Integrated Time and Phase Synchronization Strategy for a Multichannel Spaceborne-Stationary Bistatic SAR System

Directory of Open Access Journals (Sweden)

Feng Hong

2016-07-01

Full Text Available The spatial separation of the transmitter and receiver in Bistatic Synthetic Aperture Radar (BiSAR makes it a promising and useful supplement to a classical Monostatic SAR system (MonoSAR. This paper proposes a novel integrated time and phase synchronization strategy for a multichannel spaceborne-stationary BiSAR system. Firstly, the time synchronization strategy is proposed, which includes Pulse Repetition Frequency (PRF generation under noisy conditions, multichannel calibration and the alignment of the recorded data with the orbital data. Furthermore, the phase synchronization strategy, which fully considers the deteriorative factors in the BiSAR configuration, is well studied. The contribution of the phase synchronization strategy includes two aspects: it not only compensates the phase error, but also improves the Signal to Noise Ratio (SNR of the obtained signals. Specifically, all direct signals on different PRF time can be reconstructed with the shift and phase compensation operation using a reference signal. Besides, since the parameters of the reference signal can be estimated only once using the selected practical direct signal and a priori information, the processing complexity is well reduced. Final imaging results with and without compensation for real data are presented to validate the proposed synchronization strategy.

Stormwater runoff plumes in the Southern California Bight: A comparison study with SAR and MODIS imagery.

Science.gov (United States)

Holt, Benjamin; Trinh, Rebecca; Gierach, Michelle M

2017-05-15

Stormwater runoff is the largest source of pollution in the Southern California Bight (SCB), resulting from untreated runoff and pollutants from urban watersheds entering the coastal waters after rainstorms. We make use of both satellite SAR and MODIS-Aqua ocean color imagery to examine two different components of runoff plumes, the surface slick and the sediment discharge. We expand on earlier satellite SAR studies by examining an extensive collection of multi-platform SAR imagery, spanning from 1992 to 2014, that provides a more comprehensive view of the plume surface slick characteristics, illustrated with distribution maps of the extent and flow direction of the plumes. The SAR-detected surface plumes are compared with coincident rain and runoff measurements, and with available measured shoreline fecal bacteria loads. We illustrate differences in the detection of SAR surface plumes with the sediment-related discharge plumes derived from MODIS imagery. A conceptual satellite stormwater runoff monitoring approach is presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of macroalgae blooms by complex SAR imagery

International Nuclear Information System (INIS)

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

2014-01-01

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

Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery

Science.gov (United States)

Yang, L.; Jiang, L.; Lin, H.; Liao, M.

2009-01-01

In this study, we explored the potential to improve urban impervious surface modeling and mapping with the synergistic use of optical and Interferometric Synthetic Aperture Radar (InSAR) imagery. We used a Classification and Regression Tree (CART)-based approach to test the feasibility and accuracy of quantifying Impervious Surface Percentage (ISP) using four spectral bands of SPOT 5 high-resolution geometric (HRG) imagery and three parameters derived from the European Remote Sensing (ERS)-2 Single Look Complex (SLC) SAR image pair. Validated by an independent ISP reference dataset derived from the 33 cm-resolution digital aerial photographs, results show that the addition of InSAR data reduced the ISP modeling error rate from 15.5% to 12.9% and increased the correlation coefficient from 0.71 to 0.77. Spatially, the improvement is especially noted in areas of vacant land and bare ground, which were incorrectly mapped as urban impervious surfaces when using the optical remote sensing data. In addition, the accuracy of ISP prediction using InSAR images alone is only marginally less than that obtained by using SPOT imagery. The finding indicates the potential of using InSAR data for frequent monitoring of urban settings located in cloud-prone areas.

Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters

Science.gov (United States)

Ajadi, Olaniyi A.

Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to

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

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L. Guida

2018-04-01

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

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

Science.gov (United States)

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

2018-04-01

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

Rapid Flood Map Generation from Spaceborne SAR Observations

Science.gov (United States)

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

2016-12-01

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

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

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Julie Betbeder

2014-04-01

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

AN ASSESSMENT OF SPACEBORNE NEAR-NADIR INTERFEROMETRIC SAR PERFORMANCE OVER INLAND WATERS WITH REAL

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H. Tan

2018-04-01

Full Text Available Elevation measurements of the continental water surface have been poorly collected with in situ measurements or occasionally with conventional altimeters with low accuracy. Techniques using InSAR at near-nadir angles to measure the inland water elevation with large swath and with high accuracy have been proposed, for instance, the WSOA on Jason 2 and the KaRIn on SWOT. However, the WSOA was abandoned unfortunately and the SWOT is planned to be launched in 2021. In this paper, we show real acquisitions of the first spaceborne InSAR of such kind, the Interferometric Imaging Radar Altimeter (InIRA, which has been working on Tiangong II spacecraft since 2016. We used the 90-m SRTM DEM as a reference to estimate the phase offset, and then an empirical calibration model was used to correct the baseline errors.

An Assessment of Spaceborne Near-Nadir Interferometric SAR Performance Over Inland Waters with Real

Science.gov (United States)

Tan, H.; Li, S. Y.; Liu, Z. W.

2018-04-01

Elevation measurements of the continental water surface have been poorly collected with in situ measurements or occasionally with conventional altimeters with low accuracy. Techniques using InSAR at near-nadir angles to measure the inland water elevation with large swath and with high accuracy have been proposed, for instance, the WSOA on Jason 2 and the KaRIn on SWOT. However, the WSOA was abandoned unfortunately and the SWOT is planned to be launched in 2021. In this paper, we show real acquisitions of the first spaceborne InSAR of such kind, the Interferometric Imaging Radar Altimeter (InIRA), which has been working on Tiangong II spacecraft since 2016. We used the 90-m SRTM DEM as a reference to estimate the phase offset, and then an empirical calibration model was used to correct the baseline errors.

Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery

Science.gov (United States)

Qiu, Chunping; Schmitt, Michael; Zhu, Xiao Xiang

2018-04-01

In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.

Bilge dump detection from SAR imagery using local binary patterns

CSIR Research Space (South Africa)

Mdakane, LW

2015-07-01

Full Text Available 2015: Remote Sensing: Understanding the Earth for a Safer World, Milan, Italy, 26-31 July 2015 Bilge dump detection from SAR imagery using local binary patterns yz L.W. Mdakane,yz W. Kleynhans,yz C.P. Schwegmann yDepartment of Electrical...

Identification of sea ice types in spaceborne synthetic aperture radar data

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Kwok, Ronald; Rignot, Eric; Holt, Benjamin; Onstott, R.

1992-01-01

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

Azimuth-Variant Signal Processing in High-Altitude Platform Passive SAR with Spaceborne/Airborne Transmitter

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Huaizong Shao

2013-03-01

Full Text Available High-altitude platforms (HAP or near-space vehicle offers several advantages over current low earth orbit (LEO satellite and airplane, because HAP is not constrained by orbital mechanics and fuel consumption. These advantages provide potential for some specific remote sensing applications that require persistent monitoring or fast-revisiting frequency. This paper investigates the azimuth-variant signal processing in HAP-borne bistatic synthetic aperture radar (BiSAR with spaceborne or airborne transmitter for high-resolution remote sensing. The system configuration, azimuth-variant Doppler characteristics and two-dimensional echo spectrum are analyzed. Conceptual system simulation results are also provided. Since the azimuth-variant BiSAR geometry brings a challenge for developing high precision data processing algorithms, we propose an image formation algorithm using equivalent velocity and nonlinear chirp scaling (NCS to address the azimuth-variant signal processing problem. The proposed algorithm is verified by numerical simulation results.

Mapping Deforestation and Land Use in Amazon Rainforest Using SAR-C Imagery

Science.gov (United States)

Saatchi, Sasan S.; Soares, Joao Vianei; Alves, Diogenes Salas

1996-01-01

Land use changes and deforestation in tropical rainforests are among the major factors affecting the overall function of the global environment. To routinely assess the spatial extend and temporal dynamics of these changes has become an important challenge in several scientific disciplines such as climate and environmental studies. In this paper, the feasibility of using polarimetric spaceborne SAR data in mapping land cover types in the Amazon is studied.

Comparison of Laser and Stereo Optical, SAR and InSAR Point Clouds from Air- and Space-Borne Sources in the Retrieval of Forest Inventory Attributes

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Xiaowei Yu

2015-11-01

Full Text Available It is anticipated that many of the future forest mapping applications will be based on three-dimensional (3D point clouds. A comparison study was conducted to verify the explanatory power and information contents of several 3D remote sensing data sources on the retrieval of above ground biomass (AGB, stem volume (VOL, basal area (G, basal-area weighted mean diameter (Dg and Lorey’s mean height (Hg at the plot level, utilizing the following data: synthetic aperture radar (SAR Interferometry, SAR radargrammetry, satellite-imagery having stereo viewing capability, airborne laser scanning (ALS with various densities (0.8–6 pulses/m2 and aerial stereo imagery. Laser scanning is generally known as the primary source providing a 3D point cloud. However, photogrammetric, radargrammetric and interferometric techniques can be used to produce 3D point clouds from space- and air-borne stereo images. Such an image-based point cloud could be utilized in a similar manner as ALS providing that accurate digital terrain model is available. In this study, the performance of these data sources for providing point cloud data was evaluated with 91 sample plots that were established in Evo, southern Finland within a boreal forest zone and surveyed in 2014 for this comparison. The prediction models were built using random forests technique with features derived from each data sources as independent variables and field measurements of forest attributes as response variable. The relative root mean square errors (RMSEs varied in the ranges of 4.6% (0.97 m–13.4% (2.83 m for Hg, 11.7% (3.0 cm–20.6% (5.3 cm for Dg, 14.8% (4.0 m2/ha–25.8% (6.9 m2/ha for G, 15.9% (43.0 m3/ha–31.2% (84.2 m3/ha for VOL and 14.3% (19.2 Mg/ha–27.5% (37.0 Mg/ha for AGB, respectively, depending on the data used. Results indicate that ALS data achieved the most accurate estimates for all forest inventory attributes. For image-based 3D data, high-altitude aerial images and WorldView-2

Combined DEM Extration Method from StereoSAR and InSAR

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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.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

Science.gov (United States)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Wind class sampling of satellite SAR imagery for offshore wind resource mapping

DEFF Research Database (Denmark)

Badger, Merete; Badger, Jake; Nielsen, Morten

2010-01-01

developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter......High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical......-dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally...

SAR Imagery Applied to the Monitoring of Hyper-Saline Deposits: Death Valley Example (CA)

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Lasne, Yannick; Paillou, Philippe; Freeman, Anthony; Chapman, Bruce

2009-01-01

The present study aims at understanding the influence of salinity on the dielectric constant of soils and then on the backscattering coeff cients recorded by airborne/spaceborne SAR systems. Based on dielectric measurements performed over hyper-saline deposits in Death Valley (CA), as well as laboratory electromagnetic characterization of salts and water mixtures, we used the dielectric constants as input parameters of analytical IEM simulations to model both the amplitude and phase behaviors of SAR signal at C, and L-bands. Our analytical simulations allow to reproduce specif c copolar signatures recorded in SAR data, corresponding to the Cottonball Basin saltpan. We also propose the copolar backscattering ratio and phase difference as indicators of moistened and salt-affected soils. More precisely, we show that these copolar indicators should allow to monitor the seasonal variations of the dielectric properties of saline deposits.

On the interpretation of SAR imagery from the Sea Empress oil spill

International Nuclear Information System (INIS)

Jones, B.; Mitchelson-Jacob, E.G.

1998-01-01

A method for monitoring oil spills using SAR imagery is suggested, based on the simulation of the wave spectrum using modelled surface winds. A first order separation of the purely wind-driven backscatter distribution and its modifications due to surfactant was made by parametrizing the effect of surfactant on the wave growth rate and on the reflective properties of the sea surface. The technique was applied to an SAR image showing the Sea Empress oil spill, in south-west Wales, UK. (author)

Ocean Wave Parameters Retrieval from Sentinel-1 SAR Imagery

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Weizeng Shao

2016-08-01

Full Text Available In this paper, a semi-empirical algorithm for significant wave height (Hs and mean wave period (Tmw retrieval from C-band VV-polarization Sentinel-1 synthetic aperture radar (SAR imagery is presented. We develop a semi-empirical function for Hs retrieval, which describes the relation between Hs and cutoff wavelength, radar incidence angle, and wave propagation direction relative to radar look direction. Additionally, Tmw can be also calculated through Hs and cutoff wavelength by using another empirical function. We collected 106 C-band stripmap mode Sentinel-1 SAR images in VV-polarization and wave measurements from in situ buoys. There are a total of 150 matchup points. We used 93 matchups to tune the coefficients of the semi-empirical algorithm and the rest 57 matchups for validation. The comparison shows a 0.69 m root mean square error (RMSE of Hs with a 18.6% of scatter index (SI and 1.98 s RMSE of Tmw with a 24.8% of SI. Results indicate that the algorithm is suitable for wave parameters retrieval from Sentinel-1 SAR data.

OIL SPILL DETECTION AND MONITORING OF ABU DHABI COASTAL ZONE USING KOMPSAT-5 SAR IMAGERY

OpenAIRE

H. A. Harahsheh

2016-01-01

Abu Dhabi Government endorsed vision for its Maritime Strategy ‘A safe, secure and sustainable maritime domain for Abu Dhabi'. This research study share this vision using the concept of monitoring as tool for marine protection against any possible oil pollution. The best technology to detect and monitor oil pollution and in particularly oil spill is SAR imagery In this case study we chose KOMPSAT-5 SAR. KOMPSAT-5 carries X-band SAR for earth observation, and is capable of day-...

Accuracy Analysis Comparison of Supervised Classification Methods for Anomaly Detection on Levees Using SAR Imagery

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Ramakalavathi Marapareddy

2017-10-01

Full Text Available This paper analyzes the use of a synthetic aperture radar (SAR imagery to support levee condition assessment by detecting potential slide areas in an efficient and cost-effective manner. Levees are prone to a failure in the form of internal erosion within the earthen structure and landslides (also called slough or slump slides. If not repaired, slough slides may lead to levee failures. In this paper, we compare the accuracy of the supervised classification methods minimum distance (MD using Euclidean and Mahalanobis distance, support vector machine (SVM, and maximum likelihood (ML, using SAR technology to detect slough slides on earthen levees. In this work, the effectiveness of the algorithms was demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory’s (JPL’s uninhabited aerial vehicle synthetic aperture radar (UAVSAR. The study area is a section of the lower Mississippi River valley in the Southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers.

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

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Tingting Jin

2017-04-01

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

A study on rational function model generation for TerraSAR-X imagery.

Science.gov (United States)

Eftekhari, Akram; Saadatseresht, Mohammad; Motagh, Mahdi

2013-09-09

The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10-3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

A Study on Rational Function Model Generation for TerraSAR-X Imagery

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Mahdi Motagh

2013-09-01

Full Text Available The Rational Function Model (RFM has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10−3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

Verification of target motion effects on SAR imagery using the Gotcha GMTI challenge dataset

Science.gov (United States)

Hack, Dan E.; Saville, Michael A.

2010-04-01

This paper investigates the relationship between a ground moving target's kinematic state and its SAR image. While effects such as cross-range offset, defocus, and smearing appear well understood, their derivations in the literature typically employ simplifications of the radar/target geometry and assume point scattering targets. This study adopts a geometrical model for understanding target motion effects in SAR imagery, termed the target migration path, and focuses on experimental verification of predicted motion effects using both simulated and empirical datasets based on the Gotcha GMTI challenge dataset. Specifically, moving target imagery is generated from three data sources: first, simulated phase history for a moving point target; second, simulated phase history for a moving vehicle derived from a simulated Mazda MPV X-band signature; and third, empirical phase history from the Gotcha GMTI challenge dataset. Both simulated target trajectories match the truth GPS target position history from the Gotcha GMTI challenge dataset, allowing direct comparison between all three imagery sets and the predicted target migration path. This paper concludes with a discussion of the parallels between the target migration path and the measurement model within a Kalman filtering framework, followed by conclusions.

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

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P. Fischer

2018-04-01

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

Stormwater Runoff Plumes in Southern California Detected with Satellite SAR and MODIS Imagery - Areas of Increased Contamination Risk

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Trinh, R. C.; Holt, B.; Gierach, M.

2016-12-01

Coastal pollution poses both a major health and environmental hazard, not only for beachgoers and coastal communities, but for marine organisms as well. Stormwater runoff is the largest source of pollution in the coastal waters of the Southern California Bight (SCB). The SCB is the final destination of four major urban watersheds and associated rivers, Ballona Creek, the Los Angeles River, the San Gabriel River, and the Santa Ana River, which act as channels for runoff and pollution during and after episodic rainstorms. Previous studies of SCB water quality have made use of both fine resolution Synthetic Aperture Radar (SAR) imagery and wide-swath medium resolution optical "ocean color" imagery from SeaWiFS and MODIS. In this study, we expand on previous SAR efforts, compiling a more extensive collection of multi-sensor SAR data, spanning from 1992 to 2014, analyzing the surface slick component of stormwater plumes. We demonstrate the use of SAR data in early detection of coastal stormwater plumes, relating plume extent to cumulative river discharge, and shoreline fecal bacteria loads. Intensity maps of the primary extent and direction of plumes were created, identifying coastal areas that may be subject to the greatest risk of environmental contamination. Additionally, we illustrate the differences in the detection of SAR surface plumes with the sediment-related discharge plumes derived from MODIS ocean color imagery. Finally, we provide a concept for satellite monitoring of stormwater plumes, combining both optical and radar sensors, to be used to guide the collection of in situ water quality data and enhance the assessment of related beach closures.

Dual-Polarized L-Band SAR Imagery for Temporal Monitoring of Marine Oil Slick Concentration

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Sébastien Angelliaume

2018-06-01

Full Text Available SAR sensors are usually used in the offshore domain to detect marine oil slicks which allows the authorities to guide cleanup operations or prosecute polluters. As radar imagery can be used any time of day or year and in almost any weather conditions, the use and programming of such remote sensing data is usually favored over optical imagery. Nevertheless, images collected in the optical domain provide access to key information not accessible today by SAR instruments, such as the thickness or the amount of pollutant. To address this knowledge gap, a methodology based on the joint use of a scattering model (U-WCA and remote sensing data collected by a low frequency (e.g., L-band imaging radar over controlled release of mineral oil spill is reported in this paper. The proposed method allows estimation of the concentration of pollutant within an oil-in-water mixture as well as the temporal variation of this quantity due to weathering processes.

The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey

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Fabiana Calò

2015-12-01

Full Text Available In today’s urbanizing world, home of 28 megacities, there is a growing need for tools to assess urban policies and support the design and implementation of effective development strategies. Unsustainable practices of urbanization bring major implications for land and environment, and cause a dramatic increase of urban vulnerability to natural hazards. In Istanbul megacity, disaster risk reduction represents a challenging issue for urban managers. In this paper, we show the relevance of the space-borne Differential SAR Interferometry (DInSAR technique as a tool for supporting risk management, and thus contributing to achieve the urban sustainability. To this aim, we use a dataset of high resolution SAR images collected by the TerraSAR-X satellite that have been processed through the advanced (multi-temporal Small BAseline Subset (SBAS—DInSAR technique, thus producing spatially-dense deformation velocity maps and associated time-series. Results allow to depict an up-to-date picture of surface deformations occurring in Istanbul, and thus to identify urban areas subject to potential risk. The joint analysis of remotely sensed measurements and ancillary data (geological and urban development information provides an opportunity for city planners and land professionals to discuss on the mutual relationship between urban development policies and natural/man-made hazards.

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

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Zhi Zhao

2013-01-01

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

Massachusetts Bay - Internal wave packets digitized from SAR imagery and intersected with a bathymetrically derived slope surface

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This feature class contains internal wave packets digitized from SAR imagery and intersected with a bathymetrically derived slope surface for Massachusetts Bay. The...

Studies of Bagley Icefield during surge and Black Rapids Glacier, Alaska, using spaceborne SAR interferometry

Science.gov (United States)

Fatland, Dennis Robert

1998-12-01

This thesis presents studies of two temperate valley glaciers---Bering Glacier in the Chugach-St.Elias Mountains, South Central Alaska, and Black Rapids Glacier in the Alaska Range, Interior Alaska---using differential spaceborne radar interferometry. The first study was centered on the 1993--95 surge of Bering Glacier and the resultant ice dynamics on its accumulation area, the Bagley Icefield. The second study site was chosen for purposes of comparison of the interferometry results with conventional field measurements, particularly camera survey data and airborne laser altimetry. A comprehensive suite of software was written to interferometrically process synthetic aperture radar (SAR) data in order to derive estimates of surface elevation and surface velocity on these subject glaciers. In addition to these results, the data revealed unexpected but fairly common concentric rings called 'phase bull's-eyes', image features typically 0.5 to 4 km in diameter located over the central part of various glaciers. These bull's-eyes led to a hypothetical model in which they were interpreted to indicate transitory instances of high subglacial water pressure that locally lift the glacier from its bed by several centimeters. This model is associated with previous findings about the nature of glacier bed hydrology and glacier surging. In addition to the dynamical analysis presented herein, this work is submitted as a contribution to the ongoing development of spaceborne radar interferometry as a glaciological tool.

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

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Nobuoto Nojima

2010-09-01

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

Mapping Regional Inundation with Spaceborne L-Band SAR

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Bruce Chapman

2015-04-01

Full Text Available Shortly after the launch of ALOS PALSAR L-band SAR by the Japan Space Exploration Agency (JAXA, a program to develop an Earth Science Data Record (ESDR for inundated wetlands was funded by NASA. Using established methodologies, extensive multi-temporal L-band ALOS ScanSAR data acquired bi-monthly by the PALSAR instrument onboard ALOS were used to classify the inundation state for South America for delivery as a component of this Inundated Wetlands ESDR (IW-ESDR and in collaboration with JAXA’s ALOS Kyoto and Carbon Initiative science programme. We describe these methodologies and the final classification of the inundation state, then compared this with results derived from dual-season data acquired by the JERS-1 L-band SAR mission in 1995 and 1996, as well as with estimates of surface water extent measured globally every 10 days by coarser resolution sensors. Good correspondence was found when comparing open water extent classified from multi-temporal ALOS ScanSAR data with surface water fraction identified from coarse resolution sensors, except in those regions where there may be differences in sensitivity to widespread and shallow seasonal flooding event, or in areas that could be excluded through use of a continental-scale inundatable mask. It was found that the ALOS ScanSAR classification of inundated vegetation was relatively insensitive to inundated herbaceous vegetation. Inundation dynamics were examined using the multi-temporal ALOS ScanSAR acquisitions over the Pacaya-Samiria and surrounding areas in the Peruvian Amazon.

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

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Frery Alejandro C

2002-01-01

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

PRF Ambiguity Detrmination for Radarsat ScanSAR System

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Jin, Michael Y.

1998-01-01

PRF ambiguity is a potential problem for a spaceborne SAR operated at high frequencies. For a strip mode SAR, there were several approaches to solve this problem. This paper, however, addresses PRF ambiguity determination algorithms suitable for a burst mode SAR system such as the Radarsat ScanSAR. The candidate algorithms include the wavelength diversity algorithm, range look cross correlation algorithm, and multi-PRF algorithm.

Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

Science.gov (United States)

Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

2017-12-01

Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

Estimating Velocities of Glaciers Using Sentinel-1 SAR Imagery

Science.gov (United States)

Gens, R.; Arnoult, K., Jr.; Friedl, P.; Vijay, S.; Braun, M.; Meyer, F. J.; Gracheva, V.; Hogenson, K.

2017-12-01

In an international collaborative effort, software has been developed to estimate the velocities of glaciers by using Sentinel-1 Synthetic Aperture Radar (SAR) imagery. The technique, initially designed by the University of Erlangen-Nuremberg (FAU), has been previously used to quantify spatial and temporal variabilities in the velocities of surging glaciers in the Pakistan Karakoram. The software estimates surface velocities by first co-registering image pairs to sub-pixel precision and then by estimating local offsets based on cross-correlation. The Alaska Satellite Facility (ASF) at the University of Alaska Fairbanks (UAF) has modified the software to make it more robust and also capable of migration into the Amazon Cloud. Additionally, ASF has implemented a prototype that offers the glacier tracking processing flow as a subscription service as part of its Hybrid Pluggable Processing Pipeline (HyP3). Since the software is co-located with ASF's cloud-based Sentinel-1 archive, processing of large data volumes is now more efficient and cost effective. Velocity maps are estimated for Single Look Complex (SLC) SAR image pairs and a digital elevation model (DEM) of the local topography. A time series of these velocity maps then allows the long-term monitoring of these glaciers. Due to the all-weather capabilities and the dense coverage of Sentinel-1 data, the results are complementary to optically generated ones. Together with the products from the Global Land Ice Velocity Extraction project (GoLIVE) derived from Landsat 8 data, glacier speeds can be monitored more comprehensively. Examples from Sentinel-1 SAR-derived results are presented along with optical results for the same glaciers.

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

Science.gov (United States)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a

Dynamic behavior of the Bering Glacier-Bagley icefield system during a surge, and other measurements of Alaskan glaciers with ERS SAR imagery

Science.gov (United States)

Lingle, Craig S.; Fatland, Dennis R.; Voronina, Vera A.; Ahlnaes, Kristina; Troshina, Elena N.

1997-01-01

ERS-1 synthetic aperture radar (SAR) imagery was employed for the measurement of the dynamics of the Bagley icefield during a major surge in 1993-1994, the measurement of ice velocities on the Malaspina piedmont glacier during a quiescent phase between surges, and for mapping the snow lines and the position of the terminus of Nabesna glacier on Mount Wrangell (a 4317 m andesitic shield volcano) in the heavily glacierized Saint Elias and Wrangell Mountains of Alaska. An overview and summary of results is given. The methods used include interferometry, cross-correlation of sequential images, and digitization of boundaries using terrain-corrected SAR imagery.

An enhanced structure tensor method for sea ice ridge detection from GF-3 SAR imagery

Science.gov (United States)

Zhu, T.; Li, F.; Zhang, Y.; Zhang, S.; Spreen, G.; Dierking, W.; Heygster, G.

2017-12-01

In SAR imagery, ridges or leads are shown as the curvilinear features. The proposed ridge detection method is facilitated by their curvilinear shapes. The bright curvilinear features are recognized as the ridges while the dark curvilinear features are classified as the leads. In dual-polarization HH or HV channel of C-band SAR imagery, the bright curvilinear feature may be false alarm because the frost flowers of young leads may show as bright pixels associated with changes in the surface salinity under calm surface conditions. Wind roughened leads also trigger the backscatter increasing that can be misclassified as ridges [1]. Thus the width limitation is considered in this proposed structure tensor method [2], since only shape feature based method is not enough for detecting ridges. The ridge detection algorithm is based on the hypothesis that the bright pixels are ridges with curvilinear shapes and the ridge width is less 30 meters. Benefited from GF-3 with high spatial resolution of 3 meters, we provide an enhanced structure tensor method for detecting the significant ridge. The preprocessing procedures including the calibration and incidence angle normalization are also investigated. The bright pixels will have strong response to the bandpass filtering. The ridge training samples are delineated from the SAR imagery in the Log-Gabor filters to construct structure tensor. From the tensor, the dominant orientation of the pixel representing the ridge is determined by the dominant eigenvector. For the post-processing of structure tensor, the elongated kernel is desired to enhance the ridge curvilinear shape. Since ridge presents along a certain direction, the ratio of the dominant eigenvector will be used to measure the intensity of local anisotropy. The convolution filter has been utilized in the constructed structure tensor is used to model spatial contextual information. Ridge detection results from GF-3 show the proposed method performs better compared to the

Satellite SAR imagery for site discovery, change detection and monitoring activities in cultural heritage sites: experiments on the Nasca region, Peru

Science.gov (United States)

Tapete, D.; Cigna, F.; Masini, N.; Lasaponara, R.

2012-04-01

Besides their suitability for multi-temporal and spatial deformation analysis, the Synthetic Aperture Radar (SAR) image archives acquired by space-borne radar sensors can be exploited to support archaeological investigations over huge sites, even those partially or totally buried and still to be excavated. Amplitude information is one of the main properties of SAR data from which it is possible to retrieve evidences of buried structures, using feature extraction and texture analysis. Multi-temporality allows the reconstruction of past and recent evolution of both landscape and built-up environment, with the possibility to detect natural and/or anthropogenic changes, including human-induced damages to the conservation of cultural heritage. We present the methodology and first results of the experiments currently undertaken using SAR data in the Nasca region (Southern Peru), where two important civilizations such as Paracas and Nasca developed and flourished from 4th century BC to the 6th century AD. The study areas include a wide spectrum of archaeological and environmental elements to be preserved, among which: the archaeological site of Cahuachi and its surroundings, considered the largest adobe Ceremonial Centre in the World; the Nasca lines and geoglyphs in the areas of Palpa, Atarco and Nasca; the ancient networks of aqueducts and drainage galleries in the Puquios area, built by Nasca in the 1st-6th centuries AD. Archaeological prospection and multi-purpose remote sensing activities are currently carried out in the framework of the Italian mission of heritage Conservation and Archaeogeophysics (ITACA), with the direct involvement of researchers from the Institute for Archaeological and Monumental Heritage and the Institute of Methodologies for Environmental Analysis, Italian National Research Council. In this context, C- and L-band SAR images covering the Nasca region since 2001 were identified for the purposes of this research and, in particular, the following

Wave directional spectrum from SAR imagery

Digital Repository Service at National Institute of Oceanography (India)

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

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

Wave directional spectrum from SAR imagery

Digital Repository Service at National Institute of Oceanography (India)

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

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

Rapid Response to a Typhoon-Induced Flood with an SAR-Derived Map of Inundated Areas: Case Study and Validation

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Hsiao-Wei Chung

2015-09-01

Full Text Available We report the successful case of a rapid response to a flash flood in I-Lan County of Taiwan with a map of inundated areas derived from COSMO-SkyMed 1 radar satellite imagery within 24 hours. The flood was caused by the intensive precipitation brought by Typhoon Soulik in July 2013. Based on the ensemble forecasts of trajectory, an urgent request of spaceborne SAR imagery was made 24 hours before Typhoon Soulik made landfall. Two COSMO-SkyMed images were successfully acquired when the center of Typhoon Soulik had just crossed the northern part of Taiwan. The standard level-1b product (radiometric-corrected, geometric-calibrated and orthorectified image was generated by using the off-the-shelf SARscape software. Following the same approach used with the Expert Landslide and Shadow Area Delineating System, the regional threshold of each tile image was determined to delineate still water surface and quasi-inundated areas in a fully-automatic manner. The results were overlaid on a digital elevation model, and the same tile was visually compared to an optical image taken by Formosat-2 before this event. With this ancillary information, the inundated areas were accurately and quickly identified. The SAR-derived map of inundated areas was published on a web-based platform powered by Google Earth within 24 hours, with the aim of supporting the decision-making process of disaster prevention and mitigation. A detailed validation was made afterwards by comparing the map with in situ data of the water levels at 17 stations. The results demonstrate the feasibility of rapidly responding to a typhoon-induced flood with a spaceborne SAR-derived map of inundated areas. A standard operating procedure was derived from this work and followed by the Water Hazard Mitigation Center of the Water Resources Agency, Taiwan, in subsequent typhoon seasons, such as Typhoon Trami (August, 2013 and Typhoon Soudelor (August, 2015.

Research on Strong Clutter Suppression for Gaofen-3 Dual-Channel SAR/GMTI

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Mingjie Zheng

2018-03-01

Full Text Available In spaceborne synthetic aperture radar (SAR, moving targets are almost buried in ground clutter due to the wide clutter Doppler spectrum and the restricted pulse repetition frequency (PRF, which increases the difficulty of moving target detection. Clutter suppression is one of the key issues in the spaceborne SAR moving target indicator operation. In this paper, we describe the clutter suppression principle and analyze the influence of amplitude and phase error on clutter suppression. In the following, a novel dual-channel SAR clutter suppression algorithm is proposed, which is suitable for the Gaofen-3(GF-3 SAR sensor. The proposed algorithm consists of three technique steps, namely adaptive two-dimensional (2D channel calibration, refined amplitude error correction and refined phase error correction. After channel error is corrected by these procedures, the clutter component, especially a strong clutter component, can be well suppressed. The validity of the proposed algorithm is verified by GF-3 SAR real data which demonstrates the ground moving-target indication (GMTI capability of GF-3 SAR sensor.

Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

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K. Andrea Scott

2015-09-01

Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR

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Sonia Asilo

2014-12-01

Full Text Available Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice

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

Science.gov (United States)

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

2014-12-01

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

New challenges for a SAR toolbox

International Nuclear Information System (INIS)

Loreaux, P.; Quin, G.

2013-01-01

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

Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

Science.gov (United States)

Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

2009-11-01

In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

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

Science.gov (United States)

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.

SAR Ambiguity Study for the Cassini Radar

Science.gov (United States)

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

1993-01-01

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

Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

Science.gov (United States)

Saatchi, Sassan; Moghaddam, Mahta

1995-01-01

In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

Science.gov (United States)

Qin, Rongjun

2014-10-01

Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are

Mapping and monitoring renewable resources with space SAR

Science.gov (United States)

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

1983-01-01

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

C-band solid state dual polarization T/R modules for airborne SAR systems

NARCIS (Netherlands)

Vermeulen, B.C.B.; Koomen, P.J.; Hoogeboom, P.; Snoeij, P.; Pouwels, H.

1996-01-01

The use of distributed power in a, on a phased array antenna based, SAR system offers new possibilities for the system operation. As a preparation for future spaceborne SAR systems using solid state transmitters with electronically steerable phased array antenna, the PHARUS system has been

Polarimetric scattering and SAR information retrieval

CERN Document Server

Jin, Ya-Qiu

2013-01-01

Taking an innovative look at Synthetic Aperture Radar (SAR), this practical reference fully covers new developments in SAR and its various methodologies and enables readers to interpret SAR imagery An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics. It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface. The book includes quantitative app

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

Science.gov (United States)

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

2018-04-01

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

Methods of flood extent mapping using SAR imagery in the Zambezi (Caprivi) Region, Namibia

CSIR Research Space (South Africa)

Kemp, J

2014-10-01

Full Text Available mapping using SAR imagery in the Zambezi (Caprivi) Region, Namibia Jaco Kemp1, Mariel Bessinger1, Melanie Luck-Vogel2 y o u r k n o w l e d g e p a r t n e r Department of Geography and Environmental Studies 2 Zambezi Region y o... u r k n o w l e d g e p a r t n e r Department of Geography and Environmental Studies 3 Zambezi Region y o u r k n o w l e d g e p a r t n e r Department of Geography and Environmental Studies 4 Zambezi...

Seasonal deformation and active landslide thickness revealed by spaceborne InSAR observations: a case study of Crescent lake landslide, WA

Science.gov (United States)

Hu, X.; Lu, Z.; Pierson, T. C.; Kramer, R.

2017-12-01

Understanding the precipitation triggering mechanism and quantifying the creeping landslide thickness are important to conduct early warnings and estimate potential failure volume and runout extent. However, it is problematic to use traditional geodetic methods to identify the active landslide boundaries and capture the transient mobility over hilly and vegetated landslide landscape. Here we present a novel InSAR processing strategy to characterize the spatial distribution and temporal behavior of the landslide movement in response to precipitation over Crescent lake landslide, WA using spaceborne SAR data of ALOS-1 PALSAR-1, ALOS-2 PALSAR-2 and Sentinel-1A. Time-series measurements reveal the seasonal deformation of landslide lobe, showing a much larger magnitude compared to the motion at lower elevated terrain expressed by an off-slide GPS station, suggesting an amplified hydrological loading effect associated with thick unconsolidated zone. Thanks to the high temporal resolution of Sentinel-1A and on-slide GPS data, we capture the progressive incipient motions in the wet season, characterized by the elastic slope-normal contraction due to loading during antecedent rainfall, followed by downslope slip and lateral propagation in less than one-month intense precipitation, because the elevated pore pressure and the reduced friction at the basal instigate the shear motion. The proposed threshold precipitation concept, in terms of the intensity and duration, can be an integral part of the landslide warning system. The active thickness can be inverted using three-dimensional (3D) displacement map based on the principle of mass conservation. We extract quasi-3D displacements using two independent (ascending and descending) InSAR measurements assuming that the targets move exclusively along the aspect direction on the slope-parallel plane. This routine of the extraction of quasi-3D displacement and the inversion of active lobe thickness can be utilized in the study of

Urban remote sensing in areas of conflict: TerraSAR-X and Sentinel-1 change detection in the Middle East

Science.gov (United States)

Tapete, Deodato; Cigna, Francesca

2016-08-01

Timely availability of images of suitable spatial resolution, temporal frequency and coverage is currently one of the major technical constraints on the application of satellite SAR remote sensing for the conservation of heritage assets in urban environments that are impacted by human-induced transformation. TerraSAR-X and Sentinel-1A, in this regard, are two different models of SAR data provision: very high resolution on-demand imagery with end user-selected acquisition parameters, on one side, and freely accessible GIS-ready products with intended regular temporal coverage, on the other. What this means for change detection analyses in urban areas is demonstrated in this paper via the experiment over Homs, the third largest city of Syria with an history of settlement since 2300 BCE, where the impacts of the recent civil war combine with pre- and post-conflict urban transformation . The potential performance of Sentinel-1A StripMap scenes acquired in an emergency context is simulated via the matching StripMap beam mode offered by TerraSAR-X. Benefits and limitations of the different radar frequency band, spatial resolution and single/multi-channel polarization are discussed, as a proof-of-concept of regular monitoring currently achievable with space-borne SAR in historic urban settings. Urban transformation observed across Homs in 2009, 2014 and 2015 shows the impact of the Syrian conflict on the cityscape and proves that operator-driven interpretation is required to understand the complexity of multiple and overlapping urban changes.

