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.

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

Science.gov (United States)

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.

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...

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.

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.

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

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...

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.

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.

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.

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

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...

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

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

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

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.

Combined DEM Extration Method from StereoSAR and InSAR

Science.gov (United States)

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

2015-06-01

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

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

Science.gov (United States)

Ajadi, Olaniyi A.

increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

Image intelligence online consulting: A flexible and remote access to strategic information applied to verification of declaration

International Nuclear Information System (INIS)

Chassy, A.F. de; Denizot, L.

2001-01-01

Commercial satellite imagery is giving International Institutions specialized Information Departments access to a great source of valuable intelligence. High resolution and multiple sensors have also led to a growing complexity of interpretation that calls for a greater need of consulting, verification and training in the field in order to make it eligible as an operational source of verification. Responding to this need, Fleximage is extending its Image intelligence (IMINT) training program to include a fully operational and flexible online consulting and training program. Image Intelligence (IMINT) Online Program, a new approach to acquiring IMINT expertise, supported by Internet technologies, and managed by a professional team of experts and technical staff. Fleximage has developed a virtual learning environment on the Internet for acquiring IMINT expertise. Called the IMINT Online Program, this dynamic learning environment provides complete flexibility and personalization of the process for acquiring expertise. The IMINT online program includes two services: Online Consulting and Online Training. The Online Consulting service is designed for the technical staff of an organization who are already operational in the field of image intelligence. Online Consulting enables these staff members to acquire pertinent expertise online that can be directly applied to their professional activity, such as IAEA verification tasks. The Online Training service is designed for the technical staff of an organization who are relatively new to the field of image intelligence. These staff members need to build expertise within a formal training program. Online Training is a flexible and structured program for acquiring IMINT expertise online

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

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Image intelligence online consulting: A flexible and remote access to strategic information applied to verification of declaration

International Nuclear Information System (INIS)

Chassy, A.F. de; Denizot, L.

2001-01-01

Commercial satellite imagery is giving International Institutions specialized Information Departments access to a great source of valuable intelligence. High resolution and multiple sensors have also led to a growing complexity of interpretation that calls for a greater need of consulting, verification and training in the field in order to make it eligible as an operational source of verification. Responding to this need, Fleximage is extending its Image Intelligence (IMINT) training program to include a fully operational and flexible online consulting and training program. Image Intelligence (IMINT) Online Program, a new approach to acquiring IMINT expertise, supported by Internet technologies, and managed by a professional team of experts and technical staff. Fleximage has developed a virtual learning environment on the Internet for acquiring IMINT expertise. Called the IMINT Online Program, this dynamic learning environment provides complete flexibility and personalization of the process for acquiring expertise. The IMINT online program includes two services: Online Consulting and Online Training. The Online Consulting service is designed for the technical staff of an organization who are already operational in the field of image intelligence. Online Consulting enables these staff members to acquire pertinent expertise online that can be directly applied to their professional activity, such as IAEA verification tasks. The IMINT virtual Consulting and Training services indicated above are made possible thanks to the latest in Internet-based technologies including: multimedia CD-ROM, Internet technologies, rich media content (Audio, Video and Flash), application sharing, platform Maintenance Tools, secured connections and authentication, knowledge database technologies. IMINT Online Program operates owing to: specialized experts in fields relating to IMINT. These experts carry out the tasks of consultants, coaches, occasional speakers, and course content designers

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...

Multi-image Matching of Airborne SAR Imagery by SANCC

Directory of Open Access Journals (Sweden)

DING Hao

2015-03-01

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

Enhanced tactical radar correlator (ETRAC): true interoperability of the 1990s

Science.gov (United States)

Guillen, Frank J.

1994-10-01

The enhanced tactical radar correlator (ETRAC) system is under development at Westinghouse Electric Corporation for the Army Space Program Office (ASPO). ETRAC is a real-time synthetic aperture radar (SAR) processing system that provides tactical IMINT to the corps commander. It features an open architecture comprised of ruggedized commercial-off-the-shelf (COTS), UNIX based workstations and processors. The architecture features the DoD common SAR processor (CSP), a multisensor computing platform to accommodate a variety of current and future imaging needs. ETRAC's principal functions include: (1) Mission planning and control -- ETRAC provides mission planning and control for the U-2R and ASARS-2 sensor, including capability for auto replanning, retasking, and immediate spot. (2) Image formation -- the image formation processor (IFP) provides the CPU intensive processing capability to produce real-time imagery for all ASARS imaging modes of operation. (3) Image exploitation -- two exploitation workstations are provided for first-phase image exploitation, manipulation, and annotation. Products include INTEL reports, annotated NITF SID imagery, high resolution hard copy prints and targeting data. ETRAC is transportable via two C-130 aircraft, with autonomous drive on/off capability for high mobility. Other autonomous capabilities include rapid setup/tear down, extended stand-alone support, internal environmental control units (ECUs) and power generation. ETRAC's mission is to provide the Army field commander with accurate, reliable, and timely imagery intelligence derived from collections made by the ASARS-2 sensor, located on-board the U-2R aircraft. To accomplish this mission, ETRAC receives video phase history (VPH) directly from the U-2R aircraft and converts it in real time into soft copy imagery for immediate exploitation and dissemination to the tactical users.

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.

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.

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.

Intelligence Community Spending: Trends and Issues

Science.gov (United States)

2016-11-08

The Deputy Director CIA manages the CIAP. Funds CIA activities to include HUMINT and OSINT . The CIAP funds everything related to the CIA. It...Human Intelligence (HUMINT); Imagery Intelligence (IMINT); Measurement and Signature Intelligence (MASINT); Open Source Intelligence ( OSINT ); and

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.

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.

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)

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...

Improved spatial mapping of rainfall events with spaceborne SAR imagery

Science.gov (United States)

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

1983-01-01

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

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

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

H. T. Chu

2012-07-01

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

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

Directory of Open Access Journals (Sweden)

Oscar Garcia-Pineda

2017-06-01

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

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

Directory of Open Access Journals (Sweden)

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.

An Advanced Rotation Invariant Descriptor for SAR Image Registration

Directory of Open Access Journals (Sweden)

Yuming Xiang

2017-07-01

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

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.

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.

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

data stacks were selected: ERS-2 ascending data acquired in 2001-2011, ENVISAT ASAR ascending and descending data acquired in 2003-2007, and ALOS PALSAR descending and ascending data acquired in 2007 and 2008. The feature extraction was specifically addressed to the recognition of buried structures, archaeological deposits and the study of the buried networks of aqueducts, as well as the morphological study of the Nasca geoglyphs. Change detection analysis also included the multi-temporal reconstruction of the evolution of the Rio Nasca catchment basin, while specific tests were performed to demonstrate the usefulness of SAR imagery for monitoring looting activities. The results of the radar-interpretation compared and integrated with the field investigations will support the archaeological activities and contribute to the monitoring and enhancement of archaeological heritage and cultural landscape of the Nasca region.

