link to a ground terminal or the tape can be delivered to the ground station after the shuttle lands. A description of data processing equipment and display devices is given.

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

Spacecraft on-board SAR image generation for EOS-type missions

NASA Technical Reports Server (NTRS)

Liu, K. Y.; Arens, W. E.; Assal, H. M.; Vesecky, J. F.

1987-01-01

Spacecraft on-board synthetic aperture radar (SAR) image generation is an extremely difficult problem because of the requirements for high computational rates (usually on the order of Giga-operations per second), high reliability (some missions last up to 10 years), and low power dissipation and mass (typically less than 500 watts and 100 Kilograms). Recently, a JPL study was performed to assess the feasibility of on-board SAR image generation for EOS-type missions. This paper summarizes the results of that study. Specifically, it proposes a processor architecture using a VLSI time-domain parallel array for azimuth correlation. Using available space qualifiable technology to implement the proposed architecture, an on-board SAR processor having acceptable power and mass characteristics appears feasible for EOS-type applications.

Oil Spill Detection: Past and Future Trends

NASA Astrophysics Data System (ADS)

Topouzelis, Konstantinos; Singha, Suman

2016-08-01

In the last 15 years, the detection of oil spills by satellite means has been moved from experimental to operational. Actually, what is really changed is the satellite image availability. From the late 1990's, in the age of "no data" we have moved forward 15 years to the age of "Sentinels" with an abundance of data. Either large accident related to offshore oil exploration and production activity or illegal discharges from tankers, oil on the sea surface is or can be now regularly monitored, over European Waters. National and transnational organizations (i.e. European Maritime Safety Agency's 'CleanSeaNet' Service) are routinely using SAR imagery to detect oil due to it's all weather, day and night imaging capability. However, all these years the scientific methodology on the detection remains relatively constant. From manual analysis to fully automatic detection methodologies, no significant contribution has been published in the last years and certainly none has dramatically changed the rules of the detection. On the contrary, although the overall accuracy of the methodology is questioned, the four main classification steps (dark area detection, features extraction, statistic database creation, and classification) are continuously improving. In recent years, researchers came up with the use of polarimetric SAR data for oil spill detection and characterizations, although utilization of Pol-SAR data for this purpose still remains questionable due to lack of verified dataset and low spatial coverage of Pol-SAR data. The present paper is trying to point out the drawbacks of the oil spill detection in the last years and focus on the bottlenecks of the oil spill detection methodologies. Also, solutions on the basis of data availability, management and analysis are proposed. Moreover, an ideal detection system is discussed regarding satellite image and in situ observations using different scales and sensors.

Tie Points Extraction for SAR Images Based on Differential Constraints

NASA Astrophysics Data System (ADS)

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.

Three-dimensional brain MRI for DBS patients within ultra-low radiofrequency power limits.

PubMed

Sarkar, Subhendra N; Papavassiliou, Efstathios; Hackney, David B; Alsop, David C; Shih, Ludy C; Madhuranthakam, Ananth J; Busse, Reed F; La Ruche, Susan; Bhadelia, Rafeeque A

2014-04-01

For patients with deep brain stimulators (DBS), local absorbed radiofrequency (RF) power is unknown and is much higher than what the system estimates. We developed a comprehensive, high-quality brain magnetic resonance imaging (MRI) protocol for DBS patients utilizing three-dimensional (3D) magnetic resonance sequences at very low RF power. Six patients with DBS were imaged (10 sessions) using a transmit/receive head coil at 1.5 Tesla with modified 3D sequences within ultra-low specific absorption rate (SAR) limits (0.1 W/kg) using T2 , fast fluid-attenuated inversion recovery (FLAIR) and T1 -weighted image contrast. Tissue signal and tissue contrast from the low-SAR images were subjectively and objectively compared with routine clinical images of six age-matched controls. Low-SAR images of DBS patients demonstrated tissue contrast comparable to high-SAR images and were of diagnostic quality except for slightly reduced signal. Although preliminary, we demonstrated diagnostic quality brain MRI with optimized, volumetric sequences in DBS patients within very conservative RF safety guidelines offering a greater safety margin. © 2014 International Parkinson and Movement Disorder Society.

Exploring cloud and big data components for SAR archiving and analysis

NASA Astrophysics Data System (ADS)

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 goals.

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

NASA Technical Reports Server (NTRS)

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.

Ocean-ice interaction in the marginal ice zone using synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chich Y.; Weingartner, Thomas J.

1994-01-01

Ocean-ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) images and an ocean-ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR-observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean-ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Rapid Flood Map Generation from Spaceborne SAR Observations

NASA Astrophysics Data System (ADS)

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 satellite, the composite expected wait time until a SAR satellite to fly over a flooded area became smaller than 12 hours. With more SAR missions, such as SAOCOM, RADARSAT Constellation, Sentinel-1C/D, ALOS-3, and NISAR, SAR data are becoming more useful for rapid mapping of devastating floods, which are becoming more frequent and more severe around the world.

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

NASA Astrophysics Data System (ADS)

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).

Acoustic Characterization of Soil

DTIC Science & Technology

1996-03-28

modified SAR imaging algorithm. Page 26 Final Report In the acoustic subsurface imaging scenario, the "object" to be imaged (i.e., cultural artifacts... subsurface imaging scenario. To combat this potential difficulty we can utilize a new SAR imaging algorithm (Lee et al., 1996) derived from a geophysics...essentially a transmit plane wave. This is a cost-effective means to evaluate the feasibility of subsurface imaging . A more complete (and costly

The geophysical processor system: Automated analysis of ERS-1 SAR imagery

NASA Technical Reports Server (NTRS)

Stern, Harry L.; Rothrock, D. Andrew; Kwok, Ronald; Holt, Benjamin

1994-01-01

The Geophysical Processor System (GPS) at the Alaska (U.S.) SAR (Synthetic Aperture Radar) Facility (ASF) uses ERS-1 SAR images as input to generate three types of products: sea ice motion, sea ice type, and ocean wave spectra. The GPS, operating automatically with minimal human intervention, delivers its output to the Archive and Catalog System (ACS) where scientists can search and order the products on line. The GPS has generated more than 10,000 products since it became operational in Feb. 1992, and continues to deliver 500 new products per month to the ACS. These products cover the Beaufort and Chukchi Seas and the western portion of the central Arctic Ocean. More geophysical processing systems are needed to handle the large volumes of data from current and future satellites. Images must be routinely and consistently analyzed to yield useful information for scientists. The current GPS is a good, working prototype on the way to more sophisticated systems.

ARIA: Delivering state-of-the-art InSAR products to end users

NASA Astrophysics Data System (ADS)

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

2016-12-01

Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards aims to bring state-of-the-art geodetic imaging capabilities to an operational level in support of local, national, and international hazard response communities. ARIA project's first foray into operational generation of InSAR products was with Calimap Project, in collaboration with ASI-CIDOT, using X-band data from the Cosmo-SkyMed constellation. Over the last year, ARIA's processing infrastructure has been significantly upgraded to exploit the free stream of high quality C-band SAR data from ESA's Sentinel-1 mission and related algorithmic improvements to the ISCE software. ARIA's data system can now operationally generate geocoded unwrapped phase and coherence products in GIS-friendly formats from Sentinel-1 TOPS mode data in an automated fashion, and this capability is currently being exercised various study sites across the United States including Hawaii, Central California, Iceland and South America. The ARIA team, building on the experience gained from handling X-band data and C-band data, has also built an automated machine learning-based classifier to label the auto-generated interferograms based on phase unwrapping quality. These high quality "time-series ready" InSAR products generated using state-of-the-art processing algorithms can be accessed by end users using two different mechanisms - 1) a Faceted-search interface that includes browse imagery for quick visualization and 2) an ElasticSearch-based API to enable bulk automated download, post-processing and time-series analysis. In this talk, we will present InSAR results from various global events that ARIA system has responded to. We will also discuss the set of geospatial big data tools including GIS libraries and API tools, that end users will need to familiarize themselves with in order to maximize the utilization of continuous stream of InSAR products from the Sentinel-1 and NISAR missions that the ARIA project will generate.

Oil spill analysis by means of full polarimetric UAVSAR (L-band) and Radarsat-2 (C-band) products acquired during Deepwater Horizon Disaster

NASA Astrophysics Data System (ADS)

Latini, Daniele; Del Frate, Fabio; Jones, Cathleen E.

2014-10-01

SAR instruments with polarimetric capabilities, high resolution and short revisit time can provide powerful support in oil spill monitoring and different techniques of analysis have been developed for this purpose [1][2]. An oil film on the sea surface results in darker areas in SAR images, but careful interpretation is required because dark spots can also be caused by natural phenomena. In view of the very low backscatter from slicks, the Noise Equivalent Sigma Zero (NESZ) is a primary sensor parameter to be considered when using a sensor for slick analysis. Among the existing full polarimetric sensors, the high resolution and very low NESZ values of UAVSAR (L-band) and RADARSAT-2 (C-band) make them preferable for oil spill analysis compared to the last generation SAR instruments. The Deepwater Horizon disaster that occurred in the Gulf of Mexico in 2010 represents a unique and extensive test site where large amounts of SAR imagery and ground validation data are available. By applying the Cloude-Pottier decomposition method to full polarimetric UAVSAR (L-band) and RADARSAT-2 (C-band), it is possible to extract parameters that describe the scattering mechanism of the target. By comparing quasi-simultaneous acquisitions and exploiting the different penetration capabilities of the sensors, we investigate the potential of full polarimetric SAR to discriminate oil on the sea surface from look-alike phenomena covering the full range of backscattering values down to those at the instrument noise floor.

Basic to Advanced InSAR Processing: GMTSAR

NASA Astrophysics Data System (ADS)

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.

Analysis of Mining-Induced Subsidence Prediction by Exponent Knothe Model Combined with Insar and Leveling

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Liguo; Tang, Yixian; Zhang, Hong

2018-04-01

The principle of exponent Knothe model was introduced in detail and the variation process of mining subsidence with time was analysed based on the formulas of subsidence, subsidence velocity and subsidence acceleration in the paper. Five scenes of radar images and six levelling measurements were collected to extract ground deformation characteristics in one coal mining area in this study. Then the unknown parameters of exponent Knothe model were estimated by combined levelling data with deformation information along the line of sight obtained by InSAR technique. By compared the fitting and prediction results obtained by InSAR and levelling with that obtained only by levelling, it was shown that the accuracy of fitting and prediction combined with InSAR and levelling was obviously better than the other that. Therefore, the InSAR measurements can significantly improve the fitting and prediction accuracy of exponent Knothe model.

Space Radar Image of West Texas - SAR Scan

NASA Image and Video Library

1999-04-15

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 forthcoming Canadian RADARSAT satellite. http://photojournal.jpl.nasa.gov/catalog/PIA01787

Summer Arctic ice concentrations and characteristics from SAR and SSM/I data

NASA Technical Reports Server (NTRS)

Comiso, Joey C.; Kwok, Ron

1993-01-01

The extent and concentration of the Summer minima provide indirect information about the long term ability of the perennial portion of the ice pack to survive the Arctic atmosphere and ocean system. Both active and passive microwave data were used with some success for monitoring the ice cover during the Summer, but they both suffer from similar problems caused by the presence of meltponding, surface wetness, flooding, and freeze/thaw cycles associated with periodic changes in surface air temperatures. A comparative analysis of ice conditions in the Arctic region using coregistered ERS-1 SAR (Synthetic Aperture Radar) and SSM/I (Special Sensor Microwave/Imager) data was made. The analysis benefits from complementary information from the two systems, the good spatial resolution of SAR data, and the good time resolution of and global coverage by SSM/I data. The results show that in many areas ice concentrations derived from SAR data are significantly different (usually higher) than those derived from passive microwave data. Additional insights about surface conditions can be inferred depending on the nature of the discrepancies.

Preliminary results of SAR soil moisture experiment, November 1975

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Chang, A. T. C.; Schmugge, T. J.; Salomonson, V. V.; Wang, J. R.

1979-01-01

The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

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

NASA Astrophysics Data System (ADS)

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.

From local to national scale DInSAR analysis for the comprehension of Earth's surface dynamics.

NASA Astrophysics Data System (ADS)

De Luca, Claudio; Casu, Francesco; Manunta, Michele; Zinno, Ivana; lanari, Riccardo

2017-04-01

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 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. While the application of SBAS to ERS and ENVISAT data at local scale is widely testified, very few examples involving those archives for analysis at huge spatial scale are available in literature. This is mainly due to the required processing power (in terms of CPUs, memory and storage) and the limited availability of automatic processing procedures (unsupervised tools), which are mandatory requirements for obtaining displacement results in a time effective way. Accordingly, in this work we present a methodology for generating the Vertical and Horizontal (East-West) components of Earth's surface deformation at very large (national/continental) spatial scale. In particular, it relies on the availability of a set of SAR data collected over an Area of Interest (AoI), which could be some hundreds of thousands of square kilometers wide, from ascending and descending orbits. The exploited SAR data are processed, on a local basis, through the Parallel SBAS (P-SBAS) approach thus generating the displacement time series and the corresponding mean deformation velocity maps. Subsequently, starting from the so generated DInSAR results, the proposed methodology lays on a proper mosaicking procedure to finally retrieve the mean velocity maps of the Vertical and Horizontal (East-West) deformation components relevant to the overall AoI. This technique permits to account for possible regional trends (tectonics trend) not easily detectable by the local scale DInSAR analyses. We tested the proposed methodology with the ENVISAT ASAR archives that have been acquired, from ascending and descending orbits, over California (US), covering an area of about 100.000 km2. The presented methodology can be easily applied also to other SAR satellite data. Above all, it is particularly suitable to deal with the very large data flow provided by the Sentinel-1 constellation, which collects data with a global coverage policy and an acquisition mode specifically designed for interferometric applications.

JPL Researcher Bruce Chapman at an AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign

NASA Image and Video Library

2004-03-03

JPL Researcher Bruce Chapman at an AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign. AirSAR 2004 is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.

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

NASA Astrophysics Data System (ADS)

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.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Dynamic experiment design regularization approach to adaptive imaging with array radar/SAR sensor systems.

PubMed

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

Combining TerraSAR-X and SPOT-5 data for object-based landslide detection

NASA Astrophysics Data System (ADS)

Friedl, B.; Hölbling, D.; Füreder, P.

2012-04-01

Landslide detection and classification is an essential requirement in pre- and post-disaster hazard analysis. In earlier studies landslide detection often was achieved through time-consuming and cost-intensive field surveys and visual orthophoto interpretation. Recent studies show that Earth Observation (EO) data offer new opportunities for fast, reliable and accurate landslide detection and classification, which may conduce to an effective landslide monitoring and landslide hazard management. To ensure the fast recognition and classification of landslides at a regional scale, a (semi-)automated object-based landslide detection approach is established for a study site situated in the Huaguoshan catchment, Southern Taiwan. The study site exhibits a high vulnerability to landslides and debris flows, which are predominantly typhoon-induced. Through the integration of optical satellite data (SPOT-5 with 2.5 m GSD), SAR (Synthetic Aperture Radar) data (TerraSAR-X Spotlight with 2.95 m GSD) and digital elevation information (DEM with 5 m GSD) including its derived products (e.g. slope, curvature, flow accumulation) landslides may be examined in a more efficient way as if relying on single data sources only. The combination of optical and SAR data in an object-based image analysis (OBIA) domain for landslide detection and classification has not been investigated so far, even if SAR imagery show valuable properties for landslide detection, which differ from optical data (e.g. high sensitivity to surface roughness and soil moisture). The main purpose of this study is to recognize and analyze existing landslides by applying object-based image analysis making use of eCognition software. OBIA provides a framework for examining features defined by spectral, spatial, textural, contextual as well as hierarchical properties. Objects are derived through image segmentation and serve as input for the classification process, which relies on transparent rulesets, representing knowledge. Through class modeling, an iterative process of segmentation and classification, objects can be addressed individually in a region-specific manner. The presented approach is marked by the comprehensive use of available data sets from various sources. This full integration of optical, SAR and DEM data conduces to the development of a robust method, which makes use of the most appropriate characteristics (e.g. spectral, textural, contextual) of each data set. The proposed method contributes to a more rapid and accurate landslide mapping in order to assist disaster and crisis management. Especially SAR data proves to be useful in the aftermath of an event, as radar sensors are mostly independent of illumination and weather conditions and therefore data is more likely to be available. The full data integration allows coming up with a robust approach for the detection and classification of landslides. However, more research is needed to make the best of the integration of SAR data in an object-based environment and for making the approach easier adaptable to different study sites and data.

Superpixel edges for boundary detection

DOEpatents

Moya, Mary M.; Koch, Mark W.

2016-07-12

Various embodiments presented herein relate to identifying one or more edges in a synthetic aperture radar (SAR) image comprising a plurality of superpixels. Superpixels sharing an edge (or boundary) can be identified and one or more properties of the shared superpixels can be compared to determine whether the superpixels form the same or two different features. Where the superpixels form the same feature the edge is identified as an internal edge. Where the superpixels form two different features, the edge is identified as an external edge. Based upon classification of the superpixels, the external edge can be further determined to form part of a roof, wall, etc. The superpixels can be formed from a speckle-reduced SAR image product formed from a registered stack of SAR images, which is further segmented into a plurality of superpixels. The edge identification process is applied to the SAR image comprising the superpixels and edges.

Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments

NASA Astrophysics Data System (ADS)

Garzelli, Andrea; Zoppetti, Claudia; Pinelli, Gianpaolo

2017-10-01

Coastline detection in synthetic aperture radar (SAR) images is crucial in many application fields, from coastal erosion monitoring to navigation, from damage assessment to security planning for port facilities. The backscattering difference between land and sea is not always documented in SAR imagery, due to the severe speckle noise, especially in 1-look data with high spatial resolution, high sea state, or complex coastal environments. This paper presents an unsupervised, computationally efficient solution to extract the coastline acquired by only one single-polarization 1-look SAR image. Extensive tests on Spotlight COSMO-SkyMed images of complex coastal environments and objective assessment demonstrate the validity of the proposed procedure which is compared to state-of-the-art methods through visual results and with an objective evaluation of the distance between the detected and the true coastline provided by regional authorities.

Research on Multi-Temporal PolInSAR Modeling and Applications

NASA Astrophysics Data System (ADS)

Hong, Wen; Pottier, Eric; Chen, Erxue

2014-11-01

In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman-Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal Land P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.

Research on Multi-Temporal PolInSAR Modeling and Applications

NASA Astrophysics Data System (ADS)

Hong, Wen; Pottier, Eric; Chen, Erxue

2014-11-01

In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman- Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal L- and P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.

Non-Reporting Ship Traffic in the Western Indian Ocean

NASA Astrophysics Data System (ADS)

Greidanus, Harm; Santamaria, Carlos; Alvarez, Marlene; Krause, Detmar; Stasolla, Mattia; Vachon, Paris W.