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

Directory of Open Access Journals (Sweden)

Fan Zhang

2016-04-01

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

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

Science.gov (United States)

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

2016-04-07

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

OIL SPILL DETECTION AND MONITORING OF ABU DHABI COASTAL ZONE USING KOMPSAT-5 SAR IMAGERY

Directory of Open Access Journals (Sweden)

H. A. Harahsheh

2016-06-01

Full Text Available Abu Dhabi Government endorsed vision for its Maritime Strategy ‘A safe, secure and sustainable maritime domain for Abu Dhabi'. This research study share this vision using the concept of monitoring as tool for marine protection against any possible oil pollution. The best technology to detect and monitor oil pollution and in particularly oil spill is SAR imagery In this case study we chose KOMPSAT-5 SAR. KOMPSAT-5 carries X-band SAR for earth observation, and is capable of day-and-night imaging under all weather condition. It provides three operation modes: High Resolution Mode to provide 1 m resolution, Standard Mode to provide 3 m resolution and Wide Swath Mode to provide 20 m resolution with 100 km swath at 550 km altitude, with four modes of polarization. KOMPSAT-5 provides products for various applications; security and defense, mapping, and natural resource management, environmental monitoring, disaster monitoring and more. For our case study we chose to work with Wide Swath mode (WS with Vertical polarization (VV to cover a wide area of interest located to the north west of Abu Dhabi including some important islands like ”Zirku Island”, and areas with oil production activities. The results of data acquired on 4th May 2015 show some spot of oil spill with length estimated about 3 KM, and the daily satellite data acquisition over the period July 24 through July 31 shows serious and many oil spill events some are small, but many others are considered to be big with area size around 20 km2. In the context of oil spill pollution in the seas, we have to consider the development and increase of overseas transportation, which is an important factor for both social and economic sectors. The harmful effects of marine pollution are numerous, from the damage of marine life to the damage of the aquatic ecosystem as whole. As such, the need for oil slick detection is crucial, for the location of polluted areas and to evaluate slick drift to

Oil Spill Detection and Monitoring of Abu Dhabi Coastal Zone Using KOMPSAT-5 SAR Imagery

Science.gov (United States)

Harahsheh, H. A.

2016-06-01

Abu Dhabi Government endorsed vision for its Maritime Strategy `A safe, secure and sustainable maritime domain for Abu Dhabi'. This research study share this vision using the concept of monitoring as tool for marine protection against any possible oil pollution. The best technology to detect and monitor oil pollution and in particularly oil spill is SAR imagery In this case study we chose KOMPSAT-5 SAR. KOMPSAT-5 carries X-band SAR for earth observation, and is capable of day-and-night imaging under all weather condition. It provides three operation modes: High Resolution Mode to provide 1 m resolution, Standard Mode to provide 3 m resolution and Wide Swath Mode to provide 20 m resolution with 100 km swath at 550 km altitude, with four modes of polarization. KOMPSAT-5 provides products for various applications; security and defense, mapping, and natural resource management, environmental monitoring, disaster monitoring and more. For our case study we chose to work with Wide Swath mode (WS) with Vertical polarization (VV) to cover a wide area of interest located to the north west of Abu Dhabi including some important islands like "Zirku Island", and areas with oil production activities. The results of data acquired on 4th May 2015 show some spot of oil spill with length estimated about 3 KM, and the daily satellite data acquisition over the period July 24 through July 31 shows serious and many oil spill events some are small, but many others are considered to be big with area size around 20 km2. In the context of oil spill pollution in the seas, we have to consider the development and increase of overseas transportation, which is an important factor for both social and economic sectors. The harmful effects of marine pollution are numerous, from the damage of marine life to the damage of the aquatic ecosystem as whole. As such, the need for oil slick detection is crucial, for the location of polluted areas and to evaluate slick drift to protect the coastline

Mapping Palaeohydrography in Deserts: Contribution from Space-Borne Imaging Radar

Directory of Open Access Journals (Sweden)

Philippe Paillou

2017-03-01

Full Text Available Space-borne Synthetic Aperture Radar (SAR has the capability to image subsurface features down to several meters in arid regions. A first demonstration of this capability was performed in the Egyptian desert during the early eighties, thanks to the first Shuttle Imaging Radar mission. Global coverage provided by recent SARs, such as the Japanese ALOS/PALSAR sensor, allowed the mapping of vast ancient hydrographic systems in Northern Africa. We present a summary of palaeohydrography results obtained using PALSAR data over large deserts such as the Sahara and the Gobi. An ancient river system was discovered in eastern Lybia, connecting in the past the Kufrah oasis to the Mediterranean Sea, and the terminal part of the Tamanrasett river was mapped in western Mauritania, ending with a large submarine canyon. In southern Mongolia, PALSAR images combined with topography analysis allowed the mapping of the ancient Ulaan Nuur lake. We finally show the potentials of future low frequency SAR sensors by comparing L-band (1.25 GHz and P-band (435 MHz airborne SAR acquisitions over a desert site in southern Tunisia.

Demonstrator for Automatic Target Classification in SAR Imagery

NARCIS (Netherlands)

Wit, J.J.M. de; Broek, A.C. van den; Dekker, R.J.

2006-01-01

Due to the increasing use of unmanned aerial vehicles (UAV) for reconnaissance, surveillance, and target acquisition applications, the interest in synthetic aperture radar (SAR) systems is growing. In order to facilitate the processing of the enormous amount of SAR data on the ground, automatic

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

Science.gov (United States)

Gies, Tobias; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey

2014-05-01

1. Introduction Numerous large-scale offshore wind farms have been built in European waters and play an important role in providing renewable energy. Therefore, knowledge of behavior of wakes, induced by large wind turbines and their impact on wind power output is important. The spatial variation of offshore wind turbine wake is very complex, depending on wind speed, wind direction, ambient atmospheric turbulence and atmospheric stability. In this study we demonstrate the application of X-band TerraSAR-X (TS-X) data with high spatial resolution for studies on wind turbine wakes in the near and far field of the offshore wind farm Alpha Ventus, located in the North Sea. Two cases which different weather conditions and different wake pattern as observed in the TS-X image are presented. 2. Methods The space-borne synthetic aperture radar (SAR) is a unique sensor that provides two-dimensional information on the ocean surface. Due to their high resolution, daylight and weather independency and global coverage, SARs are particularly suitable for many ocean and coastal applications. SAR images reveal wind variations on small scales and thus represent a valuable means in detailed wind-field analysis. The general principle of imaging turbine wakes is that the reduced wind speed downstream of offshore wind farms modulates the sea surface roughness, which in turn changes the Normalized Radar Cross Section (NRCS, denoted by σ0) in the SAR image and makes the wake visible. In this study we present two cases at the offshore wind farm Alpha Ventus to investigate turbine-induced wakes and the retrieved sea surface wind field. Using the wind streaks, visible in the TS-X image and the shadow behind the offshore wind farm, induced by turbine wake, the sea surface wind direction is derived and subsequently the sea surface wind speed is calculated using the latest generation of wind field algorithm XMOD2. 3. Case study alpha ventus Alpha Ventus is located approximately 45 km from the

Structural Health and Stability Assessment of High-Speed Railways via Thermal Dilation Mapping With Time-Series InSAR Analysis

NARCIS (Netherlands)

Qin, Xiaoqiong; Liao, Mingsheng; Zhang, L; Yang, M.

2017-01-01

Thermal dilation is a vital component of deformation along the extensive railway network infrastructure. To monitor subtle deformation, the synthetic aperture radar interferometry (InSAR) technique has been adopted as a space-borne geodetic tool. However, InSAR applications in railway stability

Mapping mountain meadow with high resolution and polarimetric SAR data

International Nuclear Information System (INIS)

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

2014-01-01

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

Oil Spill detection off the eastern coast of India using Sentinel-1 dual polarimeteric SAR imagery

Science.gov (United States)

De, S.; Bhattacharya, A.; Gautam, R.

2017-12-01

Among the various Earth observing sensors, the spaceborne Polarimetric Synthetic Aperture Radar (PolSAR) is considered as one of the most flexible and has been widely used in disaster response applications due to its all-weather illumination independent capability. Sentinel-1 is a two-satellite constellation with a C-band polarimetric Synthetic Aperture Radar (PolSAR) sensor, which provides global coverage with a 12-day repeat cycle in the same acquisition geometry, and the possibility of a 3-day repeat imaging in independent geometry, making it ideal for operational geodynamic monitoring. The proposed study aims to detect changes in polarimetric parameters associated with an oil spill event occurred off the coast of Ennore, Tamil Nadu, India (13.228° N Lon: 80.363° E ) on 28 January 2017. The initial spill covered an area of approximately 7.26 sq. km, spreading to an area of 12.56 sq. km. in a single day. The spread was mainly attributed to the strong shore parallel southerly current. To this end, two PolSAR images were used from before and after the event acquired on 17 and 29 January 2017, respectively in dual-polarimetric (VV,VH) interferometric wide swath mode and with same acquisition geometry. The images are first calibrated, co-registered and terrain corrected to make them comparable in a geo-coordinate framework. A refined Lee speckle filter is applied with a 5x5 window to reduce the influence of coherent speckle. The pair of images are then used to generate a hellinger distance based change index corresponding to each polarimetric channel. The indices are then applied as input to a Convolutional Neural Network (CNN) with the objective of discriminating the areas corresponding to changes due to the oil spill, movement of ships, rough ocean surface etc. The final result is a binary change detection map of the oil spill area. The results obtained were compared with that obtained by survey of the affected oil spill area by the Integrated Coastal and Marine

High resolution radar satellite imagery analysis for safeguards applications

Energy Technology Data Exchange (ETDEWEB)

Minet, Christian; Eineder, Michael [German Aerospace Center, Remote Sensing Technology Institute, Department of SAR Signal Processing, Wessling, (Germany); Rezniczek, Arnold [UBA GmbH, Herzogenrath, (Germany); Niemeyer, Irmgard [Forschungszentrum Juelich, Institue of Energy and Climate Research, IEK-6: Nuclear Waste Management and Reactor Safety, Juelich, (Germany)

2011-12-15

For monitoring nuclear sites, the use of Synthetic Aperture Radar (SAR) imagery shows essential promises. Unlike optical remote sensing instruments, radar sensors operate under almost all weather conditions and independently of the sunlight, i.e. time of the day. Such technical specifications are required both for continuous and for ad-hoc, timed surveillance tasks. With Cosmo-Skymed, TerraSARX and Radarsat-2, high-resolution SAR imagery with a spatial resolution up to 1m has recently become available. Our work therefore aims to investigate the potential of high-resolution TerraSAR data for nuclear monitoring. This paper focuses on exploiting amplitude of a single acquisition, assessing amplitude changes and phase differences between two acquisitions, and PS-InSAR processing of an image stack.

CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

Directory of Open Access Journals (Sweden)

T. Alipour Fard

2014-10-01

Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

Sea-Ice Feature Mapping using JERS-1 Imagery

Science.gov (United States)

Maslanik, James; Heinrichs, John

1994-01-01

JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

Forest parameter estimation using polarimetric SAR interferometry techniques at low frequencies

International Nuclear Information System (INIS)

Lee, Seung-Kuk

2013-01-01

Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) is an active radar remote sensing technique based on the coherent combination of both polarimetric and interferometric observables. The Pol-InSAR technique provided a step forward in quantitative forest parameter estimation. In the last decade, airborne SAR experiments evaluated the potential of Pol-InSAR techniques to estimate forest parameters (e.g., the forest height and biomass) with high accuracy over various local forest test sites. This dissertation addresses the actual status, potentials and limitations of Pol-InSAR inversion techniques for 3-D forest parameter estimations on a global scale using lower frequencies such as L- and P-band. The multi-baseline Pol-InSAR inversion technique is applied to optimize the performance with respect to the actual level of the vertical wave number and to mitigate the impact of temporal decorrelation on the Pol-InSAR forest parameter inversion. Temporal decorrelation is a critical issue for successful Pol-InSAR inversion in the case of repeat-pass Pol-InSAR data, as provided by conventional satellites or airborne SAR systems. Despite the limiting impact of temporal decorrelation in Pol-InSAR inversion, it remains a poorly understood factor in forest height inversion. Therefore, the main goal of this dissertation is to provide a quantitative estimation of the temporal decorrelation effects by using multi-baseline Pol-InSAR data. A new approach to quantify the different temporal decorrelation components is proposed and discussed. Temporal decorrelation coefficients are estimated for temporal baselines ranging from 10 minutes to 54 days and are converted to height inversion errors. In addition, the potential of Pol-InSAR forest parameter estimation techniques is addressed and projected onto future spaceborne system configurations and mission scenarios (Tandem-L and BIOMASS satellite missions at L- and P-band). The impact of the system parameters (e.g., bandwidth

Mapping alteration using imagery from the Tiangong-1 hyperspectral spaceborne system: Example for the Jintanzi gold province, China

Science.gov (United States)

Liu, Lei; Feng, Jilu; Rivard, Benoit; Xu, Xinliang; Zhou, Jun; Han, Ling; Yang, Junlu; Ren, Guangli

2018-02-01

The Tiangong-1 Hyperspectral Imager (HSI) is a relatively new spaceborne hyperspectral remote sensing system that was launched by the Chinese government on September 29th 2011. The system has 64 shortwave infrared (SWIR) spectral bands (1000-2500 nm) and imagery is at a spatial resolution of 20 m. This study represents an evaluation of Tiangong-1 data for the production of alteration mineral maps. Alteration mineral maps resulting from the analysis of Tiangong-1 HSI data and airborne SASI (Shortwave infrared Airborne Spectrographic Imager) data are compared for the Jintanzi area, Beishan, Gansu province, northwest China where gold bearing veins are documented. The results illustrate the detection of muscovite, kaolinite, chlorite, epidote, calcite and dolomite from Tiangong-1 HSI data and most anomalies seen in the airborne SASI data are captured. The Tiangong-1 data appears to be well suited for the detection of surface mineralogy in support of regional mapping and exploration. The data complements that which will be offered by the Chinese GF-5 Hyperspectral Imager and the German EnMAP system, both scheduled for launch in 2018.

New Processing of Spaceborne Imaging Radar-C (SIR-C) Data

Science.gov (United States)

Meyer, F. J.; Gracheva, V.; Arko, S. A.; Labelle-Hamer, A. L.

2017-12-01

The Spaceborne Imaging Radar-C (SIR-C) was a radar system, which successfully operated on two separate shuttle missions in April and October 1994. During these two missions, a total of 143 hours of radar data were recorded. SIR-C was the first multifrequency and polarimetric spaceborne radar system, operating in dual frequency (L- and C- band) and with quad-polarization. SIR-C had a variety of different operating modes, which are innovative even from today's point of view. Depending on the mode, it was possible to acquire data with different polarizations and carrier frequency combinations. Additionally, different swaths and bandwidths could be used during the data collection and it was possible to receive data with two antennas in the along-track direction.The United States Geological Survey (USGS) distributes the synthetic aperture radar (SAR) images as single-look complex (SLC) and multi-look complex (MLC) products. Unfortunately, since June 2005 the SIR-C processor has been inoperable and not repairable. All acquired SLC and MLC images were processed with a course resolution of 100 m with the goal of generating a quick look. These images are however not well suited for scientific analysis. Only a small percentage of the acquired data has been processed as full resolution SAR images and the unprocessed high resolution data cannot be processed any more at the moment.At the Alaska Satellite Facility (ASF) a new processor was developed to process binary SIR-C data to full resolution SAR images. ASF is planning to process the entire recoverable SIR-C archive to full resolution SLCs, MLCs and high resolution geocoded image products. ASF will make these products available to the science community through their existing data archiving and distribution system.The final paper will describe the new processor and analyze the challenges of reprocessing the SIR-C data.

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

Science.gov (United States)

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

2018-04-01

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

Classification of sea-ice types in SAR imagery

International Nuclear Information System (INIS)

Baraldi, A.; Parmiggiani, F.

2001-01-01

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

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

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C. Ozkan

2012-07-01

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

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

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Shuangshang Zhang

2017-11-01

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

SAR Imaging through the Earth’s Ionosphere

Science.gov (United States)

2013-11-06

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

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

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C. Li

2018-04-01

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

Image based SAR product simulation for analysis

Science.gov (United States)

Domik, G.; Leberl, F.

1987-01-01

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

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

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Simon Plank

2016-04-01

Full Text Available Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth’s landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

Slope Superficial Displacement Monitoring by Small Baseline SAR Interferometry Using Data from L-band ALOS PALSAR and X-band TerraSAR: A Case Study of Hong Kong, China

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Fulong Chen

2014-02-01

Full Text Available Owing to the development of spaceborne synthetic aperture radar (SAR platforms, and in particular the increase in the availability of multi-source (multi-band and multi-resolution data, it is now feasible to design a surface displacement monitoring application using multi-temporal SAR interferometry (MT-InSAR. Landslides have high socio-economic impacts in many countries because of potential geo-hazards and heavy casualties. In this study, taking into account the merits of ALOS PALSAR (L-band, good coherence preservation and TerraSAR (X-band, high resolution and short revisit times data, we applied an improved small baseline InSAR (SB-InSAR with 3-D phase unwrapping approach, to monitor slope superficial displacement in Hong Kong, China, a mountainous subtropical zone city influenced by over-urbanization and heavy monsoonal rains. Results revealed that the synergistic use of PALSAR and TerraSAR data produces different outcomes in relation to data reliability and spatial-temporal resolution, and hence could be of significant value for a comprehensive understanding and monitoring of unstable slopes.

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

Science.gov (United States)

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

Monitoring the ongoing deformation and seasonal behaviour affecting Mosul Dam through space-borne SAR data

Science.gov (United States)

Tessari, G.; Riccardi, P.; Pasquali, P.

2017-12-01

Monitoring of dam structural health is an important practice to control the structure itself and the water reservoir, to guarantee efficient operation and safety of surrounding areas. Ensuring the longevity of the structure requires the timely detection of any behaviour that could deteriorate the dam and potentially result in its shutdown or failure.The detection and monitoring of surface displacements is increasingly performed through the analysis of satellite Synthetic Aperture Radar (SAR) data, thanks to the non-invasiveness of their acquisition, the possibility to cover large areas in a short time and the new space missions equipped with high spatial resolution sensors. The availability of SAR satellite acquisitions from the early 1990s enables to reconstruct the historical evolution of dam behaviour, defining its key parameters, possibly from its construction to the present. Furthermore, the progress on SAR Interferometry (InSAR) techniques through the development of Differential InSAR (DInSAR) and Advanced stacking techniques (A-DInSAR) allows to obtain accurate velocity maps and displacement time-series.The importance of these techniques emerges when environmental or logistic conditions do not allow to monitor dams applying the traditional geodetic techniques. In such cases, A-DInSAR constitutes a reliable diagnostic tool of dam structural health to avoid any extraordinary failure that may lead to loss of lives.In this contest, an emblematic case will be analysed as test case: the Mosul Dam, the largest Iraqi dam, where monitoring and maintaining are impeded for political controversy, causing possible risks for the population security. In fact, it is considered one of the most dangerous dams in the world because of the erosion of the gypsum rock at the basement and the difficult interventions due to security problems. The dam consists of 113 m tall and 3.4 km long earth-fill embankment-type, with a clay core, and it was completed in 1984.The deformation

Research on Synthetic Aperture Radar Processing for the Spaceborne Sliding Spotlight Mode.

Science.gov (United States)

Shen, Shijian; Nie, Xin; Zhang, Xinggan

2018-02-03

Gaofen-3 (GF-3) is China' first C-band multi-polarization synthetic aperture radar (SAR) satellite, which also provides the sliding spotlight mode for the first time. Sliding-spotlight mode is a novel mode to realize imaging with not only high resolution, but also wide swath. Several key technologies for sliding spotlight mode in spaceborne SAR with high resolution are investigated in this paper, mainly including the imaging parameters, the methods of velocity estimation and ambiguity elimination, and the imaging algorithms. Based on the chosen Convolution BackProjection (CBP) and PFA (Polar Format Algorithm) imaging algorithms, a fast implementation method of CBP and a modified PFA method suitable for sliding spotlight mode are proposed, and the processing flows are derived in detail. Finally, the algorithms are validated by simulations and measured data.

Research on Synthetic Aperture Radar Processing for the Spaceborne Sliding Spotlight Mode

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Shijian Shen

2018-02-01

Full Text Available Gaofen-3 (GF-3 is China’ first C-band multi-polarization synthetic aperture radar (SAR satellite, which also provides the sliding spotlight mode for the first time. Sliding-spotlight mode is a novel mode to realize imaging with not only high resolution, but also wide swath. Several key technologies for sliding spotlight mode in spaceborne SAR with high resolution are investigated in this paper, mainly including the imaging parameters, the methods of velocity estimation and ambiguity elimination, and the imaging algorithms. Based on the chosen Convolution BackProjection (CBP and PFA (Polar Format Algorithm imaging algorithms, a fast implementation method of CBP and a modified PFA method suitable for sliding spotlight mode are proposed, and the processing flows are derived in detail. Finally, the algorithms are validated by simulations and measured data.

Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site

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Federica Bardi

2016-03-01

Full Text Available This work concerns a proposal of the integration of InSAR (Interferometric Synthetic Aperture Radar data acquired by ground-based (GB and satellite platforms. The selected test site is the Åknes rockslide, which affects the western Norwegian coast. The availability of GB-InSAR and satellite InSAR data and the accessibility of a wide literature make the landslide suitable for testing the proposed procedure. The first step consists of the organization of a geodatabase, performed in the GIS environment, containing all of the available data. The second step concerns the analysis of satellite and GB-InSAR data, separately. Two datasets, acquired by RADARSAT-2 (related to a period between October 2008 and August 2013 and by a combination of TerraSAR-X and TanDEM-X (acquired between July 2010 and October 2012, both of them in ascending orbit, processed applying SBAS (Small BAseline Subset method, are available. GB-InSAR data related to five different campaigns of measurements, referred to the summer seasons of 2006, 2008, 2009, 2010 and 2012, are available, as well. The third step relies on data integration, performed firstly from a qualitative point of view and later from a semi-quantitative point of view. The results of the proposed procedure have been validated by comparing them to GPS (Global Positioning System data. The proposed procedure allowed us to better define landslide sectors in terms of different ranges of displacements. From a qualitative point of view, stable and unstable areas have been distinguished. In the sector concerning movement, two different sectors have been defined thanks to the results of the semi-quantitative integration step: the first sector, concerning displacement values higher than 10 mm, and the 2nd sector, where the displacements did not exceed a 10-mm value of displacement in the analyzed period.

Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India

OpenAIRE

Pazhanivelan, S.; Kannan, P.; Christy Nirmala Mary, P.; Subramanian, E.; Jeyaraman, S.; Nelson, A.; Setiyono, T.; Holecz, F.; Barbieri, M.; Yadav, M.

2015-01-01

Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used...

Spaceborne synthetic aperture radar: Current status and future directions. A report to the Committee on Earth Sciences, Space Studies Board, National Research Council

Science.gov (United States)

Evans, D. L. (Editor); Apel, J.; Arvidson, R.; Bindschadler, R.; Carsey, F.; Dozier, J.; Jezek, K.; Kasischke, E.; Li, F.; Melack, J.

1995-01-01

This report provides a context in which questions put forth by NASA's Office of Mission to Planet Earth (OMPTE) regarding the next steps in spaceborne synthetic aperture radar (SAR) science and technology can be addressed. It summarizes the state-of-the-art in theory, experimental design, technology, data analysis, and utilization of SAR data for studies of the Earth, and describes potential new applications. The report is divided into five science chapters and a technology assessment. The chapters summarize the value of existing SAR data and currently planned SAR systems, and identify gaps in observational capabilities needing to be filled to address the scientific questions. Cases where SAR provides complementary data to other (non-SAR) measurement techniques are also described. The chapter on technology assessment outlines SAR technology development which is critical not only to NASA's providing societally relevant geophysical parameters but to maintaining competitiveness in SAR technology, and promoting economic development.

SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

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Yang Wei

2015-02-01

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

Multi-image Matching of Airborne SAR Imagery by SANCC

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DING Hao

2015-03-01

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

Spaceborne Potential for Examining Taiga-Tundra Ecotone Form and Vulnerability

Science.gov (United States)

Montesano, Paul M.; Sun, Guoqing; Dubayah, Ralph O.; Ranson, K. Jon

2016-01-01

In the taiga-tundra ecotone (TTE), site-dependent forest structure characteristics can influence the subtle and heterogeneous structural changes that occur across the broad circumpolar extent. Such changes may be related to ecotone form, described by the horizontal and vertical patterns of forest structure (e.g., tree cover, density and height) within TTE forest patches, driven by local site conditions, and linked to ecotone dynamics. The unique circumstance of subtle, variable and widespread vegetation change warrants the application of spaceborne data including high-resolution (less than 5m) spaceborne imagery (HRSI) across broad scales for examining TTE form and predicting dynamics. This study analyzes forest structure at the patch-scale in the TTE to provide a means to examine both vertical and horizontal components of ecotone form. We demonstrate the potential of spaceborne data for integrating forest height and density to assess TTE form at the scale of forest patches across the circumpolar biome by (1) mapping forest patches in study sites along the TTE in northern Siberia with a multi-resolution suite of spaceborne data, and (2) examining the uncertainty of forest patch height from this suite of data across sites of primarily diffuse TTE forms. Results demonstrate the opportunities for improving patch-scale spaceborne estimates of forest height, the vertical component of TTE form, with HRSI. The distribution of relative maximum height uncertainty based on prediction intervals is centered at approximately 40%, constraining the use of height for discerning differences in forest patches. We discuss this uncertainty in light of a conceptual model of general ecotone forms, and highlight how the uncertainty of spaceborne estimates of height can contribute to the uncertainty in identifying TTE forms. A focus on reducing the uncertainty of height estimates in forest patches may improve depiction of TTE form, which may help explain variable forest responses in the

Data Analytics for SAR

Energy Technology Data Exchange (ETDEWEB)

Murphy, David Patrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Calef, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-10-02

We assess the ability of variants of anomalous change detection (ACD) to identify human activity associated with large outdoor music festivals as they are seen from synthetic aperture radar (SAR) imagery collected by the Sentinel-1 satellite constellation. We found that, with appropriate feature vectors, ACD using random-forest machine learning was most effective at identifying changes associated with the human activity.

An Unsupervised Method of Change Detection in Multi-Temporal PolSAR Data Using a Test Statistic and an Improved K&I Algorithm

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Jinqi Zhao

2017-12-01

Full Text Available In recent years, multi-temporal imagery from spaceborne sensors has provided a fast and practical means for surveying and assessing changes in terrain surfaces. Owing to the all-weather imaging capability, polarimetric synthetic aperture radar (PolSAR has become a key tool for change detection. Change detection methods include both unsupervised and supervised methods. Supervised change detection, which needs some human intervention, is generally ineffective and impractical. Due to this limitation, unsupervised methods are widely used in change detection. The traditional unsupervised methods only use a part of the polarization information, and the required thresholding algorithms are independent of the multi-temporal data, which results in the change detection map being ineffective and inaccurate. To solve these problems, a novel method of change detection using a test statistic based on the likelihood ratio test and the improved Kittler and Illingworth (K&I minimum-error thresholding algorithm is introduced in this paper. The test statistic is used to generate the comparison image (CI of the multi-temporal PolSAR images, and improved K&I using a generalized Gaussian model simulates the distribution of the CI. As a result of these advantages, we can obtain the change detection map using an optimum threshold. The efficiency of the proposed method is demonstrated by the use of multi-temporal PolSAR images acquired by RADARSAT-2 over Wuhan, China. The experimental results show that the proposed method is effective and highly accurate.

Locating and defining underground goaf caused by coal mining from space-borne SAR interferometry

Science.gov (United States)

Yang, Zefa; Li, Zhiwei; Zhu, Jianjun; Yi, Huiwei; Feng, Guangcai; Hu, Jun; Wu, Lixin; Preusse, Alex; Wang, Yunjia; Papst, Markus

2018-01-01

It is crucial to locate underground goafs (i.e., mined-out areas) resulting from coal mining and define their spatial dimensions for effectively controlling the induced damages and geohazards. Traditional geophysical techniques for locating and defining underground goafs, however, are ground-based, labour-consuming and costly. This paper presents a novel space-based method for locating and defining the underground goaf caused by coal extraction using Interferometric Synthetic Aperture Radar (InSAR) techniques. As the coal mining-induced goaf is often a cuboid-shaped void and eight critical geometric parameters (i.e., length, width, height, inclined angle, azimuth angle, mining depth, and two central geodetic coordinates) are capable of locating and defining this underground space, the proposed method reduces to determine the eight geometric parameters from InSAR observations. Therefore, it first applies the Probability Integral Method (PIM), a widely used model for mining-induced deformation prediction, to construct a functional relationship between the eight geometric parameters and the InSAR-derived surface deformation. Next, the method estimates these geometric parameters from the InSAR-derived deformation observations using a hybrid simulated annealing and genetic algorithm. Finally, the proposed method was tested with both simulated and two real data sets. The results demonstrate that the estimated geometric parameters of the goafs are accurate and compatible overall, with averaged relative errors of approximately 2.1% and 8.1% being observed for the simulated and the real data experiments, respectively. Owing to the advantages of the InSAR observations, the proposed method provides a non-contact, convenient and practical method for economically locating and defining underground goafs in a large spatial area from space.

Application of Artificial Neural Networks to Ship Detection from X-Band Kompsat-5 Imagery

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Jeong-In Hwang

2017-09-01

Full Text Available For ship detection, X-band synthetic aperture radar (SAR imagery provides very useful data, in that ship targets look much brighter than surrounding sea clutter due to the corner-reflection effect. However, there are many phenomena which bring out false detection in the SAR image, such as noise of background, ghost phenomena, side-lobe effects and so on. Therefore, when ship-detection algorithms are carried out, we should consider these effects and mitigate them to acquire a better result. In this paper, we propose an efficient method to detect ship targets from X-band Kompsat-5 SAR imagery using the artificial neural network (ANN. The method produces the ship-probability map using ANN, and then detects ships from the ship-probability map by using a threshold value. For the purpose of getting an improved ship detection, we strived to produce optimal input layers used for ANN. In order to reduce phenomena related to the false detections, the non-local (NL-means filter and median filter were utilized. The NL-means filter effectively reduced noise on SAR imagery without smoothing edges of the objects, and the median filter was used to remove ship targets in SAR imagery. Through the filtering approaches, we generated two input layers from a Kompsat-5 SAR image, and created a ship-probability map via ANN from the two input layers. When the threshold value of 0.67 was imposed on the ship-probability map, the result of ship detection from the ship-probability map was a 93.9% recall, 98.7% precision and 6.1% false alarm rate. Therefore, the proposed method was successfully applied to the ship detection from the Kompsat-5 SAR image.

Active Satellite Sensors for the needs of Cultural Heritage: Introducing SAR applications in Cyprus through ATHENA project

Science.gov (United States)

Kouhartsiouk, Demetris; Agapiou, Athos; Lynsadrou, Vasiliki; Themistocleous, Kyriacos; Nisantzi, Argyro; Hadjimitsis, Diofantos G.; Lasaponara, Rosa; Masini, Nicola; Brcic, Ramon; Eineder, Michael; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter

2017-04-01

Non-invasive landscape investigation for archaeological purposes includes a wide range of survey techniques, most of which include in-situ methods. In the recent years, a major advance in the non-invasive surveying techniques has been the introduction of active remote sensing technologies. One of such technologies is spaceborne radar, known as Synthetic Aperture Radar (SAR). SAR has proven to be a valuable tool in the analysis of potential archaeological marks and in the systematic cultural heritage site monitoring. With the use of SAR, it is possible to monitor slight variations in vegetation and soil often interpreted as archaeological signs, while radar sensors frequently having penetrating capabilities offering an insight into shallow underground remains. Radar remote sensing for immovable cultural heritage and archaeological applications has been recently introduced to Cyprus through the currently ongoing ATHENA project. ATHENA project, under the Horizon 2020 programme, aims at building a bridge between research institutions of the low performing Member States and internationally-leading counterparts at EU level, mainly through training workshops and a series of knowledge transfer activities, frequently taking place on the basis of capacity development. The project is formed as the consortium of the Remote Sensing and Geo-Environment Research Laboratory of the Cyprus University of Technology (CUT), the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR). As part of the project, a number of cultural heritage sites in Cyprus have been studied testing different methodologies involving SAR imagery such as Amplitude Change Detection, Coherence Calculation and fusion techniques. The ATHENA's prospective agenda includes the continuation of the capacity building programme with upcoming training workshops to take place while expanding the knowledge of radar applications on conservation and risk monitoring of cultural heritage sites through

TOWARDS CHANGE DETECTION IN URBAN AREA BY SAR INTERFEROMETRY AND RADARGRAMMETRY

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C. Dubois

2013-04-01

Full Text Available Change detection in urban area is an active topic in remote sensing. However, well-dealt subject in optical remote sensing, this research topic is still at an early stage and needs deeper investigations and improvement in what concerns SAR and InSAR remote sensing. Due to their weather and daylight-independency, SAR sensors allow an all-time observation of the earth. This is determining in cases where rapid change detection is required after a natural – or technological – disaster. Due to the high resolution that can be achieved, the new generation of space-borne radar sensors opens up new perspectives for analysing buildings in urban areas. Moreover, due to their short revisiting cycle, they give rise to monitoring and change detection applications. In this paper, we present a concept for change detection in urban area at building level, relying only on SAR- and InSAR data. In this approach, interferometric and radargrammetric SAR data are merged in order to detect changes. Here, we present the overall workflow, the test area, the required data as well as first findings on the best-suited stereo-configurations for change detection.

Confined aquifer head measurements and storage properties in the San Luis Valley, Colorado, from spaceborne InSAR observations

Science.gov (United States)

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

2016-05-01

Interferometric Synthetic Aperture Radar (InSAR), a remote sensing technique for measuring centimeter-level surface deformation, is used to estimate hydraulic head in the confined aquifer of the San Luis Valley (SLV), Colorado. Reconstructing head measurements from InSAR in agricultural regions can be difficult, as InSAR phase data are often decorrelated due to vegetation growth. Analysis of 17 L-band ALOS PALSAR scenes, acquired between January 2007 and March 2011, demonstrates that comprehensive InSAR deformation measurements can be recovered over the vegetated groundwater basin with an improved processing strategy. Local skeletal storage coefficients and time delays between the head change and deformation are estimated through a joint InSAR-well data analysis. InSAR subsidence estimates are transformed to head changes with finer temporal and spatial resolution than is possible using existing well records alone. Both InSAR and well data suggest that little long-term water-storage loss occurred in the SLV over the study period and that inelastic compaction was negligible. The seasonal head variations derived from InSAR are consistent with the existing well data at most locations where confined aquifer pumping activity dominates. Our results demonstrate the advantages of InSAR measurements for basin-wide characterization of aquifer storage properties and groundwater levels over agricultural regions.

SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

Energy Technology Data Exchange (ETDEWEB)

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

2010-05-22

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

The 2006-2012 deformation at Sakurajima stratovolcano (Japan) detected via spaceborne multisensor SAR Interferometry

Science.gov (United States)

Pepe, Susi; Trippanera, Daniele; Casu, Francesco; Tizzani, Pietro; Nobile, Adriano; Aoki, Yosuke; Zoffoli, Simona; Acocella, Valerio; Sansosti, Eugenio

2013-04-01

We analyze the evolution of the ground deformation at Sakurajima active stratovolcano located in the Aira caldera (Kagoshima prefecture Japan). This caldera, extending over more than 20 km, has been formed as a consequence of a huge eruption, occurred 22,000 years ago, that caused a magma chamber collapse. The Sakurajima volcano is an andesitic cone formed by more recent activity within the caldera, beginning about 13,000 years ago. Its first historical recorded eruption occurred in 963 AD. Most eruptions are Strombolian and Vulcanian and affect only the summit area. The larger explosive (plinian) eruptions occurred in 1471-1476, 1779-1782 and 1914, each producing 1 - 2 km3 of lava and pyroclastic materials. Explosive eruptions of Vulcanian type, with ash emissions, have occurred intermittently from 1955 to 2002. From 2009 to December 2012, a strong and continuous period of volcanic activity has been recorded mainly at the Showa Crater producing plumes that reached altitudes of 1.8-3.5 km. In order to analyze the active deformation processes of the volcano complex and its surrounding areas, we performed SAR Interferometry (InSAR) techniques by using COSMOSkyMed (X-band) and ALOS (L-band) data. The joint data analysis allowed us to increase the spatial coverage of InSAR measurements., we processed 19 descending and 25 ascending orbit SAR images acquired by ALOS satellite from 2008 to 2011 and 2006 to 2011, respectively; we computed 57 descending and 71 ascending interferograms which were subsequently inverted via SBAS-InSAR algorithm to obtain mean velocity maps and deformation time series. The X-band dataset consists of 20 images acquired only on descending orbits between 2011 and 2012; from this dataset we computed 44 interferograms. The preliminary analysis of the mean deformation velocity reveals the presence of a consistent uplift signal in the North region of the Sakurajima Island that extends also to the North sector of Kagoshima bay. The corresponding

Towards monitoring surface and subsurface lakes on the Greenland Ice Sheet using Sentinel-1 SAR and Landsat-8 OLI imagery

Science.gov (United States)

Miles, Katie E.; Willis, Ian C.; Benedek, Corinne L.; Williamson, Andrew G.; Tedesco, Marco

2017-07-01

Supraglacial lakes are an important component of the Greenland Ice Sheet’s mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) satellite to investigate supraglacial lakes in West Greenland. A semi-automated algorithm is developed to detect surface lakes from Sentinel-1 images during the 2015 summer. A combined Landsat-8 and Sentinel-1 dataset, which has a comparable temporal resolution to MODIS (3 days versus daily) but a higher spatial resolution (25-40 m versus 250-500 m), is then used together with a fully-automated lake drainage detection algorithm. Rapid (days) and slow (> 4 days) drainages are investigated for both small (summer. Drainage events of small lakes occur at lower elevations (mean 159 m), and slightly earlier (mean 4.5 days) in the melt season than those of large lakes. The analysis is extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August; 1270 m mean elevation). Finally, the Sentinel-1 imagery is used to detect subsurface lakes and, for the first time, their dates of appearance and freeze-through (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface lakes detected in this study (mean 1593 m and 1185 m, respectively). Sentinel-1 imagery therefore provides great potential for tracking melting, water movement and freezing within both the firn zone and ablation area of the Greenland Ice Sheet.