Pre-incident Analysis using Multigraphs and Faceted Ontologies

Science.gov (United States)

2013-08-01

intelligence (HUMINT), 5) open - source intelligence ( OSINT ) and 6) geospatial intelligence 1 . The analyst must access, parse, and correlate each of...The information comes in a range of classification levels from open - source human terrain data to highly classified and compartmentalized, and in...many types: 1) signals intelligence (SIGINT), 2) imagery intelligence (IMINT), 3) measurement and signature intelligence (MASINT), 4) human- source

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

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

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.

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

Science.gov (United States)

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.

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

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...

Multifrequency OFDM SAR in Presence of Deception Jamming

Directory of Open Access Journals (Sweden)

Schuerger Jonathan

2010-01-01

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Zhi Zhao

2013-01-01

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

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%.

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.

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

Directory of Open Access Journals (Sweden)

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

Global Rapid Flood Mapping System with Spaceborne SAR Data

Science.gov (United States)

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

2017-12-01

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

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.

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.

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

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

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.

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

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

M. Mahdian

2013-09-01

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

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

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

S. Havivi

2016-06-01

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

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.

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

Science.gov (United States)

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

2017-12-01

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

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

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

Science.gov (United States)

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

Science.gov (United States)

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

Science.gov (United States)

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

Science.gov (United States)

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.

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

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

2018-05-12

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

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

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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

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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

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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

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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.

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

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

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.

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.

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Manabu Watanabe

2010-01-01

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

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.

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...

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

Directory of Open Access Journals (Sweden)

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.

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)

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

Directory of Open Access Journals (Sweden)

K.-Y. Hwa

2008-01-01

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

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

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.

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.

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.

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...

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.

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

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.

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

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.

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.

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.

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.

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

Lambda Vision

Science.gov (United States)

Czajkowski, Michael

2014-06-01

There is an explosion in the quantity and quality of IMINT data being captured in Intelligence Surveillance and Reconnaissance (ISR) today. While automated exploitation techniques involving computer vision are arriving, only a few architectures can manage both the storage and bandwidth of large volumes of IMINT data and also present results to analysts quickly. Lockheed Martin Advanced Technology Laboratories (ATL) has been actively researching in the area of applying Big Data cloud computing techniques to computer vision applications. This paper presents the results of this work in adopting a Lambda Architecture to process and disseminate IMINT data using computer vision algorithms. The approach embodies an end-to-end solution by processing IMINT data from sensors to serving information products quickly to analysts, independent of the size of the data. The solution lies in dividing up the architecture into a speed layer for low-latent processing and a batch layer for higher quality answers at the expense of time, but in a robust and fault-tolerant way. This approach was evaluated using a large corpus of IMINT data collected by a C-130 Shadow Harvest sensor over Afghanistan from 2010 through 2012. The evaluation data corpus included full motion video from both narrow and wide area field-of-views. The evaluation was done on a scaled-out cloud infrastructure that is similar in composition to those found in the Intelligence Community. The paper shows experimental results to prove the scalability of the architecture and precision of its results using a computer vision algorithm designed to identify man-made objects in sparse data terrain.

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

Directory of Open Access Journals (Sweden)

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...

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

Directory of Open Access Journals (Sweden)

C. Ozkan

2012-07-01

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

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.

Spaceborne Polarimetric SAR Interferometry: Performance Analysis and Mission Concepts

Directory of Open Access Journals (Sweden)

Shane R. Cloude

2005-12-01

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

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...

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.

PRF Ambiguity Detrmination for Radarsat ScanSAR System

Science.gov (United States)

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.

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...

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.

Unsupervised SBAS-DInSAR Processing of Space-borne SAR data for Earth Surface Displacement Time Series Generation

Science.gov (United States)

Casu, F.; de Luca, C.; Lanari, R.; Manunta, M.; Zinno, I.

2016-12-01

During the last 25 years, the Differential Synthetic Aperture Radar Interferometry (DInSAR) has played an important role for understanding the Earth's surface deformation and its dynamics. In particular, the large collections of SAR data acquired by a number of space-borne missions (ERS, ENVISAT, ALOS, RADARSAT, TerraSAR-X, COSMO-SkyMed) have pushed toward the development of advanced DInSAR techniques for monitoring the temporal evolution of the ground displacements with an high spatial density. Moreover, the advent of the Copernicus Sentinel-1 (S1) constellation is providing a further increase in the SAR data flow available to the Earth science community, due to its characteristics of global coverage strategy and free and open access data policy. Therefore, managing and storing such a huge amount of data, processing it in an effcient way and maximizing the available archives exploitation are becoming high priority issues. In this work we present some recent advances in the DInSAR field for dealing with the effective exploitation of the present and future SAR data archives. In particular, an efficient parallel SBAS implementation (namely P-SBAS) that takes benefit from high performance computing is proposed. Then, the P-SBAS migration to the emerging Cloud Computing paradigm is shown, together with extensive tests carried out in the Amazon's Elastic Cloud Compute (EC2) infrastructure. Finally, the integration of the P-SBAS processing chain within the ESA Geohazards Exploitation Platform (GEP), for setting up operational on-demand and systematic web tools, open to every user, aimed at automatically processing stacks of SAR data for the generation of SBAS displacement time series, is also illustrated. A number of experimental results obtained by using the ERS, ENVISAT and S1 data in areas characterized by volcanic, seismic and anthropogenic phenomena will be shown. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

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.

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.

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

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.

Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

Directory of Open Access Journals (Sweden)

Michele Crosetto

2011-02-01

Full Text Available This paper is focused on spaceborne Differential Interferometric SAR (DInSAR for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors.

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.

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.

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 ...

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

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

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.

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

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.

Infrastructure monitoring with spaceborne SAR sensors

CERN Document Server

ANGHEL, ANDREI; CACOVEANU, REMUS

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

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.

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...

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

Directory of Open Access Journals (Sweden)

Flora Weissgerber

2017-09-01

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

Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

Science.gov (United States)

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

Science.gov (United States)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

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

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)

Pornographic imagery and prevalence of paraphilia.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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

Science.gov (United States)

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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.

AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

Directory of Open Access Journals (Sweden)

Y. Xiang

2017-09-01

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

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

Full Text Available 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.

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.