2016-08-01

AIS ship position reporting data from up to 17 satellites and several coastal locations covering the Western Indian Ocean were collected during a period of one year, that ended 15 Sep 2015. In addition, 1,361 satellite SAR images that were acquired over the region in the same timeframe, were analysed for ship detection. The major part of these were Sentinel-1 images that were analysed fully automatically, yielding 11,510 ship detections that were deemed reliable. Correlating these detections with the reporting ship traffic indicates that, overall, fully one-third of the ships detected with satellite SAR are not reporting on AIS. Some of the analysed SAR data was subjected to manual verification. This concerned data from TerraSAR-X, RADARSAT-2, COSMO-SkyMed, and ALOS-2- PALSAR of various image modes, plus some of the Sentinel-1 images. This confirmed the quoted average for the fraction of non-reporting ships. However, within the overall average there are large geographical variations, besides variations with image resolution.

Preliminary Assessment of Wind and Wave Retrieval from Chinese Gaofen-3 SAR Imagery

PubMed Central

Sun, Jian

2017-01-01

The Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) launched by the China Academy of Space Technology (CAST) has operated at C-band since September 2016. To date, we have collected 16/42 images in vertical-vertical (VV)/horizontal-horizontal (HH) polarization, covering the National Data Buoy Center (NDBC) buoy measurements of the National Oceanic and Atmospheric Administration (NOAA) around U.S. western coastal waters. Wind speeds from NDBC in situ buoys are up to 15 m/s and buoy-measured significant wave height (SWH) has ranged from 0.5 m to 3 m. In this study, winds were retrieved using the geophysical model function (GMF) together with the polarization ratio (PR) model and waves were retrieved using a new empirical algorithm based on SAR cutoff wavelength in satellite flight direction, herein called CSAR_WAVE. Validation against buoy measurements shows a 1.4/1.9 m/s root mean square error (RMSE) of wind speed and a 24/23% scatter index (SI) of SWH for VV/HH polarization. In addition, wind and wave retrieval results from 166 GF-3 images were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis winds, as well as the SWH from the WaveWatch-III model, respectively. Comparisons show a 2.0 m/s RMSE for wind speed with a 36% SI of SWH for VV-polarization and a 2.2 m/s RMSE for wind speed with a 37% SI of SWH for HH-polarization. Our work gives a preliminary assessment of the wind and wave retrieval results from GF-3 SAR images for the first time and will provide guidance for marine applications of GF-3 SAR. PMID:28757571

Tonga Cyclone Damage Mapped by NASA's ARIA Team

NASA Image and Video Library

2018-02-21

The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory created this Damage Proxy Map (DPM) of Tongatapu, the main island of Tonga, following the landfall of Cyclone Gita, a Category 4 storm that hit Tonga on Feb. 12-13, 2018. The map depicts areas that are likely damaged from the storm, shown by red and yellow pixels. The map was produced by comparing two pairs of interferometric synthetic aperture radar (InSAR) images from the COSMO-SkyMed satellites, operated by the Italian Space Agency (ASI). The pre- and post-cyclone images were acquired on Jan. 19 and Feb. 13, 2018, respectively. The later image was acquired just 4-1/2 hours after the peak damage by the cyclone. The map covers the entire island of Tongatapu (the 25-by-25-mile, or 40-by-40 kilometer SAR image footprint indicated with the large red polygon). Each pixel measures about 98 feet (30 meters) across. The color variation from yellow to red indicates increasingly more significant ground surface change. Preliminary validation of the SAR data was done by comparing them with high-resolution optical imagery acquired by DigitalGlobe. This Damage Proxy Map should be used as guidance to identify damaged areas and may be less reliable over vegetated and flooded areas. https://photojournal.jpl.nasa.gov/catalog/PIA22257

Nuclear scaffold attachment stimulates, but is not essential for ARS activity in Saccharomyces cerevisiae: analysis of the Drosophila ftz SAR.

PubMed Central

Amati, B; Pick, L; Laroche, T; Gasser, S M

1990-01-01

Nuclei isolated from eukaryotic cells can be depleted of histones and most soluble nuclear proteins to isolate a structural framework called the nuclear scaffold. This structure maintains specific interactions with genomic DNA at sites known as scaffold attached regions (SARs), which are thought to be the bases of DNA loops. In both Saccharomyces cerevisiae and Schizosaccharomyces pombe, genomic ARS elements are recovered as SARs. In addition, SARs from Drosophila melanogaster bind to yeast nuclear scaffolds in vitro and a subclass of these promotes autonomous replication of plasmids in yeast. In the present report, we present fine mapping studies of the Drosophila ftz SAR, which has both SAR and ARS activities in yeast. The data establish a close relationship between the sequences involved in ARS activity and scaffold binding: ARS elements that can bind the nuclear scaffold in vitro promote more efficient plasmid replication in vivo, but scaffold association is not a strict prerequisite for ARS function. Efficient interaction with nuclear scaffolds from both yeast and Drosophila requires a minimal length of SAR DNA that contains reiteration of a narrow minor groove structure of the double helix. Images Fig. 1. Fig. 2. Fig. 3. Fig. 4. PMID:2123454

MM wave SAR sensor design: Concept for an airborne low level reconnaissance system

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

NASA Astrophysics Data System (ADS)

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.

Exploitation of SAR data for measurement of ocean currents and wave velocities

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Lyzenga, D. R.; Klooster, A., Jr.

1981-01-01

Methods of extracting information on ocean currents and wave orbital velocities from SAR data by an analysis of the Doppler frequency content of the data are discussed. The theory and data analysis methods are discussed, and results are presented for both aircraft and satellite (SEASAT) data sets. A method of measuring the phase velocity of a gravity wave field is also described. This method uses the shift in position of the wave crests on two images generated from the same data set using two separate Doppler bands. Results of the current measurements are pesented for 11 aircraft data sets and 4 SEASAT data sets.

Ship heading and velocity analysis by wake detection in SAR images

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

2016-11-01

With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

Crop Identification Using Time Series of Landsat-8 and Radarsat-2 Images: Application in a Groundwater Irrigated Region, South India

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Hubert-Moy, L.; Betbederet, J.; Ruiz, L.; Sekhar, M.; Corgne, S.

2016-08-01

Monitoring land use and land cover and more particularly irrigated cropland dynamics is of great importance for water resources management and land use planning. The objective of this study was to evaluate the combined use of multi-temporal optical and radar data with a high spatial resolution in order to improve the precision of irrigated crop identification by taking into account information on crop phenological stages. SAR and optical parameters were derived from time- series of seven quad-pol RADARSAT-2 and four Landsat-8 images which were acquired on the Berambadi catchment, South India, during the monsoon crop season at the growth stages of turmeric crop. To select the best parameter to discriminate turmeric crops, an analysis of covariance (ANCOVA) was applied on all the time-series parameters and the most discriminant ones were classified using the Support Vector Machine (SVM) technique. Results show that in absence of optical images, polarimetric parameters derived from SAR time-series can be used for the turmeric area estimates and that the combined use of SAR and optical parameters can improve the classification accuracy to identify turmeric.

JPL Researcher Tim Miller at the primary AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign

NASA Image and Video Library

2004-03-03

JPL Researcher Tim Miller at the primary AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign. AirSAR 2004 is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.

A Novel Range Compression Algorithm for Resolution Enhancement in GNSS-SARs

PubMed Central

Zheng, Yu; Yang, Yang; Chen, Wu

2017-01-01

In this paper, a novel range compression algorithm for enhancing range resolutions of a passive Global Navigation Satellite System-based Synthetic Aperture Radar (GNSS-SAR) is proposed. In the proposed algorithm, within each azimuth bin, firstly range compression is carried out by correlating a reflected GNSS intermediate frequency (IF) signal with a synchronized direct GNSS base-band signal in the range domain. Thereafter, spectrum equalization is applied to the compressed results for suppressing side lobes to obtain a final range-compressed signal. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR images can be achieved by the proposed range compression algorithm, compared to the conventional range compression algorithm. PMID:28672830

The influence on the interferometry due to the instability of ground-based synthetic aperture radar work platform

NASA Astrophysics Data System (ADS)

Tao, Gang; Wei, Guohua; Wang, Xu; Kong, Ming

2018-03-01

There has been increased interest over several decades for applying ground-based synthetic aperture radar (GB-SAR) for monitoring terrain displacement. GB-SAR can achieve multitemporal surface deformation maps of the entire terrain with high spatial resolution and submilimetric accuracy due to the ability of continuous monitoring a certain area day and night regardless of the weather condition. The accuracy of the interferometric measurement result is very important. In this paper, the basic principle of InSAR is expounded, the influence of the platform's instability on the interferometric measurement results are analyzed. The error sources of deformation detection estimation are analyzed using precise geometry of imaging model. Finally, simulation results demonstrates the validity of our analysis.

High-Level Performance Modeling of SAR Systems

NASA Technical Reports Server (NTRS)

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.

On The Spatial Homogeneity Of The Wave Spectra In Deep Water Employing ERS-2 SAR Precision Image

NASA Astrophysics Data System (ADS)

Violante-Carvalho, Nelson; Robinson, Ian; Gommenginger, Christine; Carvalho, Luiz Mariano; Goldstein, Brunno

2010-04-01

Using wave spectra extracted from image mode ERS-2 SAR, the spatial homogeneity of the wave field in deep water is investigated against directional buoy measurements. From the 100 x 100 km image, several small images of 6.4 x 6.4 km are selected and the wave spectra are computed. The locally disturbed wind velocity pat- tern, caused by the sheltering effect of large mountains near the coast, translates into the selected SAR image as regions of higher and lower wind speed. Assuming that a swell component is uniform over the whole image, SAR wave spectra retrieved from the sheltered and non-sheltered areas are intercompared. Any difference between them could be related to a possible interaction between wind sea and swell, since the wind sea part of the spectrum would be slightly different due to the different wind speeds. The results show that there is no significative variation, and apparently there is no clear difference in the swell spectra despite the different wind sea components.

Doppler synthetic aperture radar interferometry: a novel SAR interferometry for height mapping using ultra-narrowband waveforms

NASA Astrophysics Data System (ADS)

Yazıcı, Birsen; Son, Il-Young; Cagri Yanik, H.

2018-05-01

This paper introduces a new and novel radar interferometry based on Doppler synthetic aperture radar (Doppler-SAR) paradigm. Conventional SAR interferometry relies on wideband transmitted waveforms to obtain high range resolution. Topography of a surface is directly related to the range difference between two antennas configured at different positions. Doppler-SAR is a novel imaging modality that uses ultra-narrowband continuous waves (UNCW). It takes advantage of high resolution Doppler information provided by UNCWs to form high resolution SAR images. We introduce the theory of Doppler-SAR interferometry. We derive an interferometric phase model and develop the equations of height mapping. Unlike conventional SAR interferometry, we show that the topography of a scene is related to the difference in Doppler frequency between two antennas configured at different velocities. While the conventional SAR interferometry uses range, Doppler and Doppler due to interferometric phase in height mapping; Doppler-SAR interferometry uses Doppler, Doppler-rate and Doppler-rate due to interferometric phase in height mapping. We demonstrate our theory in numerical simulations. Doppler-SAR interferometry offers the advantages of long-range, robust, environmentally friendly operations; low-power, low-cost, lightweight systems suitable for low-payload platforms, such as micro-satellites; and passive applications using sources of opportunity transmitting UNCW.

Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5

USGS Publications Warehouse

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Lei; Lee, Wonjin; Lee, Chang-Wook

2012-01-01

An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.

SAR image formation with azimuth interpolation after azimuth transform

DOEpatents

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.

Fast iterative censoring CFAR algorithm for ship detection from SAR images

NASA Astrophysics Data System (ADS)

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.

Remote sensing with spaceborne synthetic aperture imaging radars: A review

NASA Technical Reports Server (NTRS)

Cimino, J. B.; Elachi, C.

1983-01-01

A review is given of remote sensing with Spaceborne Synthetic Aperture Radars (SAR's). In 1978, a spaceborne SA was flown on the SEASAT satellite. It acquired high resulution images over many regions in North America and the North Pacific. The acquired data clearly demonstrate the capability of spaceborne SARs to: image and track polar ice floes; image ocean surface patterns including swells, internal waves, current boundaries, weather boundaries and vessels; and image land features which are used to acquire information about the surface geology and land cover. In 1981, another SAR was flown on the second shuttle flight. This Shuttle Imaging Radar (SIR-A) acquired land and ocean images over many areas around the world. The emphasis of the SIR-A experiment was mainly toward geologic mapping. Some of the key results of the SIR-A experiment are given.

The Theoretical Problem of Partial Coherence and Partial Polarization in PolSAR and PolInSAR

NASA Astrophysics Data System (ADS)

Alvarez-Perez, J. L.

2013-08-01

Coherence is a key concept in all aspects related to SAR, and it is also an essential ingredient not only of its signal processing and image formation but also of the data postprocessing stages of SAR data. Coherence is however a non-trivial concept that has been the subject of much debate in the last sixty years, even if its definition in the context of PolInSAR has been almost univocal. Nevertheless, the mutual relationships between coherence, polarization and statistical independence in PolSAR has recently been the subject of discussion in [1]. Some of these questions affect the eigenanalysis-based approach to PolInSAR, as developed by Cloude and Papathanassiou's foundational work. Coherence involves the behaviour of electromagnetic waves in at least a pair of points and in this sense it plays an important role in interferometry that is not present in non-interferometric radar polarimetry. PolInSAR inherits some of the difficulties found in [1], which stem from the controversial confusion between coherence and polarization as present in PolSAR, as well as the ability of separating different physical contributors to the scattering phenomenon through the use of eigenvalues and eigenvectors. Although these are also issues present in eigenanalysis-based PolInSAR, it is still possible to analyze a scene in terms of coherence and this very concept of coherence is the subject of this paper. A new analysis of the concept of coherence for interferometry is proposed, including multiple observation point configurations that bring about statistical moments whose order is higher than two.

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

NASA Astrophysics Data System (ADS)

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.

Space Radar Image of North Sea, Germany

NASA Technical Reports Server (NTRS)

1994-01-01

This is an X-band image of an oil slick experiment conducted in the North Sea, Germany. The image is centered at 54.58 degrees north latitude and 7.48 degrees east longitude. This image was acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour on October 6, 1994, during the second flight of the spaceborne radar. The experiment was designed to differentiate between petroleum oil spills and natural slicks floating on the sea surface. Two types of petroleum oil and six types of oils resembling natural sea surface slicks were poured on the sea surface from ships and a helicopter just before the space shuttle flew over the region. At the bottom of the image is the Sylt peninsula, a famous holiday resort. Twenty-six gallons (100 liters) of diesel oil was dissipated due to wave action before the shuttle reached the site. The oil spill seen at the uppermost part of the image is about 105 gallons (400 liters) of heavy heating oil and the largest spill is about 58 gallons (220 liters) of oleyl alcohol, resembling a 'natural oil' like the remaining five spills used to imitate natural slicks that have occurred offshore from various states. The volume of these other oils spilled on the ocean surface during the five experimental spills varied from 16 gallons to 21 gallons (60 liters to 80 liters). The distance between neighboring spills was about half a mile (800 meters) at the most. The largest slick later thinned out to monomolecular sheets of about 10 microns, which is the dimension of a molecule. Oceanographers found that SIR-C/X-SAR was able to clearly distinguish the oil slicks from algae products dumped nearby. Preliminary indications are that various types of slicks may be distinguished, especially when other radar wavelengths are included in the analysis. Radar imaging of the world's oceans on a continuing basis may allow oceanographers in the future to detect and clean up oil spills much more swiftly than is currently possible. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR.

Measuring Surface Subsidence in Wuhan, China with SENTINEL-1 Data Using Psinsar

NASA Astrophysics Data System (ADS)

Benattou, M. M.; Balz, T.; Liao, M.

2018-04-01

We use the potential of Sentinel-1 for urban subsidence monitoring. A case study was conducted in Wuhan using Sentinel-1A images acquired from 22nd June 2015 to the 24th of April 2017 acquired from an ascending orbit. Our results using PSInSAR are compared to a recent study using SBAS. Moreover, in another experiment, only more recent data, containing 18 images from the 7th of March 2017 to the 14th of March 2018, have been processed in order to analysis changes in the subsidence behavior over the study area. In addition to that, the proposed method (PSInSAR) was used to measure the water height in the east lake using metallic objects as stable PS points.

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

PubMed

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.

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

PubMed Central

Zhou, Rui; Hu, Yuxin; Qi, Yaolong

2018-01-01

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. PMID:29385059

Geocoding of AIRSAR/TOPSAR SAR Data

NASA Technical Reports Server (NTRS)

Holecz, Francesco; Lou, Yun-Ling; vanZyl, Jakob

1996-01-01

It has been demonstrated and recognized that radar interferometry is a promising method for the determination of digital elevation information and terrain slope from Synthetic Aperture Radar (SAR) data. An important application of Interferometric SAR (InSAR) data in areas with topographic variations is that the derived elevation and slope can be directly used for the absolute radiometric calibration of the amplitude SAR data as well as for scattering mechanisms analysis. On the other hand polarimetric SAR data has long been recognized as permitting a more complete inference of natural surfaces than a single channel radar system. In fact, imaging polarimetry provides the measurement of the amplitude and relative phase of all transmit and receive polarizations. On board the NASA DC-8 aircraft, NASA/JPL operates the multifrequency (P, L and C bands) multipolarimetric radar AIRSAR. The TOPSAR, a special mode of the AIRSAR system, is able to collect single-pass interferometric C- and/or L-band VV polarized data. A possible configuration of the AIRSAR/TOPSAR system is to acquire single-pass interferometric data at C-band VV polarization and polarimetric radar data at the two other lower frequencies. The advantage of this system configuration is to get digital topography information at the same time the radar data is collected. The digital elevation information can therefore be used to correctly calibrate the SAR data. This step is directly included in the new AIRSAR Integrated Processor. This processor uses a modification of the full motion compensation algorithm described by Madsen et al. (1993). However, the Digital Elevation Model (DEM) with the additional products such as local incidence angle map, and the SAR data are in a geometry which is not convenient, since especially DEMs must be referred to a specific cartographic reference system. Furthermore, geocoding of SAR data is important for multisensor and/or multitemporal purposes. In this paper, a procedure to geocode the new AIRSAR/TOPSAR data is presented. As an example an AIRSAR/TOPSAR image acquired in 1994 is geocoded and evaluated in terms of geometric accuracy.

Performance of Scattering Matrix Decomposition and Color Spaces for Synthetic Aperture Radar Imagery

DTIC Science & Technology

2010-03-01

Color Spaces and Synthetic Aperture Radar (SAR) Multicolor Imaging. 15 2.3.1 Colorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2...III. Decomposition Techniques on SAR Polarimetry and Colorimetry applied to SAR Imagery...space polarimetric SAR systems. Colorimetry is also introduced in this chapter, presenting the fundamentals of the RGB and CMY color spaces, defined for

Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network.