Landslide detection using very high-resolution satellite imageries

Science.gov (United States)

Suga, Yuzo; Konishi, Tomohisa

2012-10-01

The heavy rain induced by the 12th typhoon caused landslide disaster at Kii Peninsula in the middle part of Japan. We propose a quick response method for landslide disaster mapping using very high resolution (VHR) satellite imageries. Especially, Synthetic Aperture Radar (SAR) is effective because it has the capability of all weather and day/night observation. In this study, multi-temporal COSMO-SkyMed imageries were used to detect the landslide areas. It was difficult to detect the landslide areas using only backscatter change pattern derived from pre- and post-disaster COSMOSkyMed imageries. Thus, the authors adopted a correlation analysis which the moving window was selected for the correlation coefficient calculation. Low value of the correlation coefficient reflects land cover change between pre- and post-disaster imageries. This analysis is effective for the detection of landslides using SAR data. The detected landslide areas were compared with the area detected by EROS-B high resolution optical image. In addition, we have developed 3D viewing system for geospatial visualizing of the damaged area using these satellite image data with digital elevation model. The 3D viewing system has the performance of geographic measurement with respect to elevation height, area and volume calculation, and cross section drawing including landscape viewing and image layer construction using a mobile personal computer with interactive operation. As the result, it was verified that a quick response for the detection of landslide disaster at the initial stage could be effectively performed using optical and SAR very high resolution satellite data by means of 3D viewing system.

Land movement monitoring at the Mavropigi lignite mine using spaceborne D-InSAR

Science.gov (United States)

Papadaki, Eirini; Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis; Schilizzi, Pavlos

2013-08-01

This paper examines the capability of remote sensing radar interferometry to monitor land movements, as it varies with time, in areas close to open pit lignite mines. The study area is the "Mavropigi" lignite mine in Ptolemais, Northern Greece; whose continuous operation is of vital importance to the electric power supply of Greece. The mine is presently 100-120m deep while horizontal and vertical movements have been measured in the vicinity of the pit. Within the mine, ground geodetic monitoring has revealed an average rate of movement amounting to 10-20mm/day at the southeast slopes. In this work, differential interferometry (DInSAR), using 19 Synthetic Aperture Radar (SAR) images of ALOS satellite, has been applied to monitor progression of land movement caused my mining within the greater area of "Mavropigi" region. The results of this work show that DInSAR can be used effectively to capture ground movement information, well before signs of movements can be observed visually in the form of imminent fissures and tension cracks. The advantage of remote sensing interferometry is that it can be applied even in inaccessible areas where monitoring with ground equipment is either impossible or of high-cost (large areas).

RADARGRAMMETRIC DIGITAL SURFACE MODELS GENERATION FROM TERRASAR-X IMAGERY: CASE STUDIES, PROBLEMS AND POTENTIALITIES

Directory of Open Access Journals (Sweden)

P. Capaldo

2012-07-01

Full Text Available The interest for the radargrammetric approach to Digital Surface Models (DSMs generation has been growing in last years thanks to the availability of very high resolution imagery acquired by new SAR (Synthetic Aperture Radar sensors, as COSMO-SkyMed, Radarsat-2 and TerraSAR-X, which are able to supply imagery up to 1 m ground resolution. DSMs radargrammetric generation approach consists of two basic steps, as for the standard photogrammetry applied to optical imagery: the imagery (at least a stereo pair orientation and the image matching for the generation of the points cloud. The steps of the radargrammetric DSMs generation have been implemented into SISAR (Software per Immagini Satellitari ad Alta Risoluzione, a scientific software developed at Geodesy and Geomatics Institute of the University of Rome “La Sapienza”. Moreover, starting from the radargrammetric orientation model, a tool for the Rational Polynomial Coefficients (RPCs for SAR images have been implemented. The possibility to generate RPCs, re-parametrizing a rigorous orientation model through a standardized set of coefficients which can be managed by a Rational Polynomial Coefficients (RPFs model (similarly to optical high resolution imagery sounds of particular interest since, at present, the most part of SAR imagery (except from Radarsat-2 is not supplied with RPCs, although the corresponding RPFs model is available in several commercial software. In particular the RPCs model has been used in the matching process and in the stereo restitution for the DSMs generation, with the advantage of shorter computational time. This paper discusses the application and the results of the implemented algorithm for radargrammetric DSMs generation from TerraSAR-X SpotLight imagery, acquired in Spotlight mode over Trento (Northern Italy. Urban and extra-urban (forested, cultivated areas were considered in two different tiles, and a final overall accuracy ranging from 4.5 to 6 meters was

Differential InSAR Monitoring of the Lampur Sidoarjo Mud Volcano (Java, Indonesia) Using ALOS PALSAR Imagery

Science.gov (United States)

Thomas, Adam; Holley, Rachel; Burren, Richard; Meikle, Chris; Shilston, David

2010-03-01

The Lampur Sidoarjo mud volcano (Java, Indonesia), colloquially called LUSI, first appeared in May 2006. Its cause, whether the result of natural or anthropogenic activities (or a combination of both), is still being debated within the academic, engineering and political communities.The mud volcano expels up to 150,000 m3 of mud per day; and over time, this large volume of mud has had a major environmental and economic impact on the region. The mud flow from LUSI has now covered 6 km2 to depths some tens of metres, displacing approximately 30,000 residents; and continues to threaten local communities, businesses and industry. With such a large volume of mud being expelled each day it is inevitable (as with onshore oil and gas production fields) that there will be some ground surface movement and instability issues at the mud source (the main vent), and in the vicinity of the mud volcano footprint.Due to the dynamic ground surface conditions, engineers and academics alike have found it difficult to reliably monitor ground surface movements within the effected region using conventional surveying techniques. Consequently, engineers responsible for the risk assessment of ground surface instabilities within the proximity of LUSI have called upon the use of satellite interferometry to continually monitor the hazard.The Advanced Land Observing Satellite (ALOS), launched on 24th January 2006, carries onboard an L- band Synthetic Aperture Radar (SAR) instrument called PALSAR (Phased Array type L-band Synthetic Aperture Radar). In contrast to established C-band (5.6cm wavelength) SAR instruments onboard ERS-1 & -2, Envisat, Radarsat-1, and the recently launched Radarsat-2 satellite, PALSAR's (L-band/23.8cm wavelength) instrument presents a number of advantages, including the ability to map larger-scale ground motions, over relatively short timeframes, in tropical environments, without suffering as significantly from signal decorrelation associated with C-band imagery

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

Science.gov (United States)

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

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

Identification of glacier motion and potentially dangerous glacial lakes in the Mt. Everest region/Nepal using spaceborne imagery

Directory of Open Access Journals (Sweden)

T. Bolch

2008-12-01

Full Text Available Failures of glacial lake dams can cause outburst floods and represents a serious hazard. The potential danger of outburst floods depends on various factors like the lake's area and volume, glacier change, morphometry of the glacier and its surrounding moraines and valley, and glacier velocity. Remote sensing offers an efficient tool for displacement calculations and risk assessment of the identification of potentially dangerous glacial lakes (PDGLs and is especially helpful for remote mountainous areas. Not all important parameters can, however, be obtained using spaceborne imagery. Additional interpretation by an expert is required. ASTER data has a suitable accuracy to calculate surface velocity. Ikonos data offers more detail but requires more effort for rectification. All investigated debris-covered glacier tongues show areas with no or very slow movement rates. From 1962 to 2003 the number and area of glacial lakes increased, dominated by the occurrence and almost linear areal expansion of the moraine-dammed lakes, like the Imja Lake. Although the Imja Lake will probably still grow in the near future, the risk of an outburst flood (GLOF is considered not higher than for other glacial lakes in the area. Potentially dangerous lakes and areas of lake development are identified. There is a high probability of further lake development at Khumbu Glacier, but a low one at Lhotse Glacier.

Space Radar Image of West Texas - SAR scan

Science.gov (United States)

1999-01-01

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

A strategy for Local Surface Stability Monitoring Using SAR Imagery

Science.gov (United States)

Kim, J.; Lan, C. W.; Lin, S. Y.; vanGasselt, S.; Yun, H.

2017-12-01

In order to provide sufficient facilities to satisfy a growing number of residents, nowadays there are many constructions and maintenance of infrastructures or buildings undergoing above and below the surface of urban area. In some cases we have learned that disasters might happen if the developments were conducted on unknown or geologically unstable ground or in over-developed areas. To avoid damages caused by such settings, it is essential to perform a regular monitoring scheme to understand the ground stability over the whole urban area. Through long-term monitoring, we firstly aim to observe surface stability over the construction sites. Secondly, we propose to implement an automatic extraction and tracking of suspicious unstable area. To achieve this, we used 12-days-interval C-band Sentinel-1A Synthetic Aperture Radar (SAR) images as the main source to perform regular monitoring. Differential Interferometric SAR (D-InSAR) technique was applied to generate interferograms. Together with the accumulation of updated Sentinel-1A SAR images, time series interferograms were formed accordingly. For the purpose of observing surface stability over known construction sites, the interferograms and the unwrapped products could be used to identify the surface displacement occurring before and after specific events. In addition, Small Baseline Subset (SBAS) and Permanent Scatterers (PS) approaches combining a set of unwrapped D-InSAR interferograms were also applied to derive displacement velocities over long-term periods. For some cases, we conducted the ascending and descending mode time series analysis to decompose three surface migration vectors and to precisely identify the risk pattern. Regarding the extraction of suspicious unstable areas, we propose to develop an automatic pattern recognition algorithm for the identification of specific fringe patterns involving various potential risks. The detected fringes were tracked in the time series interferograms and

Toward Monitoring Surface and Subsurface Lakes on the Greenland Ice Sheet Using Sentinel-1 SAR and Landsat-8 OLI Imagery

Directory of Open Access Journals (Sweden)

Katie E. Miles

2017-07-01

Full Text Available Supraglacial lakes are an important component of the Greenland Ice Sheet's mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR satellite to investigate supraglacial lakes in West Greenland. A semi-automated algorithm is developed to detect surface lakes from Sentinel-1 images during the 2015 summer. A combined Landsat-8 and Sentinel-1 dataset, which has a comparable temporal resolution to MODIS (3 days vs. daily but a higher spatial resolution (25–40 vs. 250–500 m, is then used together with a fully automated lake drainage detection algorithm. Rapid (<4 days and slow (>4 days drainages are investigated for both small (<0.125 km2, the minimum size detectable by MODIS and large (≥0.125 km2 lakes through the summer. Drainage events of small lakes occur at lower elevations (mean 159 m, and slightly earlier (mean 4.5 days in the melt season than those of large lakes. The analysis is extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August; 1,270 m mean elevation. Finally, the Sentinel-1 imagery is used to detect subsurface lakes and, for the first time, their dates of appearance and freeze-through (mean 9 August and 7 October, respectively. These subsurface lakes occur at higher elevations than the surface lakes detected in this study (mean 1,593 and 1,185 m, respectively. Sentinel-1 imagery therefore provides great potential for tracking melting, water movement and freezing within both the firn zone and ablation area of the Greenland Ice Sheet.

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-04-25

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

Ocean Remote Sensing from Chinese Spaceborne Microwave Sensors

Science.gov (United States)

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

Estimation of Atmospheric Path Delays in TerraSAR-X Data using Models vs. Measurements

Directory of Open Access Journals (Sweden)

Donat Perler

2008-12-01

Full Text Available Spaceborne synthetic aperture radar (SAR measurements of the Earth’s surface depend on electromagnetic waves that are subject to atmospheric path delays, in turn affecting geolocation accuracy. The atmosphere influences radar signal propagation by modifying its velocity and direction, effects which can be modeled. We use TerraSAR-X (TSX data to investigate improvements in the knowledge of the scene geometry. To precisely estimate atmospheric path delays, we analyse the signal return of four corner reflectors with accurately surveyed positions (based on differential GPS, placed at different altitudes yet with nearly identical slant ranges to the sensor. The comparison of multiple measurements with path delay models under these geometric conditions also makes it possible to evaluate the corrections for the atmospheric path delay made by the TerraSAR processor and to propose possible improvements.

ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR

Directory of Open Access Journals (Sweden)

P. J. Ni Made

2016-06-01

Full Text Available 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.

Theory and approach of information retrievals from electromagnetic scattering and remote sensing

CERN Document Server

Jin, Ya-Qiu

2006-01-01

Covers several hot topics in current research of electromagnetic scattering, and radiative transfer in complex and random media, polarimetric scattering and SAR imagery technology, data validation and information retrieval from space-borne remote sensing, computational electromagnetics, etc.Including both forward modelling and inverse problems, analytic theory and numerical approachesAn overall summary of the author's works during most recent yearsAlso presents some insight for future research topics.

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

Science.gov (United States)

Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood

Detection and Classification of Objects in Synthetic Aperture Radar Imagery

National Research Council Canada - National Science Library

Cooke, Tristrom

2006-01-01

.... The reports concern the detection of faint trails, and the theory and evaluation of a number of existing and novel methods for the detection and classification of ground and maritime targets with SAR imagery...

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

Science.gov (United States)

An, Jubai; Zhu, Lisong

2006-01-01

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

The physical basis for estimating wave energy spectra from SAR imagery

Science.gov (United States)

Lyzenga, David R.

1987-01-01

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

Stellwagen Bank National Marine Sanctuary - Synthetic Aperture Radar (SAR) Imagery

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This geodatabase contains Synthetic Aperture Radar images (SAR), which consist of a fine resolution (12.5-50m), two-dimensional radar backscatter map of the...

Quality Assessment of Surface Current Fields From TerraSAR-X and TanDEM-X Along-Track Interferometry and Doppler Centroid Analysis

OpenAIRE

Romeiser, Roland; Runge, Harmut; Suchandr, Steffan; Kahle, Ralph; Rossi, Cristian; Bell, Paul S.

2014-01-01

All existing examples of current measurements by spaceborne synthetic aperture radar (SAR) along-track (AT) interferometry (ATI) have suffered from short baselines and corresponding low sensitivities. Theoretically, the best data quality at X-band is expected at effective baselines on the order of 30 m, i.e., 30 times as long as the baselines of the divided-antenna modes of TerraSAR-X. In early 2012, we had a first opportunity to obtain data at near-optimum baselines from the TanDEM-X satelli...

AIRBORNE X-HH INCIDENCE ANGLE IMPACT ON CANOPY HEIGHT RETREIVAL: IMPLICATIONS FOR SPACEBORNE X-HH TANDEM-X GLOBAL CANOPY HEIGHT MODEL

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M. L. Tighe

2012-07-01

Full Text Available To support international climate change mitigation efforts, the United Nations REDD+ initiative (Reducing Emissions from Deforestation and Degradation seeks to reduce land use induced greenhouse gas emissions to the atmosphere. It requires independent monitoring of forest cover and forest biomass information in a spatially explicit form. It is widely recognised that remote sensing is required to deliver this information. Synthetic Aperture Radar interferometry (InSAR techniques have gained traction in the last decade as a viable technology from which vegetation canopy height and bare earth elevations can be derived. The viewing geometry of a SAR sensor is side-looking where the radar pulse is transmitted out to one side of the aircraft or satellite, defining an incidence angle (θ range. The incidence angle will change from near-range (NR to far-range (FR across of the track of the SAR platform. InSAR uses image pairs and thus, contain two set of incidence angles. Changes in the InSAR incidence angles can alter the relative contributions from the vegetation canopy and the ground surface and thus, affect the retrieved vegetation canopy height. Incidence angle change is less pronounced in spaceborne data than in airborne data and mitigated somewhat when multiple InSAR-data takes are combined. This study uses NEXTMap® single- and multi-pass X-band HH polarized InSAR to derive vegetation canopy height from the scattering phase centre height (hspc. Comparisons with in situ vegetation canopy height over three test sites (Arizona-1, Minnesota-2; the effect of incidence angle changes across swath on the X-HH InSAR hspc was examined. Results indicate at steep incidence angles (θ = 35º, more exposure of lower vegetation canopy structure (e.g. tree trunks led to greater lower canopy double bounce, increased ground scattering, and decreased volume scattering. This resulted in a lower scattering phase centre height (hspc or a greater underestimation of

Using Lattice Topology Information to Investigate Persistent Scatterers at Facades in Urban Areas

Science.gov (United States)

Schack, L.; Soergel, U.

2013-05-01

Modern spaceborne SAR sensors like TerraSAR-X offer ground resolution of up to one meter in range and azimuth direction. Buildings, roads, bridges, and other man-made structures appear in such data often as regular patterns of strong and temporally stable points (Persistent Scatterer, PS). As one step in the process of unveiling what object structure actually causes the PS (i.e., physical nature) we compare those regular structures in SAR data to their correspondences in optical imagery. We use lattices as a common data representation for visible facades. By exploiting the topology information given by the lattices we can complete gaps in the structures which is one step towards the understanding of the complex scattering characteristics of distinct facade objects.

C/X-band SAR interferometry applied to ground monitoring: examples and new potential

Science.gov (United States)

Nutricato, Raffaele; Nitti, Davide O.; Bovenga, Fabio; Refice, Alberto; Wasowski, Janusz; Chiaradia, Maria T.

2013-10-01

Classical applications of the MTInSAR techniques have been carried out in the past on medium resolution data acquired by the ERS, Envisat (ENV) and Radarsat sensors. The new generation of high-resolution X-Band SAR sensors, such as TerraSAR-X (TSX) and the COSMO-SkyMed (CSK) constellation allows acquiring data with spatial resolution reaching metric/submetric values. Thanks to the finer spatial resolution with respect to C-band data, X-band InSAR applications result very promising for monitoring single man-made structures (buildings, bridges, railways and highways), as well as landslides. This is particularly relevant where C-band data show low density of coherent scatterers. Moreover, thanks again to the higher resolution, it is possible to infer reliable estimates of the displacement rates with a number of SAR scenes significantly lower than in C-band within the same time span or by using more images acquired in a narrower time span. We present examples of the application of a Persistent Scatterers Interferometry technique, namely the SPINUA algorithm, to data acquired by ENV, TSX and CSK on selected number of sites. Different cases are considered concerning monitoring of both instable slopes and infrastructure. Results are compared and commented with particular attention paid to the advantages provided by the new generation of X-band high resolution space-borne SAR sensors.

Offshore wind potential evaluation and remote sensing imagery; Evaluation du potentiel eolien offshore et imagerie satellitale

Energy Technology Data Exchange (ETDEWEB)

Fichaux, N.

2003-12-15

Offshore wind energy may help to contribute to the respect of the Kyoto objectives by Europe. It is a key issue to struggle against global change. To sit the future offshore wind parks, it is necessary to accurately evaluate the spatial repartition of the wind potential. We demonstrate that the offshore wind potential shall be represented by maps of wind statistics. As remote sensing is a tool for measuring space physical phenomena, we evaluate its potentialities for mapping wind statistics. Space-borne scatterometers enables the obtention of wind statistics, but far from our areas of interest and at low spatial resolution. Synthetic Aperture Radar (SAR) enables the computation of high resolution wind maps over our areas of interest, but are unsuitable to compute wind statistics. We define the mathematical framework of a statistical method. That method enables to take advantage of both scatterometer and SAR to compute maps of wind statistics at high spatial resolution over the areas of interest. It enables remote sensing to be used operationally to map the offshore wind potential. (author)

An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery

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Lizhang Zhou

2017-06-01

Full Text Available Sea surface wind affects the fluxes of energy, mass and momentum between the atmosphere and ocean, and therefore regional and global weather and climate. With various satellite microwave sensors, sea surface wind can be measured with large spatial coverage in almost all-weather conditions, day or night. Like any other remote sensing measurements, sea surface wind measurement is also indirect. Therefore, it is important to develop appropriate wind speed and direction retrieval models for different types of microwave instruments. In this paper, a new sea surface wind direction retrieval method from synthetic aperture radar (SAR imagery is developed. In the method, local gradients are computed in frequency domain by combining the operation of smoothing and computing local gradients in one step to simplify the process and avoid the difference approximation. This improved local gradients (ILG method is compared with the traditional two-dimensional fast Fourier transform (2D FFT method and local gradients (LG method, using interpolating wind directions from the European Centre for Medium-Range Weather Forecast (ECMWF reanalysis data and the Cross-Calibrated Multi-Platform (CCMP wind vector product. The sensitivities to the salt-and-pepper noise, the additive noise and the multiplicative noise are analyzed. The ILG method shows a better performance of retrieval wind directions than the other two methods.

Opium Field Detection in South Oxfordshire Using SAR Polarimetry

Science.gov (United States)

Walker, Nick; Marino, Armando

2011-03-01

To-date the use of satellite imagery to monitor the growth of illicit crops such as marijuana, opium and coca has mostly been conducted using optical frequencies. However, it is well known that while optical imagery can be hampered by localised aerosols such as thin clouds, cirrus, haze and smoke, these do not present a problem for Synthetic Aperture Radar (SAR). In recent years a new generation of satellite borne sensors have also been equipped with enhanced polarimetric capabilities, which can potentially help with detecting and classifying different terrain types. For these reasons we believe it is useful to consider whether high resolution polarimetric SAR data can be applied to illicit crop detection.In this paper we present the results of an experiment whereby opium poppy fields were successfully detected in the south Oxfordshire region in the UK using RadarSat-2 quad-polarisation imagery. It should be noted that these crops are not being grown illicitly but instead are being cultivated for medicinal reasons in parts of the UK. It is interesting to note that the poppies cultivated for opium in the UK have white flowers rather than the more familiar red as can be seen from the photograph in Figure 1, which was taken 11 days earlier in the season compared to Figure 4 and Figure 5.

COMBINATION OF GENETIC ALGORITHM AND DEMPSTER-SHAFER THEORY OF EVIDENCE FOR LAND COVER CLASSIFICATION USING INTEGRATION OF SAR AND OPTICAL SATELLITE IMAGERY

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H. T. Chu

2012-07-01

Full Text Available The integration of different kinds of remotely sensed data, in particular Synthetic Aperture Radar (SAR and optical satellite imagery, is considered a promising approach for land cover classification because of the complimentary properties of each data source. However, the challenges are: how to fully exploit the capabilities of these multiple data sources, which combined datasets should be used and which data processing and classification techniques are most appropriate in order to achieve the best results. In this paper an approach, in which synergistic use of a feature selection (FS methods with Genetic Algorithm (GA and multiple classifiers combination based on Dempster-Shafer Theory of Evidence, is proposed and evaluated for classifying land cover features in New South Wales, Australia. Multi-date SAR data, including ALOS/PALSAR, ENVISAT/ASAR and optical (Landsat 5 TM+ images, were used for this study. Textural information were also derived and integrated with the original images. Various combined datasets were generated for classification. Three classifiers, namely Artificial Neural Network (ANN, Support Vector Machines (SVMs and Self-Organizing Map (SOM were employed. Firstly, feature selection using GA was applied for each classifier and dataset to determine the optimal input features and parameters. Then the results of three classifiers on particular datasets were combined using the Dempster-Shafer theory of Evidence. Results of this study demonstrate the advantages of the proposed method for land cover mapping using complex datasets. It is revealed that the use of GA in conjunction with the Dempster-Shafer Theory of Evidence can significantly improve the classification accuracy. Furthermore, integration of SAR and optical data often outperform single-type datasets.

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

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Oscar Garcia-Pineda

2017-06-01

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

A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation.

Science.gov (United States)

Wen, Xuejiao; Qiu, Xiaolan; Han, Bing; Ding, Chibiao; Lei, Bin; Chen, Qi

2018-05-07

Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

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

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Jinhui Li

2018-04-01

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

Science.gov (United States)

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.

Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

Science.gov (United States)

Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

2017-05-01

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

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S. Wittke

2017-05-01

Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

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

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Bo Zhang

2017-02-01

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

An Advanced Rotation Invariant Descriptor for SAR Image Registration

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Yuming Xiang

2017-07-01

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

A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation

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Xuejiao Wen

2018-05-01

Full Text Available Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico

OpenAIRE

Pacheco-Martínez, Jesús; Cabral-Cano, Enrique; Wdowinski, Shimon; Hernández-Marín, Martín; Ortiz-Lozano, José; Zermeño-de-León, Mario

2015-01-01

In this work we present an application of InSAR and gravimetric surveys for risk management related to land subsidence and surface ground faulting generation. A subsidence velocity map derived from the 2007–2011 ALOS SAR imagery and a sediment thicknesses map obtained from the inversion of gravimetric data were integrated with a surface fault map to produce a subsidence hazard zoning in the city of Aguascalientes, Mexico. The resulting zoning is presented together with specific recommendation...

First Image Products from EcoSAR - Osa Peninsula, Costa Rica

Science.gov (United States)

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

2016-01-01

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

DSM GENERATION FROM HIGH RESOLUTION COSMO-SKYMED IMAGERY WITH RADARGRAMMETRIC MODEL

OpenAIRE

P. Capaldo; M. Crespi; F. Fratarcangeli; A. Nascetti; F. Pieralice

2012-01-01

The availability of new high resolution radar spaceborne sensors offers new interesting potentialities for the geomatics application: spatial and temporal change detection, features extraction, generation of Digital Surface (DSMs). As regards the DSMs generation from new high resolution data (as SpotLight imagery), the development and the accuracy assessment of method based on radargrammetric approach are topics of great interest and relevance. The aim of this investigation is the DSM generat...

Integrated Data Processing Methodology for Airborne Repeat-pass Differential SAR Interferometry

Science.gov (United States)

Dou, C.; Guo, H.; Han, C.; Yue, X.; Zhao, Y.

2014-11-01

Short temporal baseline and multiple ground deformation information can be derived from the airborne differential synthetic aperture radar Interforemetry (D-InSAR). However, affected by the turbulence of the air, the aircraft would deviate from the designed flight path with high frequent vibrations and changes both in the flight trajectory and attitude. Restricted by the accuracy of the position and orientation system (POS), these high frequent deviations can not be accurately reported, which would pose great challenges in motion compensation and interferometric process. Thus, these challenges constrain its wider applications. The objective of this paper is to investigate the accurate estimation and compensation of the residual motion errors in the airborne SAR imagery and time-varying baseline errors between the diffirent data acquirations, furthermore, to explore the integration data processing theory for the airborne D-InSAR system, and thus help to accomplish the correct derivation of the ground deformation by using the airborne D-InSAR measurements.

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

Science.gov (United States)

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

2006-12-01

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

Automated inundation monitoring using TerraSAR-X multitemporal imagery

Science.gov (United States)

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

2009-04-01

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

Advanced InSAR imaging for dune mapping

Science.gov (United States)

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

2015-04-01

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

Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry.

Science.gov (United States)

Bovenga, Fabio; Belmonte, Antonella; Refice, Alberto; Pasquariello, Guido; Nutricato, Raffaele; Nitti, Davide O; Chiaradia, Maria T

2018-04-27

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry

Directory of Open Access Journals (Sweden)

Fabio Bovenga

2018-04-01

Full Text Available Multi-temporal InSAR (MTI applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

Space-Variant Post-Filtering for Wavefront Curvature Correction in Polar-Formatted Spotlight-Mode SAR Imagery

Energy Technology Data Exchange (ETDEWEB)

DOREN,NEALL E.

1999-10-01

Wavefront curvature defocus effects occur in spotlight-mode SAR imagery when reconstructed via the well-known polar-formatting algorithm (PFA) under certain imaging scenarios. These include imaging at close range, using a very low radar center frequency, utilizing high resolution, and/or imaging very large scenes. Wavefront curvature effects arise from the unrealistic assumption of strictly planar wavefronts illuminating the imaged scene. This dissertation presents a method for the correction of wavefront curvature defocus effects under these scenarios, concentrating on the generalized: squint-mode imaging scenario and its computational aspects. This correction is accomplished through an efficient one-dimensional, image domain filter applied as a post-processing step to PF.4. This post-filter, referred to as SVPF, is precalculated from a theoretical derivation of the wavefront curvature effect and varies as a function of scene location. Prior to SVPF, severe restrictions were placed on the imaged scene size in order to avoid defocus effects under these scenarios when using PFA. The SVPF algorithm eliminates the need for scene size restrictions when wavefront curvature effects are present, correcting for wavefront curvature in broadside as well as squinted collection modes while imposing little additional computational penalty for squinted images. This dissertation covers the theoretical development, implementation and analysis of the generalized, squint-mode SVPF algorithm (of which broadside-mode is a special case) and provides examples of its capabilities and limitations as well as offering guidelines for maximizing its computational efficiency. Tradeoffs between the PFA/SVPF combination and other spotlight-mode SAR image formation techniques are discussed with regard to computational burden, image quality, and imaging geometry constraints. It is demonstrated that other methods fail to exhibit a clear computational advantage over polar-formatting in conjunction

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

Directory of Open Access Journals (Sweden)

D. Xue

2018-04-01

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

Spaceborne Photonics Institute

Science.gov (United States)

Venable, D. D.; Farrukh, U. O.; Han, K. S.; Hwang, I. H.; Jalufka, N. W.; Lowe, C. W.; Tabibi, B. M.; Lee, C. J.; Lyons, D.; Maclin, A.

1994-01-01

This report describes in chronological detail the development of the Spaceborne Photonics Institute as a sustained research effort at Hampton University in the area of optical physics. This provided the research expertise to initiate a PhD program in Physics. Research was carried out in the areas of: (1) modelling of spaceborne solid state laser systems; (2) amplified spontaneous emission in solar pumped iodine lasers; (3) closely simulated AM0 CW solar pumped iodine laser and repeatedly short pulsed iodine laser oscillator; (4) a materials spectroscopy and growth program; and (5) laser induced fluorescence and atomic and molecular spectroscopy.

Multisource Remote Sensing Imagery Fusion Scheme Based on Bidimensional Empirical Mode Decomposition (BEMD and Its Application to the Extraction of Bamboo Forest

Directory of Open Access Journals (Sweden)

Guang Liu

2016-12-01

Full Text Available Most bamboo forests grow in humid climates in low-latitude tropical or subtropical monsoon areas, and they are generally located in hilly areas. Bamboo trunks are very straight and smooth, which means that bamboo forests have low structural diversity. These features are beneficial to synthetic aperture radar (SAR microwave penetration and they provide special information in SAR imagery. However, some factors (e.g., foreshortening can compromise the interpretation of SAR imagery. The fusion of SAR and optical imagery is considered an effective method with which to obtain information on ground objects. However, most relevant research has been based on two types of remote sensing image. This paper proposes a new fusion scheme, which combines three types of image simultaneously, based on two fusion methods: bidimensional empirical mode decomposition (BEMD and the Gram-Schmidt transform. The fusion of panchromatic and multispectral images based on the Gram-Schmidt transform can enhance spatial resolution while retaining multispectral information. BEMD is an adaptive decomposition method that has been applied widely in the analysis of nonlinear signals and to the nonstable signal of SAR. The fusion of SAR imagery with fused panchromatic and multispectral imagery using BEMD is based on the frequency information of the images. It was established that the proposed fusion scheme is an effective remote sensing image interpretation method, and that the value of entropy and the spatial frequency of the fused images were improved in comparison with other techniques such as the discrete wavelet, à-trous, and non-subsampled contourlet transform methods. Compared with the original image, information entropy of the fusion image based on BEMD improves about 0.13–0.38. Compared with the other three methods it improves about 0.06–0.12. The average gradient of BEMD is 4%–6% greater than for other methods. BEMD maintains spatial frequency 3.2–4.0 higher than

Integration of X-SAR observations with data of other remote sensing techniques: preliminary results achieved with Cosmo/SkyMed announcement of opportunity projects

Science.gov (United States)

Vespe, Francesco; Baldini, Luca; Notarnicola, Claudia; Prati, Claudio; Zerbini, Susanna; Celidonio, G.

2011-11-01

The Italian Space Agency is funding 27 scientific projects in the framework of Cosmo/Skymed program (hereafter CSK) . A subset of them are focusing on the improvements of the quality and quantity of information which can be extracted from X-SAR data if integrated with other independent techniques like GPS or SAR imagery in L and C bands. The GPS observations, namely zenith total delays estimated by means of GPS ground stations, could be helpful to estimate the troposphere bias to remove from IN-SAR imagery. Another contribution of GPS could be the improvements of the orbits of Cosmo/SkyMed satellites. In particular the GPS navigation data of the CSK satellites could serve to improve the atmospheric drag models acting on them. The integration of SAR data in L and C bands on the other hand are helpful to investigate land hydrogeology parameters as well as to improve global precipitation observations. The combined use of L, C and X SAR data with different penetration depth could give profiles of land surface properties, especially in forest and snow/ice-packs. For what concern the use of X-SAR imagery for rain precipitation monitoring, particular attention will be paid to its polarimetric properties that we plan to determine aligning the CSK observations with those obtained with ground L and C radars. Anyway the study goals, the approaches proposed, the test sites identified and the external data selected for the development and validation will be described for each project. Particular attention will be paid to single the advantages that the research activities can benefit from the added potentials of CSK system: the more frequent revisiting time and the higher resolution capabilities.

Satellite SAR interferometric techniques applied to emergency mapping

Science.gov (United States)

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

2017-04-01

This paper aim to investigate the capabilities of the currently available SAR interferometric algorithms in the field of emergency mapping. Several tests have been performed exploiting the Copernicus Sentinel-1 data using the COTS software ENVI/SARscape 5.3. Emergency Mapping can be defined as "creation of maps, geo-information products and spatial analyses dedicated to providing situational awareness emergency management and immediate crisis information for response by means of extraction of reference (pre-event) and crisis (post-event) geographic information/data from satellite or aerial imagery". The conventional differential SAR interferometric technique (DInSAR) and the two currently available multi-temporal SAR interferometric approaches, i.e. Permanent Scatterer Interferometry (PSI) and Small BAseline Subset (SBAS), have been applied to provide crisis information useful for the emergency management activities. Depending on the considered Emergency Management phase, it may be distinguished between rapid mapping, i.e. fast provision of geospatial data regarding the area affected for the immediate emergency response, and monitoring mapping, i.e. detection of phenomena for risk prevention and mitigation activities. In order to evaluate the potential and limitations of the aforementioned SAR interferometric approaches for the specific rapid and monitoring mapping application, five main factors have been taken into account: crisis information extracted, input data required, processing time and expected accuracy. The results highlight that DInSAR has the capacity to delineate areas affected by large and sudden deformations and fulfills most of the immediate response requirements. The main limiting factor of interferometry is the availability of suitable SAR acquisition immediately after the event (e.g. Sentinel-1 mission characterized by 6-day revisiting time may not always satisfy the immediate emergency request). PSI and SBAS techniques are suitable to produce

Near real-time geocoding of SAR imagery with orbit error removal.

NARCIS (Netherlands)

Smith, A.J.E.

2003-01-01

When utilizing knowledge of the spacecraft trajectory for near real-time geocoding of Synthetic Aperture Radar (SAR) images, the main problem is that predicted satellite orbits have to be used, which may be in error by several kilometres. As part of the development of a Dutch autonomous mobile

Interference Mitigation Technique Using Active Spaceborne Sensor Antenna in EESS (Active) and Space Research Service (Active) for Use in 500 MHz Bandwidth Near 9.6 GHz

Science.gov (United States)

Huneycutt, Bryan L.

2005-01-01

This document presents an interference mitigation technique using the active spaceborne sensor SAR3 antenna in the Earth Exploration-Satellite Service (active) and Space Research Service (active) for use in a 500 MHz bandwidth near 9.6 GHz. The purpose of the document is present antenna designs which offer lower sidelobes and faster rolloff in the sidelobes which in turn mitigates the interference to other services from the EESS (active) and SRS (active) sensors.

Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle

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Takashi Shibayama

2015-11-01

Full Text Available This paper addresses the local incidence angle dependence of several polarimetric indices corresponding to landslides in forested areas. Landslide is deeply related to the loss of human lives and their property. Various kinds of remote sensing techniques, including aerial photography, high-resolution optical satellite imagery, LiDAR and SAR interferometry (InSAR, have been available for landslide investigations. SAR polarimetry is potentially an effective measure to investigate landslides because fully-polarimetric SAR (PolSAR data contain more information compared to conventional single- or dual-polarization SAR data. However, research on landslide recognition utilizing polarimetric SAR (PolSAR is quite limited. Polarimetric properties of landslides have not been examined quantitatively so far. Accordingly, we examined the polarimetric scattering properties of landslides by an assessment of how the decomposed scattering power components and the polarimetric correlation coefficient change with the local incidence angle. In the assessment, PolSAR data acquired from different directions with both spaceborne and airborne SARs were utilized. It was found that the surface scattering power and the polarimetric correlation coefficient of landslides significantly decrease with the local incidence angle, while these indices of surrounding forest do not. This fact leads to establishing a method of effective detection of landslide area by polarimetric information.