Volcano-tectonic control of Merapi's lava dome splitting observed from high resolution TerraSAR-X data

KAUST Repository

Luehr, Birger-G.; Walter, Thomas R.; Subandriyo, Joko; Sri Brotopuspito, Kirbani; Vasyura-Bathke, Hannes; Suryanto, Wiwit; Aisyah, Naning; Darmawan, Herlan; Nikkhoo, Mehdi; Richter, Nicole; Jousset, Philippe; Dahm, Torsten

2015-01-01

Volcanism at active andesite-dacite volcanoes is often associated with the formation and collapse of circular shaped protrusions of extruded, highly viscous lava, the so-called domes, which are emplaced in the near summit region. Growing domes may experience stable and instable structural phases, with a gradual transition in between. Dome collapse and the break-off of instable blocks of viscous lava may lead to pyroclastic flows, one of the most lethal hazards at stratovolcanoes. At Merapi volcano, Indonesia, nearly 50 % of all eruptions are accompanied by these phenomena. After the climactic eruption in 2010 which left an amphitheater in the summit region, a new dome started growing. Three years later, the dome reached a height of approximately 100 m and diameters of 220 and 190 m with a plateau-like surface area of 40,000m2 approximately. On 18/11/2013, an explosion occurred without identified precursors, leaving a major fracture cutting the complete dome structure. Based on high resolution TerraSAR-X satellite radar imagery, we could identify this linear fracture, traceable over ~200m in the long axis, and up to 40m width. After geocoding of the radar amplitude imagery, the fractures azimuthal trend could be compared to other structural lineaments, indicative of a significant NNW-SSE structural direction that has formed on Merapi volcano in the past. This alignment is also visible in a seismic velocity tomographic imagery for the upper crust, down to 15 km depth. The Merapi dome fractured in a NW-SE direction, and is consistent with the alignment of regional tectonic structures and of anticipated directions of pyroclastic flows. The fracture may be part of a larger volcano-tectonic system and may affect the dynamics and the stability of the Merapi dome.

Volcano-tectonic control of Merapi's lava dome splitting observed from high resolution TerraSAR-X data

KAUST Repository

Luehr, Birger-G.

2015-04-01

Volcanism at active andesite-dacite volcanoes is often associated with the formation and collapse of circular shaped protrusions of extruded, highly viscous lava, the so-called domes, which are emplaced in the near summit region. Growing domes may experience stable and instable structural phases, with a gradual transition in between. Dome collapse and the break-off of instable blocks of viscous lava may lead to pyroclastic flows, one of the most lethal hazards at stratovolcanoes. At Merapi volcano, Indonesia, nearly 50 % of all eruptions are accompanied by these phenomena. After the climactic eruption in 2010 which left an amphitheater in the summit region, a new dome started growing. Three years later, the dome reached a height of approximately 100 m and diameters of 220 and 190 m with a plateau-like surface area of 40,000m2 approximately. On 18/11/2013, an explosion occurred without identified precursors, leaving a major fracture cutting the complete dome structure. Based on high resolution TerraSAR-X satellite radar imagery, we could identify this linear fracture, traceable over ~200m in the long axis, and up to 40m width. After geocoding of the radar amplitude imagery, the fractures azimuthal trend could be compared to other structural lineaments, indicative of a significant NNW-SSE structural direction that has formed on Merapi volcano in the past. This alignment is also visible in a seismic velocity tomographic imagery for the upper crust, down to 15 km depth. The Merapi dome fractured in a NW-SE direction, and is consistent with the alignment of regional tectonic structures and of anticipated directions of pyroclastic flows. The fracture may be part of a larger volcano-tectonic system and may affect the dynamics and the stability of the Merapi dome.

SARS Risk Perception, Knowledge, Precautions, and Information Sources, the Netherlands

Science.gov (United States)

Aro, Arja R.; Oenema, Anke; de Zwart, Onno; Richardus, Jan Hendrik; Bishop, George D.

2004-01-01

Severe acute respiratory syndrome (SARS)–related risk perceptions, knowledge, precautionary actions, and information sources were studied in the Netherlands during the 2003 SARS outbreak. Although respondents were highly aware of the SARS outbreak, the outbreak did not result in unnecessary precautionary actions or fears. PMID:15496256

NAIP 2015 Imagery Feedback

Data.gov (United States)

Farm Service Agency, Department of Agriculture — The NAIP 2015 Imagery Feedback web application allows users to make comments and observations about the quality of the 2015 National Agriculture Imagery Program...

SAR antenna design for ambiguity and multipath suppression

DEFF Research Database (Denmark)

Christensen, Erik Lintz; Dich, Mikael

1993-01-01

A high resolution airborne synthetic aperture radar (SAR) has been developed at the Electromagnetics Institute (EMI) for remote sensing applications. The paper considers the radiation of antennas for a SAR system from a systems perspective. The basic specifications of an idealised antenna...... are obtained from the required swath and the azimuth footprint needed for the SAR processing. The radiation from a real antenna causes unwanted signal returns that lead to intensity variations (multipath) and ghost echoes (ambiguity). Additional specifications are deduced by considering these signals...

Bats and SARS

Centers for Disease Control (CDC) Podcasts

Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.

Current Resource Imagery Projects

Data.gov (United States)

Farm Service Agency, Department of Agriculture — Map showing coverage of current Resource imagery projects. High resolution/large scale Resource imagery is typically acquired for the U.S. Forest Service and other...

Research on Airborne SAR Imaging Based on Esc Algorithm

Science.gov (United States)

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

2017-09-01

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

RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

Directory of Open Access Journals (Sweden)

X. T. Dong

2017-09-01

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

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. PMID:22573992

Applications of SAR Interferometry in Earth and Environmental Science Research

Directory of Open Access Journals (Sweden)

Xiaobing Zhou

2009-03-01

Full Text Available 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.

Evaluation of the Wishart test statistics for polarimetric SAR data

DEFF Research Database (Denmark)

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

2003-01-01

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

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.

Wavelet Filter Banks for Super-Resolution SAR Imaging

Science.gov (United States)

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

2011-01-01

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

The economic impact of SARS in Beijing, China.

Science.gov (United States)

Beutels, Philippe; Jia, Na; Zhou, Qing-Yi; Smith, Richard; Cao, Wu-Chun; de Vlas, Sake J

2009-11-01

To document the impact of the severe acute respiratory syndrome (SARS) outbreak in Beijing on indicators of social and economic activity. Associations between time series of daily and monthly SARS cases and deaths and volume of public train, airplane and cargo transport, tourism, household consumption patterns and gross domestic product growth in Beijing were investigated using the cross-correlation function. Significant correlation coefficients were found for all indicators except wholesale accounts and expenditures on necessities, with the most significant correlations occurring with a delay of 1 day to 1 month. Especially leisure activities, local and international transport and tourism were affected by SARS particularly in May 2003. Much of this consumption was merely postponed; but irrecoverable losses to the tourist sector alone were estimated at about US$ 1.4 bn, or 300 times the cost of treatment for SARS cases in Beijing.