PubMed

Salehpour, Mehdi; Behrad, Alireza

2017-10-01

This study proposes a new algorithm for nonrigid coregistration of synthetic aperture radar (SAR) and optical images. The proposed algorithm employs point features extracted by the binary robust invariant scalable keypoints algorithm and a new method called weighted bidirectional matching for initial correspondence. To refine false matches, we assume that the transformation between SAR and optical images is locally rigid. This property is used to refine false matches by assigning scores to matched pairs and clustering local rigid transformations using a two-layer Kohonen network. Finally, the thin plate spline algorithm and mutual information are used for nonrigid coregistration of SAR and optical images.

Ship Detection Using High Resolution Satellite Imagery and Space-Based AIS

NASA Astrophysics Data System (ADS)

Hannevik, Tonje Nanette; Skauen, Andreas N.; Olsen, R. B.

2013-03-01

This paper presents a trial carried out in the Malangen area close to Tromsø city in the north of Norway in September 2010. High resolution Synthetic Aperture Radar (SAR) images from RADARSAT-2 were used to analyse how SAR images and cooperative reporting can be combined. Data from the Automatic Identification System, both land-based and space-based, have been used to identify detected vessels in the SAR images. The paper presents results of ship detection in high resolution RADARSAT-2 Standard Quad-Pol images, and how these results together with land-based and space-based AIS can be used. Some examples of tracking of vessels are also shown.

SAR image segmentation using skeleton-based fuzzy clustering

NASA Astrophysics Data System (ADS)

Cao, Yun Yi; Chen, Yan Qiu

2003-06-01

SAR image segmentation can be converted to a clustering problem in which pixels or small patches are grouped together based on local feature information. In this paper, we present a novel framework for segmentation. The segmentation goal is achieved by unsupervised clustering upon characteristic descriptors extracted from local patches. The mixture model of characteristic descriptor, which combines intensity and texture feature, is investigated. The unsupervised algorithm is derived from the recently proposed Skeleton-Based Data Labeling method. Skeletons are constructed as prototypes of clusters to represent arbitrary latent structures in image data. Segmentation using Skeleton-Based Fuzzy Clustering is able to detect the types of surfaces appeared in SAR images automatically without any user input.

Multiresolution MAP despeckling of SAR images based on locally adaptive generalized Gaussian pdf modeling.

PubMed

Argenti, Fabrizio; Bianchi, Tiziano; Alparone, Luciano

2006-11-01

In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori MIAP) estimation is proposed. Such a method relies on the assumption that the probability density function (pdf) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG pdf are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed pdf model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.

An all-optronic synthetic aperture lidar

NASA Astrophysics Data System (ADS)

Turbide, Simon; Marchese, Linda; Terroux, Marc; Babin, François; Bergeron, Alain

2012-09-01

Synthetic Aperture Radar (SAR) is a mature technology that overcomes the diffraction limit of an imaging system's real aperture by taking advantage of the platform motion to coherently sample multiple sections of an aperture much larger than the physical one. Synthetic Aperture Lidar (SAL) is the extension of SAR to much shorter wavelengths (1.5 μm vs 5 cm). This new technology can offer higher resolution images in day or night time as well as in certain adverse conditions. It could be a powerful tool for Earth monitoring (ship detection, frontier surveillance, ocean monitoring) from aircraft, unattended aerial vehicle (UAV) or spatial platforms. A continuous flow of high-resolution images covering large areas would however produce a large amount of data involving a high cost in term of post-processing computational time. This paper presents a laboratory demonstration of a SAL system complete with image reconstruction based on optronic processing. This differs from the more traditional digital approach by its real-time processing capability. The SAL system is discussed and images obtained from a non-metallic diffuse target at ranges up to 3m are shown, these images being processed by a real-time optronic SAR processor origiinally designed to reconstruct SAR images from ENVISAT/ASAR data.

Large Scale Assessment of Radio Frequency Interference Signatures in L-band SAR Data

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Nicoll, J.

2011-12-01

Imagery of L-band Synthetic Aperture Radar (SAR) systems such as the PALSAR sensor on board the Advanced Land Observing Satellite (ALOS) has proven to be a valuable tool for observing environmental changes around the globe. Besides offering 24/7 operability, the L-band frequency provides improved interferometric coherence, and L-band polarimetric data has shown great potential for vegetation monitoring, sea ice classification, and the observation of glaciers and ice sheets. To maximize the benefit of missions such as ALOS PALSAR for environmental monitoring, data consistency and calibration are vital. Unfortunately, radio frequency interference (RFI) signatures from ground-based radar systems regularly impair L-band SAR data quality and consistency. With this study we present a large-scale analysis of typical RFI signatures that are regularly observed in L-band SAR data over the Americas. Through a study of the vast archive of L-band SAR data in the US Government Research Consortium (USGRC) data pool at the Alaska Satellite Facility (ASF) we were able to address the following research goals: 1. Assessment of RFI Signatures in L-band SAR data and their Effects on SAR Data Quality: An analysis of time-frequency properties of RFI signatures in L-band SAR data of the USGRC data pool is presented. It is shown that RFI-filtering algorithms implemented in the operational ALOS PALSAR processor are not sufficient to remove all RFI-related artifacts. In examples, the deleterious effects of RFI on SAR image quality, polarimetric signature, SAR phase, and interferometric coherence are presented. 2. Large-Scale Assessment of Severity, Spatial Distribution, and Temporal Variation of RFI Signatures in L-band SAR data: L-band SAR data in the USGRC data pool were screened for RFI using a custom algorithm. Per SAR frame, the algorithm creates geocoded frame bounding boxes that are color-coded according to RFI intensity and converted to KML files for analysis in Google Earth. From the screening results, parameters such as RFI severity and spatial distribution of RFI were derived. Through a comparison of RFI signatures in older SAR data from JAXA's Japanese Earth Resources Satellite (JERS-1) and recent ALOS PALSAR data, changes in RFI signatures in the Americas were derived, indicating a strong increase of L-band signal contamination over time. 3. An Optimized RFI Filter and its Performance in Data Restoration: An optimized RFI filter has been developed and tested at ASF. The algorithm has proven to be effective in detecting and removing RFI signatures in L-band SAR data and restoring the advertised quality of SAR imagery, polarization, and interferometric phase. The properties of the RFI filter will be described and its performance will be demonstrated in examples. The presented work is a prime example of large-scale research that is made possible by the availability of SAR data through the extensive data archive of the USGRC data pool at ASF.

Integration of GB-InSAR, laser scanning and in situ monitoring on the rockslope instability of Mannen/Børa (western Norway)

NASA Astrophysics Data System (ADS)

Rouyet, Line; Kristensen, Lene; Derron, Marc-Henri; Michoud, Clément; Harald, Blikra Lars; Michel, Jaboyedoff

2013-04-01

This work is part of a master thesis about the use of Ground-Based InSAR for the monitoring of rock instabilities (University of Lausanne in cooperation with the Åknes/Tafjord Early Warning Centre in Norway). Main goals are (1) the evaluation of the GB-InSAR potential to investigate different kinds of instabilities, (2) the combination of data from GB-InSAR, conventional in situ devices and laser scanning to get information about instability behavior and geometry. The rockslope instability of Mannen/Børa is located in Møre of Romsdal County (western Norway). Mannen is a complex rockslide of 15-25 mill. m3 of volume, affecting the left side of the Romsdalen valley. Børa is a large plateau directly located on its south-eastern side and showing signs of activity. In this case, the analysis included GB-InSAR data of 2011 and 2012 campaigns in Børa compared with results of a permanent GB-InSAR in Mannen. The results of continuous monitoring in Mannen (GPS, extensometers, laser-reflectors and tiltmeters) since end of 2009, as well as periodical GPS campaigns on Børa plateau were integrated. The analysis showed a quite regular inter-annual velocity with seasonal effects in Mannen site and a slower movement in Børa. Moreover, it allowed highlighting an area in mid-slope, affected by high variations and periodical inversions of movement in the overlap sector between the two GB-InSAR. The first interpretation of this pattern involves networks of water flow across the slope. A novel point of this site is to have two GB-InSAR systems (one permanent and one temporary) imaging the rockslope with an overlap of views. GB-InSAR results were compared to other types of monitoring data, in terms of spatial coverage (punctual vs. large area), temporal scale (continuous monitoring vs. periodical campaigns) or recorded information (eg. 3D vs. 1D along the LOS). Moreover, a structural geology analysis based on terrestrial and airborne laser scanning data provided information about the geometry of rock instabilities and sliding surfaces.

Estimation of Damaged Areas due to the 2010 Chile Earthquake and Tsunami Using SAR Imagery of Alos/palsar

NASA Astrophysics Data System (ADS)

Made, Pertiwi Jaya Ni; Miura, Fusanori; Besse Rimba, A.

2016-06-01

A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km2. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.

An evaluation of processing InSAR Sentinel-1A/B data for correlation of mining subsidence with mining induced tremors in the Upper Silesian Coal Basin (Poland)

NASA Astrophysics Data System (ADS)

Krawczyk, Artur; Grzybek, Radosław

2018-01-01

The Satellite Radar Interferometry is one of the common methods that allow to measure the land subsidence caused by the underground black coal excavation. The interferometry images processed from the repeat-pass Synthetic Aperture Radar (SAR) systems give the spatial image of the terrain subjected to the surface subsidence over mining areas. Until now, the InSAR methods using data from the SAR Systems like ERS-1/ERS-2 and Envisat-1 were limited to a repeat-pass cycle of 35-day only. Recently, the ESA launched Sentinel-1A and 1B, and together they can provide the InSAR coverage in a 6-day repeat cycle. The studied area was the Upper Silesian Coal Basin in Poland, where the underground coal mining causes continuous subsidence of terrain surface and mining tremors (mine-induced seismicity). The main problem was with overlapping the subsidence caused by the mining exploitation with the epicentre tremors. Based on the Sentinel SAR images, research was done in regard to the correlation between the short term ground subsidence range border and the mine-induced seismicity epicentres localisation.

Pixel-based flood mapping from SAR imagery: a comparison of approaches

NASA Astrophysics Data System (ADS)

Landuyt, Lisa; Van Wesemael, Alexandra; Van Coillie, Frieke M. B.; Verhoest, Niko E. C.

2017-04-01

Due to their all-weather, day and night capabilities, SAR sensors have been shown to be particularly suitable for flood mapping applications. Thus, they can provide spatially-distributed flood extent data which are valuable for calibrating, validating and updating flood inundation models. These models are an invaluable tool for water managers, to take appropriate measures in times of high water levels. Image analysis approaches to delineate flood extent on SAR imagery are numerous. They can be classified into two categories, i.e. pixel-based and object-based approaches. Pixel-based approaches, e.g. thresholding, are abundant and in general computationally inexpensive. However, large discrepancies between these techniques exist and often subjective user intervention is needed. Object-based approaches require more processing but allow for the integration of additional object characteristics, like contextual information and object geometry, and thus have significant potential to provide an improved classification result. As means of benchmark, a selection of pixel-based techniques is applied on a ERS-2 SAR image of the 2006 flood event of River Dee, United Kingdom. This selection comprises Otsu thresholding, Kittler & Illingworth thresholding, the Fine To Coarse segmentation algorithm and active contour modelling. The different classification results are evaluated and compared by means of several accuracy measures, including binary performance measures.

The SARVIEWS Project: Automated SAR Processing in Support of Operational Near Real-time Volcano Monitoring

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Webley, P. W.; Dehn, J.; Arko, S. A.; McAlpin, D. B.; Gong, W.

2016-12-01

Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing has become established in operational volcano monitoring. Centers like the Alaska Volcano Observatory rely heavily on remote sensing data from optical and thermal sensors to provide time-critical hazard information. Despite this high use of remote sensing data, the presence of clouds and a dependence on solar illumination often limit their impact on decision making. Synthetic Aperture Radar (SAR) systems are widely considered superior to optical sensors in operational monitoring situations, due to their weather and illumination independence. Still, the contribution of SAR to operational volcano monitoring has been limited in the past due to high data costs, long processing times, and low temporal sampling rates of most SAR systems. In this study, we introduce the automatic SAR processing system SARVIEWS, whose advanced data analysis and data integration techniques allow, for the first time, a meaningful integration of SAR into operational monitoring systems. We will introduce the SARVIEWS database interface that allows for automatic, rapid, and seamless access to the data holdings of the Alaska Satellite Facility. We will also present a set of processing techniques designed to automatically generate a set of SAR-based hazard products (e.g. change detection maps, interferograms, geocoded images). The techniques take advantage of modern signal processing and radiometric normalization schemes, enabling the combination of data from different geometries. Finally, we will show how SAR-based hazard information is integrated in existing multi-sensor decision support tools to enable joint hazard analysis with data from optical and thermal sensors. We will showcase the SAR processing system using a set of recent natural disasters (both earthquakes and volcanic eruptions) to demonstrate its robustness. We will also show the benefit of integrating SAR with data from other sensors to support volcano monitoring. For historic eruptions at Okmok and Augustine volcano, both located in the North Pacific, we will demonstrate that the addition of SAR can lead to a significant improvement in activity detection and eruption forecasting.

Separated Component-Based Restoration of Speckled SAR Images

DTIC Science & Technology

2013-01-01

unsupervised change detection from SAR amplitude imagery,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 10, pp. 2972–2982, Oct. 2006. [5] F. Argenti , T...Sens., vol. 40, no. 10, pp. 2196–2212, Oct. 2002. [13] F. Argenti and L. Alparone, “Speckle removal from SAR images in the undecimated wavelet domain...iterative thresh- olding algorithm for linear inverse problems with a sparsity con- straint,” Commun . Pure Appl. Math., vol. 57, no. 11, pp. 1413

Flood Extent Delineation by Thresholding Sentinel-1 SAR Imagery Based on Ancillary Land Cover Information

NASA Astrophysics Data System (ADS)

Liang, J.; Liu, D.

2017-12-01

Emergency responses to floods require timely information on water extents that can be produced by satellite-based remote sensing. As SAR image can be acquired in adverse illumination and weather conditions, it is particularly suitable for delineating water extent during a flood event. Thresholding SAR imagery is one of the most widely used approaches to delineate water extent. However, most studies apply only one threshold to separate water and dry land without considering the complexity and variability of different dry land surface types in an image. This paper proposes a new thresholding method for SAR image to delineate water from other different land cover types. A probability distribution of SAR backscatter intensity is fitted for each land cover type including water before a flood event and the intersection between two distributions is regarded as a threshold to classify the two. To extract water, a set of thresholds are applied to several pairs of land cover types—water and urban or water and forest. The subsets are merged to form the water distribution for the SAR image during or after the flooding. Experiments show that this land cover based thresholding approach outperformed the traditional single thresholding by about 5% to 15%. This method has great application potential with the broadly acceptance of the thresholding based methods and availability of land cover data, especially for heterogeneous regions.

Detecting and monitoring UCG subsidence with InSAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 subsidencemore » 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.« less

Spaceborne synthetic aperture radar signal processing using FPGAs

NASA Astrophysics Data System (ADS)

Sugimoto, Yohei; Ozawa, Satoru; Inaba, Noriyasu

2017-10-01

Synthetic Aperture Radar (SAR) imagery requires image reproduction through successive signal processing of received data before browsing images and extracting information. The received signal data records of the ALOS-2/PALSAR-2 are stored in the onboard mission data storage and transmitted to the ground. In order to compensate the storage usage and the capacity of transmission data through the mission date communication networks, the operation duty of the PALSAR-2 is limited. This balance strongly relies on the network availability. The observation operations of the present spaceborne SAR systems are rigorously planned by simulating the mission data balance, given conflicting user demands. This problem should be solved such that we do not have to compromise the operations and the potential of the next-generation spaceborne SAR systems. One of the solutions is to compress the SAR data through onboard image reproduction and information extraction from the reproduced images. This is also beneficial for fast delivery of information products and event-driven observations by constellation. The Emergence Studio (Sōhatsu kōbō in Japanese) with Japan Aerospace Exploration Agency is developing evaluation models of FPGA-based signal processing system for onboard SAR image reproduction. The model, namely, "Fast L1 Processor (FLIP)" developed in 2016 can reproduce a 10m-resolution single look complex image (Level 1.1) from ALOS/PALSAR raw signal data (Level 1.0). The processing speed of the FLIP at 200 MHz results in twice faster than CPU-based computing at 3.7 GHz. The image processed by the FLIP is no way inferior to the image processed with 32-bit computing in MATLAB.

Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery

NASA Astrophysics Data System (ADS)

Iino, Shota; Ito, Riho; Doi, Kento; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

In the developing countries, urban areas are expanding rapidly. With the rapid developments, a short term monitoring of urban changes is important. A constant observation and creation of urban distribution map of high accuracy and without noise pollution are the key issues for the short term monitoring. SAR satellites are highly suitable for day or night and regardless of atmospheric weather condition observations for this type of study. The current study highlights the methodology of generating high-accuracy urban distribution maps derived from the SAR satellite imagery based on Convolutional Neural Network (CNN), which showed the outstanding results for image classification. Several improvements on SAR polarization combinations and dataset construction were performed for increasing the accuracy. As an additional data, Digital Surface Model (DSM), which are useful to classify land cover, were added to improve the accuracy. From the obtained result, high-accuracy urban distribution map satisfying the quality for short-term monitoring was generated. For the evaluation, urban changes were extracted by taking the difference of urban distribution maps. The change analysis with time series of imageries revealed the locations of urban change areas for short-term. Comparisons with optical satellites were performed for validating the results. Finally, analysis of the urban changes combining X-band, L-band and C-band SAR satellites was attempted to increase the opportunity of acquiring satellite imageries. Further analysis will be conducted as future work of the present study

Techniques and Tools for Estimating Ionospheric Effects in Interferometric and Polarimetric SAR Data

NASA Technical Reports Server (NTRS)

Rosen, P.; Lavalle, M.; Pi, X.; Buckley, S.; Szeliga, W.; Zebker, H.; Gurrola, E.

2011-01-01

The InSAR Scientific Computing Environment (ISCE) is a flexible, extensible software tool designed for the end-to-end processing and analysis of synthetic aperture radar data. ISCE inherits the core of the ROI_PAC interferometric tool, but contains improvements at all levels of the radar processing chain, including a modular and extensible architecture, new focusing approach, better geocoding of the data, handling of multi-polarization data, radiometric calibration, and estimation and correction of ionospheric effects. In this paper we describe the characteristics of ISCE with emphasis on the ionospheric modules. To detect ionospheric anomalies, ISCE implements the Faraday rotation method using quadpolarimetric images, and the split-spectrum technique using interferometric single-, dual- and quad-polarimetric images. The ability to generate co-registered time series of quad-polarimetric images makes ISCE also an ideal tool to be used for polarimetric-interferometric radar applications.

SAR imaging of ocean waves - Theory

NASA Technical Reports Server (NTRS)

Jain, A.