Localized landslide risk assessment with multi pass L band DInSAR analysis

Science.gov (United States)

Yun, HyeWon; Rack Kim, Jung; Lin, Shih-Yuan; Choi, YunSoo

2014-05-01

In terms of data availability and error correction, landslide forecasting by Differential Interferometric SAR (DInSAR) analysis is not easy task. Especially, the landslides by the anthropogenic construction activities frequently occurred in the localized cutting side of mountainous area. In such circumstances, it is difficult to attain sufficient enough accuracy because of the external factors inducing the error component in electromagnetic wave propagation. For instance, the local climate characteristics such as orographic effect and the proximity to water source can produce the significant anomalies in the water vapor distribution and consequently result in the error components of InSAR phase angle measurements. Moreover the high altitude parts of target area cause the stratified tropospheric delay error in DInSAR measurement. The other obstacle in DInSAR observation over the potential landside site is the vegetation canopy which causes the decorrelation of InSAR phase. Thus rather than C band sensor such as ENVISAT, ERS and RADARSAT, DInSAR analysis with L band ALOS PLASAR is more recommendable. Together with the introduction of L band DInSAR analysis, the improved DInSAR technique to cope all above obstacles is necessary. Thus we employed two approaches i.e. StaMPS/MTI (Stanford Method for Persistent Scatterers/Multi-Temporal InSAR, Hopper et al., 2007) which was newly developed for extracting the reliable deformation values through time series analysis and two pass DInSAR with the error term compensation based on the external weather information in this study. Since the water vapor observation from spaceborne radiometer is not feasible by the temporal gap in this case, the quantities from weather Research Forecasting (WRF) with 1 km spatial resolution was used to address the atmospheric phase error in two pass DInSAR analysis. Also it was observed that base DEM offset with time dependent perpendicular baselines of InSAR time series produce a significant error

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

Science.gov (United States)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement

An approach for flood monitoring by the combined use of Landsat 8 optical imagery and COSMO-SkyMed radar imagery

Science.gov (United States)

Tong, Xiaohua; Luo, Xin; Liu, Shuguang; Xie, Huan; Chao, Wei; Liu, Shuang; Liu, Shijie; Makhinov, A. N.; Makhinova, A. F.; Jiang, Yuying

2018-02-01

Remote sensing techniques offer potential for effective flood detection with the advantages of low-cost, large-scale, and real-time surface observations. The easily accessible data sources of optical remote sensing imagery provide abundant spectral information for accurate surface water body extraction, and synthetic aperture radar (SAR) systems represent a powerful tool for flood monitoring because of their all-weather capability. This paper introduces a new approach for flood monitoring by the combined use of both Landsat 8 optical imagery and COSMO-SkyMed radar imagery. Specifically, the proposed method applies support vector machine and the active contour without edges model for water extent determination in the periods before and during the flood, respectively. A map difference method is used for the flood inundation analysis. The proposed approach is particularly suitable for large-scale flood monitoring, and it was tested on a serious flood that occurred in northeastern China in August 2013, which caused immense loss of human lives and properties. High overall accuracies of 97.46% for the optical imagery and 93.70% for the radar imagery are achieved by the use of the techniques presented in this study. The results show that about 12% of the whole study area was inundated, corresponding to 5466 km2 of land surface.

Parametric estimation of time varying baselines in airborne interferometric SAR

DEFF Research Database (Denmark)

Mohr, Johan Jacob; Madsen, Søren Nørvang

1996-01-01

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

Using an active contour method to detect bilge dumps from SAR imagery

CSIR Research Space (South Africa)

Mdakane, Lizwe W

2016-07-01

Full Text Available An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based active contour model (ACM) algorithm to achieve...

Retrieval of the ocean wave spectrum in open and thin ice covered ocean waters from ERS Synthetic Aperture Radar images

International Nuclear Information System (INIS)

De Carolis, G.

2001-01-01

This paper concerns with the task of retrieving ocean wave spectra form imagery provided by space-borne SAR systems such as that on board ERS satellite. SAR imagery of surface wave fields travelling into open ocean and into thin sea ice covers composed of frazil and pancake icefields is considered. The major purpose is to gain insight on how the spectral changes can be related to sea ice properties of geophysical interest such as the thickness. Starting from SAR image cross spectra computed from Single Look Complex (SLC) SAR images, the ocean wave spectrum is retrieved using an inversion procedure based on the gradient descent algorithm. The capability of this method when applied to satellite SAR sensors is investigated. Interest in the SAR image cross spectrum exploitation is twofold: first, the directional properties of the ocean wave spectra are retained; second, external wave information needed to initialize the inversion procedure may be greatly reduced using only information included in the SAR image cross spectrum itself. The main drawback is that the wind waves spectrum could be partly lost and its spectral peak wave number underestimated. An ERS-SAR SLC image acquired on April 10, 1993 over the Greenland Sea was selected as test image. A pair of windows that include open-sea only and sea ice cover, respectively, were selected. The inversions were carried out using different guess wave spectra taken from SAR image cross spectra. Moreover, care was taken to properly handle negative values eventually occurring during the inversion runs. This results in a modification of the gradient descending the technique that is required if a non-negative solution of the wave spectrum is searched for. Results are discussed in view of the possibility of SAR data to detect ocean wave dispersion as a means for the retrieval of ice thickness

Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project

Directory of Open Access Journals (Sweden)

Recep Gundogan

2008-02-01

Full Text Available The satellite imagery has been effectively utilized for classifying land covertypes and detecting land cover conditions. The Advanced Spaceborne Thermal Emissionand Reflection Radiometer (ASTER sensor imagery has been widely used in classificationprocess of land cover. However, atmospheric corrections have to be made by preprocessingsatellite sensor imagery since the electromagnetic radiation signals received by the satellitesensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study,an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance(TOA, was used to classify the land use/cover types, according to COoRdination ofINformation on the Environment (CORINE land cover nomenclature, for an arearepresenting the heterogonous characteristics of eastern Mediterranean regions inKahramanmaras, Turkey. The results indicated that using the surface reflectance data ofASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of83.2% and 0.79, respectively and low-cost cover mapping as a part of inventory forCORINE Land Cover Project.

ARCHAEOLOGICAL SURVEYS ON THE GERMAN NORTH SEA COAST USING HIGH-RESOLUTION SYNTHETIC APERTURE RADAR DATA

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M. Gade

2017-11-01

Full Text Available We show that high-resolution space-borne Synthetic Aperture Radar (SAR imagery with pixel sizes well below 1 m2 can be used to complement archaeological surveys in areas that are difficult to access. After major storm surges in the 14th and 17th centuries, vast areas on the German North Sea coast were lost to the sea. Areas of former settlements and historical land use were buried under sediments for centuries, but when the surface layer is driven away under the permanent action of wind, currents, and waves, they appear again on the Wadden Sea surface. However, the frequent flooding and erosion of the intertidal flats make any archaeological monitoring a difficult task, so that remote sensing techniques appear to be an efficient and cost-effective instrument for any archaeological surveillance of that area. Space-borne SAR images clearly show remnants of farmhouse foundations and of former systems of ditches, dating back to the 14th and to the 16th/17th centuries. In particular, the very high-resolution acquisition (staring spotlight mode of the German TerraSAR/ TanDEM-X satellites allows for the detection of various kinds of residuals of historical land use with high precision. In addition, we also investigate the capability of SARs working at lower microwave frequencies (on Radarsat-2 to complement our archaeological survey of historical cultural traces, some of which have been unknown so far.

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

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Hui Meng

2017-02-01

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

Multifrequency OFDM SAR in Presence of Deception Jamming

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Schuerger Jonathan

2010-01-01

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

The InSAR Scientific Computing Environment (ISCE): A Python Framework for Earth Science

Science.gov (United States)

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

2015-12-01

The InSAR Scientific Computing Environment (ISCE, funded by NASA ESTO) provides a modern computing framework for geodetic image processing of InSAR data from a diverse array of radar satellites and aircraft. ISCE is both a modular, flexible, and extensible framework for building software components and applications as well as a toolbox of applications for processing raw or focused InSAR and Polarimetric InSAR data. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. Components are independently configurable in a layered manner to provide maximum control. Polymorphism is used to define a workflow in terms of abstract facilities for each processing step that are realized by specific components at run-time. This enables a single workflow to work on either raw or focused data from all sensors. ISCE can serve as the core of a production center to process Level-0 radar data to Level-3 products, but is amenable to interactive processing approaches that allow scientists to experiment with data to explore new ways of doing science with InSAR data. The NASA-ISRO SAR (NISAR) Mission will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystems. 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 new data. NISAR will be but one mission in a constellation of radar satellites in the future delivering such data. ISCE currently supports all publicly available strip map mode space-borne SAR data since ERS and is expected to include support for upcoming missions. ISCE has been incorporated into two prototype cloud-based systems that have demonstrated its elasticity in addressing larger data processing problems in a "production" context and its ability to be

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

Science.gov (United States)

Boesswetter, C.

1986-07-01

The basic system design considerations for a high resolution SAR system operating at 35 GHz or 94 GHz are given. First it is shown that only the focussed SAR concept in the side looking configuration matches the requirements and constraints. After definition of illumination geometry and airborne modes the fundamental SAR parameters in range and azimuth direction are derived. A review of the performance parameters of some critical mm wave components (coherent pulsed transmitters, front ends, antennas) establish the basis for further analysis. The power and contrast budget in the processed SAR image shows the feasibility of a 35/94 GHz SAR sensor design. The discussion of the resulting system parameters points out that this unusual system design implies both benefits and new risk areas. One of the benefits besides the compactness of sensor hardware turns out to be the short synthetic aperture length simplifying the design of the digital SAR processor, preferably operating in real time. A possible architecture based on current state-of-the-art correlator hardware is shown. One of the potential risk areas in achieving high resolution SAR imagery in the mm wave frequency band is motion compensation. However, it is shown that the short range and short synthetic aperture lengths ease the problem so that correction of motion induced phase errors and thus focussed synthetic aperture processing should be possible.

SAR processing in the cloud for oil detection in the Arctic

Science.gov (United States)

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

2016-12-01

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

Sea ice local surface topography from single-pass satellite InSAR measurements: a feasibility study

Directory of Open Access Journals (Sweden)

W. Dierking

2017-08-01

Full Text Available Quantitative parameters characterizing the sea ice surface topography are needed in geophysical investigations such as studies on atmosphere–ice interactions or sea ice mechanics. Recently, the use of space-borne single-pass interferometric synthetic aperture radar (InSAR for retrieving the ice surface topography has attracted notice among geophysicists. In this paper the potential of InSAR measurements is examined for several satellite configurations and radar frequencies, considering statistics of heights and widths of ice ridges as well as possible magnitudes of ice drift. It is shown that, theoretically, surface height variations can be retrieved with relative errors  ≤  0.5 m. In practice, however, the sea ice drift and open water leads may contribute significantly to the measured interferometric phase. Another essential factor is the dependence of the achievable interferometric baseline on the satellite orbit configurations. Possibilities to assess the influence of different factors on the measurement accuracy are demonstrated: signal-to-noise ratio, presence of a snow layer, and the penetration depth into the ice. Practical examples of sea surface height retrievals from bistatic SAR images collected during the TanDEM-X Science Phase are presented.

An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

Directory of Open Access Journals (Sweden)

Weizeng Shao

2017-07-01

Full Text Available In this study, we proposed an empirical algorithm for significant wave height (SWH retrieval from TerraSAR-X/TanDEM (TS-X/TD-X X-band synthetic aperture radar (SAR co-polarization (vertical-vertical (VV and horizontal-horizontal (HH images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF reanalysis field at a 0.125° grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA National Data Buoy Center (NDBC buoys. It is found that the algorithm performs well with a SWH stander deviation (STD of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6–7 m, we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information.

Applications of Environmental Remote Sensing by HJ-1C SAR Imageries

Directory of Open Access Journals (Sweden)

Tian Wei

2014-06-01

Full Text Available The HJ-1C satellite was successfully launched in November 19, 2012. The HJ-1C and HJ-1A/1B satellites, which were launched in September 06, 2008, constitute the “2+1” small satellite constellation for environmental and disaster monitoring. This study focuses on the analysis and evaluation of the satellite performance with respect to environmental remote sensing, including land use interpretation, land cover classification, oil spill identification, retrieval of sea waves, and monitoring of coastal mariculture. The data used in this study cover the city of Beijing and the sea of the Fujian Province. Nine HJ-1C satellite images (level-2, S band, VV Pol, strip mode, 5 m resolution from December 2012 to January 2013 are used. The conclusions are as follows: (1 the HJ-1C SAR images can be used to manually identify farmland, woodland, roads, rivers, urban construction, and rural residential areas; (2 the accuracy of the automatic land cover classification increased significantly when the HJ-1C SAR and HJ-1B CCD fusion images are used; (3 the HJ-1C satellite can be used to identify oil spills, to invert wave parameters, and to extract information regarding inshore aquaculture.

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

Directory of Open Access Journals (Sweden)

Timo Balz

2016-09-01

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

TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

G. Agugiaro

2012-07-01

Full Text Available Today the use of spaceborne Very High Spatial Resolution (VHSR optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM Unit of the Bruno Kessler Foundation (FBK in Trento (Italy has collected stereo VHSR satellite imagery, as well as aerial and terrestrial data over Trento, with the aim to create a complete data collection with state-of-the-art datasets for investigations on image analysis, automatic digital surface model (DSM generation, 2D/3D feature extraction, city modelling and data fusion. The testfield region covers the city of Trento, characterised by very dense urban (historical centre, residential and industrial areas, and the surrounding hills and steep mountains (approximate height range 200-2100 m with cultivations, forests and bare soil. This paper reports the analysis conducted in FBK on the VHSR spaceborne imagery of Trento testfield for 3D information extraction. The data include two stereo-pairs acquired by WorldView-2 in August 2010 and by GeoEye-1 in September 2011 in panchromatic and multispectral mode, together with their original Rational Polynomial Coefficients (RPC, and the position and description of well distributed ground points. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project and the dataset characteristics. The results achieved by 3DOM on DSM extraction from WorldView-2 and GeoEye-1 stereo-pairs are shown and commented.

Ground Deformation Detection Using China’s ZY-3 Stereo Imagery in an Opencast Mining Area

OpenAIRE

Wenmin Hu; Lixin Wu; Wei Zhang; Bin Liu; Jiaxing Xu

2017-01-01

Detection and extraction of mining-induced ground deformation can be used to understand the deformation process and space distribution and to estimate the deformation laws and trends. This study focuses on the application of ground deformation detection and extraction combined with digital surface model (DSM), derived from China’s ZiYuan-3 (ZY-3) satellite stereo imagery and the advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM) data. A ...

A comparison of visual observations of surface oil with Synthetic Aperture Radar imagery of the Sea Empress oil spill

Energy Technology Data Exchange (ETDEWEB)

Jones, B.

2001-06-15

A comparison has been made between the visual observations of surface oil and four satellite-borne Synthetic Aperture Radar (SAR) images taken during the Sea Empress oil spill in February 1996. Whilst the basic oil slick imaging capabilities of SAR are well documented, to be of use at the time of a major oil spill, the imagery must be able to provide information on the thickness of oil. This analysis suggests that, under certain environmental conditions, this is possible. The optimum wind speed for the identification of heavy surface oil is around 5-6 m s{sup -1}. At this wind speed, light and medium sheen is not evident in the imagery and there is a distinction between the backscatter reductions due to heavy sheen and thick brown/black oil. At higher wind speeds, even thick oil slicks readily mix into the water column and their SAR signature weakens. In light winds, pattern recognition is very important to the identification of oil sticks. The images are more sensitive to the presence of sheen within the sheltered waters of Milford Haven than in the open coastal waters, indicating a possible relationship between sheen visibility in satellite-borne SAR and sea state. (author)

TerraSAR-X basierte Pre- und Post- Desaster Analyse zur Abschätzung vulkanbedingter Landbedeckungsveränderungen Fallbeispiel: Merapi 2010

OpenAIRE

Kalia, Andre Cahyadi

2011-01-01

This work demonstrates how Synthetic Aperture Radar (SAR) image analysis can successfully be used for supporting disaster and crisis-management concerning volcanic eruptions. In October/November 2010 the strato-volcano Mt. Merapi erupted leading to about 300 deaths and more than 380 000 refugees. Satellite imagery can be a very useful source to derive rapid crisis information for post-disaster relief efforts. Modern, space borne radar sensors like TerraSAR-X can deliver very high resolution r...

Satellite imagery in safeguards: progress and prospects

International Nuclear Information System (INIS)

Niemeyer, I.; Listner, C.

2013-01-01

The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

Oceanographic Applications of ALOS PALSAR Imagery to the Coast of the Korea Peninsula- A Case Study of the Hebei Spirit Oil Spill

Science.gov (United States)

Kim, Duk-jin; Kang, Jinho; Kim, Younsoo; Lee, Hoonyol; Moon, Wooil M.

2008-11-01

On December 7th, 2007, the nation's largest maritime oil spill occurred on the west coast of the Korean peninsula. More than 10,000 tons of crude oil from an oil tanker leaked into the Yellow Sea and contaminated an ecologically pristine region as well as polluted the western coastline of the Korean peninsula. All SAR sensors then available including TerraSAR-X, ENVISAT ASAR, RADARSAT-1, ERS-2 SAR and ALOS PALSAR acquired imageries over the contaminated area from oil spill. Dark patches observed in SAR images, due to the presence of oil slicks, were extracted using adaptive thresholding methods. From multi-frequency SAR images, the damping ratios were calculated and analyzed with measured wind speed and radar frequency. With the multi-temporal SAR images, the movement of oil slicks was monitored and traced.

A new DEM of the Austfonna ice cap by combining differential SAR interferometry with ICESat laser altimetry

Directory of Open Access Journals (Sweden)

Geir Moholdt

2012-05-01

Full Text Available We present a new digital elevation model (DEM of the Austfonna ice cap in the Svalbard Archipelago, Norwegian Arctic. Previous DEMs derived from synthetic aperture radar (SAR and optical shape-from-shading have been tied to airborne radio echo-sounding surface profiles from 1983 which contain an elevation-dependent bias of up to several tens of metres compared with recent elevation data. The new and freely available DEM is constructed purely from spaceborne remote sensing data using differential SAR interferometry (DInSAR in combination with ICESat laser altimetry. Interferograms were generated from pairs of SAR scenes from the one-day repeat tandem phase of the European Remote Sensing Satellites 1/2 (ERS-1/2 in 1996. ICESat elevations from winter 2006–08 were used as ground control points to refine the interferometric baseline. The resulting DEM is validated against the same ground control points and independent surface elevation profiles from Global Navigation Satellite Systems (GNSS and airborne laser altimetry, yielding root mean square (RMS errors of about 10 m in all cases. This quality is sufficient for most glaciological applications, and the new DEM will be a baseline data set for ongoing and future research at Austfonna. The technique of combining satellite DInSAR with high-resolution satellite altimetry for DEM generation might also be a good solution in other glacier regions with similar characteristics, especially when data from TanDEM-X and CryoSat-2 become available.

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

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Qingjun Zhang

2014-01-01

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

InSAR Time Series Analysis and Geophysical Modeling of City Uplift Associated with Geothermal Drillings in Staufen im Breisgau, Germany

Science.gov (United States)

Motagh, M.; Lubitz, C.

2014-12-01

Geothermal energy is of increasing importance as alternative, environmentally friendly technology for heat management. Direct interaction with the subsurface requires careful implementation, in particular in geological complex regions. The historical city Staufen im Breisgau, SW Germany, has attracted national attention as a case of implementation failure with severe consequences, causing debates on the applicability and security of this sustainable technique. Located at the eastern transition zone of the Upper Rhine Graben and the Schwarzwald massif, the geothermal potential is high at Staufen due to strong temperature gradients. In September 2007, seven boreholes for geothermal probes were drilled up to a depth of 140 m to provide a new heat management for the city hall. Within five years an uplift phenomenon has been observed in Staufen reaching more than 40 cm in places and 269 buildings were damaged. Hydro-chemical driven anhydrite-gypsum transformation in the subsurface was identified as the cause leading to volume increase that is observable as surface uplift. This process is associated with the geothermal drilling activities that have crossed several groundwater levels. In this work, we summarize and present the findings of spaceborne Synthetic Aperture Radar Interferometry (InSAR) analysis of the uplift in Staufen over the last five years from July 2008 through July 2013. By applying the Small Baseline Subset (SBAS) method, we find a localized elliptical-shaped deformation field in NE-SW orientation. Area of maximum uplift is located 50 m NNE of the drilling zone. At this location, we observe a cumulative uplift of approx. 13.7 cm ± 0.34 cm (mean value within an area of 30 m by 30 m) from July 2008 to July 2009, which reduced to cumulative uplift of 3 cm ± 0.25 cm from July 2012 to July 2013. The deceleration can be related to applied countermeasures as borehole sealing and groundwater pumping. The observed ground surface response was compared to

Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

Science.gov (United States)

McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

1999-01-01

This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

Quantitative Estimation of Above Ground Crop Biomass using Ground-based, Airborne and Spaceborne Low Frequency Polarimetric Synthetic Aperture Radar

Science.gov (United States)

Koyama, C.; Watanabe, M.; Shimada, M.

2016-12-01

Estimation of crop biomass is one of the important challenges in environmental remote sensing related to agricultural as well as hydrological and meteorological applications. Usually passive optical data (photographs, spectral data) operating in the visible and near-infrared bands is used for such purposes. The virtue of optical remote sensing for yield estimation, however, is rather limited as the visible light can only provide information about the chemical characteristics of the canopy surface. Low frequency microwave signals with wavelength longer 20 cm have the potential to penetrate through the canopy and provide information about the whole vertical structure of vegetation from the top of the canopy down to the very soil surface. This phenomenon has been well known and exploited to detect targets under vegetation in the military radar application known as FOPEN (foliage penetration). With the availability of polarimetric interferometric SAR data the use PolInSAR techniques to retrieve vertical vegetation structures has become an attractive tool. However, PolInSAR is still highly experimental and suitable data is not yet widely available. In this study we focus on the use of operational dual-polarization L-band (1.27 GHz) SAR which is since the launch of Japan's Advanced Land Observing Satellite (ALOS, 2006-2011) available worldwide. Since 2014 ALOS-2 continues to deliver such kind of partial polarimetric data for the entire land surface. In addition to these spaceborne data sets we use airborne L-band SAR data acquired by the Japanese Pi-SAR-L2 as well as ultra-wideband (UWB) ground based SAR data operating in the frequency range from 1-4 GHz. By exploiting the complex dual-polarization [C2] Covariance matrix information, the scattering contributions from the canopy can be well separated from the ground reflections allowing for the establishment of semi-empirical relationships between measured radar reflectivity and the amount of fresh-weight above

A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery

Directory of Open Access Journals (Sweden)

A. Castillo Atoche

2013-01-01

Full Text Available A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU, achieving considerable speedups compared to the serial version of the same techniques implemented in C language.

Ionospheric correction for spaceborne single-frequency GPS based ...

Indian Academy of Sciences (India)

A modified ionospheric correction method and the corresponding approximate algorithm for spaceborne single-frequency Global Positioning System (GPS) users are proposed in this study. Single Layer Model (SLM) mapping function for spaceborne GPS was analyzed. SLM mapping functions at different altitudes were ...

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

Science.gov (United States)

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

2016-04-01

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

Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

Science.gov (United States)

Moore, Angelyn W.; Webb, Frank H.; Fishbein, Evan F.; Fielding, Eric J.; Owen, Susan E.; Granger, Stephanie L.; Bjoerndahl, Fredrik; Loefgren, Johan; Fang, Peng; Means, James D.;

Sea Ice Deformation State From Synthetic Aperture Radar Imagery - Part II: Effects of Spatial Resolution and Noise Level

DEFF Research Database (Denmark)

Dierking, Wolfgang; Dall, Jørgen

2008-01-01

C- and L-band airborne synthetic aperture radar (SAR) imagery acquired at like- and cross-polarization over sea ice under winter conditions is examined with the objective to study the discrimination between level ice and ice deformation features. High-resolution low-noise data were analysed...... in the first paper. In this second paper, the main topics are the effects of spatial resolution and signal-to-noise ratio. Airborne, high-resolution SAR scenes are used to generate a sequence of images with increasingly coarser spatial resolution from 5 m to 25 m, keeping the number of looks constant....... The signal-to-noise ratio is varied between typical noise levels for airborne imagery and satellite data. Areal fraction of deformed ice and average deformation distance are determined for each image product. At L-band, the retrieved values of the areal fraction get larger as the image resolution is degraded...

Utility of Characterizing and Monitoring Suspected Underground Nuclear Sites with VideoSAR

Science.gov (United States)

Dauphin, S. M.; Yocky, D. A.; Riley, R.; Calloway, T. M.; Wahl, D. E.

2016-12-01

Sandia National Laboratories proposed using airborne synthetic aperture RADAR (SAR) collected in VideoSAR mode to characterize the Underground Nuclear Explosion Signature Experiment (UNESE) test bed site at the Nevada National Security Site (NNSS). The SNL SAR collected airborne, Ku-band (16.8 GHz center frequency), 0.2032 meter ground resolution over NNSS in August 2014 and X-band (9.6 GHz), 0.1016 meter ground resolution fully-polarimetric SAR in April 2015. This paper reports the findings of processing and exploiting VideoSAR for creating digital elevation maps, detecting cultural artifacts and exploiting full-circle polarimetric signatures. VideoSAR collects a continuous circle of phase history data, therefore, imagery can be formed over the 360-degrees of the site. Since the Ku-band VideoSAR had two antennas suitable for interferometric digital elevation mapping (DEM), DEMs could be generated over numerous aspect angles, filling in holes created by targets with height by imaging from all sides. Also, since the X-band VideoSAR was fully-polarimetric, scattering signatures could be gleaned from all angles also. Both of these collections can be used to find man-made objects and changes in elevation that might indicate testing activities. VideoSAR provides a unique, coherent measure of ground objects allowing one to create accurate DEMS, locate man-made objects, and identify scattering signatures via polarimetric exploitation. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. The authors would like to thank the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development, for sponsoring this work. We would also like to thank the Underground Nuclear Explosion Signatures Experiment team, a multi

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

Directory of Open Access Journals (Sweden)

Ross F. Nelson

2012-06-01

Full Text Available The objective of this study was to determine whether leaf area index (LAI in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric, five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R² to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors, when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

Lightweight high-performance 1-4 meter class spaceborne mirrors: emerging technology for demanding spaceborne requirements

Science.gov (United States)

Hull, Tony; Hartmann, Peter; Clarkson, Andrew R.; Barentine, John M.; Jedamzik, Ralf; Westerhoff, Thomas

2010-07-01

Pending critical spaceborne requirements, including coronagraphic detection of exoplanets, require exceptionally smooth mirror surfaces, aggressive lightweighting, and low-risk cost-effective optical manufacturing methods. Simultaneous development at Schott for production of aggressively lightweighted (>90%) Zerodur® mirror blanks, and at L-3 Brashear for producing ultra-smooth surfaces on Zerodur®, will be described. New L-3 techniques for large-mirror optical fabrication include Computer Controlled Optical Surfacing (CCOS) pioneered at L-3 Tinsley, and the world's largest MRF machine in place at L-3 Brashear. We propose that exceptional mirrors for the most critical spaceborne applications can now be produced with the technologies described.

Context and Quasi-Invariants in Automatic Target Recognition (ATR) with Synthetic Aperture Radar (SAR) Imagery

National Research Council Canada - National Science Library

Binford, Thomas

2000-01-01

.... Experiments based on conventional recognition techniques were conducted for comparisons. Study of persistent scattering confirms the feasibility of implementing a SAR ATR system using physical image features...

A comparison of SAR ATR performance with information theoretic predictions

Science.gov (United States)

Blacknell, David

2003-09-01

Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

Directory of Open Access Journals (Sweden)

Simon Plank

2014-12-01

Full Text Available In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads—rectangular features of bare land covering an area of approximately 50–60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery and the possibility of detailed land use classification (vs. single-pol SAR. The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59%–71% in each case (area based accuracy assessment. Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74%–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are

An ice-motion tracking system at the Alaska SAR facility

Science.gov (United States)

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

1990-01-01

An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.

Unsupervised DInSAR processing chain for multi-scale displacement analysis

Science.gov (United States)

Casu, Francesco; Manunta, Michele

2016-04-01

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

Visualization of and Software for Omnibus Test Based Change Detected in a Time Series of Polarimetric SAR Data

DEFF Research Database (Denmark)

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

2017-01-01

Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution and a factorization of this test statistic with associated p-values, change analysis in a time series of multilook polarimetric SAR data...... in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change occurs. Using airborne EMISAR and spaceborne RADARSAT-2 data this paper focuses on change detection based on the p-values, on visualization of change at pixel as well as segment level......, and on computer software....

Block adjustment of airborne InSAR based on interferogram phase and POS data

Science.gov (United States)

Yue, Xijuan; Zhao, Yinghui; Han, Chunming; Dou, Changyong

2015-12-01

High-precision surface elevation information in large scale can be obtained efficiently by airborne Interferomatric Synthetic Aperture Radar (InSAR) system, which is recently becoming an important tool to acquire remote sensing data and perform mapping applications in the area where surveying and mapping is difficult to be accomplished by spaceborne satellite or field working. . Based on the study of the three-dimensional (3D) positioning model using interferogram phase and Position and Orientation System (POS) data and block adjustment error model, a block adjustment method to produce seamless wide-area mosaic product generated from airborne InSAR data is proposed in this paper. The effect of 6 parameters, including trajectory and attitude of the aircraft, baseline length and incline angle, slant range, and interferometric phase, on the 3D positioning accuracy is quantitatively analyzed. Using the data acquired in the field campaign conducted in Mianyang county Sichuan province, China in June 2011, a mosaic seamless Digital Elevation Model (DEM) product was generated from 76 images in 4 flight strips by the proposed block adjustment model. The residuals of ground control points (GCPs), the absolute positioning accuracy of check points (CPs) and the relative positioning accuracy of tie points (TPs) both in same and adjacent strips were assessed. The experimental results suggest that the DEM and Digital Orthophoto Map (DOM) product generated by the airborne InSAR data with sparse GCPs can meet mapping accuracy requirement at scale of 1:10 000.

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

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Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

Remote Sensing of Deformation of a High Concrete-Faced Rockfill Dam Using InSAR: A Study of the Shuibuya Dam, China

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Wei Zhou

2016-03-01

Full Text Available Settlement is one of the most important deformation characteristics of high concrete faced rockfill dams (CFRDs, >100 m. High CFRDs safety would pose a great threat to the security of people’s lives and property downstream if this kind of deformation were not to be measured correctly, as traditional monitoring approaches have limitations in terms of durability, coverage, and efficiency. It has become urgent to develop new monitoring techniques to complement or replace traditional monitoring approaches for monitoring the safety and operation status of high CFRDs. This study examines the Shuibuya Dam (up to 233.5 m in height in China, which is currently the highest CFRD in the world. We used space-borne Interferometric Synthetic Aperture Radar (InSAR time series to monitor the surface deformation of the Shuibuya Dam. Twenty-one ALOS PALSAR images that span the period from 28 February 2007 to 11 March 2011 were used to map the spatial and temporal deformation of the dam. A high correlation of 0.93 between the InSAR and the in-situ monitoring results confirmed the reliability of the InSAR method; the deformation history derived from InSAR is also consistent with the in-situ settlement monitoring system. In addition, the InSAR results allow continuous investigation of dam deformation over a wide area that includes the entire dam surface as well as the surrounding area, offering a clear picture continuously of the dam deformation.

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

Science.gov (United States)

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

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

Characterize the hydrogeological properties and probe the stress field in Salt Lake Valley, Utah using SAR imagery

Science.gov (United States)

Hu, X.; Lu, Z.; Barbot, S.; Wang, T.

2017-12-01

Aquifer skeletons deform actively in response to the groundwater redistribution and hydraulic head changes with varied time scales of delay and sensitivity, that can also, in some instances, trigger earthquakes. However, determining the key hydrogeological properties and understanding the interactions between aquifer and seismicity generally requires the analysis of dense water level data combined with expensive drilling data (borehole breakouts). Here we investigate the spatiotemporal correlation among ground motions, hydrological changes, earthquakes, and faults in Salt Lake Valley, Utah, based on InSAR observations from ENVISAT ASAR (2004-2010) and Sentinel-1A (2015-2016). InSAR results show a clear seasonal and long-term correlation between surface uplift/subsidence and groundwater recharge/discharge, with evidence for an average net uplift of 15 mm/yr for a period of 7 years. The long-term uplift, remarkably bounded by faults, reflects a net increase in pore pressure associated with prolonged water recharge probably decades ago. InSAR-derived ground deformation and its correlation with head variations allow us to quantify hydrogeological properties - decay coefficient, storage coefficient, and bulk compressibility. We also model the long-term deformation using a shallow vertical shearing reservoir to constrain its thickness and strain rate. InSAR-derived deformation help reveal the coupled hydrological and tectonic processes in Salt Lake Valley: the embedded faults disrupt the groundwater flow and partition the hydrological units, and the pore pressure changes rearrange the aquifer skeleton and modulate the stress field, which may affect the basin-wide seismicity.

Mapping rice ecosystem dynamics and greenhouse gas emissions using multiscale imagery and biogeochemical models

Science.gov (United States)

Salas, W.; Torbick, N.

2017-12-01

Rice greenhouse gas (GHG) emissions in production hot spots have been mapped using multiscale satellite imagery and a processed-based biogeochemical model. The multiscale Synthetic Aperture Radar (SAR) and optical imagery were co-processed and fed into a machine leanring framework to map paddy attributes that are tuned using field observations and surveys. Geospatial maps of rice extent, crop calendar, hydroperiod, and cropping intensity were then used to parameterize the DeNitrification-DeComposition (DNDC) model to estimate emissions. Results, in the Red River Detla for example, show total methane emissions at 345.4 million kgCH4-C equivalent to 11.5 million tonnes CO2e (carbon dioxide equivalent). We further assessed the role of Alternative Wetting and Drying and the impact on GHG and yield across production hot spots with uncertainty estimates. The approach described in this research provides a framework for using SAR to derive maps of rice and landscape characteristics to drive process models like DNDC. These types of tools and approaches will support the next generation of Monitoring, Reporting, and Verification (MRV) to combat climate change and support ecosystem service markets.

Remote Monitoring of Groundwater Overdraft Using GRACE and InSAR

Science.gov (United States)

Scher, C.; Saah, D.

2017-12-01

Gravity Recovery and Climate Experiment (GRACE) data paired with radar-derived analyses of volumetric changes in aquifer storage capacity present a viable technique for remote monitoring of aquifer depletion. Interferometric Synthetic Aperture Radar (InSAR) analyses of ground level subsidence can account for a significant portion of mass loss observed in GRACE data and provide information on point-sources of overdraft. This study summed one water-year of GRACE monthly mass change grids and delineated regions with negative water storage anomalies for further InSAR analyses. Magnitude of water-storage anomalies observed by GRACE were compared to InSAR-derived minimum volumetric changes in aquifer storage capacity as a result of measurable compaction at the surface. Four major aquifers were selected within regions where GRACE observed a net decrease in water storage (Central Valley, California; Mekong Delta, Vietnam; West Bank, occupied Palestinian Territory; and the Indus Basin, South Asia). Interferogram imagery of the extent and magnitude of subsidence within study regions provided estimates for net minimum volume of groundwater extracted between image acquisitions. These volumetric estimates were compared to GRACE mass change grids to resolve a percent contribution of mass change observed by GRACE likely due to groundwater overdraft. Interferograms revealed characteristic cones of depression within regions of net mass loss observed by GRACE, suggesting point-source locations of groundwater overdraft and demonstrating forensic potential for the use of InSAR and GRACE data in remote monitoring of aquifer depletion. Paired GRACE and InSAR analyses offer a technique to increase the spatial and temporal resolution of remote applications for monitoring groundwater overdraft in addition to providing a novel parameter - measurable vertical deformation at the surface - to global groundwater models.

Mapping boreal forest biomass with imagery from polarimetric and semi-polarimetric SAR sensors / Mapeamento da biomassa fl orestal boreal com imagens dos sensores SAR polarimétricos e semi-polarimétricos

Directory of Open Access Journals (Sweden)

Yrjo Rauste

2008-09-01

Full Text Available Data from ALOS/Palsar and TerraSAR-X were used to estimate forest biomass in Boreal forest zone in Finland. In the study site in Heinavesi (forest biomass between 0 and 255 tons/ha, the HH-polarised componentof dual-polarised ALOS/Palsar produced biomass estimation accuracies (RMSE between 35 and 42 tons/ha. In the Kuortane site (biomass0…188 tons/ha the RMSE varied between 25 and 28 tons/ha. Since onlytwo winter-time scenes from TerraSAR-X were available, TerraSAR-X results were very preliminary. The phase of the HH-VV cross-coherenceproduced the highest biomass-correlations among the TerraSAR-X derived features. This produced a biomass estimation accuracy (RMSE of 49 tons/ha in the Heinavesi study site.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

Science.gov (United States)

Changyong, Dou; Huadong, Guo; Chunming, Han; Ming, Liu

2014-03-01

With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.

High Fidelity Non-Gravitational Force Models for Precise and Accurate Orbit Determination of TerraSAR-X

Science.gov (United States)

Hackel, Stefan; Montenbruck, Oliver; Steigenberger, -Peter; Eineder, Michael; Gisinger, Christoph

Remote sensing satellites support a broad range of scientific and commercial applications. The two radar imaging satellites TerraSAR-X and TanDEM-X provide spaceborne Synthetic Aperture Radar (SAR) and interferometric SAR data with a very high accuracy. The increasing demand for precise radar products relies on sophisticated validation methods, which require precise and accurate orbit products. Basically, the precise reconstruction of the satellite’s trajectory is based on the Global Positioning System (GPS) measurements from a geodetic-grade dual-frequency receiver onboard the spacecraft. The Reduced Dynamic Orbit Determination (RDOD) approach utilizes models for the gravitational and non-gravitational forces. Following a proper analysis of the orbit quality, systematics in the orbit products have been identified, which reflect deficits in the non-gravitational force models. A detailed satellite macro model is introduced to describe the geometry and the optical surface properties of the satellite. Two major non-gravitational forces are the direct and the indirect Solar Radiation Pressure (SRP). Due to the dusk-dawn orbit configuration of TerraSAR-X, the satellite is almost constantly illuminated by the Sun. Therefore, the direct SRP has an effect on the lateral stability of the determined orbit. The indirect effect of the solar radiation principally contributes to the Earth Radiation Pressure (ERP). The resulting force depends on the sunlight, which is reflected by the illuminated Earth surface in the visible, and the emission of the Earth body in the infrared spectra. Both components of ERP require Earth models to describe the optical properties of the Earth surface. Therefore, the influence of different Earth models on the orbit quality is assessed within the presentation. The presentation highlights the influence of non-gravitational force and satellite macro models on the orbit quality of TerraSAR-X.

Coupling SAR X-band and optical data for NDVI retrieval: model calibration and validation on two test areas

Science.gov (United States)

Capodici, Fulvio; D'Urso, Guido; Maltese, Antonino; Ciraolo, Giuseppe

2013-10-01

Sustainability of modern agro-hydrology requires the knowledge of spatial and temporal variability of vegetation biomass to optimize management of land and water resources. Diversely from optical imaging, temporal resolution of active sensors, such as SAR, is not limited by sky cloudiness; thus, they may be combined with optical imageries to provide a more continuous monitoring of land surfaces. Several new SAR missions (e.g., ALOS-PALSAR, COSMO-SkyMed 1 and 2, TerraSAR-X, TerraSAR-X2, Sentinel 1) acquiring at X-, C- and L-bands and dual polarization capability, are characterized by a short revisit time (from 12 h to ~10 days) and high spatial resolution (COSMOSkyMed images and 2 Landsat 7 SLC-off images were acquired in the southwestern part of Sicily (Italy) between 8 and 25 August 2011. Determination coefficients of the validation set were similar to those of the calibration set. Results confirm that VISAR obtained using the combined model is a suitable surrogate of VIopt if estimated at parcel scale.