INVENTORY OF IRRIGATED RICE ECOSYSTEM USING POLARIMETRIC SAR DATA

Directory of Open Access Journals (Sweden)

P. Srikanth

2012-08-01

Full Text Available An attempt has been made in the current study to assess the potential of polarimetric SAR data for inventory of kharif rice and the major competing crop like cotton. In the process, physical process of the scattering mechanisms occurring in rice and cotton crops at different phonological stages was studied through the use of temporal Radarsat 2 Fine quadpol SAR data. The temporal dynamics of the volume, double and odd bounce, entropy, anisotropy, alpha parameters and polarimertic signatures, classification through isodata clustering and Wishart techniques were assessed. The Wishart (H-a classification showed higher overall as well as rice and cotton crop accuracies compared to the isodata clustering from Freeman 3-component decomposition. The classification of temporal SAR data sets independently showed that the rice crop forecasting can be advanced with the use of appropriate single date polarimetric SAR data rather than using temporal SAR amplitude data sets with the single polarization in irrigated rice ecosystems

Guided SAR image despeckling with probabilistic non local weights

Science.gov (United States)

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

2017-12-01

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

Kinesthetic imagery of musical performance

Directory of Open Access Journals (Sweden)

Martin eLotze

2013-06-01

Full Text Available 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. Training difficult passages repeatedly has the potential to induce fatigue in tendons and muscles and can ultimately result in the development of dystonia. 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 travelling 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. Furthermore, slight co-movement, for instance of the fingers, usually occurs when imagining musical performance, a situation different to the laboratory condition where movement execution is strictly controlled. 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.

Hypnagogic imagery and EEG activity.

Science.gov (United States)

Hayashi, M; Katoh, K; Hori, T

1999-04-01

The relationships between hypnagogic imagery and EEG activity were studied. 7 subjects (4 women and 3 men) reported the content of hypnagogic imagery every minute and the hypnagogic EEGs were classified into 5 stages according to Hori's modified criteria. The content of the hypnagogic imagery changed as a function of the hypnagogic EEG stages.

Prototype Theory Based Feature Representation for PolSAR Images

OpenAIRE

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

2016-01-01

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

One carbon metabolism in SAR11 pelagic marine bacteria.

Directory of Open Access Journals (Sweden)

Jing Sun

Full Text Available The SAR11 Alphaproteobacteria are the most abundant heterotrophs in the oceans and are believed to play a major role in mineralizing marine dissolved organic carbon. Their genomes are among the smallest known for free-living heterotrophic cells, raising questions about how they successfully utilize complex organic matter with a limited metabolic repertoire. Here we show that conserved genes in SAR11 subgroup Ia (Candidatus Pelagibacter ubique genomes encode pathways for the oxidation of a variety of one-carbon compounds and methyl functional groups from methylated compounds. These pathways were predicted to produce energy by tetrahydrofolate (THF-mediated oxidation, but not to support the net assimilation of biomass from C1 compounds. Measurements of cellular ATP content and the oxidation of (14C-labeled compounds to (14CO(2 indicated that methanol, formaldehyde, methylamine, and methyl groups from glycine betaine (GBT, trimethylamine (TMA, trimethylamine N-oxide (TMAO, and dimethylsulfoniopropionate (DMSP were oxidized by axenic cultures of the SAR11 strain Ca. P. ubique HTCC1062. Analyses of metagenomic data showed that genes for C1 metabolism occur at a high frequency in natural SAR11 populations. In short term incubations, natural communities of Sargasso Sea microbial plankton expressed a potential for the oxidation of (14C-labeled formate, formaldehyde, methanol and TMAO that was similar to cultured SAR11 cells and, like cultured SAR11 cells, incorporated a much larger percentage of pyruvate and glucose (27-35% than of C1 compounds (2-6% into biomass. Collectively, these genomic, cellular and environmental data show a surprising capacity for demethylation and C1 oxidation in SAR11 cultures and in natural microbial communities dominated by SAR11, and support the conclusion that C1 oxidation might be a significant conduit by which dissolved organic carbon is recycled to CO(2 in the upper ocean.

Alcohol imagery on New Zealand television

Directory of Open Access Journals (Sweden)

Reeder Anthony I

2007-02-01

Full Text Available Abstract Background To examine the extent and nature of alcohol imagery on New Zealand (NZ television, a content analysis of 98 hours of prime-time television programs and advertising was carried out over 7 consecutive days' viewing in June/July 2004. The main outcome measures were number of scenes in programs, trailers and advertisements depicting alcohol imagery; the extent of critical versus neutral and promotional imagery; and the mean number of scenes with alcohol per hour, and characteristics of scenes in which alcohol featured. Results There were 648 separate depictions of alcohol imagery across the week, with an average of one scene every nine minutes. Scenes depicting uncritical imagery outnumbered scenes showing possible adverse health consequences of drinking by 12 to 1. Conclusion The evidence points to a large amount of alcohol imagery incidental to storylines in programming on NZ television. Alcohol is also used in many advertisements to market non-alcohol goods and services. More attention needs to be paid to the extent of alcohol imagery on television from the industry, the government and public health practitioners. Health education with young people could raise critical awareness of the way alcohol imagery is presented on television.

Comparison of SAR calculation algorithms for the finite-difference time-domain method

International Nuclear Information System (INIS)

Laakso, Ilkka; Uusitupa, Tero; Ilvonen, Sami

2010-01-01

Finite-difference time-domain (FDTD) simulations of specific-absorption rate (SAR) have several uncertainty factors. For example, significantly varying SAR values may result from the use of different algorithms for determining the SAR from the FDTD electric field. The objective of this paper is to rigorously study the divergence of SAR values due to different SAR calculation algorithms and to examine if some SAR calculation algorithm should be preferred over others. For this purpose, numerical FDTD results are compared to analytical solutions in a one-dimensional layered model and a three-dimensional spherical object. Additionally, the implications of SAR calculation algorithms for dosimetry of anatomically realistic whole-body models are studied. The results show that the trapezium algorithm-based on the trapezium integration rule-is always conservative compared to the analytic solution, making it a good choice for worst-case exposure assessment. In contrast, the mid-ordinate algorithm-named after the mid-ordinate integration rule-usually underestimates the analytic SAR. The linear algorithm-which is approximately a weighted average of the two-seems to be the most accurate choice overall, typically giving the best fit with the shape of the analytic SAR distribution. For anatomically realistic models, the whole-body SAR difference between different algorithms is relatively independent of the used body model, incident direction and polarization of the plane wave. The main factors affecting the difference are cell size and frequency. The choice of the SAR calculation algorithm is an important simulation parameter in high-frequency FDTD SAR calculations, and it should be explained to allow intercomparison of the results between different studies. (note)