1981-01-01

A SAR imaging integral for a rough surface is derived. Aspects of distributed target imaging and questions of ocean-wave imaging are considered. A description is presented of the results of analyses which are performed on aircraft and a spacecraft data in order to gain an understanding of the SAR imaging of ocean waves. The analyzed data illustrate the effect of radar resolution on the images of azimuthally traveling waves, the dependence of image distortion on the angle which the waves make with the radar flight path, and the dependence of the focusing parameter of the radar matched filter on the ocean wave period for azimuthally traveling waves. A dependence of ocean-wave modulation on significant wave height is also observed. The observed dependence of the modulations of azimuth waves on radar resolution is in contradiction to the hypothesis that these modulations are caused mainly by velocity bunching.

Upper ocean fine-scale features in synthetic aperture radar imagery. Part I: Simultaneous satellite and in-situ measurements

NASA Astrophysics Data System (ADS)

Soloviev, A.; Maingot, C.; Matt, S.; Fenton, J.; Lehner, S.; Brusch, S.; Perrie, W. A.; Zhang, B.

2011-12-01

The new generation of synthetic aperture radar (SAR) satellites provides high resolution images that open new opportunities for identifying and studying fine features in the upper ocean. The problem is, however, that SAR images of the sea surface can be affected by atmospheric phenomena (rain cells, fronts, internal waves, etc.). Implementation of in-situ techniques in conjunction with SAR is instrumental for discerning the origin of features on the image. This work is aimed at the interpretation of natural and artificial features in SAR images. These features can include fresh water lenses, sharp frontal interfaces, internal wave signatures, as well as slicks of artificial and natural origin. We have conducted field experiments in the summer of 2008 and 2010 and in the spring of 2011 to collect in-situ measurements coordinated with overpasses of the TerraSAR-X, RADARSAT-2, ALOS PALSAR, and COSMO SkyMed satellites. The in-situ sensors deployed in the Straits of Florida included a vessel-mounted sonar and CTD system to record near-surface data on stratification and frontal boundaries, a bottom-mounted Nortek AWAC system to gather information on currents and directional wave spectra, an ADCP mooring at a 240 m isobath, and a meteorological station. A nearby NOAA NEXRAD Doppler radar station provided a record of rainfall in the area. Controlled releases of menhaden fish oil were performed from our vessel before several satellite overpasses in order to evaluate the effect of surface active materials on visibility of sea surface features in SAR imagery under different wind-wave conditions. We found evidence in the satellite images of rain cells, squall lines, internal waves of atmospheric and possibly oceanic origin, oceanic frontal interfaces and submesoscale eddies, as well as anthropogenic signatures of ships and their wakes, and near-shore surface slicks. The combination of satellite imagery and coordinated in-situ measurements was helpful in interpreting fine-scale features on the sea surface observed in the SAR images and, in some cases, linking them to thermohaline features in the upper ocean. Finally, we have been able to reproduce SAR signatures of freshwater plumes and sharp frontal interfaces interacting with wind stress, as well as internal waves by combining hydrodynamic simulations with a radar imaging algorithm. The modeling results are presented in a companion paper (Matt et al., 2011).

Mathematical Problems in Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Klein, Jens

2010-10-01

This thesis is concerned with problems related to Synthetic Aperture Radar (SAR). The thesis is structured as follows: The first chapter explains what SAR is, and the physical and mathematical background is illuminated. The following chapter points out a problem with a divergent integral in a common approach and proposes an improvement. Numerical comparisons are shown that indicate that the improvements allow for a superior image quality. Thereafter the problem of limited data is analyzed. In a realistic SAR-measurement the data gathered from the electromagnetic waves reflected from the surface can only be collected from a limited area. However the reconstruction formula requires data from an infinite distance. The chapter gives an analysis of the artifacts which can obscure the reconstructed images due to this problem. Additionally, some numerical examples are shown that point to the severity of the problem. In chapter 4 the fact that data is available only from a limited area is used to propose a new inversion formula. This inversion formula has the potential to make it easier to suppress artifacts due to limited data and, depending on the application, can be refined to a fast reconstruction formula. In the penultimate chapter a solution to the problem of left-right ambiguity is presented. This problem exists since the invention of SAR and is caused by the geometry of the measurements. This leads to the fact that only symmetric images can be obtained. With the solution from this chapter it is possible to reconstruct not only the even part of the reflectivity function, but also the odd part, thus making it possible to reconstruct asymmetric images. Numerical simulations are shown to demonstrate that this solution is not affected by stability problems as other approaches have been. The final chapter develops some continuative ideas that could be pursued in the future.

Polarimetric C-/X-band Synthetic Aperture Radar Observations of Melting Sea Ice in the Canadian Arctic Archipelago

NASA Astrophysics Data System (ADS)

Casey, J. A.; Beckers, J. F.; Brossier, E.; Haas, C.

2013-12-01

Operational ice information services rely heavily on space-borne synthetic aperture radar (SAR) data for the production of ice charts to meet their mandate of providing timely and accurate sea ice information to support safe and efficient marine operations. During the summer melt period, the usefulness of SAR data for sea ice monitoring is limited by the presence of wet snow and melt ponds on the ice surface, which can mask the signature of the underlying ice. This is a critical concern for ice services whose clients (e.g. commercial shipping, cruise tourism, resource exploration and extraction) are most active at this time of year when sea ice is at its minimum extent, concentration and thickness. As a result, there is a need to further quantify the loss of ice information in SAR data during the melt season and to identify what information can still be retrieved about ice surface conditions and melt pond evolution at this time of year. To date the majority of studies have been limited to analysis of single-polarization C-band SAR data. This study will investigate the potential complimentary and unique sea ice information that polarimetric C- and X-band SAR data can provide to supplement the information available from traditional single co-polarized C-band SAR data. A time-series of polarimetric C- and X-band SAR data was acquired over Jones Sound in the Canadian Arctic Archipelago, in the vicinity of the Grise Fiord, Nunavut. Five RADARSAT-2 Wide Fine Quad-pol images and 11 TerraSAR-X StripMap dual-pol (HH/VV) images were acquired. The time-series begins at the onset of melt in early June and extends through advanced melt conditions in late July. Over this period several ponding and drainage events and two snowfall events occurred. Field observations of sea ice properties were collected using an Ice Mass Balance (IMB) buoy, hourly photos from a time-lapse camera deployed on a coastal cliff, and manual in situ measurements of snow thickness and melt pond depth. Where available, clear-sky data from optical sensors (MODIS, Landsat-8, and WorldView) are also used to provide supplementary information on melt pond coverage and evolution. Meteorological data are available from an Environment Canada weather station in Grise Fiord. In this presentation we will discuss the sea ice information provided by each polarization and frequency and evaluate the impact of melt pond evolution on SAR backscatter. Results to date indicate that C- and X-band provide predominantly redundant information, and cross-polarized backscatter (only acquired at C-band) is often very low and near the system noise floor. Early in the melt season a thick wet snow pack is present and both frequencies provide very little ice information. This is attributed to the strong attenuation of the microwave signal by the wet snow. At this time the underlying ice is effectively obscured. During heavily ponded periods backscatter is highly variable, attributed to changing winds and thus variable melt pond surface roughness. In the final week of observations the fast ice in the region is breaking up and open water is present in some images. In these images C-band appears to provide greater contrast between the melting ice and open water than X-band. Analysis of polarimetric parameters is ongoing.

Developing tools for digital radar image data evaluation

NASA Technical Reports Server (NTRS)

Domik, G.; Leberl, F.; Raggam, J.

1986-01-01

The refinement of radar image analysis methods has led to a need for a systems approach to radar image processing software. Developments stimulated through satellite radar are combined with standard image processing techniques to create a user environment to manipulate and analyze airborne and satellite radar images. One aim is to create radar products for the user from the original data to enhance the ease of understanding the contents. The results are called secondary image products and derive from the original digital images. Another aim is to support interactive SAR image analysis. Software methods permit use of a digital height model to create ortho images, synthetic images, stereo-ortho images, radar maps or color combinations of different component products. Efforts are ongoing to integrate individual tools into a combined hardware/software environment for interactive radar image analysis.

Generation and assessment of turntable SAR data for the support of ATR development

NASA Astrophysics Data System (ADS)

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.

A modified sparse reconstruction method for three-dimensional synthetic aperture radar image

NASA Astrophysics Data System (ADS)

Zhang, Ziqiang; Ji, Kefeng; Song, Haibo; Zou, Huanxin

2018-03-01

There is an increasing interest in three-dimensional Synthetic Aperture Radar (3-D SAR) imaging from observed sparse scattering data. However, the existing 3-D sparse imaging method requires large computing times and storage capacity. In this paper, we propose a modified method for the sparse 3-D SAR imaging. The method processes the collection of noisy SAR measurements, usually collected over nonlinear flight paths, and outputs 3-D SAR imagery. Firstly, the 3-D sparse reconstruction problem is transformed into a series of 2-D slices reconstruction problem by range compression. Then the slices are reconstructed by the modified SL0 (smoothed l0 norm) reconstruction algorithm. The improved algorithm uses hyperbolic tangent function instead of the Gaussian function to approximate the l0 norm and uses the Newton direction instead of the steepest descent direction, which can speed up the convergence rate of the SL0 algorithm. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed algorithm. It is shown that our method, compared with existing 3-D sparse imaging method, performs better in reconstruction quality and the reconstruction time.

Observation of high-resolution wind fields and offshore wind turbine wakes using TerraSAR-X imagery

NASA Astrophysics Data System (ADS)

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 coast of Borkum, Germany, and consists of twelve 5-Megawatt wind power turbines. The retrieved results are validated by comparing with QuikSCAT measurements, the results of the German Weather Service (DWD) atmospheric model and in-situ measurements of wind speed and wind direction, obtained from the research platform FiNO1, installed 400 m west of Alpha Ventus. 4. Conclusion In the presented case study we quantify the wake characteristics of wake length, wake width, maximum velocity de?cit, wake merging and wake meandering. We show that SAR has the capability to map the sea surface two-dimensionally in high spatial resolution which provides a unique opportunity to observe spatial characteristics of offshore wind turbine wakes. The SAR derived information can support offshore wind farming with respect to optimal siting and design and help to estimate their effects on the environment.

An Evaluation of ALOS Data in Disaster Applications

NASA Astrophysics Data System (ADS)

Igarashi, Tamotsu; Igarashi, Tamotsu; Furuta, Ryoich; Ono, Makoto

ALOS is the advanced land observing satellite, providing image data from onboard sensors; PRISM, AVNIR-2 and PALSAR. PRISM is the sensor of panchromatic stereo, high resolution three-line-scanner to characterize the earth surface. The accuracy of position in image and height of Digital Surface Model (DSM) are high, therefore the geographic information extraction is improved in the field of disaster applications with providing images of disaster area. Especially pan-sharpened 3D image composed with PRISM and the four-band visible near-infrared radiometer AVNIR-2 data is expected to provide information to understand the geographic and topographic feature. PALSAR is the advanced multi-functional synthetic aperture radar (SAR) operated in L-band, appropriate for the use of land surface feature characterization. PALSAR has many improvements from JERS-1/SAR, such as high sensitivity, having high resolution, polarimetric and scan SAR observation modes. PALSAR is also applicable for SAR interferometry processing. This paper describes the evaluation of ALOS data characteristic from the view point of disaster applications, through some exercise applications.

SAR imaging of vortex ship wakes. Volume 3: An overview of pre-ERS-1 observations and models

NASA Astrophysics Data System (ADS)

Skoeelv, Aage; Wahl, Terje

1991-05-01

The visibility of dark turbulent wakes in Synthetic Aperture Radar (SAR) imagery is focused upon. An overview of various wake observations prior to ERS-1 is given. This includes images from Seasat and airborne SAR as well as photographic observations. Different turbulent wake models and simulation, schemes are reviewed. The requirements for a complete turbulent wake model are discussed, and from results available, some conclusions are drawn with respect to possible ERS-1 applications.

Design of integrated ship monitoring system using SAR, RADAR, and AIS

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho; Hong, Danbee; Ahn, Hyung-Wook

2013-06-01

When we talk about for the ship detection, identification and its classification, we need to go for the wide area of monitoring and it may be possible only through satellite based monitoring approach which monitors and covers coastal as well as the oceanic zone. Synthetic aperture radar (SAR) has been widely used to detect targets of interest with the advantage of the operating capability in all weather and luminance free condition (Margarit and Tabasco, 2011). In EU waters, EMSA(European Maritime Safety Agency) is operating the SafeSeaNet and CleanSeaNet systems which provide the current positions of all ships and oil spill monitoring information in and around EU waters in a single picture to Member States using AIS, LRIT and SAR images. In many countries, a similar system has been developed and the key of the matter is to integrate all available data. This abstract describes the preliminary design concept for an integration system of RADAR, AIS and SAR data for vessel traffic monitoring. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should be also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Land-based RADAR can provide ships positions detected and tracked in near real time. In general, SAR are used to acquire image data over large coverage area, AIS reports are obtained from ship based transmitter, and RADAR can monitor continuously ships for a limited area. In this study, we developed individual ship monitoring algorithms using RADAR(FMCW and Pulse X-band), AIS and SAR(RADARSAT-2 Full-pol Mode). We conducted field experiments two times for displaying the RADAR, AIS and SAR integration over the Pyeongtaek Port, South Korea.

Evaluating Three Insar Time-Series Methods to Assess Creep Motion, Case Study: Masouleh Landslide in North Iran

NASA Astrophysics Data System (ADS)

Mirzaee, S.; Motagh, M.; Akbari, B.; Wetzel, H. U.; Roessner, S.

2017-05-01

Masouleh is one of the ancient cities located in a high mountainous area in Gilan province of northern Iran. The region is threatened by a hazardous landslide, which was last activated in 1998, causing 32 dead and 45 injured. Significant temporal decorrelation caused by dense vegetation coverage within the landslide area makes the use of Synthetic Aperture Radar Interferometry (InSAR) for monitoring landslide movement very challenging. In this paper, we investigate the capability of three InSAR time-series techniques for evaluating creep motion on Masouleh landslide. The techniques are Persistent Scatterer Interferometry (PSI), Small BAseline Subset (SBAS) and SqueeSAR. The analysis is done using a dataset of 33 TerraSAR-X images in SpotLight (SL) mode covering a period of 15 months between June 2015 and September 2016. Results show the distinguished capability of SqueeSAR method in comparison to 2 other techniques for assessing landslide movement. The final number of scatterers in the landslide body detected by PSI and SBAS are about 70 and 120 respectively while this increases to about 345 in SqueeSAR. The coherence of interferograms improved by about 37% for SqueeSAR as compared to SBAS. The same rate of displacement was observed in those regions where all the methods were able to detect scatterers. Maximum rates of displacement detected by SqueeSAR technique in the northern edge, older and younger part of the landslide body are about -39, -65 and -22 mm/y, respectively.

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

USGS Publications Warehouse

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.

A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data.

PubMed

Wang, Lei; Han, Bing; Yuan, Xinzhe; Lei, Bin; Ding, Chibiao; Yao, Yulin; Chen, Qi

2018-05-17

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σ VV 0 retrieved from new PR models as well as σ HH 0 is in good agreement with σ VV 0 extracted from SAR images directly.

A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data

PubMed Central

Wang, Lei; Han, Bing; Yuan, Xinzhe; Lei, Bin; Ding, Chibiao; Yao, Yulin; Chen, Qi

2018-01-01

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σVV0 retrieved from new PR models as well as σHH0 is in good agreement with σVV0 extracted from SAR images directly. PMID:29772821

3D displacement time series in the Afar rift zone computed from SAR phase and amplitude information

NASA Astrophysics Data System (ADS)

Casu, Francesco; Manconi, Andrea

2013-04-01

Large and rapid deformations, such as those caused by earthquakes, eruptions, and landslides cannot be fully measured by using standard DInSAR applications. Indeed, the phase information often degrades and some areas of the interferograms are affected by high fringe rates, leading to difficulties in the phase unwrapping, and/or to complete loss of coherence due to significant misregistration errors. This limitation can be overcome by exploiting the SAR image amplitude information instead of the phase, and by calculating the Pixel-Offset (PO) field SAR image pairs, for both range and azimuth directions. Moreover, it is possible to combine the PO results by following the same rationale of the SBAS technique, to finally retrieve the offset-based deformation time series. Such technique, named PO-SBAS, permits to retrieve the deformation field in areas affected by very large displacements at an accuracy that, for ENVISAT data, correspond to 30 cm and 15 cm for the range and azimuth, respectively [1]. Moreover, the combination of SBAS and PO-SBAS time series can help to better study and model deformation phenomena characterized by spatial and temporal heterogeneities [2]. The Dabbahu rift segment of the Afar depression has been active since 2005 when a 2.5 km3 dyke intrusion and hundreds of earthquakes marked the onset a rifting episode which continues to date. The ENVISAT satellite has repeatedly imaged the Afar depression since 2003, generating a large SAR archive. In this work, we study the Afar rift region deformations by using both the phase and amplitude information of several sets of SAR images acquired from ascending and descending ENVISAT tracks. We combined sets of small baseline interferograms through the SBAS algorithm, and we generate both ground deformation maps and time series along the satellite Line-Of-Sight (LOS). In areas where the deformation gradient causes loss of coherence, we retrieve the displacement field through the amplitude information. Furthermore, we could also retrieve the full 3D deformation field, by considering the North-South displacement component obtained from the azimuth PO information. The combination of SBAS and PO-SBAS information permits to better retrieve and constrain the full deformation field due to repeated intrusions, fault movements, as well as the magma movements from individual magma chambers. [1] Casu, F., A. Manconi, A. Pepe and R. Lanari, 2011. Deformation time-series generation in areas characterized by large displacement dynamics: the SAR amplitude Pixel-Offset SBAS technique, IEEE Transaction on Geosciences and Remote Sensing. [2] Manconi, A. and F. Casu, 2012. Joint analysis of displacement time series retrieved from SAR phase and amplitude: impact on the estimation of volcanic source parameters, Geophysical Research Letters, doi:10.1029/2012GL052202.

Interferometric synthetic aperture radar imagery of the Gulf Stream

NASA Technical Reports Server (NTRS)

Ainsworth, T. L.; Cannella, M. E.; Jansen, R. W.; Chubb, S. R.; Carande, R. E.; Foley, E. W.; Goldstein, R. M.; Valenzuela, G. R.

1993-01-01

The advent of interferometric synthetic aperture radar (INSAR) imagery brought to the ocean remote sensing field techniques used in radio astronomy. Whilst details of the interferometry differ between the two fields, the basic idea is the same: Use the phase information arising from positional differences of the radar receivers and/or transmitters to probe remote structures. The interferometric image is formed from two complex synthetic aperture radar (SAR) images. These two images are of the same area but separated in time. Typically the time between these images is very short -- approximately 50 msec for the L-band AIRSAR (Airborne SAR). During this short period the radar scatterers on the ocean surface do not have time to significantly decorrelate. Hence the two SAR images will have the same amplitude, since both obtain the radar backscatter from essentially the same object. Although the ocean surface structure does not significantly decorrelate in 50 msec, surface features do have time to move. It is precisely the translation of scattering features across the ocean surface which gives rise to phase differences between the two SAR images. This phase difference is directly proportional to the range velocity of surface scatterers. The constant of proportionality is dependent upon the interferometric mode of operation.