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

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M. Mahdian

2013-09-01

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

Soil parameter retrieval under vegetation cover using SAR polarimetery

Energy Technology Data Exchange (ETDEWEB)

Jagdhuber, Thomas

2012-07-01

values: 1-46vol.%) and of 0.37-0.45 cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.

Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

Science.gov (United States)

Bardi, Federica; Frodella, William; Ciampalini, Andrea; Bianchini, Silvia; Del Ventisette, Chiara; Gigli, Giovanni; Fanti, Riccardo; Moretti, Sandro; Basile, Giuseppe; Casagli, Nicola

2014-10-01

The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty-clayey sedimentary cover. In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques. PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14 min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to

Hydrological Regime Monitoring and Mapping of the Zhalong Wetland through Integrating Time Series Radarsat-2 and Landsat Imagery

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Xiaodong Na

2018-05-01

Full Text Available Zhalong wetland is a globally important breeding habitat for many rare migratory bird species. Prompted by the high demand for temporal and spatial information about the wetland’s hydrological regimes and landscape patterns, eight time series Radarsat-2 images were utilized to detect the flooding characteristics of the Zhalong wetland. Subsequently, a random forest model was built to discriminate wetlands from other land cover types, combining with optical, radar, and hydrological regime data derived from multitemporal synthetic aperture radar (SAR images. The results showed that hydrological regimes variables, including flooding extent and flooding frequency, derived from multitemporal SAR images, improve the land cover classification accuracy in the natural wetlands distribution area. The permutation importance scores derived from the random forest classifier indicate that normalized difference vegetation index (NDVI calculated from optical imagery and the flooding frequency derived from multitemporal SAR imagery were found to be the most important variables for land cover mapping. Accuracy testing indicate that the addition of hydrological regime features effectively depressed the omission error rates (from 52.14% to 2.88% of marsh and the commission error (from 77.34% to 51.27% of meadow, thereby improving the overall classification accuracy (from 76.49% to 91.73%. The hydrological regimes and land cover monitoring in the typical wetlands are important for eco-hydrological modeling, biodiversity conservation, and regional ecology and water security.

UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

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S. Havivi

2016-06-01

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

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

Science.gov (United States)

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

2014-05-01

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

Limitations and potential of satellite imagery to monitor environmental response to coastal flooding

Science.gov (United States)

Ramsey, Elijah W.; Werle, Dirk; Suzuoki, Yukihiro; Rangoonwala, Amina; Lu, Zhong

2012-01-01

Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

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

Science.gov (United States)

Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco

2013-04-01

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

Estimation of Melt Pond Fractions on First Year Sea Ice Using Compact Polarization SAR

Science.gov (United States)

Li, Haiyan; Perrie, William; Li, Qun; Hou, Yijun

2017-10-01

Melt ponds are a common feature on Arctic sea ice. They are linked to the sea ice surface albedo and transmittance of energy to the ocean from the atmosphere and thus constitute an important process to parameterize in Arctic climate models and simulations. This paper presents a first attempt to retrieve the melt pond fraction from hybrid-polarized compact polarization (CP) SAR imagery, which has wider swath and shorter revisit time than the quad-polarization systems, e.g., from RADARSAT-2 (RS-2). The co-polarization (co-pol) ratio has been verified to provide estimates of melt pond fractions. However, it is a challenge to link CP parameters and the co-pol ratio. The theoretical possibility is presented, for making this linkage with the CP parameter C22/C11 (the ratio between the elements of the coherence matrix of CP SAR) for melt pond detection and monitoring with the tilted-Bragg scattering model for the ocean surface. The empirical transformed formulation, denoted as the "compact polarization and quad-pol" ("CPQP") model, is proposed, based on 2062 RS-2 quad-pol SAR images, collocated with in situ measurements. We compared the retrieved melt pond fraction with CP parameters simulated from quad-pol SAR data with results retrieved from the co-pol ratio from quad-pol SAR observations acquired during the Arctic-Ice (Arctic-Ice Covered Ecosystem in a Rapidly Changing Environment) field project. The results are shown to be comparable for observed melt pond measurements in spatial and temporal distributions. Thus, the utility of CP mode SAR for melt pond fraction estimation on first year level ice is presented.

Perception-oriented fusion of multi-sensor imagery: visible, IR, and SAR

Science.gov (United States)

Sidorchuk, D.; Volkov, V.; Gladilin, S.

2018-04-01

This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.

Significant Wave Height under Hurricane Irma derived from SAR Sentinel-1 Data

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Lehner, S.; Pleskachevsky, A.; Soloviev, A.; Fujimura, A.

2017-12-01

The 2017 Atlantic hurricane season was with three major hurricanes a particular active one. The Category 4 hurricane Irma made landfall on the Florida Keys on September 10th 2017 and was imaged several times by ESAs Sentinel-1 satellites in C-band and the TerraSAR-X satellite in X-band. The high resolution TerraSAR-X imagery showed the footprint of individual tornadoes on the sea surface together with their turbulent wake imaged as a dark line due to increased turbulence. The water-cloud structures of the tornadoes are analyzed and their sea surface structure is compared to optical and IR cloud imagery. An estimate of the wind field using standard XMOD algorithms is provided, although saturating under the strong rain and high wind speed conditions. Imaging the hurricanes by space radar gives the opportunity to observe the sea surface and thus measure the wind field and the sea state under hurricane conditions through the clouds even in this severe weather, although rain features, which are usually not observed in SAR become visible due to damping effects. The Copernicus Sentinel-1 A and B satellites, which are operating in C-band provided several images of the sea surface under hurricane Irma, Jose and Maria. The data were acquired daily and converted into measurements of sea surface wind field u10 and significant wave height Hs over a swath width of 280km about 1000 km along the orbit. The wind field of the hurricanes as derived by CMOD is provided by NOAA operationally on their web server. In the hurricane cases though the wind speed saturates at 20 m/sec and is thus too low in the area of hurricane wind speed. The technique to derive significant wave height is new though and does not show any calibration issues. This technique provides for the first time measurements of the areal coverage and distribution of the ocean wave height as caused by a hurricane on SAR wide swath images. Wave heights up to 10 m were measured under the forward quadrant of the hurricane

Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

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Clark, J.

1981-01-01

In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

Monitoring of "urban villages" in Shenzhen, China from high-resolution GF-1 and TerraSAR-X data

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Wei, Chunzhu; Blaschke, Thomas; Taubenböck, Hannes

2015-10-01

Urban villages comprise mainly low-rise and congested, often informal settlements surrounded by new constructions and high-rise buildings whereby structures can be very different between neighboring areas. Monitoring urban villages and analyzing their characteristics are crucial for urban development and sustainability research. In this study, we carried out a combined analysis of multispectral GaoFen-1 (GF-1) and high resolution TerraSAR-X radar (TSX) imagery to extract the urban village information. GF-1 and TSX data are combined with the Gramshmidt spectral sharpening method so as to provide new input data for urban village classification. The Grey-Level Co-occurrence Matrix (GLCM) approach was also applied to four directions to provide another four types (all, 0°, 90°, 45° directions) of TSX-based inputs for urban village detection. We analyzed the urban village mapping performance using the Random Forest approach. The results demonstrate that the best overall accuracy and the best producer accuracy of urban villages reached with the GLCM 90° dataset (82.33%, 68.54% respectively). Adding single polarization TSX data as input information to the optical image GF-1 provided an average product accuracy improvement of around 7% in formal built-up area classification. The SAR and optical fusion imagery also provided an effective means to eliminate some layover, shadow effects, and dominant scattering at building locations and green spaces, improving the producer accuracy by 7% in urban area classification. To sum up, the added value of SAR information is demonstrated by the enhanced results achievable over built-up areas, including formal and informal settlements.

Investigating the backscatter contrast anomaly in synthetic aperture radar (SAR) imagery of the dunes along the Israel-Egypt border

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Rozenstein, Offer; Siegal, Zehava; Blumberg, Dan G.; Adamowski, Jan

2016-04-01

The dune field intersected by the Israel-Egypt borderline has attracted many remote sensing studies over the years because it exhibits unique optical phenomena in several domains, from the visual to the thermal infrared. These phenomena are the result of land-use policies implemented by the two countries, which have differing effects on the two ecosystems. This study explores the surface properties that affect radar backscatter, namely the surface roughness and dielectric properties, in order to determine the cause for the variation across the border. The backscatter contrast was demonstrated for SIR-C, the first synthetic aperture radar (SAR) sensor to capture this phenomenon, as well as ASAR imagery that coincides with complementary ground observations. These field observations along the border, together with an aerial image from the same year as the SIR-C acquisition were used to analyze differences in vegetation patterns that can affect the surface roughness. The dielectric permittivity of two kinds of topsoil (sand, biocrust) was measured in the field and in the laboratory. The results suggest that the vegetation structure and spatial distribution differ between the two sides of the border in a manner that is consistent with the radar observations. The dielectric permittivity of sand and biocrust was found to be similar, although they are not constant across the radar spectral region (50 MHz-20 GHz). These findings support the hypothesis that changes to the vegetation, as a consequence of the different land-use practices in Israel and Egypt, are the cause for the radar backscatter contrast across the border.

A new approach for river flood extent delineation in rural and urban areas combining RADARSAT-2 imagery and flood recurrence interval data

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Tanguy, Marion; Bernier, Monique; Chokmani, Karem

2015-04-01

When a flood hits an inhabited area, managers and services responsible for public safety need precise, reliable and up to date maps of the areas affected by the flood, in order to quickly roll out and to coordinate the adequate intervention and assistance plans required to limit the human and material damages caused by the disaster. Synthetic aperture radar (SAR) sensors are now considered as one of the most adapted tool for flood detection and mapping in a context of crisis management. Indeed, due to their capacity to acquire data night and day, in almost all meteorological conditions, SAR sensors allow the acquisition of synoptic but detailed views of the areas affected by the flood, even during the active phases of the event. Moreover, new generation sensors such as RADARSAT-2, TerraSAR-X, COSMO-SkyMed, are providing very high resolution images of the disaster (down to 1m ground resolution). Further, critical improvements have been made on the temporal repetitivity of acquisitions and on data availability, through the development of satellite constellations (i.e the four COSMO-Skymed or the Sentinel-1A and 1B satellites) and thanks to the implementation of the International Charter "Space and Major Disasters", which guarantees high priority images acquisition and delivery with 4 to 12 hours. If detection of open water flooded areas is relatively straightforward with SAR imagery, flood detection in built-up areas is often associated with important issues. Indeed, because of the side looking geometry of the SAR sensors, structures such as tall vegetation and structures parallel to the satellite direction of travel may produce shadow and layover effects, leading to important over and under-detections of flooded pixels. Besides, the numerous permanent water-surfaces like radar response areas present in built-up environments, such as parking lots, roads etc., may be mixed up with flooded areas, resulting in substantial inaccuracies in the final flood map. In spite of

SAR Agriculture Rice Production Estimation (SARPE)

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Raimadoya, M.

2013-12-01

The study of SAR Agriculture Rice Production Estimation (SARPE) was held in Indonesia on 2012, as part of Asia-Rice Crop Estimation & Monitoring (Asia-RiCE), which is a component for the GEO Global Agricultural Monitoring (GEOGLAM) initiative. The study was expected to give a breakthrough result, by using radar technology and paradigm shift of the standard production estimation system from list frame to area frame approach. This initial product estimation system is expected to be refined (fine tuning) in 2013, by participating as part of Technical Demonstration Site (Phase -1A) of Asia-RICE. The implementation period of this initial study was from the date of March 12 to December 10, 2012. The implementation of the study was done by following the approach of the BIMAS-21 framework, which has been developed since 2008. The results of this study can be briefly divided into two major components, namely: Rice-field Baseline Mapping (PESBAK - Peta Sawah Baku) and Crop Growth Monitoring. Rice-fields were derived from the mapping results of the Ministry of Agriculture (Kemtan), and validated through Student Extension Campaign of the Faculty of Agriculture, Bogor Agricultural University (IPB). While for the crop growth, it was derived from the results of image analysis process. The analysis was done, either on radar/Radarsat-2 (medium resolution) or optical/ MODIS (low resolution), based on the Planting Calendar (KATAM) of Kemtan. In this case, the planting season II/2012-2013 of rice production centers in West Java Province (Karawang, Subang and Indramayu counties). The selection of crop season and county were entirely dependent on the quality of the available PESBAK and procurement process of radar imagery. The PESBAK is still in the form of block instead of fields, so it can not be directly utilized in this study. Efforts to improve the PESBAK can not be optimal because the provided satellite image (ECW format) is not the original one. While the procurement process of

Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico

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Jesús Pacheco-Martínez

2015-12-01

Full Text Available In this work we present an application of InSAR and gravimetric surveys for risk management related to land subsidence and surface ground faulting generation. A subsidence velocity map derived from the 2007–2011 ALOS SAR imagery and a sediment thicknesses map obtained from the inversion of gravimetric data were integrated with a surface fault map to produce a subsidence hazard zoning in the city of Aguascalientes, Mexico. The resulting zoning is presented together with specific recommendations about geotechnical studies needed for further evaluation of surface faulting in these hazard zones. The derived zoning map consists in four zones including null hazard (stable terrain without subsidence, low hazard (areas prone to subsidence, medium hazard (zones with subsidence and high hazard (zones with surface faulting. InSAR results displayed subsidence LOS velocities up to 10 cm/year and two subsidence areas unknown before this study. Gravimetric results revealed that the thicker sediment sequence is located toward north of Aguascalientes City reaching up to 600 m in thickness, which correspond to a high subsidence LOS velocity zone (up to 6 cm/year.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-10-15

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

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

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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.

SAR Observation and Numerical Simulation of Internal Solitary Wave Refraction and Reconnection Behind the Dongsha Atoll

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Jia, T.; Liang, J. J.; Li, X.-M.; Sha, J.

2018-01-01

The refraction and reconnection of internal solitary waves (ISWs) around the Dongsha Atoll (DSA) in the northern South China Sea (SCS) are investigated based on spaceborne synthetic aperture radar (SAR) observations and numerical simulations. In general, a long ISW front propagating from the deep basin of the northern SCS splits into northern and southern branches when it passes the DSA. In this study, the statistics of Envisat Advanced SAR (ASAR) images show that the northern and southern wave branches can reconnect behind the DSA, but the reconnection location varies. A previously developed nonlinear refraction model is set up to simulate the refraction and reconnection of the ISWs behind the DSA, and the model is used to evaluate the effects of ocean stratification, background currents, and incoming ISW characteristics at the DSA on the variation in reconnection locations. The results of the first realistic simulation agree with consecutive TerraSAR-X (TSX) images captured within 12 h of each other. Further sensitivity simulations show that ocean stratification, background currents, and initial wave amplitudes all affect the phase speeds of wave branches and therefore shift their reconnection locations while shapes and locations of incoming wave branches upstream of the DSA profoundly influence the subsequent propagation paths. This study clarifies the variation in reconnection locations of ISWs downstream of the DSA and reveals the important mechanisms governing the reconnection process, which can improve our understanding of the propagation of ISWs near the DSA.

TerraSAR-X InSAR multipass analysis on Venice, Italy)

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

2009-09-01

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

Observations and Mitigation of RFI in ALOS PALSAR SAR Data; Implications for the Desdyni Mission

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Rosen, Paul A.; Hensley, Scott; Le, Charles

2008-01-01

Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystems, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems as well. Therefore the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands is of considerable interest. RFI is observed in ALOS PALSAR in California, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straightforward spectral normalization to time-domain, multi-phase filtering techniques are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

SPACE-BORNE LASER ALTIMETER GEOLOCATION ERROR ANALYSIS

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Y. Wang

2018-05-01

Full Text Available This paper reviews the development of space-borne laser altimetry technology over the past 40 years. Taking the ICESAT satellite as an example, a rigorous space-borne laser altimeter geolocation model is studied, and an error propagation equation is derived. The influence of the main error sources, such as the platform positioning error, attitude measurement error, pointing angle measurement error and range measurement error, on the geolocation accuracy of the laser spot are analysed by simulated experiments. The reasons for the different influences on geolocation accuracy in different directions are discussed, and to satisfy the accuracy of the laser control point, a design index for each error source is put forward.

Simulating return signals of a spaceborne high-spectral resolution lidar channel at 532 nm

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Xiao, Yu; Binglong, Chen; Min, Min; Xingying, Zhang; Lilin, Yao; Yiming, Zhao; Lidong, Wang; Fu, Wang; Xiaobo, Deng

2018-06-01

High spectral resolution lidar (HSRL) system employs a narrow spectral filter to separate the particulate (cloud/aerosol) and molecular scattering components in lidar return signals, which improves the quality of the retrieved cloud/aerosol optical properties. To better develop a future spaceborne HSRL system, a novel simulation technique was developed to simulate spaceborne HSRL return signals at 532 nm using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/aerosol extinction coefficients product and numerical weather prediction data. For validating simulated data, a mathematical particulate extinction coefficient retrieval method for spaceborne HSRL return signals is described here. We compare particulate extinction coefficient profiles from the CALIPSO operational product with simulated spaceborne HSRL data. Further uncertainty analysis shows that relative uncertainties are acceptable for retrieving the optical properties of cloud and aerosol. The final results demonstrate that they agree well with each other. It indicates that the return signals of the spaceborne HSRL molecular channel at 532 nm will be suitable for developing operational algorithms supporting a future spaceborne HSRL system.

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

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Tae-Sung Kim

2018-04-01

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

Wetland Classification for Black Duck Habitat Management Using Combined Polarimetric RADARSAT 2 and SPOT Imagery

Science.gov (United States)

Zhang, W.; Hu, B.; Brown, G.

2018-04-01

The black duck population has decreased significantly due to loss of its breeding habitat. Wetlands are an important feature that relates to habitat management and requires monitoring. Synthetic Aperture Radar (SAR) systems are helpful to map the wetland as the microwave signals are sensitive to water content and can be used to map surface water extent, saturated soils, and flooded vegetation. In this study, RadarSat 2 Polarimetric data is employed to map surface water and track changes in extent over the years through image thresholding and reviewed different approaches of Polarimetric decompositions for detecting flooded vegetation. Also, object-based analysis associated with beaver activity is conducted with combined multispectral SPOT satellite imagery. Results show SAR data has proven ability to improve mapping open water areas and locate flooded vegetation areas.

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

Science.gov (United States)

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

2012-07-23

We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

LE NUOVE FRONTIERE DELL’ARCHEOLOGIA DALLA FOTOGRAFIA AEREA AL TELERILEVAMENTO SATELLITARE SAR

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Nicole Dore

2012-04-01

Full Text Available

Il grande progresso tecnologico ha dato la possibilità a campi di indagine più tradizionali, come l’archeologia, di usufruire di tecnologie per trarne il massimo vantaggio ai fini di indagini preventive sul campo. È sulla sciadi conquiste come il telerilevamento satellitare ottico ad alta risoluzione spaziale, che la presente ricerca si è spinta oltre tali confini, con lo scopo di indagare la tecnica polarimetrica SAR (Synthetic Aperture Radar.

New Frontiers in Archaeology. From Aerial Photography to Satellite Remote Sensing SAR

This work is part of an ongoing PhD project held at the Area di Geodesia e Geomatica – University ofRome ‘La Sapienza’. The work involves the study of archaeological sites through the analysis of polarimetric L-band data from the PALSAR sensor (on the Japanese ALOS satellite, launched in May 2006 with the aim of understanding the spectral signature of archaeologicalremains (above and below ground. The Italian sites of Vulci (VTand Arpi (FG, analyzed through polarimetric imagery, were chosen according to the availability of polarimetric SAR data at the time of the study and to the different geomorphologic characteristics of theterrain, with the purpose of observing the scattering mechanisms associated to the features present in the scene.

Long term SAR interferometry monitoring for assessing changing levels of slope instability hazards

Science.gov (United States)

Wasowski, J.; Ferretti, A.

The population growth with increasing impact of man on the environment and urbanisation of areas susceptible to slope failures coupled with the ongoing change in climate patterns will require a shift in the approaches to landslide hazard reduction Indeed there is evidence that landslide activity and related socio-economic loss are increasing in both rich and less developed countries throughout the world Because of this and because the urbanisation of hillside and mountain slopes prone to failure will likely continue in the future the protection of new and pre-existing developed areas via traditional engineering stabilisation works and in situ monitoring is not considered economically feasible Furthermore in most cases the ground control systems are installed post-factum and for short term monitoring and hence their role in preventing disasters is limited Considering the global dimension of the slope instability problem a sustainable road to landslide hazard reduction seems to be via exploitation of EO systems with focus on early detection long term monitoring and early warning Thanks to the wide-area coverage regular schedule and improving resolution of space-borne sensors the EO can foster the auspicious shift from a culture of repair to a culture of awarness and prevention Under this scenario the space-borne synthetic aperture radar differential interferometry DInSAR is attractive because of its capability to provide both wide-area and spatially dense information on surface displacements Since the presence of movements represents a direct evidence of

USING COMBINATION OF PLANAR AND HEIGHT FEATURES FOR DETECTING BUILT-UP AREAS FROM HIGH-RESOLUTION STEREO IMAGERY

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F. Peng

2017-09-01

Full Text Available Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slope and building height are often used to optimize the results, but extracted from auxiliary data (e.g. LIDAR data, DSM. Moreover, the auxiliary data must be acquired around the same time as image acquisition. Otherwise, built-up area detection accuracy is affected. Stereo imagery incorporates both planar and height information unlike single remotely sensed images. Stereo imagery acquired by many satellites (e.g. Worldview-4, Pleiades-HR, ALOS-PRISM, and ZY-3 can be used as data source of identifying built-up areas. A new method of identifying high-accuracy built-up areas from stereo imagery is achieved by using a combination of planar and height features. The digital surface model (DSM and digital orthophoto map (DOM are first generated from stereo images. Then, height values of above-ground objects (e.g. buildings are calculated from the DSM, and used to obtain raw built-up areas. Other raw built-up areas are obtained from the DOM using Pantex and Gabor, respectively. Final high-accuracy built-up area results are achieved from these raw built-up areas using the decision level fusion. Experimental results show that accurate built-up areas can be achieved from stereo imagery. The height information used in the proposed method is derived from stereo imagery itself, with no need to require auxiliary height data (e.g. LIDAR data. The proposed method is suitable for spaceborne and airborne stereo pairs and triplets.

Using Combination of Planar and Height Features for Detecting Built-Up Areas from High-Resolution Stereo Imagery

Science.gov (United States)

Peng, F.; Cai, X.; Tan, W.

2017-09-01

Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slope and building height are often used to optimize the results, but extracted from auxiliary data (e.g. LIDAR data, DSM). Moreover, the auxiliary data must be acquired around the same time as image acquisition. Otherwise, built-up area detection accuracy is affected. Stereo imagery incorporates both planar and height information unlike single remotely sensed images. Stereo imagery acquired by many satellites (e.g. Worldview-4, Pleiades-HR, ALOS-PRISM, and ZY-3) can be used as data source of identifying built-up areas. A new method of identifying high-accuracy built-up areas from stereo imagery is achieved by using a combination of planar and height features. The digital surface model (DSM) and digital orthophoto map (DOM) are first generated from stereo images. Then, height values of above-ground objects (e.g. buildings) are calculated from the DSM, and used to obtain raw built-up areas. Other raw built-up areas are obtained from the DOM using Pantex and Gabor, respectively. Final high-accuracy built-up area results are achieved from these raw built-up areas using the decision level fusion. Experimental results show that accurate built-up areas can be achieved from stereo imagery. The height information used in the proposed method is derived from stereo imagery itself, with no need to require auxiliary height data (e.g. LIDAR data). The proposed method is suitable for spaceborne and airborne stereo pairs and triplets.

Speckle Filtering of GF-3 Polarimetric SAR Data with Joint Restriction Principle.

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Xie, Jinwei; Li, Zhenfang; Zhou, Chaowei; Fang, Yuyuan; Zhang, Qingjun

2018-05-12

Polarimetric SAR (PolSAR) scattering characteristics of imagery are always obtained from the second order moments estimation of multi-polarization data, that is, the estimation of covariance or coherency matrices. Due to the extra-paths that signal reflected from separate scatterers within the resolution cell has to travel, speckle noise always exists in SAR images and has a severe impact on the scattering performance, especially on single look complex images. In order to achieve high accuracy in estimating covariance or coherency matrices, three aspects are taken into consideration: (1) the edges and texture of the scene are distinct after speckle filtering; (2) the statistical characteristic should be similar to the object pixel; and (3) the polarimetric scattering signature should be preserved, in addition to speckle reduction. In this paper, a joint restriction principle is proposed to meet the requirement. Three different restriction principles are introduced to the processing of speckle filtering. First, a new template, which is more suitable for the point or line targets, is designed to ensure the morphological consistency. Then, the extent sigma filter is used to restrict the pixels in the template aforementioned to have an identical statistic characteristic. At last, a polarimetric similarity factor is applied to the same pixels above, to guarantee the similar polarimetric features amongst the optional pixels. This processing procedure is named as speckle filtering with joint restriction principle and the approach is applied to GF-3 polarimetric SAR data acquired in San Francisco, CA, USA. Its effectiveness of keeping the image sharpness and preserving the scattering mechanism as well as speckle reduction is validated by the comparison with boxcar filters and refined Lee filter.

Extraction of advanced geospatial intelligence (AGI) from commercial synthetic aperture radar imagery

Science.gov (United States)

Kanberoglu, Berkay; Frakes, David

2017-04-01

The extraction of objects from advanced geospatial intelligence (AGI) products based on synthetic aperture radar (SAR) imagery is complicated by a number of factors. For example, accurate detection of temporal changes represented in two-color multiview (2CMV) AGI products can be challenging because of speckle noise susceptibility and false positives that result from small orientation differences between objects imaged at different times. These cases of apparent motion can result in 2CMV detection, but they obviously differ greatly in terms of significance. In investigating the state-of-the-art in SAR image processing, we have found that differentiating between these two general cases is a problem that has not been well addressed. We propose a framework of methods to address these problems. For the detection of the temporal changes while reducing the number of false positives, we propose using adaptive object intensity and area thresholding in conjunction with relaxed brightness optical flow algorithms that track the motion of objects across time in small regions of interest. The proposed framework for distinguishing between actual motion and misregistration can lead to more accurate and meaningful change detection and improve object extraction from a SAR AGI product. Results demonstrate the ability of our techniques to reduce false positives up to 60%.

Soil Moisture Estimation in South-Eastern New Mexico Using High Resolution Synthetic Aperture Radar (SAR Data

Directory of Open Access Journals (Sweden)

A.K.M. Azad Hossain

2016-01-01

Full Text Available Soil moisture monitoring and characterization of the spatial and temporal variability of this hydrologic parameter at scales from small catchments to large river basins continues to receive much attention, reflecting its critical role in subsurface-land surface-atmospheric interactions and its importance to drought analysis, irrigation planning, crop yield forecasting, flood protection, and forest fire prevention. Synthetic Aperture Radar (SAR data acquired at different spatial resolutions have been successfully used to estimate soil moisture in different semi-arid areas of the world for many years. This research investigated the potential of linear multiple regressions and Artificial Neural Networks (ANN based models that incorporate different geophysical variables with Radarsat 1 SAR fine imagery and concurrently measured soil moisture measurements to estimate surface soil moisture in Nash Draw, NM. An artificial neural network based model with vegetation density, soil type, and elevation data as input in addition to radar backscatter values was found suitable to estimate surface soil moisture in this area with reasonable accuracy. This model was applied to a time series of SAR data acquired in 2006 to produce soil moisture data covering a normal wet season in the study site.

InSAR atmospheric correction using Himawari-8 Geostationary Meteorological Satellite

Science.gov (United States)

Kinoshita, Y.; Nimura, T.; Furuta, R.

2017-12-01

The atmospheric delay effect is one of the limitations for the accurate surface displacement detection by Synthetic Aperture Radar Interferometry (InSAR). Many previous studies have attempted to mitigate the neutral atmospheric delay in InSAR (e.g. Jolivet et al. 2014; Foster et al. 2006; Kinoshita et al. 2013). Hanssen et al. (2001) investigated the relationship between the 27 hourly observations of GNSS precipitable water vapor (PWV) and the infrared brightness temperature derived from visible satellite imagery, and showed a good correlation. Here we showed a preliminary result of the newly developed method for the neutral atmospheric delay correction using the Himawari-8 Japanese geostationary meteorological satellite data. The Himawari-8 satellite is the Japanese state-of-the-art geostationary meteorological satellite that has 16 observation channels and has spatial resolutions of 0.5 km (visible) and 2.0 km (near-infrared and infrared) with an time interval of 2.5 minutes around Japan. To estimate the relationship between the satellite brightness temperature and the atmospheric delay amount. Since the InSAR atmospheric delay is principally the same as that in GNSS, we at first compared the Himawari-8 data with the GNSS zenith tropospheric delay data derived from the Japanese dense GNSS network. The comparison of them showed that the band with the wavelength of 6.9 μm had the highest correlation to the GNSS observation. Based on this result, we developed an InSAR atmospheric delay model that uses the Himawari-8 6.9 μm band data. For the model validation, we generated InSAR images from the ESA's C-band Sentinel-1 SLC data with the GAMMA SAR software. We selected two regions around Tokyo and Sapporo (both in Japan) as the test sites because of the less temporal decorrelation. The validation result showed that the delay model reasonably estimate large scale phase variation whose spatial scale was on the order of over 20 km. On the other hand, phase variations of

SARS - Diagnosis

Indian Academy of Sciences (India)

SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

Directory of Open Access Journals (Sweden)

Simon Plank

2014-05-01

Full Text Available Fast crisis response after natural disasters, such as earthquakes and tropical storms, is necessary to support, for instance, rescue, humanitarian, and reconstruction operations in the crisis area. Therefore, rapid damage mapping after a disaster is crucial, i.e., to detect the affected area, including grade and type of damage. Thereby, satellite remote sensing plays a key role due to its fast response, wide field of view, and low cost. With the increasing availability of remote sensing data, numerous methods have been developed for damage assessment. This article gives a comprehensive review of these techniques focusing on multi-temporal SAR procedures for rapid damage assessment: interferometric coherence and intensity correlation. The review is divided into six parts: First, methods based on coherence; second, the ones using intensity correlation; and third, techniques using both methodologies combined to increase the accuracy of the damage assessment are reviewed. Next, studies using additional data (e.g., GIS and optical imagery to support the damage assessment and increase its accuracy are reported. Moreover, selected studies on post-event SAR damage assessment techniques and examples of other applications of the interferometric coherence are presented. Then, the preconditions for a successful worldwide application of multi-temporal SAR methods for damage assessment and the limitations of current SAR satellite missions are reported. Finally, an outlook to the Sentinel-1 SAR mission shows possible solutions of these limitations, enabling a worldwide applicability of the presented damage assessment methods.

A prototype of an automated high resolution InSAR volcano-monitoring system in the MED-SUV project

Science.gov (United States)

Chowdhury, Tanvir A.; Minet, Christian; Fritz, Thomas

2016-04-01

Volcanic processes which produce a variety of geological and hydrological hazards are difficult to predict and capable of triggering natural disasters on regional to global scales. Therefore it is important to monitor volcano continuously and with a high spatial and temporal sampling rate. The monitoring of active volcanoes requires the reliable measurement of surface deformation before, during and after volcanic activities and it helps for the better understanding and modelling of the involved geophysical processes. Space-borne synthetic aperture radar (SAR) interferometry (InSAR), persistent scatterer interferometry (PSI) and small baseline subset algorithm (SBAS) provide a powerful tool for observing the eruptive activities and measuring the surface changes of millimetre accuracy. All the mentioned techniques with deformation time series extraction address the challenges by exploiting medium to large SAR image stacks. The process of selecting, ordering, downloading, storing, logging, extracting and preparing the data for processing is very time consuming has to be done manually for every single data-stack. In many cases it is even an iterative process which has to be done regularly and continuously. Therefore, data processing becomes slow which causes significant delays in data delivery. The SAR Satellite based High Resolution Data Acquisition System, which will be developed at DLR, will automate this entire time consuming tasks and allows an operational volcano monitoring system. Every 24 hours the system runs for searching new acquired scene over the volcanoes and keeps track of the data orders, log the status and download the provided data via ftp-transfer including E-Mail alert. Furthermore, the system will deliver specified reports and maps to a database for review and use by specialists. The user interaction will be minimized and iterative processes will be totally avoided. In this presentation, a prototype of SAR Satellite based High Resolution Data

Synthetic Aperture Radar Technology Conference, New Mexico State University, Las Cruces, N. Mex., March 8-10, 1978, Proceedings

Science.gov (United States)

1978-01-01

The following aspects of SAR development are discussed: calibration techniques, image simulation and interpretability, antennas, data processing, and system design. Papers are presented on such topics as a postlaunch calibration experiment for the Seasat-A SAR, computer simulation of an orbital SAR system, definition study of the Shuttle Imaging Radar, custom LSI circuits for spaceborne SAR processors, and random sampling adaptively focusing SAR.

Bistatic sAR data processing algorithms

CERN Document Server

Qiu, Xiaolan; Hu, Donghui

2013-01-01

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

Developing Initial Response Products Using Data from Optical and SAR Earth Observing Platforms for Natural Disaster Response

Science.gov (United States)

Bell, J. R.; Molthan, A.; Dabboor, M.

2016-12-01

After a disaster occurs, decision makers require timely information to assist decision making and support. Earth observing satellites provide tools including optical remote sensors that sample in various spectral bands within the visible, near-infrared, and thermal infrared. However, views from optical sensors can be blocked when clouds are present, and cloud-free observations can be significantly delayed depending upon on their repeat cycle. Synthetic aperture radar (SAR) offers several advantages over optical sensors in terms of spatial resolution and the ability to map the Earth's surface whether skies are clear or cloudy. In cases where both SAR and cloud-free optical data are available, these instruments can be used together to provide additional confidence in what is being observed at the surface. This presentation demonstrates cases where SAR imagery can enhance the usefulness for mapping natural disasters and their impacts to the land surface, specifically from severe weather and flooding. The Missouri and Mississippi River flooding from early in 2016 and damage from hail swath in northwestern Iowa on 17 June 2016 are just two events that will be explored. Data collected specifically from the EO-1 (optical), Landsat (optical) and Sentinel 1 (SAR) missions are used to explore several applicable methodologies to determine which products and methodologies may provide decision makers with the best information to provide actionable information in a timely manner.

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

Science.gov (United States)

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.

Spaceborne potential for examining taiga-tundra ecotone form and vulnerability

Science.gov (United States)

Montesano, Paul M.; Sun, Guoqing; Dubayah, Ralph O.; Ranson, K. Jon

2016-07-01

In the taiga-tundra ecotone (TTE), site-dependent forest structure characteristics can influence the subtle and heterogeneous structural changes that occur across the broad circumpolar extent. Such changes may be related to ecotone form, described by the horizontal and vertical patterns of forest structure (e.g., tree cover, density, and height) within TTE forest patches, driven by local site conditions, and linked to ecotone dynamics. The unique circumstance of subtle, variable, and widespread vegetation change warrants the application of spaceborne data including high-resolution (ecotone form. We demonstrate the potential of spaceborne data for integrating forest height and density to assess TTE form at the scale of forest patches across the circumpolar biome by (1) mapping forest patches in study sites along the TTE in northern Siberia with a multi-resolution suite of spaceborne data and (2) examining the uncertainty of forest patch height from this suite of data across sites of primarily diffuse TTE forms. Results demonstrate the opportunities for improving patch-scale spaceborne estimates of forest height, the vertical component of TTE form, with HRSI. The distribution of relative maximum height uncertainty based on prediction intervals is centered at ˜ 40 %, constraining the use of height for discerning differences in forest patches. We discuss this uncertainty in light of a conceptual model of general ecotone forms and highlight how the uncertainty of spaceborne estimates of height can contribute to the uncertainty in identifying TTE forms. A focus on reducing the uncertainty of height estimates in forest patches may improve depiction of TTE form, which may help explain variable forest responses in the TTE to climate change and the vulnerability of portions of the TTE to forest structure change.

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

Science.gov (United States)

Hayati, Noorlaila; Riedel, Björn; Niemeier, Wolfgang

2016-04-01

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

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

Science.gov (United States)

Dietterich, Hannah R.; Poland, Michael P.; Schmidt, David; Cashman, Katharine V.; Sherrod, David R.; Espinosa, Arkin Tapia

2012-01-01

Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu‘u ‘Ō‘ō-Kupaianaha eruption at Kīlauea, Hawai‘i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post-emplacement flow subsidence.

Flood Extent Mapping for Namibia Using Change Detection and Thresholding with SAR

Science.gov (United States)

Long, Stephanie; Fatoyinbo, Temilola E.; Policelli, Frederick

2014-01-01

A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km2, 720 km2, and 673 km2 respectively. Pixels determined to be flooded in vegetation were typically flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes.

Keynote presentation : SAR systems

NARCIS (Netherlands)

Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

2011-01-01

Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

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

Science.gov (United States)

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

2018-06-01

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

Landslide Susceptibility Mapping Using GIS-based Vector Grid File (VGF Validating with InSAR Techniques: Three Gorges, Yangtze River (China

Directory of Open Access Journals (Sweden)

Cem Kıncal

2017-04-01

Full Text Available A landslide susceptibility assessment for the Three Gorges (TG region (China was performed in a Geographical Information System (GIS environment and Persistent Scatterer (PS InSAR derived displacements were used for validation purposes. Badong County of TG was chosen as case study field. Landslide parameters were derived from two datasets. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER Global Digital Elevation Map (GDEM was used to calculate slope geometry parameters (slope, aspect, drainage, and lineament, while geology and vegetation cover were obtained from Landsat and ASTER data. The majority of historical landslides occurred in the sandstone-shale-claystone intercalations. It appears that slope gradients are more critical than other parameters such as aspect and drainage. The susceptibility assessment was based on a summation of assigned susceptibility scores (points for each 30×30 m unit in a database of a Vector Grid File (VGF composed of ‘vector pixels’. A landslide susceptibility map (LSM was generated using VGF and classified with low, moderate and high landslide susceptibility zones. The comparison between the LSM and PS InSAR derived displacements suggests that landslides only account for parts of the observed surface movements.