Evidence of rock slope breathing using ground-based InSAR

Science.gov (United States)

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

2017-07-01

Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) campaigns were performed in summer 2011 and 2012 in the Romsdalen valley (Møre & Romsdal county, western Norway) in order to assess displacements on Mannen/Børa rock slope. Located 1 km northwest, a second GB-InSAR system continuously monitors the large Mannen rockslide. The availability of two GB-InSAR positions creates a wide coverage of the rock slope, including a slight dataset overlap valuable for validation. A phenomenon of rock slope breathing is detected in a remote and hard-to-access area in mid-slope. Millimetric upward displacements are recorded in August 2011. Analysis of 2012 GB-InSAR campaign, combined with the large dataset from the continuous station, shows that the slope is affected by inflation/deflation phenomenon between 5 and 10 mm along the line-of-sight. The pattern is not homogenous in time and inversions of movement have a seasonal recurrence. These seasonal changes are confirmed by satellite InSAR observations and can possibly be caused by hydrogeological variations. In addition, combination of GB-InSAR results, in situ measurements and satellite InSAR analyses contributes to a better overview of movement distribution over the whole area.

Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation.

Science.gov (United States)

Lebon, Florent; Horn, Ulrike; Domin, Martin; Lotze, Martin

2018-04-01

Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. However, with respect to performance, well-controlled functional imaging studies on MI training are sparse. We investigated changes in fMRI representation going along with performance changes of a finger sequence (error and velocity) after MI training in 48 healthy young volunteers. Before training, we tested the vividness of kinesthetic and visual imagery. During tests, participants were instructed to move or to imagine moving the fingers of the right hand in a specific order. During MI training, participants repeatedly imagined the sequence for 15 min. Imaging analysis was performed using a full-factorial design to assess brain changes due to imagery training. We also used regression analyses to identify those who profited from training (performance outcome and gain) with initial imagery scores (vividness) and fMRI activation magnitude during MI at pre-test (MI pre ). After training, error rate decreased and velocity increased. We combined both parameters into a common performance index. FMRI activation in the left inferior parietal lobe (IPL) was associated with MI and increased over time. In addition, fMRI activation in the right IPL during MI pre was associated with high initial kinesthetic vividness. High kinesthetic imagery vividness predicted a high performance after training. In contrast, occipital activation, associated with visual imagery strategies, showed a negative predictive value for performance. Our data echo the importance of high kinesthetic vividness for MI training outcome and consider IPL as a key area during MI and through MI training. © 2018 Wiley Periodicals, Inc.

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China.

Science.gov (United States)

Cao, Chunxiang; Chen, Wei; Zheng, Sheng; Zhao, Jian; Wang, Jinfeng; Cao, Wuchun

2016-01-01

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

Hydrodynamics of the groundwater-fed Sian Ka'an Wetlands, Mexico, From InSAR and SAR Data

DEFF Research Database (Denmark)

Gondwe, Bibi Ruth Neuman; Hong, S.; Wdowinski, S.

2008-01-01

The 5300 km2 pristine Sian Ka'an wetland in Mexico is fed entirely by groundwater from the karst aquifer of the Yucatan Peninsula. The area is undeveloped and hence difficult to access. The inflow through underground rivers and karst structures is hard to observe resulting in difficulties......-changes of the backscattered radar signal, which can be related to the water level changes in vegetated wetlands. SAR data reveals information of surface properties such as the degree of flooding through the amplitude of the backscattered signal. We used RADARSAT-1 InSAR and SAR data to form 36 interferograms and 13 flooding...... maps with 24 to 48 day intervals covering the time span of October 2006 to March 2008. The dataset has a high spatial resolution of ca. 20 to 60 m. Sian Ka'an consists of a mosaic of freshwater sloughs, canals, floodplains and brackish tidally-influenced areas. Throughout most of the year, water level...

Methodology of dose calculation for the SRS SAR

International Nuclear Information System (INIS)

Price, J.B.

1991-07-01

The Savannah River Site (SRS) Safety Analysis Report (SAR) covering K reactor operation assesses a spectrum of design basis accidents. The assessment includes estimation of the dose consequences from the analyzed accidents. This report discusses the methodology used to perform the dose analysis reported in the SAR and also includes the quantified doses. Doses resulting from postulated design basis reactor accidents in Chapter 15 of the SAR are discussed, as well as an accident in which three percent of the fuel melts. Doses are reported for both atmospheric and aqueous releases. The methodology used to calculate doses from these accidents as reported in the SAR is consistent with NRC guidelines and industry standards. The doses from the design basis accidents for the SRS reactors are below the limits set for commercial reactors by the NRC and also meet industry criteria. A summary of doses for various postulated accidents is provided

Measuring Creative Imagery Abilities

Directory of Open Access Journals (Sweden)

Dorota M. Jankowska

2015-10-01

Full Text Available Over the decades, creativity and imagination research developed in parallel, but they surprisingly rarely intersected. This paper introduces a new theoretical model of creative imagination, which bridges creativity and imagination research, as well as presents a new psychometric instrument, called the Test of Creative Imagery Abilities (TCIA, developed to measure creative imagery abilities understood in accordance with this model. Creative imagination is understood as constituted by three interrelated components: vividness (the ability to create images characterized by a high level of complexity and detail, originality (the ability to produce unique imagery, and transformativeness (the ability to control imagery. TCIA enables valid and reliable measurement of these three groups of abilities, yielding the general score of imagery abilities and at the same time making profile analysis possible. We present the results of eight studies on a total sample of more than 1,700 participants, showing the factor structure of TCIA using confirmatory factor analysis, as well as provide data confirming this instrument’s validity and reliability. The availability of TCIA for interested researchers may result in new insights and possibilities of integrating the fields of creativity and imagination science.