Neural networks for oil spill detection using TerraSAR-X data

NASA Astrophysics Data System (ADS)

Avezzano, Ruggero G.; Velotto, Domenico; Soccorsi, Matteo; Del Frate, Fabio; Lehner, Susanne

2011-11-01

The increased amount of available Synthetic Aperture Radar (SAR) images involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In this paper we present the potentialities of TerraSAR-X (TS-X) data and Neural Network algorithms for oil spills detection. The radar on board satellite TS-X provides X-band images with a resolution of up to 1m. Such resolution can be very effective in the monitoring of coastal areas to prevent sea oil pollution. The network input is a vector containing the values of a set of features characterizing an oil spill candidate. The network output gives the probability for the candidate to be a real oil spill. Candidates with a probability less than 50% are classified as look-alikes. The overall classification performances have been evaluated on a data set of 50 TS-X images containing more than 150 examples of certified oil spills and well-known look-alikes (e.g. low wind areas, wind shadows, biogenic films). The preliminary classification results are satisfactory with an overall detection accuracy above 80%.

Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

PubMed Central

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859

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

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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 of the order of 2m compared to LiDAR estimates, is then used to generalize this tomographic technique by selecting in an adaptive way the height at which reflectivity is estimated. Results indicate that this generalized techniques reduces the estimation error to values inferior to 10% and improve the representativity of the obtained AGB maps.

Mapping ground surface deformation using temporarily coherent point SAR interferometry: Application to Los Angeles Basin

USGS Publications Warehouse

Zhang, L.; Lu, Zhong; Ding, X.; Jung, H.-S.; Feng, G.; Lee, C.-W.

2012-01-01

Multi-temporal interferometric synthetic aperture radar (InSAR) is an effective tool to detect long-term seismotectonic motions by reducing the atmospheric artifacts, thereby providing more precise deformation signal. The commonly used approaches such as persistent scatterer InSAR (PSInSAR) and small baseline subset (SBAS) algorithms need to resolve the phase ambiguities in interferogram stacks either by searching a predefined solution space or by sparse phase unwrapping methods; however the efficiency and the success of phase unwrapping cannot be guaranteed. We present here an alternative approach – temporarily coherent point (TCP) InSAR (TCPInSAR) – to estimate the long term deformation rate without the need of phase unwrapping. The proposed approach has a series of innovations including TCP identification, TCP network and TCP least squares estimator. We apply the proposed method to the Los Angeles Basin in southern California where structurally active faults are believed capable of generating damaging earthquakes. The analysis is based on 55 interferograms from 32 ERS-1/2 images acquired during Oct. 1995 and Dec. 2000. To evaluate the performance of TCPInSAR on a small set of observations, a test with half of interferometric pairs is also performed. The retrieved TCPInSAR measurements have been validated by a comparison with GPS observations from Southern California Integrated GPS Network. Our result presents a similar deformation pattern as shown in past InSAR studies but with a smaller average standard deviation (4.6 mm) compared with GPS observations, indicating that TCPInSAR is a promising alternative for efficiently mapping ground deformation even from a relatively smaller set of interferograms.

Research on Inversion Models for Forest Height Estimation Using Polarimetric SAR Interferometry

NASA Astrophysics Data System (ADS)

Zhang, L.; Duan, B.; Zou, B.

2017-09-01

The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can't estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.

Operational shoreline mapping with high spatial resolution radar and geographic processing

USGS Publications Warehouse

Rangoonwala, Amina; Jones, Cathleen E; Chi, Zhaohui; Ramsey, Elijah W.

2017-01-01

A comprehensive mapping technology was developed utilizing standard image processing and available GIS procedures to automate shoreline identification and mapping from 2 m synthetic aperture radar (SAR) HH amplitude data. The development used four NASA Uninhabited Aerial Vehicle SAR (UAVSAR) data collections between summer 2009 and 2012 and a fall 2012 collection of wetlands dominantly fronted by vegetated shorelines along the Mississippi River Delta that are beset by severe storms, toxic releases, and relative sea-level rise. In comparison to shorelines interpreted from 0.3 m and 1 m orthophotography, the automated GIS 10 m alongshore sampling found SAR shoreline mapping accuracy to be ±2 m, well within the lower range of reported shoreline mapping accuracies. The high comparability was obtained even though water levels differed between the SAR and photography image pairs and included all shorelines regardless of complexity. The SAR mapping technology is highly repeatable and extendable to other SAR instruments with similar operational functionality.

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

NASA Astrophysics Data System (ADS)

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.

Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm

NASA Astrophysics Data System (ADS)

Zhang, Siqian; Kuang, Gangyao

2014-10-01

In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area

USGS Publications Warehouse

Stephenson, William J.; Odum, Jackson K.; Wicks, Chuck; Pratt, Thomas L.; Blakely, Richard J.

2016-01-01

In 2001, a rare swarm of small, shallow earthquakes beneath the city of Spokane, Washington, caused ground shaking as well as audible booms over a five‐month period. Subsequent Interferometric Synthetic Aperture Radar (InSAR) data analysis revealed an area of surface uplift in the vicinity of the earthquake swarm. To investigate the potential faults that may have caused both the earthquakes and the topographic uplift, we collected ∼3  km of high‐resolution seismic‐reflection profiles to image the upper‐source region of the swarm. The two profiles reveal a complex deformational pattern within Quaternary alluvial, fluvial, and flood deposits, underlain by Tertiary basalts and basin sediments. At least 100 m of arching on a basalt surface in the upper 500 m is interpreted from both the seismic profiles and magnetic modeling. Two west‐dipping faults deform Quaternary sediments and project to the surface near the location of the Spokane fault defined from modeling of the InSAR data.

InSAR Surface Deformation and Source Modelling at Semisopochnoi Island During the 2014 and 2015 Seismic Swarms with Constraints from Geochemical and Seismic Analysis

NASA Astrophysics Data System (ADS)

DeGrandpre, K.; Pesicek, J. D.; Lu, Z.

2017-12-01

During the summer of 2014 and the early spring of 2015 two notable increases in seismic activity at Semisopochnoi Island in the western Aleutian islands were recorded on AVO seismometers on Semisopochnoi and neighboring islands. These seismic swarms did not lead to an eruption. This study employs interferometric synthetic aperture radar (InSAR) techniques using TerraSAR-X images in conjunction with more accurately relocating the recorded seismic events through simultaneous inversion of event travel times and a three-dimensional velocity model using tomoDD. The InSAR images exhibit surprising coherence and an island wide spatial distribution of inflation that is then used in Mogi, Okada, spheroid, and ellipsoid source models in order to define the three-dimensional location and volume change required for a source at the volcano to produce the observed surface deformation. The tomoDD relocations provide a more accurate and realistic three-dimensional velocity model as well as a tighter clustering of events for both swarms that clearly outline a linear seismic void within the larger group of shallow (<10 km) seismicity. The source models are fit to this void and pressure estimates from geochemical analysis are used to verify the storage depth of magmas at Semisopochnoi. Comparisons of calculated source cavity, magma injection, and surface deformation volumes are made in order to assess the reality behind the various modelling estimates. Incorporating geochemical and seismic data to provide constraints on surface deformation source inversions provides an interdisciplinary approach that can be used to make more accurate interpretations of dynamic observations.

On the appropriate feature for general SAR image registration

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yunhua

2012-09-01

An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed, the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation, and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for general SAR image registration.

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

PubMed

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

2012-10-01

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. Copyright © 2012 Elsevier Ltd. All rights reserved.

Pancake Ice Thickness Mapping in the Beaufort Sea From Wave Dispersion Observed in SAR Imagery

NASA Astrophysics Data System (ADS)

Wadhams, P.; Aulicino, G.; Parmiggiani, F.; Persson, P. O. G.; Holt, B.

2018-03-01

The early autumn voyage of RV Sikuliaq to the southern Beaufort Sea in 2015 offered very favorable opportunities for observing the properties and thicknesses of frazil-pancake ice types. The operational region was overlaid by a dense network of retrieved satellite imagery, including synthetic aperture radar (SAR) imagery from Sentinel-1 and COSMO-SkyMed (CSK). This enabled us to fully test and apply the SAR-waves technique, first developed by Wadhams and Holt (1991), for deriving the thickness of frazil-pancake icefields from changed wave dispersion. A line of subimages from a main SAR image (usually CSK) is analyzed running into the ice along the main wave direction. Each subimage is spectrally analyzed to yield a wave number spectrum, and the change in the shape of the spectrum between open water and ice, or between two thicknesses of ice, is interpreted in terms of the viscous equations governing wave propagation in frazil-pancake ice. For each of the case studies considered here, there was good or acceptable agreement on thickness between the extensive in situ observations and the SAR-wave calculation. In addition, the SAR-wave analysis gave, parametrically, effective viscosities for the ice covering a consistent and narrow range of 0.03-0.05 m2 s-1.

Robust flood area detection using a L-band synthetic aperture radar: Preliminary application for Florida, the U.S. affected by Hurricane Irma

NASA Astrophysics Data System (ADS)

Nagai, H.; Ohki, M.; Abe, T.

2017-12-01

Urgent crisis response for a hurricane-induced flood needs urgent providing of a flood map covering a broad region. However, there is no standard threshold values for automatic flood identification from pre-and-post images obtained by satellite-based synthetic aperture radars (SARs). This problem could hamper prompt data providing for operational uses. Furthermore, one pre-flood SAR image does not always represent potential water surfaces and river flows especially in tropical flat lands which are greatly influenced by seasonal precipitation cycle. We are, therefore, developing a new method of flood mapping using PALSAR-2, an L-band SAR, which is less affected by temporal surface changes. Specifically, a mean-value image and a standard-deviation image are calculated from a series of pre-flood SAR images. It is combined with a post-flood SAR image to obtain normalized backscatter amplitude difference (NoBADi), with which a difference between a post-flood image and a mean-value image is divided by a standard-deviation image to emphasize anomalous water extents. Flooding areas are then automatically obtained from the NoBADi images as lower-value pixels avoiding potential water surfaces. We applied this method to PALSAR-2 images acquired on Sept. 8, 10, and 12, 2017, covering flooding areas in a central region of Dominican Republic and west Florida, the U.S. affected by Hurricane Irma. The output flooding outlines are validated with flooding areas manually delineated from high-resolution optical satellite images, resulting in higher consistency and less uncertainty than previous methods (i.e., a simple pre-and-post flood difference and pre-and-post coherence changes). The NoBADi method has a great potential to obtain a reliable flood map for future flood hazards, not hampered by cloud cover, seasonal surface changes, and "casual" thresholds in the flood identification process.

A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

2012-10-01

This paper introduces an automatic flood mapping application that is hosted on the Grid Processing on Demand (GPOD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver operationally flooded areas using both recent and historical acquisitions of SAR data. Having as a short-term target the flooding-related exploitation of data generated by the upcoming ESA SENTINEL-1 SAR mission, the flood mapping application consists of two building blocks: i) a set of query tools for selecting the "crisis image" and the optimal corresponding "reference image" from the G-POD archive and ii) an algorithm for extracting flooded areas via change detection using the previously selected "crisis image" and "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 reference image. Potential users will also be able to apply the implemented flood delineation algorithm. The latter combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. Both algorithms are computationally efficient and operate with minimum data requirements. The case study of the high magnitude flooding event that occurred in July 2007 on the Severn River, UK, and that was observed with a moderateresolution SAR sensor as well as airborne photography highlights the performance of the proposed online application. The flood mapping application on G-POD can be used sporadically, i.e. whenever a major flood event occurs and there is a demand for SAR-based flood extent maps. In the long term, a potential extension of the application could consist in systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis.

Tracking lava flow emplacement on the east rift zone of Kilauea, Hawai’i with synthetic aperture radar (SAR) coherence

USGS Publications Warehouse

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.

A new implementation of full resolution SBAS-DInSAR processing chain for the effective monitoring of structures and infrastructures

NASA Astrophysics Data System (ADS)

Bonano, Manuela; Buonanno, Sabatino; Ojha, Chandrakanta; Berardino, Paolo; Lanari, Riccardo; Zeni, Giovanni; Manunta, Michele

2017-04-01

The advanced DInSAR technique referred to as Small BAseline Subset (SBAS) algorithm has already largely demonstrated its effectiveness to carry out multi-scale and multi-platform surface deformation analyses relevant to both natural and man-made hazards. Thanks to its capability to generate displacement maps and long-term deformation time series at both regional (low resolution analysis) and local (full resolution analysis) spatial scales, it allows to get more insights on the spatial and temporal patterns of localized displacements relevant to single buildings and infrastructures over extended urban areas, with a key role in supporting risk mitigation and preservation activities. The extensive application of the multi-scale SBAS-DInSAR approach in many scientific contexts has gone hand in hand with new SAR satellite mission development, characterized by different frequency bands, spatial resolution, revisit times and ground coverage. This brought to the generation of huge DInSAR data stacks to be efficiently handled, processed and archived, with a strong impact on both the data storage and the computational requirements needed for generating the full resolution SBAS-DInSAR results. Accordingly, innovative and effective solutions for the automatic processing of massive SAR data archives and for the operational management of the derived SBAS-DInSAR products need to be designed and implemented, by exploiting the high efficiency (in terms of portability, scalability and computing performances) of the new ICT methodologies. In this work, we present a novel parallel implementation of the full resolution SBAS-DInSAR processing chain, aimed at investigating localized displacements affecting single buildings and infrastructures relevant to very large urban areas, relying on different granularity level parallelization strategies. The image granularity level is applied in most steps of the SBAS-DInSAR processing chain and exploits the multiprocessor systems with distributed memory. Moreover, in some processing steps very heavy from the computational point of view, the Graphical Processing Units (GPU) are exploited for the processing of blocks working on a pixel-by-pixel basis, requiring strong modifications on some key parts of the sequential full resolution SBAS-DInSAR processing chain. GPU processing is implemented by efficiently exploiting parallel processing architectures (as CUDA) for increasing the computing performances, in terms of optimization of the available GPU memory, as well as reduction of the Input/Output operations on the GPU and of the whole processing time for specific blocks w.r.t. the corresponding sequential implementation, particularly critical in presence of huge DInSAR datasets. Moreover, to efficiently handle the massive amount of DInSAR measurements provided by the new generation SAR constellations (CSK and Sentinel-1), we perform a proper re-design strategy aimed at the robust assimilation of the full resolution SBAS-DInSAR results into the web-based Geonode platform of the Spatial Data Infrastructure, thus allowing the efficient management, analysis and integration of the interferometric results with different data sources.

Extreme Magnetosphere-Ionosphere Coupling at the Plasmapause: a - In-A Bright SAR Arc

NASA Astrophysics Data System (ADS)

Baumgardner, J.; Wroten, J.; Semeter, J.; Mendillo, M.; Kozyra, J.

2007-05-01

Heat conduction from the ring current - plasmapause interaction region generates high electron temperature within the ionosphere that drive stable auroral red (SAR) arc emission at 6300 A. On the night of 29 October 1991, a SAR arc was observed using an all-sky imager and meridional imaging spectrograph at Millstone Hill. At xxxx UT, the SAR arc was south of Millstone at approximate L = 2 and reached emission levels of 13,000 rayleighs (R). Over two solar cycle of imaging observations have been made at Millstone Hill, and SAR arc brightness levels (excluding this event) averaged ~ 500 R. Simultaneous observations using the incoherent scatter radar (ISR), a DMSP satellite pass, the MSIS neutral atmosphere and SAR arc modeling using the Rees and Roble formalism succeeded in simulations of the observed emission. The reason for the unusual brightness was not the extreme temperatures achieved (and therefore heat conduction input), but the fact that the end of the plasmapause field line where the elevated Te values were measured did not occur in the ionospheric trough, but equatorward of it, thereby having far more ambient electrons to heat and subsequently collide with atomic oxygen. This unusual spatial geometry probably resulted from unusual convection patterns early in a superstorm scenario.

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell

PubMed Central

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-García, Mateo; Dorta-Naranjo, Blas-Pablo

2008-01-01

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar. PMID:27879884

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell.

PubMed

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-Garcia, Mateo; Dorta-Naranjo, Blas-Pablo

2008-05-23

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar.

SAR Image Change Detection Based on Fuzzy Markov Random Field Model

NASA Astrophysics Data System (ADS)

Zhao, J.; Huang, G.; Zhao, Z.

2018-04-01

Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels. So the change detection results are susceptible to image noise, and the detection effect is not ideal. Markov Random Field (MRF) can make full use of the spatial dependence of image pixels and improve detection accuracy. When segmenting the difference image, different categories of regions have a high degree of similarity at the junction of them. It is difficult to clearly distinguish the labels of the pixels near the boundaries of the judgment area. In the traditional MRF method, each pixel is given a hard label during iteration. So MRF is a hard decision in the process, and it will cause loss of information. This paper applies the combination of fuzzy theory and MRF to the change detection of SAR images. The experimental results show that the proposed method has better detection effect than the traditional MRF method.

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

NASA Astrophysics Data System (ADS)

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.

Analysis of wind and wave events at the MIZ based on TerraSAR-X satellite images

NASA Astrophysics Data System (ADS)

Gebhardt, Claus; Bidlot, Jean-Raymond; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey; Singha, Suman

2017-04-01

The seasonal opening-up of large expanses of open water in the Beaufort/Chukchi Sea is a phenomenon observed in recent years. The diameter of the open-water area is on the order of 1000 km around the sea ice minimum in summer. Thus, wind events in the area are accompanied by the build-up of sea waves. Significant wave heights of few to several meters may be reached. Under low to moderate winds, the morphology of the MIZ is governed by oceanic forcing. As a result, the MIZ resembles ocean circulation features such as eddies, meanders, etc.. In the case of strong wind events, however, the wind forcing may gain control. We analyse effects related to wind and wave events at the MIZ using TerraSAR-X satellite imagery. Methods such as the retrieval of sea state and wind data by empirical algorithms and automatic sea ice classification are applied. This is facilitated by a series of TerraSAR-X images acquired in support of a cruise of the research vessel R/V Sikuliaq in the Beaufort/Chukchi Sea in autumn 2015. For selected images, the results are presented and compared to numerical model forecasts which were as well part of the cruise support.

Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat) and Correlation of Optical (Spot5 and Aerial) Images

PubMed Central

Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc

2009-01-01

Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured. PMID:22389620

Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat) and Correlation of Optical (Spot5 and Aerial) Images.

PubMed

Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc

2009-01-01

Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C-band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr(-1) was measured.