Single-Chip FPGA Azimuth Pre-Filter for SAR

Science.gov (United States)

Gudim, Mimi; Cheng, Tsan-Huei; Madsen, Soren; Johnson, Robert; Le, Charles T-C; Moghaddam, Mahta; Marina, Miguel

2005-01-01

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals

Airborne S-Band SAR for Forest Biophysical Retrieval in Temperate Mixed Forests of the UK

Directory of Open Access Journals (Sweden)

Ramesh K. Ningthoujam

2016-07-01

Full Text Available Radar backscatter from forest canopies is related to forest cover, canopy structure and aboveground biomass (AGB. The S-band frequency (3.1–3.3 GHz lies between the longer L-band (1–2 GHz and the shorter C-band (5–6 GHz and has been insufficiently studied for forest applications due to limited data availability. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest biophysical properties. To understand the scattering mechanisms in forest canopies at S-band the Michigan Microwave Canopy Scattering (MIMICS-I radiative transfer model was used. S-band backscatter was found to have high sensitivity to the forest canopy characteristics across all polarisations and incidence angles. This sensitivity originates from ground/trunk interaction as the dominant scattering mechanism related to broadleaved species for co-polarised mode and specific incidence angles. The study was carried out in the temperate mixed forest at Savernake Forest and Wytham Woods in southern England, where airborne S-band SAR imagery and field data are available from the recent AirSAR campaign. Field data from the test sites revealed wide ranges of forest parameters, including average canopy height (6–23 m, diameter at breast-height (7–42 cm, basal area (0.2–56 m2/ha, stem density (20–350 trees/ha and woody biomass density (31–520 t/ha. S-band backscatter-biomass relationships suggest increasing backscatter sensitivity to forest AGB with least error between 90.63 and 99.39 t/ha and coefficient of determination (r2 between 0.42 and 0.47 for the co-polarised channel at 0.25 ha resolution. The conclusion is that S-band SAR data such as from NovaSAR-S is suitable for monitoring forest aboveground biomass less than 100 t/ha at 25 m resolution in low to medium incidence angle range.

Bistatic SAR: Proof of Concept.

Energy Technology Data Exchange (ETDEWEB)

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

2014-10-01

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

The Seamless SAR Archive (SSARA) Project and Other SAR Activities at UNAVCO

Science.gov (United States)

Baker, S.; Crosby, C. J.; Meertens, C. M.; Fielding, E. J.; Bryson, G.; Buechler, B.; Nicoll, J.; Baru, C.

2014-12-01

The seamless synthetic aperture radar archive (SSARA) implements a seamless distributed access system for SAR data and derived data products (i.e. interferograms). SSARA provides a unified application programming interface (API) for SAR data search and results at the Alaska Satellite Facility and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives. Interest from the international community has prompted an effort to incorporate ESA's Virtual Archive 4 Geohazard Supersites and Natural Laboratories (GSNL) collections and other archives into the federated query service. SSARA also provides Digital Elevation Model access for topographic correction via a simple web service through OpenTopography and tropospheric correction products through JPL's OSCAR service. Additionally, UNAVCO provides data storage capabilities for WInSAR PIs with approved TerraSAR-X and ALOS-2 proposals which allows easier distribution to US collaborators on associated proposals and facilitates data access through the SSARA web services. Further work is underway to incorporate federated data discovery for GSNL across SAR, GPS, and seismic datasets provided by web services from SSARA, GSAC, and COOPEUS.

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

Directory of Open Access Journals (Sweden)

J. Tao

2012-09-01

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

Optical registration of spaceborne low light remote sensing camera

Science.gov (United States)

Li, Chong-yang; Hao, Yan-hui; Xu, Peng-mei; Wang, Dong-jie; Ma, Li-na; Zhao, Ying-long

2018-02-01

For the high precision requirement of spaceborne low light remote sensing camera optical registration, optical registration of dual channel for CCD and EMCCD is achieved by the high magnification optical registration system. System integration optical registration and accuracy of optical registration scheme for spaceborne low light remote sensing camera with short focal depth and wide field of view is proposed in this paper. It also includes analysis of parallel misalignment of CCD and accuracy of optical registration. Actual registration results show that imaging clearly, MTF and accuracy of optical registration meet requirements, it provide important guarantee to get high quality image data in orbit.

Feasibility Study on Passive-radar Detection of Space Targets Using Spaceborne Illuminators of Opportunity

Directory of Open Access Journals (Sweden)

Jiang Tie-zhen

2015-01-01

Full Text Available Space target surveillance generally uses active radars. To take full advantage of passive radars, the idea of using spaceborne illuminators of opportunity for space target detection is presented in this paper. Analysis of the detectable time and direct wave suppression shows that passive radar using spaceborne illuminators of opportunity can effectively detect a Low-Earth-Orbit (LEO target. Meanwhile, Ku and L band bi-static radar cross section of passive radars that use spaceborne illuminators of opportunity are presented by simulation, providing the basis of choosing space target forward scatter. Finally the key parameters, mainly system gain, accumulation time and radiation source selection are studied. Results show that system size using satellite TV signals as illuminators of opportunity is relatively small. These encouraging results should stimulate the development of passive radar detection of space targets using spaceborne illuminators of opportunity.

Severe acute respiratory syndrome (SARS)

Science.gov (United States)

SARS; Respiratory failure - SARS ... Complications may include: Respiratory failure Liver failure Heart failure ... 366. McIntosh K, Perlman S. Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). ...

Ship Analysis and Detection in High-resolution Pol-SAR Imagery Based on Peak Zone

Directory of Open Access Journals (Sweden)

Xu Cheng-bin

2015-06-01

Full Text Available To deal with the problem of false alarm in the ship detection, a method base on proportion of spiral scattering in the peak zone is proposed. By comparing the proportion of spiral scattering in the peak zone, which is available from Krogager decomposition, the ships and interfering targets are identified and analyzed. The effectiveness of this method is justified with C-band full-polarization data from RADARSAT-2. The result show that this method can discriminate ships from interfering targets such as island, water-break, nautical platforms and bridges, thus reducing the false alarm rate of ship targets detection in SAR images.

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

Science.gov (United States)

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.

Characterizing floodplain evolution by joint analysis of SAR, GOES IR and local precipitation data: Case study of Rio Colorado, Bolivia

Science.gov (United States)

Koenders, R.; Oyen, A. M.; Weltje, G.; Sarna, K.; Donselaar, R.

2013-12-01

Dryland rivers in an endorheic basin experience downstream decrease of channel width and depth as the consequence of transmission losses by percolation and evapo-transpiration. Major changes in the river morphology take place during short peak discharge periods when the volume of water and sediment by far exceeds the river capacity and, as a consequence, meander bends are cut off, and the river path may change position by avulsion. Successive avulsions create a complex network of cross-cutting abandoned river channels. The Río Colorado, located in the southeast part of the Altiplano basin in Bolivia, is such a river system. This system consists of a very low-gradient lacustrine coastal plain onto which is deposited a 400 km2 sheet of fluvial sediment over the last 4000 year. Traditional studies to monitor the morphological changes at the terminus of the river system are based on field data acquisition of the fluvial sediments. This is time consuming and only covers a small area of the total fluvial morphology. The combination of field measurements and remote sensing imagery allows for the analysis of the development of the entire river system terminus at a longer temporal scale. Changes of alluvial surfaces affect the reflectance of objects and patterns on the ground, which is recorded by satellite images. In this study we show the response of the delta to rainfall events of various intensities in the Rio Colorado watershed. We combine precipitation data in the watershed with spaceborne synthetic aperture radar (SAR) data. We use two data sets that contain precipitation information: rainfall estimates based on Geostationary Operational Environmental Satellite (GOES) weather satellite IR window brightness temperatures and direct measures of rainfall from rain gauges in the vicinity of the delta. To detect changes on the surface water content we use the backscatter intensity or amplitude images from the European Remote Sensing Satellite (ERS) Synthetic Aperture

Forward modeling of space-borne gravitational wave detectors

International Nuclear Information System (INIS)

Rubbo, Louis J.; Cornish, Neil J.; Poujade, Olivier

2004-01-01

Planning is underway for several space-borne gravitational wave observatories to be built in the next 10 to 20 years. Realistic and efficient forward modeling will play a key role in the design and operation of these observatories. Space-borne interferometric gravitational wave detectors operate very differently from their ground-based counterparts. Complex orbital motion, virtual interferometry, and finite size effects complicate the description of space-based systems, while nonlinear control systems complicate the description of ground-based systems. Here we explore the forward modeling of space-based gravitational wave detectors and introduce an adiabatic approximation to the detector response that significantly extends the range of the standard low frequency approximation. The adiabatic approximation will aid in the development of data analysis techniques, and improve the modeling of astrophysical parameter extraction

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

Science.gov (United States)

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

2007-04-01

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

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

Directory of Open Access Journals (Sweden)

Shengli Song

2016-08-01

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

a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

Science.gov (United States)

Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

2014-10-01

In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

Science.gov (United States)

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

2016-06-01

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

LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

Directory of Open Access Journals (Sweden)

I. Schvartzman

2016-06-01

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

Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

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Manabu Watanabe

2010-01-01

Full Text Available We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR σ∘ under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the σ∘ difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that σ∘ and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

Directory of Open Access Journals (Sweden)

Shimada Masanobu

2010-01-01

Full Text Available Abstract We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

Source analysis of spaceborne microwave radiometer interference over land

Science.gov (United States)

Guan, Li; Zhang, Sibo

2016-03-01

Satellite microwave thermal emissions mixed with signals from active sensors are referred to as radiofrequency interference (RFI). Based on Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) observations from June 1 to 16, 2011, RFI over Europe was identified and analyzed using the modified principal component analysis algorithm in this paper. The X band AMSR-E measurements in England and Italy are mostly affected by the stable, persistent, active microwave transmitters on the surface, while the RFI source of other European countries is the interference of the reflected geostationary TV satellite downlink signals to the measurements of spaceborne microwave radiometers. The locations and intensities of the RFI induced by the geostationary TV and communication satellites changed with time within the observed period. The observations of spaceborne microwave radiometers in ascending portions of orbits are usually interfered with over European land, while no RFI was detected in descending passes. The RFI locations and intensities from the reflection of downlink radiation are highly dependent upon the relative geometry between the geostationary satellite and the measuring passive sensor. Only these fields of view of a spaceborne instrument whose scan azimuths are close to the azimuth relative to the geostationary satellite are likely to be affected by RFI.

SAR: Stroke Authorship Recognition

KAUST Repository

Shaheen, Sara

2015-10-15

Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

Crop Classification by Polarimetric SAR

DEFF Research Database (Denmark)

Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming

1999-01-01

Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...

Integrating SAR and derived products into operational volcano monitoring and decision support systems

Science.gov (United States)

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

2015-02-01

Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

Training visual imagery: Improvements of metacognition, but not imagery strength

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Rosanne Lynn Rademaker

2012-07-01

Full Text Available Visual imagery has been closely linked to brain mechanisms involved in perception. Can visual imagery, like visual perception, improve by means of training? Previous research has demonstrated that people can reliably evaluate the vividness of single episodes of sensory imagination – might the metacognition of imagery also improve over the course of training? We had participants imagine colored Gabor patterns for an hour a day, over the course of five consecutive days, and again two weeks after training. Participants rated the subjective vividness and effort of their mental imagery on each trial. The influence of imagery on subsequent binocular rivalry dominance was taken as our measure of imagery strength. We found no overall effect of training on imagery strength. Training did, however, improve participant’s metacognition of imagery. Trial-by-trial ratings of vividness gained predictive power on subsequent rivalry dominance as a function of training. These data suggest that, while imagery strength might be immune to training in the current context, people’s metacognitive understanding of mental imagery can improve with practice.

The Parallel SBAS-DInSAR algorithm: an effective and scalable tool for Earth's surface displacement retrieval

Science.gov (United States)

Zinno, Ivana; De Luca, Claudio; Elefante, Stefano; Imperatore, Pasquale; Manunta, Michele; Casu, Francesco

2014-05-01

been carried out on real data acquired by ENVISAT and COSMO-SkyMed sensors. Moreover, the P-SBAS performances with respect to the size of the input dataset will also be investigated. This kind of analysis is essential for assessing the goodness of the P-SBAS algorithm and gaining insight into its applicability to different scenarios. Besides, such results will also become crucial to identify and evaluate how to appropriately exploit P-SBAS to process the forthcoming large Sentinel-1 data stream. References [1] Massonnet, D., Briole, P., Arnaud, A., "Deflation of Mount Etna monitored by Spaceborne Radar Interferometry", Nature, vol. 375, pp. 567-570, 1995. [2] Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti, "A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms", IEEE Trans. Geosci. Remote Sens., vol. 40, no. 11, pp. 2375-2383, Nov. 2002. [3] Elefante, S., Imperatore, P. , Zinno, I., M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, F. Casu, "SBAS-DINSAR Time series generation on cloud computing platforms", IEEE IGARSS 2013, July 2013, Melbourne (AU). [4] Zinno, P. Imperatore, S. Elefante, F. Casu, M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, "A Novel Parallel Computational Framework for Processing Large INSAR Data Sets", Living Planet Symposium 2013, Sept. 9-13, 2013.

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

Science.gov (United States)

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

2005-10-01

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

Flood extent mapping for Namibia using change detection and thresholding with SAR

International Nuclear Information System (INIS)

Long, Stephanie; Fatoyinbo, Temilola E; Policelli, Frederick

2014-01-01

A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision-based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km 2 , 720 km 2 , and 673 km 2 respectively. Pixels determined to be flooded in vegetation were typically <0.5% of the entire scene, with the exception of 2009 where the detection of flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes. (paper)

Identification of Soil Freezing and Thawing States Using SAR Polarimetry at C-Band

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Thomas Jagdhuber

2014-03-01

Full Text Available The monitoring of soil freezing and thawing states over large areas is very challenging on ground. In order to investigate the potential and the limitations of space-borne SAR polarimetry at C-band for soil state survey, analyses were conducted on an entire winter time series of fully polarimetric RADARSAT-2 data from 2011/2012 to identify freezing as well as thawing states within the soil. The polarimetric data were acquired over the Sodankylä test site in Finland together with in situ measurements of the soil and the snow cover. The analyses indicate clearly that the dynamics of the polarimetric entropy and mean scattering alpha angle are directly correlated to soil freezing and thawing states, even under distinct dry snow cover. First modeling attempts using the Extended Bragg soil scattering model justify the observed trends, which indicate surface-like scattering during frozen soil conditions and multiple/volume scattering for thawed soils. Hence, these first investigations at C-band foster motivation to work towards a robust polarimetric detection of soil freezing and thawing states as well as their transition phase.

Peptide Mimicrying Between SARS Coronavirus Spike Protein and Human Proteins Reacts with SARS Patient Serum

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K.-Y. Hwa

2008-01-01

Full Text Available Molecular mimicry, defined as similar structures shared by molecules from dissimilar genes or proteins, is a general strategy used by pathogens to infect host cells. Severe acute respiratory syndrome (SARS is a new human respiratory infectious disease caused by SARS coronavirus (SARS-CoV. The spike (S protein of SARS-CoV plays an important role in the virus entry into a cell. In this study, eleven synthetic peptides from the S protein were selected based on its sequence homology with human proteins. Two of the peptides D07 (residues 927–937 and D08 (residues 942–951 were recognized by the sera of SARS patients. Murine hyperimmune sera against these peptides bound to proteins of human lung epithelial cells A549. Another peptide D10 (residues 490–502 stimulated A549 to proliferate and secrete IL-8. The present results suggest that the selected S protein regions, which share sequence homology with human proteins, may play important roles in SARS-CoV infection.

Impact of the Regulators SigB, Rot, SarA and sarS on the Toxic Shock Tst Promoter and TSST-1 Expression in Staphylococcus aureus.

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Diego O Andrey

Full Text Available Staphylococcus aureus is an important pathogen manifesting virulence through diverse disease forms, ranging from acute skin infections to life-threatening bacteremia or systemic toxic shock syndromes. In the latter case, the prototypical superantigen is TSST-1 (Toxic Shock Syndrome Toxin 1, encoded by tst(H, and carried on a mobile genetic element that is not present in all S. aureus strains. Transcriptional regulation of tst is only partially understood. In this study, we dissected the role of sarA, sarS (sarH1, RNAIII, rot, and the alternative stress sigma factor sigB (σB. By examining tst promoter regulation predominantly in the context of its native sequence within the SaPI1 pathogenicity island of strain RN4282, we discovered that σB emerged as a particularly important tst regulator. We did not detect a consensus σB site within the tst promoter, and thus the effect of σB is likely indirect. We found that σB strongly repressed the expression of the toxin via at least two distinct regulatory pathways dependent upon sarA and agr. Furthermore rot, a member of SarA family, was shown to repress tst expression when overexpressed, although its deletion had no consistent measurable effect. We could not find any detectable effect of sarS, either by deletion or overexpression, suggesting that this regulator plays a minimal role in TSST-1 expression except when combined with disruption of sarA. Collectively, our results extend our understanding of complex multifactorial regulation of tst, revealing several layers of negative regulation. In addition to environmental stimuli thought to impact TSST-1 production, these findings support a model whereby sporadic mutation in a few key negative regulators can profoundly affect and enhance TSST-1 expression.

Assessing ScanSAR Interferometry for Deformation Studies

Science.gov (United States)

Buckley, S. M.; Gudipati, K.

2007-12-01

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

Mapping Changes and Damages in Areas of Conflict: From Archive C-Band SAR Data to New HR X-Band Imagery, Towards the Sentinels

Science.gov (United States)

Tapete, Deodato; Cigna, Francesca; Donoghue, Daniel N. M.; Philip, Graham

2015-05-01

On the turn of radar space science with the recent launch of Sentinel-1A, we investigate how to better exploit the opportunities offered by large C-band SAR archives and increasing datasets of HR to VHR X-band data, to map changes and damages in urban and rural areas affected by conflicts. We implement a dual approach coupling multi-interferogram processing and amplitude change detection, to assess the impact of the recent civil war on the city of Homs, Western Syria, and the surrounding semi-arid landscape. More than 280,000 coherent pixels are retrieved from Small BAseline Subset (SBAS) processing of the 8year-long ENVISAT ASAR IS2 archive, to quantify land subsidence due to pre-war water abstraction in rural areas. Damages in Homs are detected by analysing the changes of SAR backscattering (σ0), comparing 3m-resolution StripMap TerraSAR-X pairs from 2009 to 2014. Pre-war alteration is differentiated from war-related damages via operator-driven interpretation of the σ0 patterns.

Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery

Science.gov (United States)

Mahdianpari, Masoud; Salehi, Bahram; Mohammadimanesh, Fariba; Motagh, Mahdi

2017-08-01

Wetlands are important ecosystems around the world, although they are degraded due both to anthropogenic and natural process. Newfoundland is among the richest Canadian province in terms of different wetland classes. Herbaceous wetlands cover extensive areas of the Avalon Peninsula, which are the habitat of a number of animal and plant species. In this study, a novel hierarchical object-based Random Forest (RF) classification approach is proposed for discriminating between different wetland classes in a sub-region located in the north eastern portion of the Avalon Peninsula. Particularly, multi-polarization and multi-frequency SAR data, including X-band TerraSAR-X single polarized (HH), L-band ALOS-2 dual polarized (HH/HV), and C-band RADARSAT-2 fully polarized images, were applied in different classification levels. First, a SAR backscatter analysis of different land cover types was performed by training data and used in Level-I classification to separate water from non-water classes. This was followed by Level-II classification, wherein the water class was further divided into shallow- and deep-water classes, and the non-water class was partitioned into herbaceous and non-herbaceous classes. In Level-III classification, the herbaceous class was further divided into bog, fen, and marsh classes, while the non-herbaceous class was subsequently partitioned into urban, upland, and swamp classes. In Level-II and -III classifications, different polarimetric decomposition approaches, including Cloude-Pottier, Freeman-Durden, Yamaguchi decompositions, and Kennaugh matrix elements were extracted to aid the RF classifier. The overall accuracy and kappa coefficient were determined in each classification level for evaluating the classification results. The importance of input features was also determined using the variable importance obtained by RF. It was found that the Kennaugh matrix elements, Yamaguchi, and Freeman-Durden decompositions were the most important parameters

SARS-related perceptions in Hong Kong.

Science.gov (United States)

Lau, Joseph T F; Yang, Xilin; Pang, Ellie; Tsui, H Y; Wong, Eric; Wing, Yun Kwok

2005-03-01

To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means of prevention; 40.4% believed that SARS would resurge in Hong Kong; and approximately equals 70% would then wear masks in public places. High percentages of respondents felt helpless, horrified, and apprehensive because of SARS. Approximately 16% showed signs of posttraumatic symptoms, and approximately equals 40% perceived increased stress in family or work settings. The general public in Hong Kong has been very vigilant about SARS but needs to be more psychologically prepared to face a resurgence of the epidemic.

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

Science.gov (United States)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

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

Science.gov (United States)

Kojima, S.; Hensley, S.

2012-12-01

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

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

Science.gov (United States)

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

SAR: Stroke Authorship Recognition

KAUST Repository

Shaheen, Sara; Rockwood, Alyn; Ghanem, Bernard

2015-01-01

Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

Generation of large-scale forest height and disturbance maps through the fusion of NISAR and GEDI along with TanDEM-X/L

Science.gov (United States)

Lei, Y.; Treuhaft, R. N.; Siqueira, P.; Torbick, N.; Lucas, R.; Keller, M. M.; Schmidt, M.; Ducey, M. J.; Salas, W.

2017-12-01

Large-scale products of forest height and disturbance are essential for understanding the global carbon distribution as well as its changes in response to natural events and human activities. Regarding this scientific need, both NASA's GEDI and NASA-ISRO's NISAR are going to be launched in the 2018-2021 timeframe in parallel with DLR's current TanDEM-X and/or the proposed TanDEM-L, which provides a lot of potential for global ecosystem mapping. A new simple and efficient method of forest height mapping has been developed for combining spaceborne repeat-pass InSAR and lidar missions (e.g. NISAR and GEDI) which estimates temporal decorrelation parameters of repeat-pass InSAR and uses the lidar data as training samples. An open-access Python-based software has been developed for automated processing. As a result, a mosaic of forest height was generated for US states of Maine and New Hampshire (11.6 million ha) using JAXA's ALOS-1 and ALOS-2 HV-pol InSAR data and a small piece of lidar training samples (44,000 ha) with the height estimates validated against airborne lidar and field inventory data over both flat and mountainous areas. In addition, through estimating and correcting for the temporal decorrelation effects in the spaceborne repeat-pass InSAR coherence data and also utilizing the spaceborne single-pass InSAR phase data, forest disturbance such as selective logging is not only detected but also quantified in subtropical forests of Australia using ALOS-1 HH-pol InSAR data (validated against NASA's Landsat), as well as in tropics of Brazil using TanDEM-X and ALOS-2 HH-pol InSAR data (validated against field inventory data). The operational simplicity and efficiency make these methods a potential observing/processing prototype for the fusion of NISAR, GEDI and TanDEM-X/L.

Bathymetric mapping of submarine sand waves using multiangle sun glitter imagery: a case of the Taiwan Banks with ASTER stereo imagery

Science.gov (United States)

Zhang, Hua-guo; Yang, Kang; Lou, Xiu-lin; Li, Dong-ling; Shi, Ai-qin; Fu, Bin

2015-01-01

Submarine sand waves are visible in optical sun glitter remote sensing images and multiangle observations can provide valuable information. We present a method for bathymetric mapping of submarine sand waves using multiangle sun glitter information from Advanced Spaceborne Thermal Emission and Reflection Radiometer stereo imagery. Based on a multiangle image geometry model and a sun glitter radiance transfer model, sea surface roughness is derived using multiangle sun glitter images. These results are then used for water depth inversions based on the Alpers-Hennings model, supported by a few true depth data points (sounding data). Case study results show that the inversion and true depths match well, with high-correlation coefficients and root-mean-square errors from 1.45 to 2.46 m, and relative errors from 5.48% to 8.12%. The proposed method has some advantages over previous methods in that it requires fewer true depth data points, it does not require environmental parameters or knowledge of sand-wave morphology, and it is relatively simple to operate. On this basis, we conclude that this method is effective in mapping submarine sand waves and we anticipate that it will also be applicable to other similar topography types.

Precision Rectification of Airborne SAR Image

DEFF Research Database (Denmark)

Dall, Jørgen; Liao, M.; Zhang, Zhe

1997-01-01

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

Precipitation evidences on X-Band Synthetic Aperture Radar imagery: an approach for quantitative detection and estimation

Science.gov (United States)

Mori, Saverio; Marzano, Frank S.; Montopoli, Mario; Pulvirenti, Luca; Pierdicca, Nazzareno

2017-04-01

Spaceborne synthetic aperture radars (SARs) operating at L-band and above are nowadays a well-established tool for Earth remote sensing; among the numerous civil applications we can indicate flood areas detection and monitoring, earthquakes analysis, digital elevation model production, land use monitoring and classification. Appealing characteristics of this kind of instruments is the high spatial resolution ensured in almost all-weather conditions and with a reasonable duty cycle and coverage. This result has achieved by the by the most recent generation of SAR missions, which moreover allow polarimetric observation of the target. Nevertheless, atmospheric clouds, in particular the precipitating ones, can significantly affect the signal backscattered from the ground surface (e.g. Ferrazzoli and Schiavon, 1997), on both amplitude and phase, with effects increasing with the operating frequency. In this respect, proofs are given by several recent works (e.g. Marzano et al., 2010, Baldini et al., 2014) using X-Band SAR data by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions. On the other hand, this sensitivity open interesting perspectives towards the SAR observation, and eventually quantification, of precipitations. In this respect, a proposal approach for X-SARs precipitation maps production and cloud masking arise from our work. Cloud masking allows detection of precipitation compromised areas. Respect precipitation maps, satellite X-SARs offer the unique possibility to ingest within flood forecasting model precipitation data at the catchment scale. This aspect is particularly innovative, even if work has been done the late years, and some aspects need to still address. Our developed processing framework allows, within the cloud masking stage, distinguishing flooded areas, precipitating clouds together with permanent water bodies, all appearing dark in the SAR image. The procedure is mainly based on image segmentation techniques and fuzzy logic (e.g. Pulvirenti et

SARS: systematic review of treatment effects.

Directory of Open Access Journals (Sweden)

Lauren J Stockman

2006-09-01

Full Text Available BACKGROUND: The SARS outbreak of 2002-2003 presented clinicians with a new, life-threatening disease for which they had no experience in treating and no research on the effectiveness of treatment options. The World Health Organization (WHO expert panel on SARS treatment requested a systematic review and comprehensive summary of treatments used for SARS-infected patients in order to guide future treatment and identify priorities for research. METHODS AND FINDINGS: In response to the WHO request we conducted a systematic review of the published literature on ribavirin, corticosteroids, lopinavir and ritonavir (LPV/r, type I interferon (IFN, intravenous immunoglobulin (IVIG, and SARS convalescent plasma from both in vitro studies and in SARS patients. We also searched for clinical trial evidence of treatment for acute respiratory distress syndrome. Sources of data were the literature databases MEDLINE, EMBASE, BIOSIS, and the Cochrane Central Register of Controlled Trials (CENTRAL up to February 2005. Data from publications were extracted and evidence within studies was classified using predefined criteria. In total, 54 SARS treatment studies, 15 in vitro studies, and three acute respiratory distress syndrome studies met our inclusion criteria. Within in vitro studies, ribavirin, lopinavir, and type I IFN showed inhibition of SARS-CoV in tissue culture. In SARS-infected patient reports on ribavirin, 26 studies were classified as inconclusive, and four showed possible harm. Seven studies of convalescent plasma or IVIG, three of IFN type I, and two of LPV/r were inconclusive. In 29 studies of steroid use, 25 were inconclusive and four were classified as causing possible harm. CONCLUSIONS: Despite an extensive literature reporting on SARS treatments, it was not possible to determine whether treatments benefited patients during the SARS outbreak. Some may have been harmful. Clinical trials should be designed to validate a standard protocol for dosage

SARS knowledge, perceptions, and behaviors: a comparison between Finns and the Dutch during the SARS outbreak in 2003

NARCIS (Netherlands)

Vartti, A.M.; Oenema, A.; Schreck, M.; Uutela, A.; Zwart, de O.; Brug, J.; Aro, A.R.

2009-01-01

BACKGROUND: The SARS outbreak served to test both local and international outbreak management and risk communication practices. PURPOSE: The study compares SARS knowledge, perceptions, behaviors, and information between Finns and the Dutch during the SARS outbreak in 2003. METHOD: The participants

MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

Directory of Open Access Journals (Sweden)

R. Dwivedi

2016-06-01

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

SARS: Key factors in crisis management.

Science.gov (United States)

Tseng, Hsin-Chao; Chen, Thai-Form; Chou, Shieu-Ming

2005-03-01

This study was conducted at a single hospital selected in Taipei during the SARS (Severe Acute Respiratory Syndrome) outbreak from March to July, 2003 in Taiwan. During this period of time, 104 SARS patients were admitted to the hospital. There were no negative reports related to the selected hospital despite its being located right in the center of an area struck by the epidemic. The purpose of this study was to identify the key factors enabling the hospital to survive SARS unscathed. Data were collected from in-depth interviews with the nursing directors and nursing managers of the SARS units, along with a review of relevant hospital documents. The five key elements identified as survival factors during this SARS crisis are as follows: 1. good control of timing for crisis management, 2. careful decision-making, 3. thorough implementation, 4. effective communication, and 5. trust between management and employees. The results of this study reconfirmed the selected hospital as a model for good crisis management during the SARS epidemic.

Linear feature extraction from radar imagery: SBIR (Small Business Innovative Research), phase 2, option 2

Science.gov (United States)

Milgram, David L.; Kahn, Philip; Conner, Gary D.; Lawton, Daryl T.

1988-12-01

The goal of this effort is to develop and demonstrate prototype processing capabilities for a knowledge-based system to automatically extract and analyze features from Synthetic Aperture Radar (SAR) imagery. This effort constitutes Phase 2 funding through the Defense Small Business Innovative Research (SBIR) Program. Previous work examined the feasibility of and technology issues involved in the development of an automated linear feature extraction system. This final report documents this examination and the technologies involved in automating this image understanding task. In particular, it reports on a major software delivery containing an image processing algorithmic base, a perceptual structures manipulation package, a preliminary hypothesis management framework and an enhanced user interface.

Imagery Integration Team

Science.gov (United States)

Calhoun, Tracy; Melendrez, Dave

2014-01-01

The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one

Spatial Analysis of Land Subsidence and Flood Pattern Based on DInSAR Method in Sentinel Sar Imagery and Weighting Method in Geo-Hazard Parameters Combination in North Jakarta Region

Science.gov (United States)

Prasetyo, Y.; Yuwono, B. D.; Ramadhanis, Z.

2018-02-01

The reclamation program carried out in most cities in North Jakarta is directly adjacent to the Jakarta Bay. Beside this program, the density of population and development center in North Jakarta office has increased the need for underground water excessively. As a result of these things, land subsidence in North Jakarta area is relatively high and so intense. The research methodology was developed based on the method of remote sensing and geographic information systems, expected to describe the spatial correlation between the land subsidence and flood phenomenon in North Jakarta. The DInSAR (Differential Interferometric Synthetic Aperture Radar) method with satellite image data Radar (SAR Sentinel 1A) for the years 2015 to 2016 acquisitions was used in this research. It is intended to obtain a pattern of land subsidence in North Jakarta and then combined with flood patterns. For the preparation of flood threat zoning pattern, this research has been modeling in spatial technique based on a weighted parameter of rainfall, elevation, flood zones and land use. In the final result, we have obtained a flood hazard zonation models then do the overlap against DInSAR processing results. As a result of the research, Geo-hazard modelling has a variety results as: 81% of flood threat zones consist of rural area, 12% consists of un-built areas and 7% consists of water areas. Furthermore, the correlation of land subsidence to flood risk zone is divided into three levels of suitability with 74% in high class, 22% in medium class and 4% in low class. For the result of spatial correlation area between land subsidence and flood risk zone are 77% detected in rural area, 17% detected in un-built area and 6% detected in a water area. Whereas the research product is the geo-hazard maps in North Jakarta as the basis of the spatial correlation analysis between the land subsidence and flooding phenomena.double point.

SAR Raw Data Generation for Complex Airport Scenes

Directory of Open Access Journals (Sweden)

Jia Li

2014-10-01

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

Deep learning for SAR image formation

Science.gov (United States)

Mason, Eric; Yonel, Bariscan; Yazici, Birsen

2017-04-01

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

Soundscapes to Landscapes (S2L): Monitoring Animal Biodiversity from Space Using Citizen Scientists

Science.gov (United States)

Clark, M. L.; Salas, L.; Goetz, S. J.

2017-12-01

Soundscapes to Landscapes (S2L) is a citizen science project with the broad goal of advancing scientific understanding of biodiversity and conservation using a combination of new and existing spaceborne sensors. The prototype phase of this project is focused on modeling bird diversity at the watershed scale in Sonoma County, California. The main objectives are to: 1) involve citizen scientists in the collection of in situ field information on bird diversity; 2) assess the accuracy and precision of bioacoustics for the detection and monitoring of individual species and richness; 3) test the predictive strength of spaceborne imaging spectroscopy, lidar, synthetic aperture radar (SAR) sensors for spatial modeling of species occupancy and overall species richness; and 4) use occupancy/richness maps to better understand factors related to conserving animal diversity. In the prototype field campaign, citizen scientists (birders, undergraduate students) deployed portable sound recorders for 3-4 days in various habitats in a local watershed. Over 50,200 minutes (866 hours) of "soundscape" recordings were collected over 3 months. Through a series of "bird blitzes", citizen scientists used the ARBIMON II web-based system to listen to spectrograms (time vs. frequency) of 1-minute recordings, tag bird calls for identifiable species, validate presence/absence of bird species, draw training-set boxes around well-formed calls, and help evaluate Random Forests machine-learning model performance. Bird-call models were applied to all soundscapes to identify presence/absence of 10 indicator species. Another phase of this project involves species distribution modeling in conjunction with C- and L-band SAR imagery, simulated Hyperspectral Infrared Imager (HyspIRI) and Global Ecosystem Dynamics Investigation (GEDI) large-footprint lidar data. Metrics derived from these data provide unique, wall-to-wall information on vegetation chemistry (HyspIRI) and three-dimensional structure (GEDI

The Nasa-Isro SAR Mission Science Data Products and Processing Workflows

Science.gov (United States)

Rosen, P. A.; Agram, P. S.; Lavalle, M.; Cohen, J.; Buckley, S.; Kumar, R.; Misra-Ray, A.; Ramanujam, V.; Agarwal, K. M.

2017-12-01

The NASA-ISRO SAR (NISAR) Mission is currently in the development phase and in the process of specifying its suite of data products and algorithmic workflows, responding to inputs from the NISAR Science and Applications Team. NISAR will provide raw data (Level 0), full-resolution complex imagery (Level 1), and interferometric and polarimetric image products (Level 2) for the entire data set, in both natural radar and geocoded coordinates. NASA and ISRO are coordinating the formats, meta-data layers, and algorithms for these products, for both the NASA-provided L-band radar and the ISRO-provided S-band radar. Higher level products will be also be generated for the purpose of calibration and validation, over large areas of Earth, including tectonic plate boundaries, ice sheets and sea-ice, and areas of ecosystem disturbance and change. This level of comprehensive product generation has been unprecedented for SAR missions in the past, and leads to storage processing challenges for the production system and the archive center. Further, recognizing the potential to support applications that require low latency product generation and delivery, the NISAR team is optimizing the entire end-to-end ground data system for such response, including exploring the advantages of cloud-based processing, algorithmic acceleration using GPUs, and on-demand processing schemes that minimize computational and transport costs, but allow rapid delivery to science and applications users. This paper will review the current products, workflows, and discuss the scientific and operational trade-space of mission capabilities.

Low-SAR metamaterial-inspired printed monopole antenna

Science.gov (United States)

Hossain, M. I.; Faruque, M. R. I.; Islam, M. T.; Ali, M. T.

2017-01-01

In this paper, a low-SAR metamaterial-embedded planar monopole antenna is introduced for a wireless communication system. A printed monopole antenna is designed for modern mobile, which operates in GSM, UMTS, LTE, WLAN, and Bluetooth frequency bands. A metamaterial structure is designed to use in the mobile handset with a multi-band printed monopole antenna. The finite integration technique of the CST microwave studio is used in this study. The measurement of antenna performances is taken in an anechoic chamber, and the SAR values are measured using COMOSAR system. The results indicate that metamaterial structure leads to reduce SAR without affecting antenna performance significantly. According to the measured results, the metamaterial attachment leads to reduce 87.7% peak SAR, 68.2% 1-g SAR, and 46.78% 10-g SAR compared to antenna without metamaterial.

Optimal spatial filtering and transfer function for SAR ocean wave spectra

Science.gov (United States)

Beal, R. C.; Tilley, D. G.

1981-01-01

The impulse response of the SAR system is not a delta function and the spectra represent the product of the underlying image spectrum with the transform of the impulse response which must be removed. A digitally computed spectrum of SEASAT imagery of the Atlantic Ocean east of Cape Hatteras was smoothed with a 5 x 5 convolution filter and the trend was sampled in a direction normal to the predominant wave direction. This yielded a transform of a noise-like process. The smoothed value of this trend is the transform of the impulse response. This trend is fit with either a second- or fourth-order polynomial which is then used to correct the entire spectrum. A 16 x 16 smoothing of the spectrum shows the presence of two distinct swells. Correction of the effects of speckle is effected by the subtraction of a bias from the spectrum.