Empirical wind retrieval model based on SAR spectrum measurements

Science.gov (United States)

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

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

C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

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Frédérique C. Pivot

2012-07-01

Full Text Available RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR systems for retrieving the snow water equivalent under dry snow conditions in the forest–tundra ecotone. The backscatter values are compared against ground measurements at six sampling sites, which are taken to be representative of the land-cover types found in the region. The contribution of dry snow to the radar return is evident when frost penetrates the first 20 cm of soil. Only then does the backscatter respond positively to changes in snow water equivalent, at least in the open and forested areas near the coast, where 1-dB increases in backscatter for each approximate 5–10 mm of accumulated water equivalent are observed at 20–31° incidence angles. Further inland, the backscatter shows either no change or a negative change with snow accumulation, which suggests that the radar signal there is dominated by ground surface scattering (e.g., fen when not attenuated by vegetation (e.g., forested and transition. With high-frequency ground-penetrating radar, we demonstrate the presence of a 10–20-cm layer of black ice underneath the snow cover, which causes the reduced radar returns (−15 dB and less observed in the inland fen. A correlation between the backscattering and the snow water equivalent cannot be determined due to insufficient observations at similar incidence angles. To establish a relationship between the snow water equivalent and the backscatter, only images acquired with similar incidence angles should be used, and they must be corrected for both vegetation and ground effects.

SAR image effects on coherence and coherence estimation.

Energy Technology Data Exchange (ETDEWEB)

Bickel, Douglas Lloyd

2014-01-01

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

Phase correction and error estimation in InSAR time series analysis

Science.gov (United States)

Zhang, Y.; Fattahi, H.; Amelung, F.

2017-12-01

During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same

Fast Superpixel Segmentation Algorithm for PolSAR Images

Directory of Open Access Journals (Sweden)

Zhang Yue

2017-10-01

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

Program Merges SAR Data on Terrain and Vegetation Heights

Science.gov (United States)

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

2007-01-01

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

The Danish (Q)SAR Database Update Project

DEFF Research Database (Denmark)

Nikolov, Nikolai Georgiev; Dybdahl, Marianne; Abildgaard Rosenberg, Sine

2013-01-01

The Danish (Q)SAR Database is a collection of predictions from quantitative structure–activity relationship ((Q)SAR) models for over 70 environmental and human health-related endpoints (covering biodegradation, metabolism, allergy, irritation, endocrine disruption, teratogenicity, mutagenicity......, carcinogenicity and others), each of them available for 185,000 organic substances. The database has been available online since 2005 (http://qsar.food.dtu.dk). A major update project for the Danish (Q)SAR database is under way, with a new online release planned in the beginning of 2015. The updated version...... will contain more than 600,000 discrete organic structures and new, more precise predictions for all endpoints, derived by consensus algorithms from a number of state-of-the-art individual predictions. Copyright © 2013 Published by Elsevier Ireland Ltd....

Research on the method of extracting DEM based on GBInSAR

Science.gov (United States)

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

2016-05-01

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

The effect of severe acute respiratory syndrome (SARS) on emergency airway management.

Science.gov (United States)

Wong, Evelyn; Ho, Khoy Kheng

2006-07-01

From early March 2003 to late May 2003, severe acute respiratory syndrome (SARS) was detected in Singapore. The increase in workload and new infection control procedures were thought to affect resuscitation and airway management. Our aim was to study the effects of wearing of personal protective equipment (PPE) and powered air-purifying respirator (PAPR) and the restriction in the number of resuscitation personnel on airway management during the SARS crisis. Data was collected prospectively through an ongoing emergency airway registry. The data was divided into three periods: (1) before PPE was instituted from 1 November 2002 to 31 March 2003; (2) during SARS (when PPE use was mandatory) from 1 April to 31 July 2003; (3) post-SARs (when PPE use was non-mandatory but encouraged) from 1 August to 31 March 2004. There was no change in patient demographics during the three periods. There were significant increases in the proportion of resuscitation cases and airway interventions during the SARS period compared to the pre-SARS period. The resident medical officer intubation rate decreased from 45.1% pre-SARS to 35.2% during SARS and 17.7% post-SARS. The complication rates were 10.5%, 9.9% and 9.4% in periods 1-3, respectively. Restriction in the number of healthcare staff attending to each patient may have influenced the department's decision to allow only the most confident or experienced personnel to manage the airway. The exposure of junior medical officers in emergency airway management during SARS and the immediate post-SARS period was decreased. This trend should be monitored further and intervention may be necessary should it continue to decline.

Synthetic aperture design for increased SAR image rate

Science.gov (United States)

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

2009-03-03

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

The Danish polarimetric SAR for remote sensing applications

DEFF Research Database (Denmark)

Christensen, Erik Lintz; Madsen, Søren Nørvang; Dall, Jørgen

1994-01-01

Presents the Danish polarimetric SAR system, EMISAR, and the approach taken in the system design to achieve a reliable high performance system. The design and implementation of the antenna system as well as the analog and digital hardware are discussed. The SAR utilises a dual polarised microstri...

SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

Directory of Open Access Journals (Sweden)

A. Rezaeian

2015-12-01

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

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

Science.gov (United States)

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

2015-12-01

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

Excretion and detection of SARS coronavirus and its nucleic acid from digestive system

Science.gov (United States)

Wang, Xin-Wei; Li, Jin-Song; Guo, Ting-Kai; Zhen, Bei; Kong, Qing-Xin; Yi, Bin; Li, Zhong; Song, Nong; Jin, Min; Wu, Xiao-Ming; Xiao, Wen-Jun; Zhu, Xiu-Mei; Gu, Chang-Qing; Yin, Jing; Wei, Wei; Yao, Wei; Liu, Chao; Li, Jian-Feng; Ou, Guo-Rong; Wang, Min-Nian; Fang, Tong-Yu; Wang, Gui-Jie; Qiu, Yao-Hui; Wu, Huai-Huan; Chao, Fu-Huan; Li, Jun-Wen

2005-01-01

AIM: To study whether severe acute respiratory syndrome coronavirus (SARS-CoV) could be excreted from digestive system. METHODS: Cell culture and semi-nested RT-PCR were used to detect SARS-CoV and its RNA from 21 stool and urine samples, and a kind of electropositive filter media particles was used to concentrate the virus in 10 sewage samples from two hospitals receiving SARS patients in Beijing in China. RESULTS: It was demonstrated that there was no live SARS-CoV in all samples collected, but the RNA of SARS-CoV could be detected in seven stool samples from SARS patients with any one of the symptoms of fever, malaise, cough, or dyspnea, in 10 sewage samples before disinfection and 3 samples after disinfection from the two hospitals. The RNA could not be detected in urine and stool samples from patients recovered from SARS. CONCLUSION: Nucleic acid of SARS-CoV can be excreted through the stool of patients into sewage system, and the possibility of SARS-CoV transmitting through digestive system cannot be excluded. PMID:16038039

Mapping Tropical Rainforest Canopy Disturbances in 3D by COSMO-SkyMed Spotlight InSAR-Stereo Data to Detect Areas of Forest Degradation

Directory of Open Access Journals (Sweden)

Manuela Hirschmugl

2013-02-01

Full Text Available Assessment of forest degradation has been emphasized as an important issue for emission calculations, but remote sensing based detecting of forest degradation is still in an early phase of development. The use of optical imagery for degradation assessment in the tropics is limited due to frequent cloud cover. Recent studies based on radar data often focus on classification approaches of 2D backscatter. In this study, we describe a method to detect areas affected by forest degradation from digital surface models derived from COSMO-SkyMed X-band Spotlight InSAR-Stereo Data. Two test sites with recent logging activities were chosen in Cameroon and in the Republic of Congo. Using the full resolution COSMO-SkyMed digital surface model and a 90-m resolution Shuttle Radar Topography Mission model or a mean filtered digital surface model we calculate difference models to detect canopy disturbances. The extracted disturbance gaps are aggregated to potential degradation areas and then evaluated with respect to reference areas extracted from RapidEye and Quickbird optical imagery. Results show overall accuracies above 75% for assessing degradation areas with the presented methods.