Airborne Multi-Band SAR in the Arctic

NASA Astrophysics Data System (ADS)

Gardner, J. M.; Brozena, J. M.; Liang, R.; Ball, D.; Holt, B.; Thomson, J.

2016-12-01

As one component of the Office of Naval Research supported Sea State Departmental Research Initiative during October of 2015 the Naval Research Laboratory flew an ultrawide-band, low-frequency, polarimetric SAR over the southward advancing sea ice in Beaufort Sea. The flights were coordinated with the research team aboard the R/V Sikuliaq working near and in the advancing pack ice. The majority of the SAR data were collected with the L-Band sensor (1000-1500 MHz) from an altitude of 10,000', providing a useful swath 6 km wide with 75o and 25 o angles of incidence at the inner and outer edge of the swath respectively. Some data were also collected with the P-Band SAR (215-915 MHz). The extremely large bandwidths allowed for formation of image pixels as small as 30 cm, however, we selected 60 cm pixel size to reduce image speckle. The separate polarimetric images are calibrated to one pixel to allow for calculations such as polarimetric decompositions that require the images to be well aligned. Both frequencies are useful particularly for the detection of ridges and areas of deformed ice. There are advantages and disadvantages to airborne SAR imagery compared to satellites. The chief advantages being the enormous allowable bandwidth leading to very fine range resolution, and the ability to fly arbitrary trajectories on demand. The latter permits specific areas to be imaged at a given time with a specified illumination direction. An area can even be illuminated from all directions by flying a circular trajectory around the target area. This captures ice features that are sensitive to illumination direction such as cracks, sastrugi orientation, and ridges. The disadvantages include variation of intensity across the swath with range and incidence angle. In addition to the SAR data, we collected photogrammetric imagery from a DSS-439, scanning lidar from a Riegl Q560 and surface brightness temperatures from a KT-19. However, since all of these sensors are nadir pointing, and some restricted to relatively low-altitude, it was difficult to obtain data co-registered with the SAR. At this meeting we will present some initial results from the SAR imagery, including differentiation of young, thin, and older ice features, and comparisons with satellite SAR with L-band and C-band frequencies.

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

1982-01-01

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Frequency Diversity for Improving Synthetic Aperture Radar Imaging

DTIC Science & Technology

2009-03-01

for broadside spotlight SAR imaging is shown to be δθ = λ 4Yo . (2.34) When θ is small, as is often the case in spotlight SAR imaging, the required...maximum distance ∆y between samples along the y-axis is shown to be ∆y ≤ λRc 4Yo . (2.35) With platform velocity vy along the y-axis, the minimum PRF is

Application of Satellite SAR for Discovery and Quantification of Natural Marine Oil Seeps

NASA Astrophysics Data System (ADS)

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. These data can be used to estimate the magnitude of discharge and the flow rates. A second goal is to distinguish the ends of the slicks proximal to the seafloor sources. These results can be used to eventually census the number of active seeps in the entire Gulf of Mexico basin. Finally, successful automation to map active seep locations and delineate slicks lays the foundation for a satellite-based monitoring system to detect oil pollution events throughout the Gulf.

Multitemporal Observations of Sugarcane by TerraSAR-X Images

PubMed Central

Baghdadi, Nicolas; Cresson, Rémi; Todoroff, Pierre; Moinet, Soizic

2010-01-01

The objective of this study is to investigate the potential of TerraSAR-X (X-band) in monitoring sugarcane growth on Reunion Island (located in the Indian Ocean). Multi-temporal TerraSAR data acquired at various incidence angles (17°, 31°, 37°, 47°, 58°) and polarizations (HH, HV, VV) were analyzed in order to study the behaviour of SAR (synthetic aperture radar) signal as a function of sugarcane height and NDVI (Normalized Difference Vegetation Index). The potential of TerraSAR for mapping the sugarcane harvest was also studied. Radar signal increased quickly with crop height until a threshold height, which depended on polarization and incidence angle. Beyond this threshold, the signal increased only slightly, remained constant, or even decreased. The threshold height is slightly higher with cross polarization and higher incidence angles (47° in comparison with 17° and 31°). Results also showed that the co-polarizations channels (HH and VV) were well correlated. High correlation between SAR signal and NDVI calculated from SPOT-4/5 images was observed. TerraSAR data showed that after strong rains the soil contribution to the backscattering of sugarcane fields can be important for canes with heights of terminal visible dewlap (htvd) less than 50 cm (total cane heights around 155 cm). This increase in radar signal after strong rains could involve an ambiguity between young and mature canes. Indeed, the radar signal on TerraSAR images acquired in wet soil conditions could be of the same order for fields recently harvested and mature sugarcane fields, making difficult the detection of cuts. Finally, TerraSAR data at high spatial resolution were shown to be useful for monitoring sugarcane harvest when the fields are of small size or when the cut is spread out in time. The comparison between incidence angles of 17°, 37° and 58° shows that 37° is more suitable to monitor the sugarcane harvest. The cut is easily detectable on TerraSAR images for data acquired less than two or three months after the cut. The radar signal decreases about 5dB for images acquired some days after the cut and 3 dB for data acquired two month after the cut (VV-37°). The difference in radar signal becomes negligible (<1 dB) between harvested fields and mature canes for sugarcane harvested since three months or more. PMID:22163387

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Space Radar Image of Manaus, Brazil

NASA Technical Reports Server (NTRS)

1999-01-01

These two images were created using data from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). On the left is a false-color image of Manaus, Brazil acquired April 12, 1994, onboard space shuttle Endeavour. In the center of this image is the Solimoes River just west of Manaus before it combines with the Rio Negro to form the Amazon River. The scene is around 8 by 8 kilometers (5 by 5 miles) with north toward the top. The radar image was produced in L-band where red areas correspond to high backscatter at HH polarization, while green areas exhibit high backscatter at HV polarization. Blue areas show low backscatter at VV polarization. The image on the right is a classification map showing the extent of flooding beneath the forest canopy. The classification map was developed by SIR-C/X-SAR science team members at the University of California,Santa Barbara. The map uses the L-HH, L-HV, and L-VV images to classify the radar image into six categories: Red flooded forest Green unflooded tropical rain forest Blue open water, Amazon river Yellow unflooded fields, some floating grasses Gray flooded shrubs Black floating and flooded grasses Data like these help scientists evaluate flood damage on a global scale. Floods are highly episodic and much of the area inundated is often tree-covered. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.v. (DLR), the major partner in science, operations and data processing of X-SAR.

Space Radar Image Isla Isabela in 3-D

NASA Technical Reports Server (NTRS)

1999-01-01

This is a three-dimensional view of Isabela, one of the Galapagos Islands located off the western coast of Ecuador, South America. This view was constructed by overlaying a Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) image on a digital elevation map produced by TOPSAR, a prototype airborne interferometric radar which produces simultaneous image and elevation data. The vertical scale in this image is exaggerated by a factor of 1.87. The SIR-C/X-SAR image was taken on the 40th orbit of space shuttle Endeavour. The image is centered at about 0.5 degree south latitude and 91 degrees west longitude and covers an area of 75 by 60 kilometers (47 by 37 miles). The radar incidence angle at the center of the image is about 20 degrees. The western Galapagos Islands, which lie about 1,200 kilometers (750 miles)west of Ecuador in the eastern Pacific, have six active volcanoes similar to the volcanoes found in Hawaii and reflect the volcanic processes that occur where the ocean floor is created. Since the time of Charles Darwin's visit to the area in 1835, there have been more than 60 recorded eruptions on these volcanoes. This SIR-C/X-SAR image of Alcedo and Sierra Negra volcanoes shows the rougher lava flows as bright features, while ash deposits and smooth pahoehoe lava flows appear dark. Vertical exaggeration of relief is a common tool scientists use to detect relationships between structure (for example, faults, and fractures) and topography. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI).

Analysis of Ground Displacements in Taipei Area by Using High Resolution X-band SAR Interferometry

NASA Astrophysics Data System (ADS)

Tung, H.; Chen, H. Y.; Hu, J. C.

2014-12-01

Located at the northern part of Taiwan, Taipei is the most densely populated city and the center of politic, economic, and culture of this island. North of the Taipei basin, the active Tatun volcano group with the eruptive potential to devastate the entire Taipei is only 15 km away from the capital Taipei. Furthermore, the active Shanchiao fault located in the western margin of Taipei basin. Therefore, it is not only an interesting scientific topic but also a strong social impact to better understand the assessment and mitigation of geological hazard in the metropolitan Taipei city. In this study, we use 12 high resolution X-band SAR images from the new generation COSMO-SkyMed (CSK) constellation for associating with leveling and GPS data to monitor surface deformation around the Shanchiao fault and the Tatun volcano group. The stripmap mode of CSK SAR images provides spatial resolution of 3 m x 3 m, which is one order of magnitude better than the previous available satellite SAR data. Furthermore, the more frequent revisit of the same Area of Interest (AOI) of the present X-band missions provides massive datasets to avoid the baseline limitation and temporal decorrelation to improve the temporal resolution of deformation in time series. After transferring the GPS vectors and leveling data to the LOS direction by referring to continuous GPS station BANC, the R square between PS velocities and GPS velocities is approximate to 0.9, which indicates the high reliability of our PSInSAR result. In addition, the well-fitting profiles between leveling data and PSInSAR result along two leveling routes both demonstrate that the significant deformation gradient mainly occurs along the Shanchiao fault. The severe land subsidence area is located in the western part of Taipei basin just next to the Shanchiao fault with a maximum of SRD rate of 30 mm/yr. However, the severe subsidence area, Wuku, is also one industrial area in Taipei which could be attributed to anthropogenic effect. In the future, we will use all available images to monitor the temporal and spatial variation in deformation to better understand the activity of the Shanchiao fault.

Evaluating suitability of Pol-SAR (TerraSAR-X, Radarsat-2) for automated sea ice classification

NASA Astrophysics Data System (ADS)

Ressel, Rudolf; Singha, Suman; Lehner, Susanne

2016-05-01

Satellite borne SAR imagery has become an invaluable tool in the field of sea ice monitoring. Previously, single polarimetric imagery were employed in supervised and unsupervised classification schemes for sea ice investigation, which was preceded by image processing techniques such as segmentation and textural features. Recently, through the advent of polarimetric SAR sensors, investigation of polarimetric features in sea ice has attracted increased attention. While dual-polarimetric data has already been investigated in a number of works, full-polarimetric data has so far not been a major scientific focus. To explore the possibilities of full-polarimetric data and compare the differences in C- and X-bands, we endeavor to analyze in detail an array of datasets, simultaneously acquired, in C-band (RADARSAT-2) and X-band (TerraSAR-X) over ice infested areas. First, we propose an array of polarimetric features (Pauli and lexicographic based). Ancillary data from national ice services, SMOS data and expert judgement were utilized to identify the governing ice regimes. Based on these observations, we then extracted mentioned features. The subsequent supervised classification approach was based on an Artificial Neural Network (ANN). To gain quantitative insight into the quality of the features themselves (and reduce a possible impact of the Hughes phenomenon), we employed mutual information to unearth the relevance and redundancy of features. The results of this information theoretic analysis guided a pruning process regarding the optimal subset of features. In the last step we compared the classified results of all sensors and images, stated respective accuracies and discussed output discrepancies in the cases of simultaneous acquisitions.

Tracking morphological changes and slope instability using spaceborne and ground-based SAR data

NASA Astrophysics Data System (ADS)

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 delta formation after the 2007 eruption and the lava overflows of 2010 and 2011. After the emplacement of the 2014 lava field, high displacements in the central and northern portions of the SdF were recorded by the GBInSAR device, whereas the spaceborne data were unable to detect these rapid movements. A comparison between IRT images and GBInSAR-derived displacement maps acquired during the same time interval revealed that the observed displacements along the SdF were related to the crumbling of newly emplaced 2014 lava and of its external breccia. Detected slope instability after the 2014 flank eruption was related to lava accumulation on the SdF and to the difference in the material underlying the 2014 lava flow: i) lava flows and breccia layers related to the 2002-03 and 2007 lava flow fields in the northern SdF sector and ii) loose volcaniclastic deposits in the central part of the SdF. This work emphasizes the importance of smart integration of spaceborne, SAR-derived hazard information with permanent-sited, operational monitoring by GBInSAR devices to detect areas impacted by mass wasting and volcanic activity.

Are We Underestimating the Significance of Pedicle Screw Misplacement?

PubMed

Sarwahi, Vishal; Wendolowski, Stephen F; Gecelter, Rachel C; Amaral, Terry; Lo, Yungtai; Wollowick, Adam L; Thornhill, Beverly

2016-05-01

A retrospective review of charts, x-rays (XRs) and computed tomography (CT) scans was performed. To evaluate the accuracy of pedicle screw placement using a novel classification system to determine potentially significant screw misplacement. The accuracy rate of pedicle screw (PS) placement varies from 85% to 95% in the literature. This demonstrates technical ability but does not represent the impact of screw misplacement on individual patients. This study quantifies the rate of screw misplacement on a per-patient basis to highlight its effect on potential morbidity. A retrospective review of charts, XRs and low-dose CT scans of 127 patients who underwent spinal fusion with pedicle screws for spinal deformity was performed. Screws were divided into four categories: screws at risk (SAR), indeterminate misplacements (IMP), benign misplacements (BMP), accurately placed (AP). A total of 2724 screws were placed in 127 patients. A total of 2396 screws were placed accurately (87.96%). A total of 247 screws (9.07%) were BMP, 52 (1.91%) were IMP, and 29 (1.06%) were considered SAR. Per-patient analysis showed 23 (18.11%) of patients had all screws AP. Thirty-five (27.56%) had IMP and 18 (14.17%) had SAR. Risk factor analysis showed smaller Cobb angles increased likelihood of all screws being AP. Sub-analysis of adolescent idiopathic scoliotic patients showed no curve or patient characteristic that correlated with IMP or SAR. Over 40% of patients had screws with either some/major concern. Overall reported screw misplacement is low, but it does not reflect the potential impact on patient morbidity. Per-patient analysis reveals more concerning numbers toward screw misplacement. With increasing pedicle screw usage, the number of patients with misplaced screws will likely increase proportionally. Better strategies need to be devised for evaluation of screw placement, including establishment of a national database of deformity surgery, use of intra-operative image guidance, and reevaluation of postoperative low-dose CT imaging. 3.

Classification of fully polarimetric F-SAR ( X / S ) airborne radar images using decomposition methods. (Polish Title: Klasyfikacja treści polarymetrycznych obrazów radarowych z wykorzystaniem metod dekompozycji na przykładzie systemu F-SAR ( X / S ))

NASA Astrophysics Data System (ADS)

Mleczko, M.

2014-12-01

Polarimetric SAR data is not widely used in practice, because it is not yet available operationally from the satellites. Currently we can distinguish two approaches in POL - In - SAR technology: alternating polarization imaging (Alt - POL) and fully polarimetric (QuadPol). The first represents a subset of another and is more operational, while the second is experimental because classification of this data requires polarimetric decomposition of scattering matrix in the first stage. In the literature decomposition process is divided in two types: the coherent and incoherent decomposition. In this paper the decomposition methods have been tested using data from the high resolution airborne F - SAR system. Results of classification have been interpreted in the context of the land cover mapping capabilities

Complex phase error and motion estimation in synthetic aperture radar imaging

NASA Astrophysics Data System (ADS)

Soumekh, M.; Yang, H.

1991-06-01

Attention is given to a SAR wave equation-based system model that accurately represents the interaction of the impinging radar signal with the target to be imaged. The model is used to estimate the complex phase error across the synthesized aperture from the measured corrupted SAR data by combining the two wave equation models governing the collected SAR data at two temporal frequencies of the radar signal. The SAR system model shows that the motion of an object in a static scene results in coupled Doppler shifts in both the temporal frequency domain and the spatial frequency domain of the synthetic aperture. The velocity of the moving object is estimated through these two Doppler shifts. It is shown that once the dynamic target's velocity is known, its reconstruction can be formulated via a squint-mode SAR geometry with parameters that depend upon the dynamic target's velocity.

Development of Oil Spill Monitoring System for the Black Sea, Caspian Sea and the Barents/Kara Seas (DEMOSS)

NASA Astrophysics Data System (ADS)

Sandven, Stein; Kudriavtsev, Vladimir; Malinovsky, Vladimir; Stanovoy, Vladimir

2008-01-01

DEMOSS will develop and demonstrate elements of a marine oil spill detection and prediction system based on satellite Synthetic Aperture Radar (SAR) and other space data. In addition, models for prediction of sea surface pollution drift will be developed and tested. The project implements field experiments to study the effect of artificial crude oil and oil derivatives films on short wind waves and multi-frequency (Ka-, Ku-, X-, and C-band) dual polarization radar backscatter power and Doppler shift at different wind and wave conditions. On the basis of these and other available experimental data, the present model of short wind waves and radar scattering will be improved and tested.A new approach for detection and quantification of the oil slicks/spills in satellite SAR images is developed that can discriminate human oil spills from biogenic slicks and look-alikes in the SAR images. New SAR images are obtained in coordination with the field experiments to test the detection algorithm. Satellite SAR images from archives as well as from new acquisitions will be analyzed for the Black/Caspian/Kara/Barents seas to investigate oil slicks/spills occurrence statistics.A model for oil spills/slicks transport and evolution is developed and tested in ice-infested arctic seas, including the Caspian Sea. Case studies using the model will be conducted to simulate drift and evolution of oil spill events observed in SAR images. The results of the project will be disseminated via scientific publications and by demonstration to users and agencies working with marine monitoring. The project lasts for two years (2007 - 2009) and is funded under INTAS Thematic Call with ESA 2006.

Monitoring of urban subsidence with SAR interferometric point target analysis: A case study in Suzhou, China

NASA Astrophysics Data System (ADS)

Zhang, Yonghong; Zhang, Jixian; Wu, Hongan; Lu, Zhong; Guangtong, Sun

2011-10-01

Ground subsidence, mainly caused by over exploitation of groundwater and other underground resources, such as oil, gas and coal, occurs in many cities in China. The annual direct loss associated with subsidence across the country is estimated to exceed 100 million US dollar. Interferometric SAR (InSAR) is a powerful tool to map ground deformation at an unprecedented level of spatial detail. It has been widely used to investigate the deformation resulting from earthquakes, volcanoes and subsidence. Repeat-pass InSAR, however, may fail due to impacts of spatial decorrelation, temporal decorrelation and heterogeneous refractivity of atmosphere. In urban areas, a large amount of natural stable radar reflectors exists, such as buildings and engineering structures, at which radar signals can remain coherent during a long time interval. Interferometric point target analysis (IPTA) technique, also known as persistent scatterers (PS) InSAR is based on these reflectors. It overcomes the shortfalls in conventional InSAR. This paper presents a procedure for urban subsidence monitoring with IPTA. Calculation of linear deformation rate and height residual, and the non-linear deformation estimate, respectively, are discussed in detail. Especially, the former is highlighted by a novel and easily implemented 2-dimensional spatial search algorithm. Practically useful solutions that can significantly improve the robustness of IPTA, are recommended. Finally, the proposed procedure is applied to mapping the ground subsidence in Suzhou city, Jiangsu province, China. Thirty-four ERS-1/2 SAR scenes are analyzed, and the deformation information over 38,881 point targets between 1992 and 2000 are generated. The IPTA-derived deformation estimates correspond well with leveling measurements, demonstrating the potential of the proposed subsidence monitoring procedure based on IPTA technique. Two shortcomings of the IPTA-based procedure, e.g., the requirement of large number of SAR images and assumed linear plus non-linear deformation model, are discussed as the topics of further research.