A portfolio of products from the rapid terrain visualization interferometric SAR

Science.gov (United States)

Bickel, Douglas L.; Doerry, Armin W.

2007-04-01

The Rapid Terrain Visualization interferometric synthetic aperture radar was designed and built at Sandia National Laboratories as part of an Advanced Concept Technology Demonstration (ACTD) to "demonstrate the technologies and infrastructure to meet the Army requirement for rapid generation of digital topographic data to support emerging crisis or contingencies." This sensor was built by Sandia National Laboratories for the Joint Programs Sustainment and Development (JPSD) Project Office to provide highly accurate digital elevation models (DEMs) for military and civilian customers, both inside and outside of the United States. The sensor achieved better than HRTe Level IV position accuracy in near real-time. The system was flown on a deHavilland DHC-7 Army aircraft. This paper presents a collection of images and data products from the Rapid Terrain Visualization interferometric synthetic aperture radar. The imagery includes orthorectified images and DEMs from the RTV interferometric SAR radar.

Observation of Drifting Icebergs and Sea Ice from Space by TerraSAR-X and TanDEM-X

Science.gov (United States)

Won, Joong-Sun

2017-04-01

Detection and monitoring drifting icebergs and sea ice is of interest across wide range of Arctic and Antarctic coastal studies such as security of navigation, climatic impact, geological impact, etc. It is not easy to discriminate drifting ices from stationary ones, and to measure their drifting speeds. There is a potential to use space-borne SAR for this purpose, but it is difficult to precisely measure because the drift velocity is usually very slow. In this study, we investigate two approaches for discriminating drifting ices on the sea from surrounding static ones and for measuring their range velocity. The first method is to utilize the quad-pol TerraSAR-X which adopts dual receive antenna (DRA), and the second one is to examine the potential use of TanDEM-X bistatic along-track interferometry (ATI). To utilize DRA mode quad-pol SAR as ATI, it is necessary to remove the phase difference of scattering centers between transmitted H- and V-pol signals. By assume that the individual scattering center of returned signal does not change for a few inter-pulse periods, it is possible to measure the Doppler frequency induced by motion through measuring slow-time (or azimuth time) Doppler phase derivative of co-pol or cross-pol pairs. Results applied to TerraSAR-X quad-pol data over the Cape Columbia in the Arctic Ocean are to be presented and discussed. It was successful to detect and measure drift sea ice that was flowing away from the antenna with a velocity of about 0.37 m/s (or 1.4 km/h) to 0.67 m/s (or 2.4 km/h) while neighboring ones were static. A more sophisticated approach would be a bistatic ATI which exploits a long along-track baseline for observation of slowly moving ground objects. TanDEM-X bistatic ATI pairs are examined, which were acquired at an Antarctic coast. The ATI interferograms show an innovative capability of TanDEM-X/TerraSAR-X constellation. An along-track baseline of a few hundred meters is superior to a few meter baseline of DRA mode ATI

Potential of Different Optical and SAR Data in Forest and Land Cover Classification to Support REDD+ MRV

Directory of Open Access Journals (Sweden)

Laura Sirro

2018-06-01

Full Text Available The applicability of optical and synthetic aperture radar (SAR data for land cover classification to support REDD+ (Reducing Emissions from Deforestation and Forest Degradation MRV (measuring, reporting and verification services was tested on a tropical to sub-tropical test site. The 100 km by 100 km test site was situated in the State of Chiapas in Mexico. Land cover classifications were computed using RapidEye and Landsat TM optical satellite images and ALOS PALSAR L-band and Envisat ASAR C-band images. Identical sample plot data from Kompsat-2 imagery of one-metre spatial resolution were used for the accuracy assessment. The overall accuracy for forest and non-forest classification varied between 95% for the RapidEye classification and 74% for the Envisat ASAR classification. For more detailed land cover classification, the accuracies varied between 89% and 70%, respectively. A combination of Landsat TM and ALOS PALSAR data sets provided only 1% improvement in the overall accuracy. The biases were small in most classifications, varying from practically zero for the Landsat TM based classification to a 7% overestimation of forest area in the Envisat ASAR classification. Considering the pros and cons of the data types, we recommend optical data of 10 m spatial resolution as the primary data source for REDD MRV purposes. The results with L-band SAR data were nearly as accurate as the optical data but considering the present maturity of the imaging systems and image analysis methods, the L-band SAR is recommended as a secondary data source. The C-band SAR clearly has poorer potential than the L-band but it is applicable in stratification for a statistical sampling when other image types are unavailable.

Mapping Tropical Forest Mosaics with C- and L-band SAR: First Results from Osa Peninsula, Costa Rica

Science.gov (United States)

Pinto, N.; Hensley, S.; Aguilar-Amuchastegui, N.; Broadbent, E. N.; Ahmed, R.

2016-12-01

In tropical countries, economic incentives and improved infrastructure are creating forest mosaics where small-scale farming and industrial plantations are embedded within and potentially replacing native ecosystems. Practices such as agroforestry, slash-and-burn cultivation, and oil palm monocultures bring widely different impacts on carbon stocks. Characterizing these production systems is not only critical to ascribe deforestation to particular drivers, but also essential to understand the impact of macroeconomic scenarios, national policies, and land tenure schemes on carbon fluxes. The last decade has experienced a dramatic improvement in the extent and consistency of tree cover and gross deforestation products from optical imagery. At the same time, recent work shows that Synthetic Aperture Radar (SAR) can complement optical data and reveal structural types that cannot be easily resolved with reflectance measurements alone. While these results demonstrate the validity of sensor fusion methodologies, they typically rely on local classifications or even manual delineation and as such they cannot support large-scale investigations. Furthermore, there have been few attempts to exploit PolInSAR or multiple wavelengths that can provide critical information to resolve natural and anthropogenic land cover types. We report results from our research at Costa Rica's Osa Peninsula. This site is ideal for algorithm development as it includes a highly diverse tropical forest within Corcovado National Park, as well as agroforestry zones, mangroves, and palm plantations. We first integrate SAR backscatter and coherence data from NASA's L-band UAVSAR, JAXA's ALOS/PALSAR, and ESA's Sentinel to produce a map of structural types. Second, we assess whether coherence measurements and PolInSAR retrievals can be used to resolve forest stand differences at 30m resolution and disitinguish between primary and secondary forest sites.

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

Directory of Open Access Journals (Sweden)

A. Taravat

2013-09-01

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

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

Science.gov (United States)

Taravat, A.; Del Frate, F.

2013-09-01

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

Application of SAR remote sensing and crop modeling for operational rice crop monitoring in South and South East Asian Countries

Science.gov (United States)

Setiyono, T. D.; Holecz, F.; Khan, N. I.; Barbieri, M.; Maunahan, A. A.; Gatti, L.; Quicho, E. D.; Pazhanivelan, S.; Campos-Taberner, M.; Collivignarelli, F.; Haro, J. G.; Intrman, A.; Phuong, D.; Boschetti, M.; Prasadini, P.; Busetto, L.; Minh, V. Q.; Tuan, V. Q.

2017-12-01

This study uses multi-temporal SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations in South and South Asian countries and assimilate the information into ORYZA Crop Growth Simulation Model (CGSM) to monitor rice yield. The study demonstrates examples of operational application of this rice monitoring system in: (1) detecting drought impact on rice planting in Central Thailand and Tamil Nadu, India, (2) mapping heat stress impact on rice yield in Andhra Pradesh, India, and (3) generating historical rice yield data for districts in Red River Delta, Vietnam.

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

Science.gov (United States)

Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

1998-01-01

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

The SARS-unique domain (SUD of SARS coronavirus contains two macrodomains that bind G-quadruplexes.

Directory of Open Access Journals (Sweden)

Jinzhi Tan

2009-05-01

Full Text Available Since the outbreak of severe acute respiratory syndrome (SARS in 2003, the three-dimensional structures of several of the replicase/transcriptase components of SARS coronavirus (SARS-CoV, the non-structural proteins (Nsps, have been determined. However, within the large Nsp3 (1922 amino-acid residues, the structure and function of the so-called SARS-unique domain (SUD have remained elusive. SUD occurs only in SARS-CoV and the highly related viruses found in certain bats, but is absent from all other coronaviruses. Therefore, it has been speculated that it may be involved in the extreme pathogenicity of SARS-CoV, compared to other coronaviruses, most of which cause only mild infections in humans. In order to help elucidate the function of the SUD, we have determined crystal structures of fragment 389-652 ("SUD(core" of Nsp3, which comprises 264 of the 338 residues of the domain. Both the monoclinic and triclinic crystal forms (2.2 and 2.8 A resolution, respectively revealed that SUD(core forms a homodimer. Each monomer consists of two subdomains, SUD-N and SUD-M, with a macrodomain fold similar to the SARS-CoV X-domain. However, in contrast to the latter, SUD fails to bind ADP-ribose, as determined by zone-interference gel electrophoresis. Instead, the entire SUD(core as well as its individual subdomains interact with oligonucleotides known to form G-quadruplexes. This includes oligodeoxy- as well as oligoribonucleotides. Mutations of selected lysine residues on the surface of the SUD-N subdomain lead to reduction of G-quadruplex binding, whereas mutations in the SUD-M subdomain abolish it. As there is no evidence for Nsp3 entering the nucleus of the host cell, the SARS-CoV genomic RNA or host-cell mRNA containing long G-stretches may be targets of SUD. The SARS-CoV genome is devoid of G-stretches longer than 5-6 nucleotides, but more extended G-stretches are found in the 3'-nontranslated regions of mRNAs coding for certain host-cell proteins

SAR Image Classification Based on Its Texture Features

Institute of Scientific and Technical Information of China (English)

LI Pingxiang; FANG Shenghui

2003-01-01

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

The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

Science.gov (United States)

Rincon, Rafael F.; Fatoyinbo, Temilola; Ranson, K. Jon; Osmanoglu, Batuhan; Sun, Guoqing; Deshpande, Manohar D.; Perrine, Martin L.; Du Toit, Cornelis F.; Bonds, Quenton; Beck, Jaclyn;

Tracking Human-Induced Landscape Disturbance at the Nasca Lines UNESCO World Heritage Site in Peru with COSMO-SkyMed InSAR

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Francesca Cigna

2018-04-01

Full Text Available The “Lines and Geoglyphs of Nasca and Palpa” in Peru are among the most well-known UNESCO World Heritage Sites globally, and an exemplar of site where heritage assets cannot be separated from their natural and anthropogenic environment. The site is exposed to interactions with natural processes, as well as human presence. In this work, 3-m resolution synthetic aperture radar (SAR StripMap HIMAGE HH-polarised scenes acquired by the X-band COSMO-SkyMed constellation are exploited to track two events of human-induced landscape disturbance that occurred in December 2014 and January 2018. Pre-, cross-, and post-event interferometric SAR (InSAR pairs characterised by small temporal and normal baselines allow the detection of temporal decorrelation associated with the two events, the extent and time reference of which match with online photographic and video evidence, published literature, web news, and press releases by the Ministry of Culture in Peru. Further elements enhancing the understanding of the 2018 event come from 10-m resolution Sentinel-2B satellite data that reveal the occurrence of apparent changes of surface reflectance due to uncovering of the light grey-yellow clay underneath the darker pebble constituting the fragile surface of the Pampa de Jumana. This scientific study confirms that SAR imagery archives, such as those being built by COSMO-SkyMed for Nasca, prove valuable for the retrospective analysis and digital recording of human-induced landscape disturbance events from space. These archives therefore act as essential sources of geospatial information on the conservation history of heritage sites and assets.

FlexSAR, a high quality, flexible, cost effective, prototype SAR system

Science.gov (United States)

Jensen, Mark; Knight, Chad; Haslem, Brent

2016-05-01

The FlexSAR radar system was designed to be a high quality, low-cost, flexible research prototype instrument. Radar researchers and practitioners often desire the ability to prototype new or advanced configurations, yet the ability to enhance or upgrade existing radar systems can be cost prohibitive. FlexSAR answers the need for a flexible radar system that can be extended easily, with minimal cost and time expenditures. The design approach focuses on reducing the resources required for developing and validating new advanced radar modalities. Such an approach fosters innovation and provides risk reduction since actual radar data can be collected in the appropriate mode, processed, and analyzed early in the development process. This allows for an accurate, detailed understanding of the corresponding trade space. This paper is a follow-on to last years paper and discusses the advancements that have been made to the FlexSAR system. The overall system architecture is discussed and presented along with several examples illustrating the system utility.

Convolutional Neural Networks for SAR Image Segmentation

DEFF Research Database (Denmark)

Malmgren-Hansen, David; Nobel-Jørgensen, Morten

2015-01-01

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

PHARUS : PHased ARray Universal SAR

NARCIS (Netherlands)

Paquay, M.H.A.; Vermeulen, B.C.B.; Koomen, P.J.; Hoogeboom, P.; Snoeij, P.; Pouwels, H.

1996-01-01

In the Netherlands, a polarimetric C-band aircraft SAR (Synthetic Aperture Radar) has been developed. The project is called PHARUS, an acronm for PHased ARray Universal SAR. This instrument serves remote sensing applications. The antenna system contains 48 active modules (expandable to 96). A module

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

Science.gov (United States)

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.

SARS-related Perceptions in Hong Kong

OpenAIRE

Lau, Joseph T.F.; Yang, Xilin; Pang, Ellie; Tsui, H.Y.; Wong, Eric; Wing, Yun Kwok

2005-01-01

To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means o...

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

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Pingping Huang

2015-03-01

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

Genome organization of the SARS-CoV

DEFF Research Database (Denmark)

Xu, Jing; Hu, Jianfei; Wang, Jing

2003-01-01

Annotation of the genome sequence of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) is indispensable to understand its evolution and pathogenesis. We have performed a full annotation of the SARS-CoV genome sequences by using annotation programs publicly available or devel......Annotation of the genome sequence of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) is indispensable to understand its evolution and pathogenesis. We have performed a full annotation of the SARS-CoV genome sequences by using annotation programs publicly available...

How infectious is SARS virus

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. How infectious is SARS virus. Influenza: 1 patient infects ten people. SARS: 1 patient infects 2-4 people. Incubation period 10 days. Are there `silent´ cases ? Is quarantine enough ? How will it behave if and when it returns ?

Imaging in severe acute respiratory syndrome (SARS)

International Nuclear Information System (INIS)

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

2003-01-01

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

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

Science.gov (United States)

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

2016-12-01

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.

Satellite on-board real-time SAR processor prototype

Science.gov (United States)

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

2017-11-01

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

Linear feature extraction from radar imagery: SBIR (Small Business Innovative Research) phase 2, option 1

Science.gov (United States)

Conner, Gary D.; Milgram, David L.; Lawton, Daryl T.; McConnell, Christopher C.

1988-04-01

The goal of this effort is to develop and demonstrate prototype processing capabilities for a knowledge-based system to automatically extract and analyze linear features from synthetic aperture radar (SAR) imagery. This effort constitutes Phase 2 funding through the Defense Small Business Innovative Research (SBIR) Program. Previous work examined the feasibility of the technology issues involved in the development of an automatedlinear feature extraction system. This Option 1 Final Report documents this examination and the technologies involved in automating this image understanding task. In particular, it reports on a major software delivery containing an image processing algorithmic base, a perceptual structures manipulation package, a preliminary hypothesis management framework and an enhanced user interface.

Monitoring Building Deformation with InSAR: Experiments and Validation

Science.gov (United States)

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

2016-01-01

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

Monitoring Building Deformation with InSAR: Experiments and Validation

Directory of Open Access Journals (Sweden)

Kui Yang

2016-12-01

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

Climate Change Indicator for Hazard Identification of Indian North West Coast Marine Environment Using Synthetic Aperture Radar (sar)

Science.gov (United States)

Gambheer, Phani Raj

2012-07-01

Stormwater runoff, Petroleum Hydrocarbon plumes are found abundantly near coastal cities, coastal population settlements especially in developing nations as more than half the world's human population. Ever increasing coastal populations and development in coastal areas have led to increased loading of toxic substances, nutrients and pathogens. These hazards cause deleterious effects on the population in many ways directly or indirectly which lead to algal blooms, hypoxia, beach closures, and damage to coastal fisheries. Hence these pollution hazards are important and the coastal administrations and people need to be aware of such a danger lurking very close to them. These hazards due to their small size, dynamic and episodic in nature are difficult to be visualized or to sample using in-situ traditional scientific methods. Natural obstructions like cloud cover and complex coastal circulations can hinder to detect and monitor such occurrences in the selected areas chosen for observations. This study takes recourse to Synthetic Aperture Radar (SAR) imagery because the pollution hazards are easily detectable as surfactants are deposited on the sea surface, along with nutrients and pathogens, smoothing capillary and small gravity waves to produce areas of reduced backscatter compared with surrounding ocean. These black spots can be termed as `Ecologic Indicator' and formed probably due to stronger thermal stratification, a deepening event of thermocline. SAR imagery that delivers useful data better than others regardless of darkness or cloud cover, should be made as an important observational tool for assessment and monitoring marine pollution hazards in the areas close to coastal regions. Till now the effects of climate change, sea level rise and global warming seems to have not affected the coastal populace of India in intrusions of sea water but it takes significance to the human health as the tides dominate these latitudes with bringing these polluted waters. KEY

Imagery Data Base Facility

Data.gov (United States)

Federal Laboratory Consortium — The Imagery Data Base Facility supports AFRL and other government organizations by providing imagery interpretation and analysis to users for data selection, imagery...

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

Directory of Open Access Journals (Sweden)

Jin Wook So

1998-06-01

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

Molecular mechanisms of severe acute respiratory syndrome (SARS

Directory of Open Access Journals (Sweden)

Zabel Peter

2005-01-01

Full Text Available Abstract Severe acute respiratory syndrome (SARS is a new infectious disease caused by a novel coronavirus that leads to deleterious pulmonary pathological features. Due to its high morbidity and mortality and widespread occurrence, SARS has evolved as an important respiratory disease which may be encountered everywhere in the world. The virus was identified as the causative agent of SARS due to the efforts of a WHO-led laboratory network. The potential mutability of the SARS-CoV genome may lead to new SARS outbreaks and several regions of the viral genomes open reading frames have been identified which may contribute to the severe virulence of the virus. With regard to the pathogenesis of SARS, several mechanisms involving both direct effects on target cells and indirect effects via the immune system may exist. Vaccination would offer the most attractive approach to prevent new epidemics of SARS, but the development of vaccines is difficult due to missing data on the role of immune system-virus interactions and the potential mutability of the virus. Even in a situation of no new infections, SARS remains a major health hazard, as new epidemics may arise. Therefore, further experimental and clinical research is required to control the disease.

An Efficient Parallel Multi-Scale Segmentation Method for Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Haiyan Gu

2018-04-01

Full Text Available Remote sensing (RS image segmentation is an essential step in geographic object-based image analysis (GEOBIA to ultimately derive “meaningful objects”. While many segmentation methods exist, most of them are not efficient for large data sets. Thus, the goal of this research is to develop an efficient parallel multi-scale segmentation method for RS imagery by combining graph theory and the fractal net evolution approach (FNEA. Specifically, a minimum spanning tree (MST algorithm in graph theory is proposed to be combined with a minimum heterogeneity rule (MHR algorithm that is used in FNEA. The MST algorithm is used for the initial segmentation while the MHR algorithm is used for object merging. An efficient implementation of the segmentation strategy is presented using data partition and the “reverse searching-forward processing” chain based on message passing interface (MPI parallel technology. Segmentation results of the proposed method using images from multiple sensors (airborne, SPECIM AISA EAGLE II, WorldView-2, RADARSAT-2 and different selected landscapes (residential/industrial, residential/agriculture covering four test sites indicated its efficiency in accuracy and speed. We conclude that the proposed method is applicable and efficient for the segmentation of a variety of RS imagery (airborne optical, satellite optical, SAR, high-spectral, while the accuracy is comparable with that of the FNEA method.

SYNERGY OF OPTICAL AND SAR DATA FOR MAPPING AND MONITORING MANGROVES

Directory of Open Access Journals (Sweden)

A. K. Monzon

2016-06-01

Full Text Available 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.

ACCURACY COMPARISON OF VHR SYSTEMATIC-ORTHO SATELLITE IMAGERIES AGAINST VHR ORTHORECTIFIED IMAGERIES USING GCP

Directory of Open Access Journals (Sweden)

E. Widyaningrum

2016-06-01

Full Text Available The Very High Resolution (VHR satellite imageries such us Pleiades, WorldView-2, GeoEye-1 used for precise mapping purpose must be corrected from any distortion to achieve the expected accuracy. Orthorectification is performed to eliminate geometric errors of the VHR satellite imageries. Orthorectification requires main input data such as Digital Elevation Model (DEM and Ground Control Point (GCP. The VHR systematic-ortho imageries were generated using SRTM 30m DEM without using any GCP data. The accuracy value differences of VHR systematic-ortho imageries and VHR orthorectified imageries using GCP currently is not exactly defined. This study aimed to identified the accuracy comparison of VHR systematic-ortho imageries against orthorectified imageries using GCP. Orthorectified imageries using GCP created by using Rigorous model. Accuracy evaluation is calculated by using several independent check points.

Estimating Coastal Lagoon Tidal Flooding and Repletion with Multidate ASTER Thermal Imagery

Directory of Open Access Journals (Sweden)

Thomas R. Allen

2012-10-01

Full Text Available Coastal lagoons mix inflowing freshwater and tidal marine waters in complex spatial patterns. This project sought to detect and measure temperature and spatial variability of flood tides for a constricted coastal lagoon using multitemporal remote sensing. Advanced Spaceborne Thermal Emission Radiometer (ASTER thermal infrared data provided estimates of surface temperature for delineation of repletion zones in portions of Chincoteague Bay, Virginia. ASTER high spatial resolution sea-surface temperature imagery in conjunction with in situ observations and tidal predictions helped determine the optimal seasonal data for analyses. The selected time series ASTER satellite data sets were analyzed at different tidal phases and seasons in 2004–2006. Skin surface temperatures of ocean and estuarine waters were differentiated by flood tidal penetration and ebb flows. Spatially variable tidal flood penetration was evaluated using discrete seed-pixel area analysis and time series Principal Components Analysis. Results from these techniques provide spatial extent and variability dynamics of tidal repletion, flushing, and mixing, important factors in eutrophication assessment, water quality and resource monitoring, and application of hydrodynamic modeling for coastal estuary science and management.

Constraints on the geomorphological evolution of the nested summit craters of Láscar volcano from high spatio-temporal resolution TerraSAR-X interferometry

Science.gov (United States)

Richter, Nicole; Salzer, Jacqueline Tema; de Zeeuw-van Dalfsen, Elske; Perissin, Daniele; Walter, Thomas R.

2018-03-01

Small-scale geomorphological changes that are associated with the formation, development, and activity of volcanic craters and eruptive vents are often challenging to characterize, as they may occur slowly over time, can be spatially localized, and difficult, or dangerous, to access. Using high-spatial and high-temporal resolution synthetic aperture radar (SAR) imagery collected by the German TerraSAR-X (TSX) satellite in SpotLight mode in combination with precise topographic data as derived from Pléiades-1A satellite data, we investigate the surface deformation within the nested summit crater system of Láscar volcano, Chile, the most active volcano of the central Andes. Our aim is to better understand the structural evolution of the three craters that comprise this system, to assess their physical state and dynamic behavior, and to link this to eruptive activity and associated hazards. Using multi-temporal SAR interferometry (MT-InSAR) from ascending and descending orbital geometries, we retrieve the vertical and east-west components of the displacement field. This time series indicates constant rates of subsidence and asymmetric horizontal displacements of all summit craters between June 2012 and July 2014, as well as between January 2015 and March 2017. The vertical and horizontal movements that we observe in the central crater are particularly complex and cannot be explained by any single crater formation mechanism; rather, we suggest that short-term activities superimposed on a combination of ongoing crater evolution processes, including gravitational slumping, cooling and compaction of eruption products, as well as possible piston-like subsidence, are responsible for the small-scale geomorphological changes apparent in our data. Our results demonstrate how high-temporal resolution synthetic aperture radar interferometry (InSAR) time series can add constraints on the geomorphological evolution and structural dynamics of active crater and vent systems at

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Chen Liangan

2005-01-01

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

Towards Snowpack Characterization using C-band Synthetic Aperture Radar (SAR)

Science.gov (United States)

Park, J.; Forman, B. A.

2017-12-01

Sentinel 1A and 1B, operated by the European Space Agency (ESA), carries a C-band synthetic aperture radar (SAR) sensor that can be used to monitor terrestrial snow properties. This study explores the relationship between terrestrial snow-covered area, snow depth, and snow water equivalent with Sentinel 1 backscatter observations in order to better characterize snow mass. Ground-based observations collected by the National Oceanic and Atmospheric Administration - Cooperative Remote Sensing Science and Technology Center (NOAA-CREST) in Caribou, Maine in the United States are also used in the comparative analysis. Sentinel 1 Ground Range Detected (GRD) imagery with Interferometric Wide swath (IW) were preprocessed through a series of steps accounting for thermal noise, sensor orbit, radiometric calibration, speckle filtering, and terrain correction using ESA's Sentinel Application Platform (SNAP) software package, which is an open-source module written in Python. Comparisons of dual-polarized backscatter coefficients (i.e., σVV and σVH) with in-situ measurements of snow depth and SWE suggest that cross-polarized backscatter observations exhibit a modest correlation between both snow depth and SWE. In the case of the snow-covered area, a multi-temporal change detection method was used. Results using Sentinel 1 yield similar spatial patterns as when using hyperspectral observations collected by the MODerate Resolution Imaging Spectroradiometer (MODIS). These preliminary results suggest the potential application of Sentinel 1A/1B backscatter coefficients towards improved discrimination of snow cover, snow depth, and SWE. One goal of this research is to eventually merge C-band SAR backscatter observations with other snow information (e.g., passive microwave brightness temperatures) as part of a multi-sensor snow assimilation framework.

Nano(Q)SAR: Challenges, pitfalls and perspectives.

Science.gov (United States)

Tantra, Ratna; Oksel, Ceyda; Puzyn, Tomasz; Wang, Jian; Robinson, Kenneth N; Wang, Xue Z; Ma, Cai Y; Wilkins, Terry

2015-01-01

Regulation for nanomaterials is urgently needed, and the drive to adopt an intelligent testing strategy is evident. Such a strategy will not only provide economic benefits but will also reduce moral and ethical concerns arising from animal testing. For regulatory purposes, such an approach is promoted by REACH, particularly the use of quantitative structure-activity relationships [(Q)SAR] as a tool for the categorisation of compounds according to their physicochemical and toxicological properties. In addition to compounds, (Q)SAR has also been applied to nanomaterials in the form of nano(Q)SAR. Although (Q)SAR in chemicals is well established, nano(Q)SAR is still in early stages of development and its successful uptake is far from reality. This article aims to identify some of the pitfalls and challenges associated with nano-(Q)SARs in relation to the categorisation of nanomaterials. Our findings show clear gaps in the research framework that must be addressed if we are to have reliable predictions from such models. Three major barriers were identified: the need to improve quality of experimental data in which the models are developed from, the need to have practical guidelines for the development of the nano(Q)SAR models and the need to standardise and harmonise activities for the purpose of regulation. Of these three, the first, i.e. the need to improve data quality requires immediate attention, as it underpins activities associated with the latter two. It should be noted that the usefulness of data in the context of nano-(Q)SAR modelling is not only about the quantity of data but also about the quality, consistency and accessibility of those data.

Computer Sciences and Data Systems, volume 2

Science.gov (United States)

1987-01-01

Topics addressed include: data storage; information network architecture; VHSIC technology; fiber optics; laser applications; distributed processing; spaceborne optical disk controller; massively parallel processors; and advanced digital SAR processors.

Playback system designed for X-Band SAR

International Nuclear Information System (INIS)

Yuquan, Liu; Changyong, Dou

2014-01-01

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

Playback system designed for X-Band SAR

Science.gov (United States)

Yuquan, Liu; Changyong, Dou

2014-03-01

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

Modeling Sub-500MHz Space-Borne Radar Signal Propagation in Complex Media

Data.gov (United States)

National Aeronautics and Space Administration — Space-borne radar platforms are becoming increasingly prevalent in current and planned missions by NASA and partner organizations (e.g. the European Space Agency...

Land cover classification accuracy from electro-optical, X, C, and L-band Synthetic Aperture Radar data fusion

Science.gov (United States)

Hammann, Mark Gregory

The fusion of electro-optical (EO) multi-spectral satellite imagery with Synthetic Aperture Radar (SAR) data was explored with the working hypothesis that the addition of multi-band SAR will increase the land-cover (LC) classification accuracy compared to EO alone. Three satellite sources for SAR imagery were used: X-band from TerraSAR-X, C-band from RADARSAT-2, and L-band from PALSAR. Images from the RapidEye satellites were the source of the EO imagery. Imagery from the GeoEye-1 and WorldView-2 satellites aided the selection of ground truth. Three study areas were chosen: Wad Medani, Sudan; Campinas, Brazil; and Fresno- Kings Counties, USA. EO imagery were radiometrically calibrated, atmospherically compensated, orthorectifed, co-registered, and clipped to a common area of interest (AOI). SAR imagery were radiometrically calibrated, and geometrically corrected for terrain and incidence angle by converting to ground range and Sigma Naught (?0). The original SAR HH data were included in the fused image stack after despeckling with a 3x3 Enhanced Lee filter. The variance and Gray-Level-Co-occurrence Matrix (GLCM) texture measures of contrast, entropy, and correlation were derived from the non-despeckled SAR HH bands. Data fusion was done with layer stacking and all data were resampled to a common spatial resolution. The Support Vector Machine (SVM) decision rule was used for the supervised classifications. Similar LC classes were identified and tested for each study area. For Wad Medani, nine classes were tested: low and medium intensity urban, sparse forest, water, barren ground, and four agriculture classes (fallow, bare agricultural ground, green crops, and orchards). For Campinas, Brazil, five generic classes were tested: urban, agriculture, forest, water, and barren ground. For the Fresno-Kings Counties location 11 classes were studied: three generic classes (urban, water, barren land), and eight specific crops. In all cases the addition of SAR to EO resulted

The Influence of DEM Quality on Mapping Accuracy of Coniferous- and Deciduous-Dominated Forest Using TerraSAR‑X Images

Directory of Open Access Journals (Sweden)

Gerald Kändler

2012-03-01

Full Text Available Climate change is a factor that largely contributes to the increase of forest areas affected by natural damages. Therefore, the development of methodologies for forest monitoring and rapid assessment of affected areas is required. Space-borne synthetic aperture radar (SAR imagery with high resolution is now available for large-scale forest mapping and forest monitoring applications. However, a correct interpretation of SAR images requires an adequate preprocessing of the data consisting of orthorectification and radiometric calibration. The resolution and quality of the digital elevation model (DEM used as reference is crucial for this purpose. Therefore, the primary aim of this study was to analyze the influence of the DEM quality used in the preprocessing of the SAR data on the mapping accuracy of forest types. In order to examine TerraSAR-X images to map forest dominated by deciduous and coniferous trees, High Resolution SpotLight images were acquired for two study sites in southern Germany. The SAR images were preprocessed with a Shuttle Radar Topography Mission (SRTM DEM (resolution approximately 90 m, an airborne laser scanning (ALS digital terrain model (DTM (5 m resolution, and an ALS digital surface model (DSM (5 m resolution. The orthorectification of the SAR images using high resolution ALS DEMs was found to be important for the reduction of errors in pixel location and to increase the classification accuracy of forest types. SAR images preprocessed with ALS DTMs resulted in the highest classification accuracies, with kappa coefficients of 0.49 and 0.41, respectively. SAR images preprocessed with ALS DTMs resulted in greater accuracy than those preprocessed with ALS DSMs in most cases. The classification accuracy of forest types using SAR images preprocessed with the SRTM DEM was fair, with kappa coefficients of 0.23 and 0.32, respectively.Analysis of the radar backscatter indicated that sample plots dominated by coniferous trees

Normalization of satellite imagery

Science.gov (United States)

Kim, Hongsuk H.; Elman, Gregory C.

1990-01-01

Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.

Reverse genetics of SARS-related coronavirus using vaccinia virus-based recombination.

Directory of Open Access Journals (Sweden)

Sjoerd H E van den Worm

Full Text Available Severe acute respiratory syndrome (SARS is a zoonotic disease caused by SARS-related coronavirus (SARS-CoV that emerged in 2002 to become a global health concern. Although the original outbreak was controlled by classical public health measures, there is a real risk that another SARS-CoV could re-emerge from its natural reservoir, either in its original form or as a more virulent or pathogenic strain; in which case, the virus would be difficult to control in the absence of any effective antiviral drugs or vaccines. Using the well-studied SARS-CoV isolate HKU-39849, we developed a vaccinia virus-based SARS-CoV reverse genetic system that is both robust and biosafe. The SARS-CoV genome was cloned in separate vaccinia virus vectors, (vSARS-CoV-5prime and vSARS-CoV-3prime as two cDNAs that were subsequently ligated to create a genome-length SARS-CoV cDNA template for in vitro transcription of SARS-CoV infectious RNA transcripts. Transfection of the RNA transcripts into permissive cells led to the recovery of infectious virus (recSARS-CoV. Characterization of the plaques produced by recSARS-CoV showed that they were similar in size to the parental SARS-CoV isolate HKU-39849 but smaller than the SARS-CoV isolate Frankfurt-1. Comparative analysis of replication kinetics showed that the kinetics of recSARS-CoV replication are similar to those of SARS-CoV Frankfurt-1, although the titers of virus released into the culture supernatant are approximately 10-fold less. The reverse genetic system was finally used to generate a recSARS-CoV reporter virus expressing Renilla luciferase in order to facilitate the analysis of SARS-CoV gene expression in human dendritic cells (hDCs. In parallel, a Renilla luciferase gene was also inserted into the genome of human coronavirus 229E (HCoV-229E. Using this approach, we demonstrate that, in contrast to HCoV-229E, SARS-CoV is not able to mediate efficient heterologous gene expression in hDCs.

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

Science.gov (United States)

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.

Benchmark Imagery FY11 Technical Report

Energy Technology Data Exchange (ETDEWEB)

Roberts, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pope, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2011-06-14

This report details the work performed in FY11 under project LL11-GS-PD06, “Benchmark Imagery for Assessing Geospatial Semantic Extraction Algorithms.” The original LCP for the Benchmark Imagery project called for creating a set of benchmark imagery for verifying and validating algorithms that extract semantic content from imagery. More specifically, the first year was slated to deliver real imagery that had been annotated, the second year to deliver real imagery that had composited features, and the final year was to deliver synthetic imagery modeled after the real imagery.

DATA PROCESSING CONCEPTS FOR THE INTEGRATION OF SAR INTO OPERATIONAL VOLCANO MONITORING SYSTEMS

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F. J. Meyer

2013-05-01

Full Text Available Remote Sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and despite its high performance in monitoring change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to (1 the high data costs associated with radar data, (2 the slow data processing and delivery procedures, and (3 the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of the above mentioned limitations and allow for a meaningful integration of radar remote sensing data into operational volcano monitoring systems. The data integration concept presented here combines advanced data processing techniques with fast data access procedures in order to provide high quality radar-based volcano hazard information at improved temporal sampling rates. First performance analyses show that the integration of SAR can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

Pyrimidine and nucleoside gamma-esters of L-Glu-Sar

DEFF Research Database (Denmark)

Eriksson, André H; Elm, Peter L; Begtrup, Mikael

2005-01-01

-tetrahydrofuran-3-yl ester)-Sar (I), l-Glu(thymine-1-yl-methyl ester)-Sar (II) and l-Glu(acyclothymidine)-Sar (III) were synthesised and in vitro stability was studied in various aqueous and biological media. Affinity to and translocation via hPEPT1 was investigated in mature Caco-2 cell monolayers, grown......The aim of the present study was to improve the synthetic pathway of bioreversible dipeptide derivatives as well as evaluate the potential of using l-Glu-Sar as a pro-moiety for delivering three newly synthesised nucleoside and pyrimidine l-Glu-Sar derivatives. l-Glu(trans-2-thymine-1-yl...

Use of SAR data for proliferation monitoring

International Nuclear Information System (INIS)

Lafitte, M.; Robin, J.P.

2013-01-01

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

SAR and LIDAR fusion: experiments and applications

Science.gov (United States)

Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

2013-05-01

In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

Cloaked similarity between HIV-1 and SARS-CoV suggests an anti-SARS strategy

Directory of Open Access Journals (Sweden)

Kliger Yossef

2003-09-01

Full Text Available Abstract Background Severe acute respiratory syndrome (SARS is a febrile respiratory illness. The disease has been etiologically linked to a novel coronavirus that has been named the SARS-associated coronavirus (SARS-CoV, whose genome was recently sequenced. Since it is a member of the Coronaviridae, its spike protein (S2 is believed to play a central role in viral entry by facilitating fusion between the viral and host cell membranes. The protein responsible for viral-induced membrane fusion of HIV-1 (gp41 differs in length, and has no sequence homology with S2. Results Sequence analysis reveals that the two viral proteins share the sequence motifs that construct their active conformation. These include (1 an N-terminal leucine/isoleucine zipper-like sequence, and (2 a C-terminal heptad repeat located upstream of (3 an aromatic residue-rich region juxtaposed to the (4 transmembrane segment. Conclusions This study points to a similar mode of action for the two viral proteins, suggesting that anti-viral strategy that targets the viral-induced membrane fusion step can be adopted from HIV-1 to SARS-CoV. Recently the FDA approved Enfuvirtide, a synthetic peptide corresponding to the C-terminal heptad repeat of HIV-1 gp41, as an anti-AIDS agent. Enfuvirtide and C34, another anti HIV-1 peptide, exert their inhibitory activity by binding to a leucine/isoleucine zipper-like sequence in gp41, thus inhibiting a conformational change of gp41 required for its activation. We suggest that peptides corresponding to the C-terminal heptad repeat of the S2 protein may serve as inhibitors for SARS-CoV entry.

Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

Science.gov (United States)

Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

2016-05-01

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

Federated query services provided by the Seamless SAR Archive project

Science.gov (United States)

Baker, S.; Bryson, G.; Buechler, B.; Meertens, C. M.; Crosby, C. J.; Fielding, E. J.; Nicoll, J.; Youn, C.; Baru, C.