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China

Directory of Open Access Journals (Sweden)

Chunxiang Cao

2016-01-01

Full Text Available Severe acute respiratory syndrome (SARS is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

Assessment of motor imagery ability and training

Directory of Open Access Journals (Sweden)

André Luiz Felix Rodacki

2010-09-01

Full Text Available The aim of this study was to evaluate changes in motor imagery ability in response to a specific dart throwing training. Twelve subjects (17-22 years with no previous experience in dart throwing or imagery agreed to participate. Changes in imagery ability were assessed using the Sports Imagery Questionnaire before (pretreatment and after (post-treatment an imagery training program consisting of 10 sessions. Retention (RET was assessed 2 weeks after training. The program included mental exercises designed to develop vivid images, to control one’s own images, and to increase perception about performance. Comparison of the imagery training conditions (training alone, training accompanied, observing a colleague, and during assessment showed no differences between the pretreatment, post-treatment and RET evaluations. Although imagery ability did not respond to training, significant differences between imagery domains (visual, auditory, kinesthetic, and animic were found (p<0.05, except between the visual and animic domains (p=0.58. These differences might be related to subject’s domain preference subject during the imagery process and to the nature of the task in which the skill technique used seems to be a relevant aspect.

Kinesthetic motor imagery modulates body sway.

Science.gov (United States)

Rodrigues, E C; Lemos, T; Gouvea, B; Volchan, E; Imbiriba, L A; Vargas, C D

2010-08-25

The aim of this study was to investigate the effect of imagining an action implicating the body axis in the kinesthetic and visual motor imagery modalities upon the balance control system. Body sway analysis (measurement of center of pressure, CoP) together with electromyography (EMG) recording and verbal evaluation of imagery abilities were obtained from subjects during four tasks, performed in the upright position: to execute bilateral plantar flexions; to imagine themselves executing bilateral plantar flexions (kinesthetic modality); to imagine someone else executing the same movement (visual modality), and to imagine themselves singing a song (as a control imagery task). Body sway analysis revealed that kinesthetic imagery leads to a general increase in CoP oscillation, as reflected by an enhanced area of displacement. This effect was also verified for the CoP standard deviation in the medial-lateral direction. An increase in the trembling displacement (equivalent to center of pressure minus center of gravity) restricted to the anterior-posterior direction was also observed to occur during kinesthetic imagery. The visual imagery task did not differ from the control (sing) task for any of the analyzed parameters. No difference in the subjects' ability to perform the imagery tasks was found. No modulation of EMG data were observed across imagery tasks, indicating that there was no actual execution during motor imagination. These results suggest that motor imagery performed in the kinesthetic modality evokes motor representations involved in balance control. Copyright (c)10 IBRO. Published by Elsevier Ltd. All rights reserved.

Chinese HJ-1C SAR And Its Wind Mapping Capability

Science.gov (United States)

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

2010-04-01

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

ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

Directory of Open Access Journals (Sweden)

J. W. Zhao

2016-06-01

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

Visuospatial imagery and working memory in schizophrenia.

Science.gov (United States)

Matthews, Natasha L; Collins, Kathleen P; Thakkar, Katharine N; Park, Sohee

2014-01-01

The ability to form mental images that reconstruct former perceptual experiences is closely related to working memory (WM) ability. However, whereas WM deficits are established as a core feature of schizophrenia, an independent body of work suggests that mental imagery ability is enhanced in the disorder. Across two experiments we investigated mental imagery in schizophrenia and its relationship with WM. In Experiment 1, individuals with schizophrenia (SZ: n=15) and matched controls (CO: n=14) completed a mental imagery generation and inspection task and a spatial delayed-response WM task. In Experiment 2, SZ (n=16) and CO (n=16) completed a novel version of the mental imagery task modified to increase WM maintenance demand. In Experiment 1, SZ demonstrated enhanced mental imagery performance, as evidenced by faster response times relative to CO, with preserved accuracy. However, enhanced mental imagery in SZ was accompanied by impaired WM as assessed by the delayed-response task. In Experiment 2, when WM maintenance load was increased, SZ no longer showed superior imagery performance. We found evidence for enhanced imagery manipulation in SZ despite their WM maintenance deficit. However, this imagery enhancement was abolished when WM maintenance demands were increased. This profile of enhanced imagery manipulation but impaired maintenance could be used to implement novel remediation strategies in the disorder.

Early appearance of SARS on chest CT scan

International Nuclear Information System (INIS)

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

2003-01-01

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

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.

Segment-based change detection for polarimetric SAR data

DEFF Research Database (Denmark)

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

2006-01-01

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

Crop Classification Using Short-Revisit Multitemporal SAR Data

DEFF Research Database (Denmark)

Skriver, Henning; Mattia, Francesco; Satalino, Giuseppe

2011-01-01

Classification of crops and other land cover types is an important application of both optical/infrared and SAR satellite data. It is already an import application of present satellite systems, as it will be for planned missions, such as the Sentinels. An airborne SAR data set with a short revisi...

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

Science data collection with polarimetric SAR

DEFF Research Database (Denmark)

Dall, Jørgen; Woelders, Kim; Madsen, Søren Nørvang

1996-01-01

Discusses examples on the use of polarimetric SAR in a number of Earth science studies. The studies are presently being conducted by the Danish Center for Remote Sensing. A few studies of the European Space Agency's EMAC programme are also discussed. The Earth science objectives are presented......, and the potential of polarimetric SAR is discussed and illustrated with data collected by the Danish airborne EMISAR system during a number of experiments in 1994 and 1995. The presentation will include samples of data acquired for the different studies...