NASA Administrator Sean O'Keefe speaking at the AirSAR 2004 Mesoamerica hangar naming ceremony

NASA Image and Video Library

2004-03-03

NASA Administrator Sean O'Keefe speaking at the AirSAR 2004 Mesoamerica hangar naming ceremony. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.

David Bushman at the Mission Manager's console onboard NASA's DC-8 during the AirSAR 2004 campaign

NASA Image and Video Library

2004-03-03

David Bushman at the Mission Manager's console onboard NASA's DC-8 during the AirSAR 2004 campaign. AirSAR 2004 is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.

Using SAR satellite data time series for regional glacier mapping

NASA Astrophysics Data System (ADS)

Winsvold, Solveig H.; Kääb, Andreas; Nuth, Christopher; Andreassen, Liss M.; van Pelt, Ward J. J.; Schellenberger, Thomas

2018-03-01

With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

Comparison of Interferometric Time-Series Analysis Techniques with Implications for Future Mission Design

NASA Astrophysics Data System (ADS)

Werner, C. L.; Wegmuller, U.; Strozzi, T.; Wiesmann, A.

2006-12-01

Principle contributors to the noise in differential SAR interferograms are temporal phase stability of the surface, geometry relating to baseline and surface slope, and propagation path delay variations due to tropospheric water vapor and the ionosphere. Time series analysis of multiple interferograms generated from a stack of SAR SLC images seeks to determine the deformation history of the surface while reducing errors. Only those scatterers within a resolution element that are stable and coherent for each interferometric pair contribute to the desired deformation signal. Interferograms with baselines exceeding 1/3 the critical baseline have substantial geometrical decorrelation for distributed targets. Short baseline pairs with multiple reference scenes can be combined using least-squares estimation to obtain a global deformation solution. Alternately point-like persistent scatterers can be identified in scenes that do not exhibit geometrical decorrelation associated with large baselines. In this approach interferograms are formed from a stack of SAR complex images using a single reference scene. Stable distributed scatter pixels are excluded however due to the presence of large baselines. We apply both point- based and short-baseline methodologies and compare results for a stack of fine-beam Radarsat data acquired in 2002-2004 over a rapidly subsiding oil field near Lost Hills, CA. We also investigate the density of point-like scatters with respect to image resolution. The primary difficulty encountered when applying time series methods is phase unwrapping errors due to spatial and temporal gaps. Phase unwrapping requires sufficient spatial and temporal sampling. Increasing the SAR range bandwidth increases the range resolution as well as increasing the critical interferometric baseline that defines the required satellite orbital tube diameter. Sufficient spatial sampling also permits unwrapping because of the reduced phase/pixel gradient. Short time intervals further reduce the differential phase due to deformation when the deformation is continuous. Lower frequency systems (L- vs. C-Band) substantially improve the ability to unwrap the phase correctly by directly reducing both interferometric phase amplitude and temporal decorrelation.

Space Radar Image of Manaus region of Brazil

NASA Technical Reports Server (NTRS)

1994-01-01

These L-band images of the Manaus region of Brazil were acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour. The left image was acquired on April 12, 1994, and the middle image was acquired on October 3, 1994. The area shown is approximately 8 kilometers by 40 kilometers (5 miles by 25 miles). The two large rivers in this image, the Rio Negro (top) and the Rio Solimoes (bottom), combine at Manaus (west of the image) to form the Amazon River. The image is centered at about 3 degrees south latitude and 61 degrees west longitude. North is toward the top left of the images. The differences in brightness between the images reflect changes in the scattering of the radar channel. In this case, the changes are indicative of flooding. A flooded forest has a higher backscatter at L-band (horizontally transmitted and received) than an unflooded river. The extent of the flooding is much greater in the April image than in the October image, and corresponds to the annual, 10-meter (33-foot) rise and fall of the Amazon River. A third image at right shows the change in the April and October images and was created by determining which areas had significant decreases in the intensity of radar returns. These areas, which appear blue on the third image at right, show the dramatic decrease in the extent of flooded forest, as the level of the Amazon River falls. The flooded forest is a vital habitat for fish and floating meadows are an important source of atmospheric methane. This demonstrates the capability of SIR-C/X-SAR to study important environmental changes that are impossible to see with optical sensors over regions such as the Amazon, where frequent cloud cover and dense forest canopies obscure monitoring of floods. Field studies by boat, on foot and in low-flying aircraft by the University of California at Santa Barbara, in collaboration with Brazil's Instituto Nacional de Pesguisas Estaciais, during the first and second flights of the SIR-C/X-SAR system have validated the interpretation of the radar images. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR.

A data compression technique for synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Minden, G. J.

1986-01-01

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

A Study on PolInSAR Coherence Based Regression Analysis of Forest Biomass (BARKOT Reserve Forest India), Using RADARSAT-2 Datasets

NASA Astrophysics Data System (ADS)

Singh, J.; Kumar, S.; Kushwaha, S. P. S.

2015-04-01

Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components

Software For Calibration Of Polarimetric SAR Data

NASA Technical Reports Server (NTRS)

Van Zyl, Jakob; Zebker, Howard; Freeman, Anthony; Holt, John; Dubois, Pascale; Chapman, Bruce

1994-01-01

POLCAL (Polarimetric Radar Calibration) software tool intended to assist in calibration of synthetic-aperture radar (SAR) systems. In particular, calibrates Stokes-matrix-format data produced as standard product by NASA/Jet Propulsion Laboratory (JPL) airborne imaging synthetic aperture radar (AIRSAR). Version 4.0 of POLCAL is upgrade of version 2.0. New options include automatic absolute calibration of 89/90 data, distributed-target analysis, calibration of nearby scenes with corner reflectors, altitude or roll-angle corrections, and calibration of errors introduced by known topography. Reduces crosstalk and corrects phase calibration without use of ground calibration equipment. Written in FORTRAN 77.

Detection of Sea Ice and Open Water from RADARSAT-2 Images for Data Assimilation

NASA Astrophysics Data System (ADS)

Komarov, A.; Buehner, M.

2016-12-01

Automated detection of sea ice and open water from SAR data is very important for further assimilation into coupled ocean-sea ice-atmosphere numerical models, such as the Regional Ice-Ocean Prediction System being implemented at the Environment and Climate Change Canada. Conventional classification approaches based on various learning techniques are found to be limited by the fact that they typically do not indicate the level of confidence for ice and water retrievals. Meanwhile, only ice/water retrievals with a very high level of confidence are allowed to be assimilated into the sea ice model to avoid propagating and magnifying errors into the numerical prediction system. In this study we developed a new technique for ice and water detection from dual-polarization RADARSAT-2 HH-HV images which provides the probability of ice/water at a given location. We collected many hundreds of thousands of SAR signatures over various sea ice types (i.e. new, grey, first-year, and multi-year ice) and open water from all available RADARSAT-2 images and the corresponding Canadian Ice Service Image Analysis products over the period from November 2010 to May 2016. Our analysis of the dataset revealed that ice/water separation can be effectively performed in the space of SAR-based variables independent of the incidence angle and noise floor (such as texture measures) and auxiliary Global Environmental Multiscale Model parameters (such as surface wind speed). Choice of the parameters will be specifically discussed in the presentation. An ice probability empirical model as a function of the selected predictors was built in a form of logistic regression, based on the training dataset from 2012 to 2016. The developed ice probability model showed very good performance on the independent testing subset (year 2011). With the ice/water probability threshold of 0.95 reflecting a very high level of confidence, 79% of the testing ice and water samples were classified with the accuracy of 99%. These results are particularly important in light of the upcoming RADARSAT Constellation mission which will drastically increase the amount of SAR data over the Arctic region.

Radar backscatter from the sea: Controlled experiments

NASA Astrophysics Data System (ADS)

Moore, R. K.

1992-04-01

The subwindowing method of modelling synthetic-aperture-radar (SAR) imaging of ocean waves was extended to allow wave propagation in arbitrary directions. Simulated images show that the SAR image response to swells that are imaged by velocity bunching is reduced by random smearing due to wind-generated waves. The magnitude of this response is not accurately predicted by introducing a finite coherence time in the radar backscatter. The smearing does not affect the imaging of waves by surface radar cross-section modulation, and is independent of the wind direction. Adjusting the focus of the SAR processor introduces an offset in the image response of the surface scatters. When adjusted by one-half the azimuthal phase velocity of the wave, this compensates the incoherent advance of the wave being imaged, leading to a higher image contrast. The azimuthal cut-off and range rotation of the spectral peak are predicted when the imaging of wind-generated wave trains is simulated. The simulated images suggest that velocity bunching and azimuthal smearing are strongly interdependent, and cannot be included in a model separately.

Surface Deformation and Source Model at Semisopochnoi Volcano from InSAR and Seismic Analysis During the 2014 and 2015 Seismic Swarms

NASA Astrophysics Data System (ADS)

DeGrandpre, K.; Pesicek, J. D.; Lu, Z.

2016-12-01

During the summer of 2014 and the early spring of 2015 two notable increases in seismic activity at Semisopochnoi volcano in the western Aleutian islands were recorded on AVO seismometers on Semisopochnoi and neighboring islands. These seismic swarms did not lead to an eruption. This study employs differential SAR techniques using TerraSAR-X images in conjunction with more accurately relocating the recorded seismic events through simultaneous inversion of event travel times and a three-dimensional velocity model using tomoDD. The interferograms created from the SAR images exhibit surprising coherence and an island wide spatial distribution of inflation that is then used in a Mogi model in order to define the three-dimensional location and volume change required for a source at Semisopochnoi to produce the observed surface deformation. The tomoDD relocations provide a more accurate and realistic three-dimensional velocity model as well as a tighter clustering of events for both swarms that clearly outline a linear seismic void within the larger group of shallow (<10 km) seismicity. While no direct conclusions as to the relationship of these seismic events and the observed surface deformation can be made at this time, these techniques are both complimentary and efficient forms of remotely monitoring volcanic activity that provide much deeper insights into the processes involved without having to risk hazardous or costly field work.

The Monitoring and Spatial-Temporal Evolution Characteristic Analysis for Land Subsidence in Beijing

NASA Astrophysics Data System (ADS)

Zhou, Q.; Zhao, W.; Yu, J.

2018-05-01

At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can't satisfy the need of aquifer recharge that product the land subsidence. As China's political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June-2010 August and ten TerraSAR images acquired in 2011 June-2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.

Chinese HJ-1C SAR And Its Wind Mapping Capability

NASA Astrophysics Data System (ADS)

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.

Titan's surface from Cassini RADAR SAR and high resolution radiometry data of the first five flybys

USGS Publications Warehouse

Paganelli, F.; Janssen, M.A.; Stiles, B.; West, R.; Lorenz, R.D.; Lunine, J.I.; Wall, S.D.; Callahan, P.; Lopes, R.M.; Stofan, E.; Kirk, R.L.; Johnson, W.T.K.; Roth, L.; Elachi, C.; ,

2007-01-01

The first five Titan flybys with Cassini's Synthetic Aperture RADAR (SAR) and radiometer are examined with emphasis on the calibration and interpretation of the high-resolution radiometry data acquired during the SAR mode (SAR-radiometry). Maps of the 2-cm wavelength brightness temperature are obtained coincident with the SAR swath imaging, with spatial resolution approaching 6 km. A preliminary calibration shows that brightness temperature in these maps varies from 64 to 89 K. Surface features and physical properties derived from the SAR-radiometry maps and SAR imaging are strongly correlated; in general, we find that surface features with high radar reflectivity are associated with radiometrically cold regions, while surface features with low radar reflectivity correlate with radiometrically warm regions. We examined scatterplots of the normalized radar cross-section ??0 versus brightness temperature, finding differing signatures that characterize various terrains and surface features. Implications for the physical and compositional properties of these features are discussed. The results indicate that volume scattering is important in many areas of Titan's surface, particularly Xanadu, while other areas exhibit complex brightness temperature variations consistent with variable slopes or surface material and compositional properties. ?? 2007 Elsevier Inc.

Urban Modelling Performance of Next Generation SAR Missions

NASA Astrophysics Data System (ADS)

Sefercik, U. G.; Yastikli, N.; Atalay, C.

2017-09-01

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.

InSAR observation of the September 3rd nuclear test in North Korea

NASA Astrophysics Data System (ADS)

Wei, M.

2017-12-01

InSAR data from ALOS-2 and Sentinel-1B satellites show significant loss of coherence in phase images covering the September 3rd event at Mt Mantap, which provide strong evidence that the nuclear test occurred there. The area with low coherence is consistent with several seismic-determined locations. The loss of coherence is much more significant than that of the January 6, 2016 event, which also has good InSAR data coverage and show surface displacement. For regions that stay coherent at peripheral area of Mt Mantap, the data show line-of-sight displacement up to 10 cm. In comparison, TerraSAR-X InSAR data (generated by Dr. Teng Wang) show subsidence up to 2 m and horizontal displacement up to 4 m in the area that ALOS2 and Sentinel-1B lost coherence. The large displacement is calculated from the shift of pixels in amplitude images, which does not work for ALOS and Sentinel-1B data. Nevertheless, all InSAR data suggest that the event occurred at Mt Mantap. We conclude that InSAR provides a powerful, independent tool for monitoring and characterizing nuclear tests, whether announced or not, to complement the seismic method.

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

PubMed Central

Zhang, Qianghui; Wu, Junjie; Li, Wenchao; Huang, Yulin; Yang, Jianyu; Yang, Haiguang

2016-01-01

Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR) equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS), which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR) provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP) is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD) based on Stolt interpolation. Finally, a modified TSP (MTSP) is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application. PMID:27472341

Comparison of four moderate-size earthquakes in southern California using seismology and InSAR

USGS Publications Warehouse

Mellors, R.J.; Magistrale, H.; Earle, P.; Cogbill, A.H.

2004-01-01

Source parameters determined from interferometric synthetic aperture radar (InSAR) measurements and from seismic data are compared from four moderate-size (less than M 6) earthquakes in southern California. The goal is to verify approximate detection capabilities of InSAR, assess differences in the results, and test how the two results can be reconciled. First, we calculated the expected surface deformation from all earthquakes greater than magnitude 4 in areas with available InSAR data (347 events). A search for deformation from the events in the interferograms yielded four possible events with magnitudes less than 6. The search for deformation was based on a visual inspection as well as cross-correlation in two dimensions between the measured signal and the expected signal. A grid-search algorithm was then used to estimate focal mechanism and depth from the InSAR data. The results were compared with locations and focal mechanisms from published catalogs. An independent relocation using seismic data was also performed. The seismic locations fell within the area of the expected rupture zone for the three events that show clear surface deformation. Therefore, the technique shows the capability to resolve locations with high accuracy and is applicable worldwide. The depths determined by InSAR agree with well-constrained seismic locations determined in a 3D velocity model. Depth control for well-imaged shallow events using InSAR data is good, and better than the seismic constraints in some cases. A major difficulty for InSAR analysis is the poor temporal coverage of InSAR data, which may make it impossible to distinguish deformation due to different earthquakes at the same location.

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

NASA Astrophysics Data System (ADS)

Pinel, V.; Poland, M. P.; Hooper, A.

2014-12-01

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work - for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

Retrieval of the thickness of undeformed sea ice from C-band compact polarimetric SAR images

NASA Astrophysics Data System (ADS)

Zhang, X.; Dierking, W.; Zhang, J.; Meng, J. M.; Lang, H. T.

2015-10-01

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. The parameter is denoted as "CP-Ratio". In model simulations we investigated the sensitivity of CP-Ratio to the dielectric constant, thickness, surface roughness, and incidence angle. From the results of the simulations we deduced optimal conditions for the thickness retrieval. On the basis of C-band CTLR SAR data, which were generated from Radarsat-2 quad-polarization images acquired jointly with helicopter-borne sea ice thickness measurements in the region of the Sea of Labrador, we tested empirical equations for thickness retrieval. An exponential fit between CP-Ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.92 for the retrieval procedure when applying it on level ice of 0.9 m mean thickness.

[Spatial-temporal evolution characterization of land subsidence by multi-temporal InSAR method and GIS technology].

PubMed

Chen, Bei-Bei; Gong, Hui-Li; Li, Xiao-Juan; Lei, Kun-Chao; Duan, Guang-Yao; Xie, Jin-Rong

2014-04-01

Long-term over-exploitation of underground resources, and static and dynamic load increase year by year influence the occurrence and development of regional land subsidence to a certain extent. Choosing 29 scenes Envisat ASAR images covering plain area of Beijing, China, the present paper used the multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches, and obtained monitoring information of regional land subsidence. Under different situation of space development and utilization, the authors chose five typical settlement areas; With classified information of land-use, multi-spectral remote sensing image, and geological data, and adopting GIS spatial analysis methods, the authors analyzed the time series evolution characteristics of uneven settlement. The comprehensive analysis results suggests that the complex situations of space development and utilization affect the trend of uneven settlement; the easier the situation of space development and utilization, the smaller the settlement gradient, and the less the uneven settlement trend.

Gradient-Modulated SWIFT

PubMed Central

Zhang, Jinjin; Idiyatullin, Djaudat; Corum, Curtis A.; Kobayashi, Naoharu; Garwood, Michael

2017-01-01

Purpose Methods designed to image fast-relaxing spins, such as sweep imaging with Fourier transformation (SWIFT), often utilize high excitation bandwidth and duty cycle, and in some applications the optimal flip angle cannot be used without exceeding safe specific absorption rate (SAR) levels. The aim is to reduce SAR and increase the flexibility of SWIFT by applying time-varying gradient-modulation (GM). The modified sequence is called GM-SWIFT. Theory and Methods The method known as gradient-modulated offset independent adiabaticity was used to modulate the radiofrequency (RF) pulse and gradients. An expanded correlation algorithm was developed for GM-SWIFT to correct the phase and scale effects. Simulations and phantom and in vivo human experiments were performed to verify the correlation algorithm and to evaluate imaging performance. Results GM-SWIFT reduces SAR, RF amplitude, and acquisition time by up to 90%, 70%, and 45%, respectively, while maintaining image quality. The choice of GM parameter influences the lower limit of short T2* sensitivity, which can be exploited to suppress unwanted image haze from unresolvable ultrashort T2* signals originating from plastic materials in the coil housing and fixatives. Conclusions GM-SWIFT reduces peak and total RF power requirements and provides additional flexibility for optimizing SAR, RF amplitude, scan time, and image quality. PMID:25800547

SAR and scan-time optimized 3D whole-brain double inversion recovery imaging at 7T.