2013-12-01

The NASA Advancing Collaborative Connections for Earth System Science (ACCESS) seamless synthetic aperture radar (SAR) archive (SSARA) project is a 2-year collaboration between UNAVCO, the Alaska Satellite Facility (ASF), the Jet Propulsion Laboratory (JPL), and OpenTopography at the San Diego Supercomputer Center (SDSC) to design and implement a seamless distributed access system for SAR data and derived data products (i.e. interferograms). A major milestone for the first year of the SSARA project was a unified application programming interface (API) for SAR data search and results at ASF and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives (http://www.unavco.org/ws/brokered/ssara/sar/search). A command line client that utilizes this new service is provided as an open source utility for the community on GitHub (https://github.com/bakerunavco/SSARA). Further API development and enhancements added more InSAR specific keywords and quality control parameters (Doppler centroid, faraday rotation, InSAR stack size, and perpendicular baselines). To facilitate InSAR processing, the federated query service incorporated URLs for DEM (from OpenTopography) and tropospheric corrections (from the JPL OSCAR service) in addition to the URLs for SAR data. This federated query service will provide relevant QC metadata for selecting pairs of SAR data for InSAR processing and all the URLs necessary for interferogram generation. Interest from the international community has prompted an effort to incorporate other SAR data archives (the ESA Virtual Archive 4 and the DLR TerraSAR-X_SSC Geohazard Supersites and Natural Laboratories collections) into the federated query service which provide data for researchers outside the US and North America.

SARS – Koch´Postulates proved.

Indian Academy of Sciences (India)

SARS – Koch´Postulates proved. Novel coronavirus identified from fluids of patients. Virus cultured in Vero cell line. Sera of patients have antibodies to virus. Cultured virus produces disease in Macaque monkeys. -produces specific immune response; -isolated virus is SARS CoV; -pathology similar to human.

Attribute Learning for SAR Image Classification

Directory of Open Access Journals (Sweden)

Chu He

2017-04-01

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

DSM GENERATION FROM HIGH RESOLUTION COSMO-SKYMED IMAGERY WITH RADARGRAMMETRIC MODEL

Directory of Open Access Journals (Sweden)

P. Capaldo

2012-09-01

Full Text Available The availability of new high resolution radar spaceborne sensors offers new interesting potentialities for the geomatics application: spatial and temporal change detection, features extraction, generation of Digital Surface (DSMs. As regards the DSMs generation from new high resolution data (as SpotLight imagery, the development and the accuracy assessment of method based on radargrammetric approach are topics of great interest and relevance. The aim of this investigation is the DSM generation from a COSMO-SkyMed Spotlight stereo pair with the radargrammetric technique. DSM generation procedure consists of two basic steps: the stereo pair orientation and the image matching. The suite for radargrammetric approach has been implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione, a scientific software developed at the Geodesy and Geomatic Institute of the University of Rome "La Sapienza". As regard the image matching the critical issue is the definition of a strategy to search the corresponding points; in SISAR software, an original matching procedure has been developed, based on a coarse-to-fine hierarchical solution with an effective combination of geometrical constrains and an Area Base Matching (ABM algorithm.

Railway infrastructure monitoring with COSMO/SkyMed imagery and multi-temporal SAR interferometry

Science.gov (United States)

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

2012-12-01

For all the European Countries, the rail network represents a key critical infrastructure, deserving protection in view of its continuous structure spread over the whole territory, of the high number of European citizens using it for personal and professional reasons, and of the large volume of freight moving through it. Railway system traverses a wide variety of terrains and encounters a range of geo-technical conditions. The interaction of these factors together with climatic and seismic forcing, may produce ground instabilities that impact on the safety and efficiency of rail operations. In such context, a particular interest is directed to the development of technologies regarding both the prevention of mishaps of infrastructures and the fast recovery of their normal working conditions after the occurrence of accidents (disaster managing). Both these issues are of strategic interest for EU Countries, and in particular for Italy, since, more than other countries, it is characterized by a geo-morphological and hydro-geological structure complexity that increases the risk of natural catastrophes due to landslides, overflowings and floods. The present study has been carried out in the framework of a scientific project aimed at producing a diagnostic system, capable to foresee and monitor landslide events along railway networks by integrating in situ data, detected from on board sophisticated innovative measuring systems, with Earth Observation (EO) techniques. Particular importance is devoted to the use of advanced SAR interferometry, thanks to their all-weather, day-night capability to detect and measure with sub-centimeter accuracy ground surface displacements that, in such context, can occur before a landslide event or after that movements . Special attention is directed to the use of SAR images acquired by COSMO/SkyMed (ASI) constellation capable to achieve very high spatial resolution and very short revisit and response time. In this context, a stack of 57 CSK

SAR system development for UAV multicopter platforms

OpenAIRE

Escartin Martínez, Antonio

2015-01-01

SAR system development for UAV multicopter platforms This thesis describes the optimization of a synthetic aperture radar (SAR) at X-band and its integration into an unmanned aerial vehicle (UAV) of type octocopter. For such optimization the SAR system functionality was extended from singlepol to fulpol and it has been optimized at hardware level in order to improve its quality against noise figure. After its integration into the octocopter platform, its features has been used in order to ...

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

Science.gov (United States)

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement (DEM), and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 meters were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Novel Polarimetric SAR Interferometry Algorithms, Phase I

Data.gov (United States)

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

CENTIMETER COSMO-SKYMED RANGE MEASUREMENTS FOR MONITORING GROUND DISPLACEMENTS

Directory of Open Access Journals (Sweden)

F. Fratarcangeli

2016-06-01

Full Text Available The SAR (Synthetic Aperture Radar imagery are widely used in order to monitor displacements impacting the Earth surface and infrastructures. The main remote sensing technique to extract sub-centimeter information from SAR imagery is the Differential SAR Interferometry (DInSAR, based on the phase information only. However, it is well known that DInSAR technique may suffer for lack of coherence among the considered stack of images. New Earth observation SAR satellite sensors, as COSMO-SkyMed, TerraSAR-X, and the coming PAZ, can acquire imagery with high amplitude resolutions too, up to few decimeters. Thanks to this feature, and to the on board dual frequency GPS receivers, allowing orbits determination with an accuracy at few centimetres level, the it was proven by different groups that TerraSAR-X imagery offer the capability to achieve, in a global reference frame, 3D positioning accuracies in the decimeter range and even better just exploiting the slant-range measurements coming from the amplitude information, provided proper corrections of all the involved geophysical phenomena are carefully applied. The core of this work is to test this methodology on COSMO-SkyMed data acquired over the Corvara area (Bolzano – Northern Italy, where, currently, a landslide with relevant yearly displacements, up to decimeters, is monitored, using GPS survey and DInSAR technique. The leading idea is to measure the distance between the satellite and a well identifiable natural or artificial Persistent Scatterer (PS, taking in account the signal propagation delays through the troposphere and ionosphere and filtering out the known geophysical effects that induce periodic and secular ground displacements. The preliminary results here presented and discussed indicate that COSMO-SkyMed Himage imagery appear able to guarantee a displacements monitoring with an accuracy of few centimetres using only the amplitude data, provided few (at least one stable PS’s are

On reconciling ground-based with spaceborne normalized radar cross section measurements

DEFF Research Database (Denmark)

Baumgartner, Francois; Munk, Jens; Jezek, K C

2002-01-01

This study examines differences in the normalized radar cross section, derived from ground-based versus spaceborne radar data. A simple homogeneous half-space model, indicates that agreement between the two improves as 1) the distance from the scatterer is increased; and/or 2) the extinction...

SAR Coherence Change Detection of Urban Areas Affected by Disasters Using SENTINEL-1 Imagery

Science.gov (United States)

Washaya, P.; Balz, T.

2018-04-01

The study focuses on two study areas: San Juan in Puerto Rico, which was affected by Hurricane Maria in September 2017, and Sarpol Zahab in Iran, which was one of the towns affected by an earthquake in November 2017. In our study, we generate coherence images, and classify them into areas of `change' and `no-change'. A statistical analysis is made by converting the coherence results into point data, creating street blocks for the study areas and integrating the point data into the street blocks to calculate the standard deviation over the whole stack of images. Additionally, Landsat imagery is used to create land-use classes, convert them to polygons and integrate the polygon classes to the coherence maps to determine the average coherence loss per class for each disaster. Results show 65 % loss in coherence after the earthquake in Sarpol-e-Zahab and 75 % loss in Puerto Rico after the Hurricane. Land-use classes show coherence losses to below 0.5 for each disaster.

PHARUS: A C-band Airborne SAR

NARCIS (Netherlands)

Hoogeboom, P.; Koomen, P.J.; Pouwels, H.; Snoeij, P.

1990-01-01

In The Netherlands a plan to design aircraft and build a polarimetric C-band SAR system of a novel design, called PHARUS (PHased Array Universal SAR) is carried out by three institutes. These institutes are the Physics and Electronics Laboratory TNO in The Hague (prime contractor and project

Pixel-based approach for building heights determination by SAR radargrammetry

Science.gov (United States)

Dubois, C.; Thiele, A.; Hinz, S.

2013-10-01

Numerous advances have been made recently in photogrammetry, laser scanning, and remote sensing for the creation of 3D city models. More and more cities are interested in getting 3D city models, be it for urban planning purposes or for supporting public utility companies. In areas often affected by natural disaster, rapid updating of the 3D information may also be useful for helping rescue forces. The high resolutions that can be achieved by the new spaceborne SAR sensor generation enables the analysis of city areas at building level and make those sensors attractive for the extraction of 3D information. Moreover, they present the advantage of weather and sunlight independency, which make them more practicable than optical data, in particular for tasks where rapid response is required. Furthermore, their short revisit time and the possibility of multi-sensor constellation enable providing several acquisitions within a few hours. This opens up the floor for new applications, especially radargrammetric applications, which consider acquisitions taken under different incidence angles. In this paper, we present a new approach for determining building heights, relying only on the radargrammetric analysis of building layover. By taking into account same-side acquisitions, we present the workflow of building height determination. Focus is set on some geometric considerations, pixel-based approach for disparity map calculation, and analysis of the building layover signature for different configurations in order to determine building height.

Global Crop Area Monitoring at High Resolution Exploiting Complementary Use of Free and Open SAR and VSNIR/SWIR Sensor Data Sets

Science.gov (United States)

Lemoine, G.; LEO, O.

2015-12-01

Earth Observation imaging sensors with spatial resolutions in the 10-30 m range allow for separation of the area and crop status contributions to the radiometric signatures, typically at parcel level for a wide range of arable crop production systems. These sensors complement current monitoring efforts that deploy low (100-1000 m) resolution VSNIR/SWIR sensors like MODIS, METOP or PROBA-V, which provide denser time series, but with aggregated and mixed radiometric information for cropped areas. "Free and Open" access to US Landsat imagery has recently been complemented by the European Union's Copernicus program with access to Sentinel-1A C-band SAR and Sentinel-2A visual, near and short-ware infrared (VSNIR/SWIR) sensor data in the 10-20 m resolution range. Sentinel-1A has already proven that consistent time series can be generated at its 12 day revisit frequency. The density of Sentinel-2 time series will greatly expand the availability of [partially cloud covered] VSNIR/SWIR imagery. The release of this large new data flow coincides with wider availability of "big data" processing capacity, the public release of ever more detailed ancillary data sets that support extraction of georeferenced and robust indicators on crop production and their spatial and temporal statistics and developments in crowd-sourced mobile data collection for data validation purposes. We will illustrate the use of hybrid SAR and VSNIR/SWIR data sets from Sentinel-1 and Landsat-8 (and initially released Sentinel-2 imagery) for a number of selected examples. These include crop area delineation and classification in the Netherlands with the support of detailed parcel delineation sets for validation, detection of winter cereal cultivation in Ukraine, impact of the Syrian civil war on irrigated summer crop cultivation and recent examples in support to crop anomaly detection in food insecure areas (North Korea, Sub-Saharan Africa). We discuss method implementation, operational issues and outline

Accelerated Scientific InSAR Processing, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Neva Ridge Technologies proposes to develop a suite of software tools for the analysis of SAR and InSAR data, focused on having a robust and adopted capability well...

Polarimetric SAR image classification based on discriminative dictionary learning model

Science.gov (United States)

Sang, Cheng Wei; Sun, Hong

2018-03-01

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

Mapping and monitoring coal mine subsidence using LiDAR and InSAR

Energy Technology Data Exchange (ETDEWEB)

Froese, C.R.; Mei, S. [Alberta Geological Survey, Edmonton, AB (Canada). Energy Resources Conservation Board

2008-07-01

In the early 1900s, the abandonment of coal mines in Alberta was not regulated and closure documentation was poor. Although the general locations of mines are known, the locations of the specific adits and shafts are not. As such, there are many cases in southwestern Alberta where infrastructure was built on top of old coal mine workings without any detailed records of the abandoned mine or displacement monitoring. The crowns of these workings have been subject to ongoing strain that is reflected at the surface. The rate at which the strain is progressing prior to collapse is not well understood. Mitigation of collapse events is site specific and reactive. This paper demonstrated that airborne LiDAR and spaceborne InSAR technologies can provide valuable information on the distribution of abandoned underground coal mine workings. Both remote sensing techniques were used on Turtle Mountain in the Crowsnest Pass to obtain quantitative information on landslide mechanics, including the patterns and rate of ground movement and subsidence. These techniques can be used to map the location of surface collapse and delineate the location of the coal mine workings that were not previously documented. It was concluded that these technologies will likely become more readily available in the future and incorporated into geo-engineering practices for use in ground hazard detection, monitoring and management. 8 refs., 6 figs.

Human monoclonal antibody as prophylaxis for SARS coronavirus infection in ferrets

NARCIS (Netherlands)

ter Meulen, Jan; Bakker, Alexander B. H.; van den Brink, Edward N.; Weverling, Gerrit J.; Martina, Byron E. E.; Haagmans, Bart L.; Kuiken, Thijs; de Kruif, John; Preiser, Wolfgang; Spaan, Willy; Gelderblom, Hans R.; Goudsmit, Jaap; Osterhaus, Albert D. M. E.

2004-01-01

SARS coronavirus continues to cause sporadic cases of severe acute respiratory syndrome (SARS) in China. No active or passive immunoprophylaxis for disease induced by SARS coronavirus is available. We investigated prophylaxis of SARS coronavirus infection with a neutralising human monoclonal

Non-Drug Pain Relief: Imagery

Science.gov (United States)

PATIENT EDUCATION patienteducation.osumc.edu Non-Drug Pain Relief: Imagery Relaxation helps lessen tension. One way to help decrease pain is to use imagery. Imagery is using your imagination to create a ...

Kinesthetic imagery of musical performance.

Science.gov (United States)

Lotze, Martin

2013-01-01

Musicians use different kinds of imagery. This review focuses on kinesthetic imagery, which has been shown to be an effective complement to actively playing an instrument. However, experience in actual movement performance seems to be a requirement for a recruitment of those brain areas representing movement ideation during imagery. An internal model of movement performance might be more differentiated when training has been more intense or simply performed more often. Therefore, with respect to kinesthetic imagery, these strategies are predominantly found in professional musicians. There are a few possible reasons as to why kinesthetic imagery is used in addition to active training; one example is the need for mental rehearsal of the technically most difficult passages. Another reason for mental practice is that mental rehearsal of the piece helps to improve performance if the instrument is not available for actual training as is the case for professional musicians when they are traveling to various appearances. Overall, mental imagery in musicians is not necessarily specific to motor, somatosensory, auditory, or visual aspects of imagery, but integrates them all. In particular, the audiomotor loop is highly important, since auditory aspects are crucial for guiding motor performance. All these aspects result in a distinctive representation map for the mental imagery of musical performance. This review summarizes behavioral data, and findings from functional brain imaging studies of mental imagery of musical performance.

High-Sensitivity Semiconductor Photocathodes for Space-Born UV Photon-Counting and Imaging, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Many UV photon-counting and imaging applications, including space-borne astronomy, missile tracking and guidance, UV spectroscopy for chemical/biological...

Geometric calibration of ERS satellite SAR images

DEFF Research Database (Denmark)

Mohr, Johan Jacob; Madsen, Søren Nørvang

2001-01-01

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

Research on the space-borne coherent wind lidar technique and the prototype experiment

Science.gov (United States)

Gao, Long; Tao, Yuliang; An, Chao; Yang, Jukui; Du, Guojun; Zheng, Yongchao

2016-10-01

Space-borne coherent wind lidar technique is considered as one of the most promising and appropriate remote Sensing methods for successfully measuring the whole global vector wind profile between the lower atmosphere and the middle atmosphere. Compared with other traditional methods, the space-borne coherent wind lidar has some advantages, such as, the all-day operation; many lidar systems can be integrated into the same satellite because of the light-weight and the small size, eye-safe wavelength, and being insensitive to the background light. Therefore, this coherent lidar could be widely applied into the earth climate research, disaster monitoring, numerical weather forecast, environment protection. In this paper, the 2μm space-borne coherent wind lidar system for measuring the vector wind profile is proposed. And the technical parameters about the sub-system of the coherent wind lidar are simulated and the all sub-system schemes are proposed. For sake of validating the technical parameters of the space-borne coherent wind lidar system and the optical off-axis telescope, the weak laser signal detection technique, etc. The proto-type coherent wind lidar is produced and the experiments for checking the performance of this proto-type coherent wind lidar are finished with the hard-target and the soft target, and the horizontal wind and the vertical wind profile are measured and calibrated, respectively. For this proto-type coherent wind lidar, the wavelength is 1.54μm, the pulse energy 80μJ, the pulse width 300ns, the diameter of the off-axis telescope 120mm, the single wedge for cone scanning with the 40°angle, and the two dualbalanced InGaAs detector modules are used. The experiment results are well consisted with the simulation process, and these results show that the wind profile between the vertical altitude 4km can be measured, the accuracy of the wind velocity and the wind direction are better than 1m/s and +/-10°, respectively.

Improved SAR Image Coregistration Using Pixel-Offset Series

KAUST Repository

Wang, Teng

2014-03-14

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

Improved SAR Image Coregistration Using Pixel-Offset Series

KAUST Repository

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

2014-01-01

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

URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

Directory of Open Access Journals (Sweden)

U. G. Sefercik

2017-09-01

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

InSAR deformation monitoring of high risk landslides

Science.gov (United States)

Singhroy, V.; Li, J.

2013-05-01

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

SAR COHERENCE CHANGE DETECTION OF URBAN AREAS AFFECTED BY DISASTERS USING SENTINEL-1 IMAGERY

Directory of Open Access Journals (Sweden)

P. Washaya

2018-04-01

Full Text Available The study focuses on two study areas: San Juan in Puerto Rico, which was affected by Hurricane Maria in September 2017, and Sarpol Zahab in Iran, which was one of the towns affected by an earthquake in November 2017. In our study, we generate coherence images, and classify them into areas of ‘change’ and ‘no-change’. A statistical analysis is made by converting the coherence results into point data, creating street blocks for the study areas and integrating the point data into the street blocks to calculate the standard deviation over the whole stack of images. Additionally, Landsat imagery is used to create land-use classes, convert them to polygons and integrate the polygon classes to the coherence maps to determine the average coherence loss per class for each disaster. Results show 65 % loss in coherence after the earthquake in Sarpol-e-Zahab and 75 % loss in Puerto Rico after the Hurricane. Land-use classes show coherence losses to below 0.5 for each disaster.

Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

DEFF Research Database (Denmark)

Sandholt, Inge; Skriver, Henning

1999-01-01

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

hPEPT1 Affinity and Translocation of Selected Gln-Sar and Glu-Sar Dipeptide Derivatives

DEFF Research Database (Denmark)

Eriksson, A. H.; Elm, Peter L.; Begtrup, Mikael

2005-01-01

using 14C-labeled Gly-Sar. Translocation was measured as fluorescence ratios induced by the substrates using the fluorescent probe BCECF and an epifluorescence microscope setup. All compounds showed high affinity to hPEPT1, but only the amides l-Gln(N,N-dimethyl)-Sar and l-Gln(N-piperidinyl)-Sar were...... been suggested. However, these are not necessarily predictive of compounds that are actually translocated by hPEPT1. More information on affinity to and translocation via hPEPT1 of side-chain-modified dipeptides may be gained by conducting a study of selected dipeptide derivatives with variety in size...... translocated by hPEPT1. hPEPT1 is very susceptible to modifications of the N-terminal amino acid side chain of dipeptidomimetic substrates, in terms of achieving compounds with high affinity for the transporter. However, as affinity is not predictive of translocation, derivatization in this position must...

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

Science.gov (United States)

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

2017-12-01

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

The experience of SARS-related stigma at Amoy Gardens.

Science.gov (United States)

Lee, Sing; Chan, Lydia Y Y; Chau, Annie M Y; Kwok, Kathleen P S; Kleinman, Arthur

2005-11-01

Severe Acute Respiratory Syndrome (SARS) possesses characteristics that render it particularly prone to stigmatization. SARS-related stigma, despite its salience for public health and stigma research, has had little examination. This study combines survey and case study methods to examine subjective stigma among residents of Amoy Gardens (AG), the first officially recognized site of community outbreak of SARS in Hong Kong. A total of 903 residents of AG completed a self-report questionnaire derived from two focus groups conducted toward the end of the 3-month outbreak. Case studies of two residents who lived in Block E, the heart of the SARS epidemic at AG, complement the survey data. Findings show that stigma affected most residents and took various forms of being shunned, insulted, marginalized, and rejected in the domains of work, interpersonal relationships, use of services and schooling. Stigma was also associated with psychosomatic distress. Residents' strategies for diminishing stigma varied with gender, age, education, occupation, and proximity to perceived risk factors for SARS such as residential location, previous SARS infection and the presence of ex-SARS household members. Residents attributed stigma to government mismanagement, contagiousness of the mysterious SARS virus, and alarmist media reporting. Stigma clearly decreased, but never completely disappeared, after the outbreak. The findings confirm and add to existing knowledge on the varied origins, correlates, and impacts of stigma. They also highlight the synergistic roles of inconsistent health policy responses and risk miscommunication by the media in rapidly amplifying stigma toward an unfamiliar illness. While recognizing the intrinsically stigmatizing nature of public health measures to control SARS, we recommend that a consistent inter-sectoral approach is needed to minimize stigma and to make an effective health response to future outbreaks.

Estimating Elevation Angles From SAR Crosstalk

Science.gov (United States)

Freeman, Anthony

1994-01-01

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

SAR Study of Mobile Phones as a function of Antenna Q

DEFF Research Database (Denmark)

Bahramzy, Pevand; Svendsen, Simon; Jagielski, Ole

2015-01-01

density associated with high-Q antennas. The higher energy stored in the electric and magnetic near-field components can result in higher SAR. Hence, SAR study of high-Q antennas is necessary which, if not addressed, might not comply with the SAR safety guidelines. In this paper, SAR as a function...

SAR calculation using FDTD simulations

OpenAIRE

Ferro, Francisco Nabais; Pinto, Guilherme Taveira; Pinho, Pedro

2009-01-01

The main intend of this work, is to determinate the Specific Absorption Rate (SAR) on human head tissues exposed to radiation caused by sources of 900 and 1800MHz, since those are the typical frequencies for mobile communications systems nowadays. In order to determinate the SAR, has been used the FDTD (Finite Difference Time Domain), which is a numeric method in time domain, obtained from the Maxwell equations in differential mode. In order to do this, a computational model from the human he...

Detection of the Hebei Spirit oil spill on SAR imagery and its temporal evolution in a coastal region of the Yellow Sea

Science.gov (United States)

Kim, Tae-Sung; Park, Kyung-Ae; Li, Xiaofeng; Lee, Moonjin; Hong, Sungwook; Lyu, Sang Jin; Nam, Sooyong

2015-09-01

To investigate the evolution of a disastrous oil spill from a vessel collision, known as the Hebei Spirit accident, off the coast of Korea in the Yellow Sea on 6 December 2007, oil slicks were identified from Synthetic Aperture Radar (SAR) images using a neural network (NN) and an adaptive threshold method. The results from the two objective methods showed good agreement, enough for the estimation of the extent of oil patches and their trajectories, with the exception of negligible errors at the boundaries. Quantitative analyses showed that the detected oil slicks moved southward, corresponding to the prevailing wind and tidal currents, and gradually dissipated during the spill, except for an extraordinary rapid decrease in onshore regions at the initial stage. The initial dissipation of the spilt oil was induced by tidal mixing in the tidal front zone. The spatial and temporal variations of the oil slicks confirmed the influence of atmospheric and oceanic environmental factors. The overall horizontal migration of the oil spills detected from consecutive SAR images was mainly driven by Ekman drift during the winter monsoon rather than the tidal residual current.

High-Level Performance Modeling of SAR Systems

Science.gov (United States)

Chen, Curtis

2006-01-01

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

Automatic Coregistration for Multiview SAR Images in Urban Areas

Science.gov (United States)

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

2017-09-01

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

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

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Flora Weissgerber

2017-09-01

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

Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

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Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

2016-04-01

in Sentinel-1data using Entropy/Alpha decomposition, unsupervised Wishart Classification, and object-based post-classification as well as semi-automatic approaches for extracting inundated areas and flood traces in rural and urban areas from VHR and HR optical imagery using machine learning techniques. Methodological developments related to fires are the implementation of fast and robust methods for mapping burnt scars using change detection procedures using SAR (Sentinel-1, TerraSAR-X) and HR optical (e.g. SPOT, Sentinel-2) data as well as the extraction of 3D surface and volume change information from Pléiades stereo-pairs. In the context of landslides, fast and transferable change detection procedures based on SAR (TerraSAR-X) and optical (SPOT) data as well methods for extracting the extent of landslides only based on polarimetric VHR SAR (TerraSAR-X) data are presented.

Relevant Scatterers Characterization in SAR Images

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Chaabouni, Houda; Datcu, Mihai

2006-11-01

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

An analytical solution for improved HIFU SAR estimation

International Nuclear Information System (INIS)

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

2012-01-01

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

Development of reaction-sintered SiC mirror for space-borne optics

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Yui, Yukari Y.; Kimura, Toshiyoshi; Tange, Yoshio

2017-11-01

We are developing high-strength reaction-sintered silicon carbide (RS-SiC) mirror as one of the new promising candidates for large-diameter space-borne optics. In order to observe earth surface or atmosphere with high spatial resolution from geostationary orbit, larger diameter primary mirrors of 1-2 m are required. One of the difficult problems to be solved to realize such optical system is to obtain as flat mirror surface as possible that ensures imaging performance in infrared - visible - ultraviolet wavelength region. This means that homogeneous nano-order surface flatness/roughness is required for the mirror. The high-strength RS-SiC developed and manufactured by TOSHIBA is one of the most excellent and feasible candidates for such purpose. Small RS-SiC plane sample mirrors have been manufactured and basic physical parameters and optical performances of them have been measured. We show the current state of the art of the RS-SiC mirror and the feasibility of a large-diameter RS-SiC mirror for space-borne optics.

Pornographic imagery and prevalence of paraphilia.

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Dietz, P E; Evans, B

1982-11-01

The authors classified 1,760 heterosexual pornographic magazines according to the imagery of the cover photographs. Covers depicting only a woman posed alone predominated in 1970 but constituted only 10.7% of the covers in 1981. Bondage and domination imagery was the most prevalent nonormative imagery and was featured in 17.2% of the magazines. Smaller proportions of material were devoted to group sexual activity (9.8%), tranvestism and transsexualism (4.4%), and other nonnormative imagery. The authors suggest that pornographic imagery is an unobtrusive measure of the relative prevalence of those paraphilias associated with preferences for specific types of visual imagery and for which better data are lacking.

Application of InSAR to detection of localized subsidence and its effects on flood protection infrastructure in the New Orleans area

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Jones, Cathleen; Blom, Ronald; Latini, Daniele

2014-05-01

The vulnerability of the United States Gulf of Mexico coast to inundation has received increasing attention in the years since hurricanes Katrina and Rita. Flood protection is a challenge throughout the area, but the population density and cumulative effect of historic subsidence makes it particularly difficult in the New Orleans area. Analysis of historical and continuing geodetic measurements identifies a surprising degree of complexity in subsidence (Dokka 2011), including regions that are subsiding at rates faster than those considered during planning for hurricane protection and for coastal restoration projects. Improved measurements are possible through combining traditional single point, precise geodetic data with interferometric synthetic aperture radar (InSAR) observations for to obtain geographically dense constraints on surface deformation. The Gulf Coast environment is very challenging for InSAR techniques, especially with systems not designed for interferometry. We are applying pair-wise InSAR to longer wavelength (L-band, 24 cm) synthetic aperture radar data acquired with the airborne UAVSAR instrument (http://uavsar.jpl.nasa.gov/) to detect localized change impacting flood protection infrastructure in the New Orleans area during the period from 2009 - 2013. Because aircraft motion creates large-scale image artifacts across the scene, we focus on localized areas on and near flood protection infrastructure to identify anomalous change relative to the surrounding area indicative of subsidence, structural deformation, and/or seepage (Jones et al., 2011) to identify areas where problems exist. C-band and particularly X-band radar returns decorrelate over short time periods in rural or less urbanized areas and are more sensitive to atmospheric affects, necessitating more elaborate analysis techniques or, at least, a strict limit on the temporal baseline. The new generation of spaceborne X-band SAR acquisitions ensure relatively high frequency of

Relations of SARS-Related Stressors and Coping to Chinese College Students' Psychological Adjustment during the 2003 Beijing SARS Epidemic

Science.gov (United States)

Main, Alexandra; Zhou, Qing; Ma, Yue; Luecken, Linda J.; Liu, Xin

2011-01-01

This study examined the main and interactive relations of stressors and coping related to severe acute respiratory syndrome (SARS) with Chinese college students' psychological adjustment (psychological symptoms, perceived general health, and life satisfaction) during the 2003 Beijing SARS epidemic. All the constructs were assessed by self-report…

User Validation of VIIRS Satellite Imagery

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Don Hillger

2015-12-01

Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

Effective delineation of urban flooded areas based on aerial ortho-photo imagery

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Zhang, Ying; Guindon, Bert; Raymond, Don; Hong, Gang

2016-10-01

The combination of rapid global urban growth and climate change has resulted in increased occurrence of major urban flood events across the globe. The distribution of flooded area is one of the key information layers for applications of emergency planning and response management. While SAR systems and technologies have been widely used for flood area delineation, radar images suffer from range ambiguities arising from corner reflection effects and shadowing in dense urban settings. A new mapping framework is proposed for the extraction and quantification of flood extent based on aerial optical multi-spectral imagery and ancillary data. This involves first mapping of flood areas directly visible to the sensor. Subsequently, the complete area of submergence is estimated from this initial mapping and inference techniques based on baseline data such as land cover and GIS information such as available digital elevation models. The methodology has been tested and proven effective using aerial photography for the case of the 2013 flood in Calgary, Canada.

Ocean Classification of Dynamical Structures Detected by SAR and Spectral Methods

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Redondo, J. M.; Martinez-Benjamin, J. J.; Tellez, J. D.; Jorge, J.; Diez, M.; Sekula, E.

2016-08-01

We discuss a taxonomy of different dynamical features in the ocean surface and provide some eddy and front statistics, as well as describing some events detected by several satellites and even with additional cruise observations and measurements, in the North-west Mediterranean Sea area between 1996 and 2012. The structure of the flows are presented using self-similar traces that may be used to parametrize mixing at both limits of the Rossby Deformation Radius scale, RL. Results show the ability to identify different SAR signatures and at the same time provide calibrations for the different local configurations of vortices, spirals, Langmuir cells, oil spills and tensioactive slicks that eventually allow the study of the self-similar structure of the turbulence. Depending on the surface wind and wave level, and also on the fetch. the bathimetry, the spiral parameters and the resolution of vortical features change. Previous descriptions did not include the new wind and buoyancy features. SAR images also show the turbulence structure of the coastal area and the Regions of Fresh Water Influence (ROFI). It is noteworthy tt such complex coastal field-dependent behavior is strongly influenced by stratification and rotation of the turbulence spectrum is observed only in the range smaller than the local Rossby deformation radius, RL. The measures of diffusivity from buoy or tracer experiments are used to calibrate the behavior of different tracers and pollutants, both natural and man-made in the NW Mediterranean Sea. Thanks to different polarization and intensity levels in ASAR satellite imagery, these can be used to distinguish between natural and man-made sea surface features due to their distinct self-similar and fractal as a function of spill and slick parameters, environmental conditions and history of both oil releases and weather conditions. Eddy diffusivity map derived from SAR measurements of the ocean surface, performing a feature spatial correlation of the

A patient with asymptomatic severe acute respiratory syndrome (SARS) and antigenemia from the 2003-2004 community outbreak of SARS in Guangzhou, China.

Science.gov (United States)

Che, Xiao-yan; Di, Biao; Zhao, Guo-ping; Wang, Ya-di; Qiu, Li-wen; Hao, Wei; Wang, Ming; Qin, Peng-zhe; Liu, Yu-fei; Chan, Kwok-hong; Cheng, Vincent C C; Yuen, Kwok-yung

2006-07-01

An asymptomatic case of severe acute respiratory syndrome (SARS) occurred early in 2004, during a community outbreak of SARS in Guangzhou, China. This was the first time that a case of asymptomatic SARS was noted in an individual with antigenemia and seroconversion. The asymptomatic case patient and the second index case patient with SARS in the 2003-2004 outbreak both worked in the same restaurant, where they served palm civets, which were found to carry SARS-associated coronaviruses. Epidemiological information and laboratory findings suggested that the findings for the patient with asymptomatic infection, together with the findings from previously reported serological analyses of handlers of wild animals and the 4 index case patients from the 2004 community outbreak, reflected a likely intermediate phase of animal-to-human transmission of infection, rather than a case of human-to-human transmission. This intermediate phase may be a critical stage for virus evolution and disease prevention.

Scattering Mechanism Extraction by a Modified Cloude-Pottier Decomposition for Dual Polarization SAR

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Kefeng Ji

2015-06-01

Full Text Available Dual polarization is a typical operational mode of polarimetric synthetic aperture radar (SAR. However, few studies have considered the scattering mechanism extraction of dual-polarization SARs. A modified Cloude-Pottier decomposition is proposed to investigate the performance of the scattering mechanism extraction of dual-polarization SARs. It is theoretically demonstrated that only HH-VV SAR can discriminate the three canonical scattering mechanisms from an isotropic surface, horizontal dipole, and isotropic dihedral. Various experiments are conducted using 21 scenes from real datasets acquired by AIRSAR, Convair-580 SAR, EMISAR, E-SAR, Pi-SAR, and RADARSAT-2. Division of the dual-polarization H-α plane is experimentally obtained. The lack of cross-polarization induces the diffusion of scattering mechanisms and their overlap in the HH-VV H-α plane. However, the performance of HH-VV SAR for extracting scattering mechanisms is acceptable. Thus, HH-VV SAR is a suitable alternative to full-polarization SAR in certain cases. Meanwhile, the extraction performance of the other two dual-polarization SARs is badly degraded due to the lack of co-polarization. Therefore, HH-HV and HV-VV SARs cannot effectively extract the scattering mechanisms in the H-α plane.

The Role of Satellite Imagery to Improve Pastureland Estimates in South America

Science.gov (United States)

Graesser, J.

2015-12-01

Agriculture has changed substantially across the globe over the past half century. While much work has been done to improve spatial-temporal estimates of agricultural changes, we still know more about the extent of row-crop agriculture than livestock-grazed land. The gap between cropland and pastureland estimates exists largely because it is challenging to characterize natural versus grazed grasslands from a remote sensing perspective. However, the impasse of pastureland estimates is set to break, with an increasing number of spaceborne sensors and freely available satellite data. The Landsat satellite archive in particular provides researchers with immense amounts of data to improve pastureland information. Here we focus on South America, where pastureland expansion has been scrutinized for the past few decades. We explore the challenges of estimating pastureland using temporal Landsat imagery and focus on key agricultural countries, regions, and ecosystems. We focus on the suggested shift of pastureland from the Argentine Pampas to northern Argentina, and the mixing of small-scale and large-scale ranching in eastern Paraguay and how it could impact the Chaco forest to the west. Further, the Beni Savannahs of northern Bolivia and the Colombian Llanos—both grassland and savannah regions historically used for livestock grazing—have been hinted at as future areas for cropland expansion. There are certainly environmental concerns with pastureland expansion into forests; but what are the environmental implications when well-managed pasture systems are converted to intensive soybean or palm oil plantation? Tropical, grazed grasslands are important habitats for biodiversity, and pasturelands can mitigate soil erosion when well managed. Thus, we must improve estimates of grazed land before we can make informed policy and conservation decisions. This talk presents insights into pastureland estimates in South America and discusses the feasibility to improve current

AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

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Y. Xiang

2017-09-01

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

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

Science.gov (United States)

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

2015-12-01

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

Applications of SAR Interferometry in Earth and Environmental Science Research.

Science.gov (United States)

Zhou, Xiaobing; Chang, Ni-Bin; Li, Shusun

2009-01-01

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions.

Mental Imagery and Visual Working Memory

Science.gov (United States)

Keogh, Rebecca; Pearson, Joel

2011-01-01

Visual working memory provides an essential link between past and future events. Despite recent efforts, capacity limits, their genesis and the underlying neural structures of visual working memory remain unclear. Here we show that performance in visual working memory - but not iconic visual memory - can be predicted by the strength of mental imagery as assessed with binocular rivalry in a given individual. In addition, for individuals with strong imagery, modulating the background luminance diminished performance on visual working memory and imagery tasks, but not working memory for number strings. This suggests that luminance signals were disrupting sensory-based imagery mechanisms and not a general working memory system. Individuals with poor imagery still performed above chance in the visual working memory task, but their performance was not affected by the background luminance, suggesting a dichotomy in strategies for visual working memory: individuals with strong mental imagery rely on sensory-based imagery to support mnemonic performance, while those with poor imagery rely on different strategies. These findings could help reconcile current controversy regarding the mechanism and location of visual mnemonic storage. PMID:22195024

Mental imagery and visual working memory.

Directory of Open Access Journals (Sweden)

Rebecca Keogh