PubMed

Pracht, Eberhard D; Feiweier, Thorsten; Ehses, Philipp; Brenner, Daniel; Roebroeck, Alard; Weber, Bernd; Stöcker, Tony

2018-05-01

The aim of this project was to implement an ultra-high field (UHF) optimized double inversion recovery (DIR) sequence for gray matter (GM) imaging, enabling whole brain coverage in short acquisition times ( ≈5 min, image resolution 1 mm 3 ). A 3D variable flip angle DIR turbo spin echo (TSE) sequence was optimized for UHF application. We implemented an improved, fast, and specific absorption rate (SAR) efficient TSE imaging module, utilizing improved reordering. The DIR preparation was tailored to UHF application. Additionally, fat artifacts were minimized by employing water excitation instead of fat saturation. GM images, covering the whole brain, were acquired in 7 min scan time at 1 mm isotropic resolution. SAR issues were overcome by using a dedicated flip angle calculation considering SAR and SNR efficiency. Furthermore, UHF related artifacts were minimized. The suggested sequence is suitable to generate GM images with whole-brain coverage at UHF. Due to the short total acquisition times and overall robustness, this approach can potentially enable DIR application in a routine setting and enhance lesion detection in neurological diseases. Magn Reson Med 79:2620-2628, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

a Method of Time-Series Change Detection Using Full Polsar Images from Different Sensors

NASA Astrophysics Data System (ADS)

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

2018-04-01

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by Rj statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the 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 detect the time-series change from different sensors.

Investigation of Land Subsidence using ALOS PALSAR data: a case study in Mentougou (Beijing, China)

NASA Astrophysics Data System (ADS)

Chen, Jianping; Xiang, Jie; Xie, Shuai; Liu, Jing; Tarolli, Paolo

2017-04-01

Mining activities have been documented for centuries in Mentougou, and land subsidence resulting from mining operations has already been known over the past few decades. However, there has been ongoing concern that excessive groundwater extraction may lead to further subsidence. Therefore it is critical to map the land cover changes to understand the actual impact of these activities. So, the land cover changes from 2006 to 2011 were examined based on multi-source remote sensing imageries( including ALOS and landsat-7) by using object-oriented classifications combined with a decision tree and retrospective approaches. Also, land subsidence in Mentougou between 2006 and 2011 has been mapped using the interferometric synthetic aperture radar (InSAR) time-series analysis with the ALOS L-band SAR data. We processed 14 ascending SAR images during May 2006 to July 2011. Comparison of InSAR measurements with the land cover changes and pre-existing faults suggest that mining activities is the main cause of land subsidence. The land subsidence observed from InSAR data are approximately up to 15 mm/year in open-pit mining area and up to 24 mm/year in underground mining areas. The InSAR result are validated by the ground survey data in several areas, and the comparison between the InSAR result with the mining schedule showed there were some correlations between them. The result underline the potential use of InSAR measurements to provide better investigation for land subsidence, and also suggest that the most influential factors for land subsidence is underground coal mine.

Decorrelation of L-band and C-band interferometry to volcanic risk prevention

NASA Astrophysics Data System (ADS)

Malinverni, E. S.; Sandwell, D.; Tassetti, A. N.; Cappelletti, L.

2013-10-01

SAR has several strong key features: fine spatial resolution/precision and high temporal pass frequency. Moreover, the InSAR technique allows the accurate detection of ground deformations. This high potential technology can be invaluable to study volcanoes: it provides important information on pre-eruption surface deformation, improving the understanding of volcanic processes and the ability to predict eruptions. As a downside, SAR measurements are influenced by artifacts such as atmospheric effects or bad topographic data. Correlation gives a measure of these interferences, quantifying the similarity of the phase of two SAR images. Different approaches exists to reduce these errors but the main concern remain the possibility to correlate images with different acquisition times: snow-covered or heavily-vegetated areas produce seasonal changes on the surface. Minimizing the time between passes partly limits decorrelation. Though, images with a short temporal baseline aren't always available and some artifacts affecting correlation are timeindependent. This work studies correlation of pairs of SAR images focusing on the influence of surface and climate conditions, especially snow coverage and temperature. Furthermore, the effects of the acquisition band on correlation are taken into account, comparing L-band and C-band images. All the chosen images cover most of the Yellowstone caldera (USA) over a span of 4 years, sampling all the seasons. Interferograms and correlation maps are generated. To isolate temporal decorrelation, pairs of images with the shortest baseline are chosen. Correlation maps are analyzed in relation to snow depth and temperature. Results obtained with ENVISAT and ERS satellites (C-band) are compared with the ones from ALOS (L-band). Results show a good performance during winter and a bad attitude towards wet snow (spring and fall). During summer both L-band and C-band maintain a good coherence with L-band performing better over vegetation.

Radargrammetric DSM generation in mountainous areas through adaptive-window least squares matching constrained by enhanced epipolar geometry

NASA Astrophysics Data System (ADS)

Dong, Yuting; Zhang, Lu; Balz, Timo; Luo, Heng; Liao, Mingsheng

2018-03-01

Radargrammetry is a powerful tool to construct digital surface models (DSMs) especially in heavily vegetated and mountainous areas where SAR interferometry (InSAR) technology suffers from decorrelation problems. In radargrammetry, the most challenging step is to produce an accurate disparity map through massive image matching, from which terrain height information can be derived using a rigorous sensor orientation model. However, precise stereoscopic SAR (StereoSAR) image matching is a very difficult task in mountainous areas due to the presence of speckle noise and dissimilar geometric/radiometric distortions. In this article, an adaptive-window least squares matching (AW-LSM) approach with an enhanced epipolar geometric constraint is proposed to robustly identify homologous points after compensation for radiometric discrepancies and geometric distortions. The matching procedure consists of two stages. In the first stage, the right image is re-projected into the left image space to generate epipolar images using rigorous imaging geometries enhanced with elevation information extracted from the prior DEM data e.g. SRTM DEM instead of the mean height of the mapped area. Consequently, the dissimilarities in geometric distortions between the left and right images are largely reduced, and the residual disparity corresponds to the height difference between true ground surface and the prior DEM. In the second stage, massive per-pixel matching between StereoSAR epipolar images identifies the residual disparity. To ensure the reliability and accuracy of the matching results, we develop an iterative matching scheme in which the classic cross correlation matching is used to obtain initial results, followed by the least squares matching (LSM) to refine the matching results. An adaptively resizing search window strategy is adopted during the dense matching step to help find right matching points. The feasibility and effectiveness of the proposed approach is demonstrated using Stripmap and Spotlight mode TerraSAR-X stereo data pairs covering Mount Song in central China. Experimental results show that the proposed method can provide a robust and effective matching tool for radargrammetry in mountainous areas.

Evolution of Nonlinear Internal Waves in China Seas

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Hsu, Ming-K.; Liang, Nai K.

1997-01-01

Synthetic Aperture Radar (SAR) images from ERS-I have been used to study the characteristics of internal waves of Taiwan in the East China Sea, and east of Hainan Island in the South China Sea. Rank-ordered packets of internal solitons propagating shoreward from the edge of the continental shelf were observed in the SAR images. Based on the assumption of a semidiurnal tidal origin, the wave speed can be estimated and is consistent with the internal wave theory. By using the SAR images and hydrographic data, internal waves of elevation have been identified in shallow water due to a thicker mixed layer as compared with the bottom layer on the continental shelf. The generation mechanism includes the influences of the tide and the Kuroshio intrusion across the continental shelf for the formations of elevation internal waves. The effects of water depth on the evolution of solitons and wave packets are modeled by nonlinear Kortweg-deVries (KdV) type equation and linked to satellite image observations. The numerical calculations of internal wave evolution on the continental shelf have been performed and compared with the SAR observations. For a case of depression waves in deep water, the solitons first disintegrate into dispersive wave trains and then evolve to a packet of elevation waves in the shallow water area after they pass through a turning point of approximately equal layer depths has been observed in the SAR image and simulated by numerical model.

Demonstration of Synthetic Aperture Radar and Hyperspectral Imaging for Wide Area Assessment at Pueblo Precision Bombing Range #2, Colorado

DTIC Science & Technology

2008-10-01

resolution orthophoto and LiDAR datasets, as well as for the vegetation modeling conducted for SAR FAR mitigation. 3.4.4 Navigation Systems An Applanix A...these accuracies. By registering eight cardinal pass-direction images per tile to the orthophotography and to each other, the horizontal error in... orthophoto image, which successfully increased the HSI image resolution to 0.25-m. 22 Table 4. SAR Performance Data. Type of Performance

The influence of processor focus on speckle correlation statistics for a Shuttle imaging radar scene of Hurricane Josephine

NASA Technical Reports Server (NTRS)

Tilley, David G.

1988-01-01

The surface wave field produced by Hurricane Josephine was imaged by the L-band SAR aboard the Challenger on October 12, 1984. Exponential trends found in the two-dimensional autocorrelations of speckled image data support an equilibrium theory model of sea surface hydrodynamics. The notions of correlated specular reflection, surface coherence, optimal Doppler parameterization and spatial resolution are discussed within the context of a Poisson-Rayleigh statistical model of the SAR imaging process.

SEASAT views oceans and sea ice with synthetic aperture radar

NASA Technical Reports Server (NTRS)

Fu, L. L.; Holt, B.

1982-01-01

Fifty-one SEASAT synthetic aperture radar (SAR) images of the oceans and sea ice are presented. Surface and internal waves, the Gulf Stream system and its rings and eddies, the eastern North Pacific, coastal phenomena, bathymetric features, atmospheric phenomena, and ship wakes are represented. Images of arctic pack and shore-fast ice are presented. The characteristics of the SEASAT SAR system and its image are described. Maps showing the area covered, and tables of key orbital information, and listing digitally processed images are provided.

Analysis and an image recovery algorithm for ultrasonic tomography system

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1994-01-01

The problem of an ultrasonic reflectivity tomography is similar to that of a spotlight-mode aircraft Synthetic Aperture Radar (SAR) system. The analysis for a circular path spotlight mode SAR in this paper leads to the insight of the system characteristics. It indicates that such a system when operated in a wide bandwidth is capable of achieving the ultimate resolution; one quarter of the wavelength of the carrier frequency. An efficient processing algorithm based on the exact two dimensional spectrum is presented. The results of simulation indicate that the impulse responses meet the predicted resolution performance. Compared to an algorithm previously developed for the ultrasonic reflectivity tomography, the throughput rate of this algorithm is about ten times higher.

Brady's Geothermal Field - Metadata for InSAR Holdings

DOE Data Explorer

Ali, Tabrez

2016-07-29

List of synthetic aperture radar (SAR) images acquired by TerraSAR-X and TanDEM-X satellite missions and archived at UNAVCO's WINSAR facility. See file "Bradys TSX Holdings.csv" for individual links. NOTE: The user must create an account in order to access the data (See "Instructions for Creating an Account" below).

The Influence of Spatial Resolutions on the Retrieval Accuracy of Sea Surface Wind Speed with Cross-polarized C-band SAR images

NASA Astrophysics Data System (ADS)

Zhang, K.; Han, B.; Mansaray, L. R.; Xu, X.; Guo, Q.; Jingfeng, H.

2017-12-01

Synthetic aperture radar (SAR) instruments on board satellites are valuable for high-resolution wind field mapping, especially for coastal studies. Since the launch of Sentinel-1A on April 3, 2014, followed by Sentinel-1B on April 25, 2016, large amount of C-band SAR data have been added to a growing accumulation of SAR datasets (ERS-1/2, RADARSAT-1/2, ENVISAT). These new developments are of great significance for a wide range of applications in coastal sea areas, especially for high spatial resolution wind resource assessment, in which the accuracy of retrieved wind fields is extremely crucial. Recently, it is reported that wind speeds can also be retrieved from C-band cross-polarized SAR images, which is an important complement to wind speed retrieval from co-polarization. However, there is no consensus on the optimal resolution for wind speed retrieval from cross-polarized SAR images. This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized SAR images. Firstly, for wind speeds retrieved from VV-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Secondly, the most suitable C-band cross-polarized ocean (C-2PO) model was selected between two C-2POs for the VH-polarized image dataset. Then, the VH-wind speeds retrieved by the selected C-2PO were compared with the VV-polarized sea surface wind speeds retrieved using the optimal CMOD, which served as reference, at different spatial resolutions. Results show that the VH-polarized wind speed retrieval accuracy increases rapidly with the decrease in spatial resolutions from 100 m to 1000 m, with a drop in RMSE of 42%. However, the improvement in wind speed retrieval accuracy levels off with spatial resolutions decreasing from 1000 m to 5000 m. This demonstrates that the pixel spacing of 1 km may be the compromising choice for the tradeoff between the spatial resolution and wind speed retrieval accuracy with cross-polarized images obtained from RADASAT-2 fine quad polarization mode. Figs. 1 illustrate the variation of the following statistical parameters: Bias, Corr, R2, RMSE and STD as a function of spatial resolution.

North Central Thailand

NASA Technical Reports Server (NTRS)

1998-01-01

This radar image shows the dramatic landscape in the Phang Hoei Range of north central Thailand, about 40 kilometers (25 miles) northeast of the city of Lom Sak. The plateau, shown in green to the left of center, is the area of Phu Kradung National Park. This plateau is a remnant of a once larger plateau, another portion of which is seen along the right side of the image. The plateaus have been dissected by water erosion over thousands of years. Forest areas appear green on the image; agricultural areas and settlements appear as red and blue. North is toward the lower right. The area shown is 38 by 50 kilometers (24 by 31 miles) and is centered at 16.96 degrees north latitude, 101.67 degrees east longitude. Colors are assigned to different radar frequencies and polarizations as follows: red is L-band horizontally transmitted and horizontally received; green is L-band horizontally transmitted and vertically received; blue is C-band horizontally transmitted and vertically received. The image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture (SIR-C/X-SAR) imaging radar on October 3, 1994, when it flew aboard the space shuttle Endeavour. SIR-C/X-SAR is a joint mission of the U.S./German and Italian space agencies.

Spaceborne Imaging Radar-C and X-Band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.v.(DLR), the major partner in science, operations, and data processing of X-SAR.

Titan's surface from the Cassini RADAR radiometry data during SAR mode

USGS Publications Warehouse

Paganelli, F.; Janssen, M.A.; Lopes, R.M.; Stofan, E.; Wall, S.D.; Lorenz, R.D.; Lunine, J.I.; Kirk, R.L.; Roth, L.; Elachi, C.

2008-01-01

We present initial results on the calibration and interpretation of the high-resolution radiometry data acquired during the Synthetic Aperture Radar (SAR) mode (SAR-radiometry) of the Cassini Radar Mapper during its first five flybys of Saturn's moon Titan. We construct maps of the brightness temperature at the 2-cm wavelength coincident with SAR swath imaging. A preliminary radiometry calibration shows that brightness temperature in these maps varies from 64 to 89 K. Surface features and physical properties derived from the SAR-radiometry maps and SAR imaging are strongly correlated; in general, we find that surface features with high radar reflectivity are associated with radiometrically cold regions, while surface features with low radar reflectivity correlate with radiometrically warm regions. We examined scatterplots of the normalized radar cross-section ??0 versus brightness temperature, outlining signatures that characterize various terrains and surface features. The results indicate that volume scattering is important in many areas of Titan's surface, particularly Xanadu, while other areas exhibit complex brightness temperature variations consistent with variable slopes or surface material and compositional properties. ?? 2007.

Integration of SAR and DEM data: Geometrical considerations

NASA Technical Reports Server (NTRS)

Kropatsch, Walter G.

1991-01-01

General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.

Pre-Columbian archaeological ruins are revealed through Costa Rican rain forest in this photo taken during NASA's AirSAR 2004 campaign

NASA Image and Video Library

2004-03-05

Pre-Columbian archaeological ruins are revealed through Costa Rican rain forest in this photo taken during NASA's AirSAR 2004 Mesoamerica campaign. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. Much of the archaeological evidence needed to understand Pre-Columbian societies in Central America comes from features on the landscape. Difficult terrain and logistics have limited ground data collection. AirSAR helped to detect signs of ancient civilizations hidden beneath the forest. Its images will shed insights into the way modern humans interact with their landscape, and how ancient peoples lived and what became of their civilizations.

C- and L-band space-borne SAR incidence angle normalization for efficient Arctic sea ice monitoring

NASA Astrophysics Data System (ADS)

Mahmud, M. S.; Geldsetzer, T.; Howell, S.; Yackel, J.; Nandan, V.

2017-12-01

C-band Synthetic Aperture Radar (SAR) has been widely used effectively for operational sea ice monitoring, owing to its greater seperability between snow-covered first-year (FYI) and multi-year (MYI) ice types, during winter. However, during the melt season, C-band SAR backscatter contrast reduces between FYI and MYI. To overcome the limitations of C-band, several studies have recommended utlizing L-band SAR, as it has the potential to significantly improve sea ice classification. Given its longer wavelength, L-band can efficiently separate FYI and MYI types, especially during melt season. Therefore, the combination of C- and L-band SAR is an optimal solution for efficient seasonal sea ice monitoring. As SAR acquires images over a range of incidence angles from near-range to far-range, SAR backscatter varies substantially. To compensate this variation in SAR backscatter, incidence angle dependency of C- and L-band SAR backscatter for different FYI and MYI types is crucial to quantify, which is the objective of this study. Time-series SAR imagery from C-band RADARSAT-2 and L-band ALOS PALSAR during winter months of 2010 across 60 sites over the Canadian Arctic was acquired. Utilizing 15 images for each sites during February-March for both C- and L-band SAR, incidence angle dependency was calculated. Our study reveals that L- and C-band backscatter from FYI and MYI decreases with increasing incidence angle. The mean incidence angle dependency for FYI and MYI were estimated to be -0.21 dB/1° and -0.30 dB/1° respectively from L-band SAR, and -0.22 dB/1° and -0.16 dB/1° from C-band SAR, respectively. While the incidence angle dependency for FYI was found to be similar in both frequencies, it doubled in case of MYI from L-band, compared to C-band. After applying the incidence angle normalization method to both C- and L-band SAR images, preliminary results indicate improved sea ice type seperability between FYI and MYI types, with substantially lower number of mixed pixels; thereby offering more reliable sea ice classification accuracies. Research findings from this study can be utilized to improve seasonal sea ice classification with higher accuracy for operational Arctic sea ice monitoring, especially in regions like the Canadian Arctic, where MYI detection is crucial for safer ship navigations.

An automatic target recognition system based on SAR image

NASA Astrophysics Data System (ADS)

Li, Qinfu; Wang, Jinquan; Zhao, Bo; Luo, Furen; Xu, Xiaojian

2009-10-01

In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR research. To establish an integral and available system, the processing of SAR image was divided into four main stages which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.