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

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Lei Zhang

2018-03-01

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

Detecting and monitoring UCG subsidence with InSAR

Energy Technology Data Exchange (ETDEWEB)

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

2012-03-23

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

Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR, optical satellite imagery, and Lidar data

Science.gov (United States)

Jahncke, Raymond; Leblon, Brigitte; Bush, Peter; LaRocque, Armand

2018-06-01

Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multi-date and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands

Kinesthetic Imagery Provides Additive Benefits to Internal Visual Imagery on Slalom Task Performance.

Science.gov (United States)

Callow, Nichola; Jiang, Dan; Roberts, Ross; Edwards, Martin G

2017-02-01

Recent brain imaging research demonstrates that the use of internal visual imagery (IVI) or kinesthetic imagery (KIN) activates common and distinct brain areas. In this paper, we argue that combining the imagery modalities (IVI and KIN) will lead to a greater cognitive representation (with more brain areas activated), and this will cause a greater slalom-based motor performance compared with using IVI alone. To examine this assertion, we randomly allocated 56 participants to one of the three groups: IVI, IVI and KIN, or a math control group. Participants performed a slalom-based driving task in a driving simulator, with average lap time used as a measure of performance. Results revealed that the IVI and KIN group achieved significantly quicker lap times than the IVI and the control groups. The discussion includes a theoretical advancement on why the combination of imagery modalities might facilitate performance, with links made to the cognitive neuroscience literature and applied practice.

Performance Analysis for Airborne Interferometric SAR Affected by Flexible Baseline Oscillation

Directory of Open Access Journals (Sweden)

Liu Zhong-sheng

2014-04-01

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

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

Genomic Characterization of Two Novel SAR11 Isolates From the Red Sea, Including the First Strain of the SAR11 Ib clade

KAUST Repository

Jimenez Infante, Francy M.

2017-06-22

The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea, one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain-specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter.

Genomic Characterization of Two Novel SAR11 Isolates From the Red Sea, Including the First Strain of the SAR11 Ib clade

KAUST Repository

Jimenez Infante, Francy M.; Ngugi, David; Vinu, Manikandan; Blom, Jochen; Alam, Intikhab; Bajic, Vladimir B.; Stingl, Ulrich

2017-01-01

The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea, one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain-specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter.

NAIP 2017 Imagery Feedback Map

Data.gov (United States)

Farm Service Agency, Department of Agriculture — The NAIP 2017 Imagery Feedback map allows users to make comments and observations about the quality of the 2017 National Agriculture Imagery Program (NAIP)...

NAIP 2015 Imagery Feedback Map

Data.gov (United States)

Farm Service Agency, Department of Agriculture — The NAIP 2015 Imagery Feedback map allows users to make comments and observations about the quality of the 2015 National Agriculture Imagery Program (NAIP)...

SAR compliance assessment of PMR 446 and FRS walkie-talkies.

Science.gov (United States)

Vermeeren, Günter; Joseph, Wout; Martens, Luc

2015-10-01

The vast amount of studies on radiofrequency dosimetry deal with exposure due to mobile devices and base station antennas for cellular communication systems. This study investigates compliance of walkie-talkies to exposure guidelines established by the International Commission on Non-Ionizing Radiation Protection and the Federal Communications Committee. The generic walkie-talkie consisted of a helical antenna and a ground plane and was derived by reverse engineering of a commercial walkie-talkie. Measured and simulated values of antenna characteristics and electromagnetic near fields of the generic walkie-talkie were within 2% and 8%, respectively. We also validated normalized electromagnetic near fields of the generic walkie-talkie against a commercial device and observed a very good agreement (deviation based on magnetic near field. Finally, we found that SAR of commercial devices is within current SAR limits for general public exposure for a worst-case duty cycle of 100%, that is, about 3 times and 6 times lower than the limit on the 1 g SAR (1.6 W/kg) and 10 g SAR (2 W/kg), respectively. But, an effective radiated power as specified by the Private Mobile Radio at 446 MHz (PMR 446) radio standard can cause localized SAR exceeding SAR limits for 1 g of tissue. © 2015 Wiley Periodicals, Inc.

RADARSAT SAR data assessment of oil lakes in the Greater Burgan Oil Field, Kuwait

International Nuclear Information System (INIS)

Kwarteng, A. Y.; Al-Ajmi, D.; Singhroy, V.; Saint-Jean, R.

1997-01-01

RADARSAT images recorded in different beam modes were processed and used to assess the oil lakes in the Burgan oil field in Kuwait created by the fire setting of oil wells by the retreating Iraqi forces in the 1990-1991 Gulf War. The images were geometrically registered to each other and used as input to a change detection program. The main interest was to map and differentiate between the oil lakes, tarmats, vegetation, buried oil lakes, and also to evaluate the usefulness of RADARSAT's beam modes in characterizing such features. Results of the RADARSAT imagery analysis were compared to similar studies using optical and SIR-C/X-SAR data. Initially, there have approximately 300 oil lakes covering an area of about 49 sq km. Twenty-one million barrels of oil were recovered and exported; about one million barrels of unrecoverable oil was left in the oil fields. Since then most of the oil has evaporated, dried up to form tarmats, or has been covered by a veneer of sand and is no longer visible on the surface

Estimating soil moisture using the Danish polarimetric SAR

DEFF Research Database (Denmark)

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

1995-01-01

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

AgSat Imagery Collection Footprints

Data.gov (United States)

Farm Service Agency, Department of Agriculture — The AgSat Imagery Collection Footprints map shows the imagery footprints which have been collected under the USDA satellite blanket purchase agreement. Click on a...

OrthoImagery Submission for Isabella county, MI

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — This data set contains 1-meter resolution imagery derived from the 2005 National Agriculture Imagery Program (NAIP) statewide aerial imagery acquisition. Data have...

SAR11 bacteria linked to ocean anoxia and nitrogen loss

DEFF Research Database (Denmark)

Tsementzi, Despina; Wu, Jieying; Deutsch, Samuel

2016-01-01

Bacteria of the SAR11 clade constitute up to one half of all microbial cells in the oxygen-rich surface ocean. SAR11 bacteria are also abundant in oxygen minimum zones (OMZs), where oxygen falls below detection and anaerobic microbes have vital roles in converting bioavailable nitrogen to N2 gas...... activity. These results link SAR11 to pathways of ocean nitrogen loss, redefining the ecological niche of Earth’s most abundant organismal group....

Unconscious Imagination and the Mental Imagery Debate

Directory of Open Access Journals (Sweden)

Berit Brogaard

2017-05-01

Full Text Available Traditionally, philosophers have appealed to the phenomenological similarity between visual experience and visual imagery to support the hypothesis that there is significant overlap between the perceptual and imaginative domains. The current evidence, however, is inconclusive: while evidence from transcranial brain stimulation seems to support this conclusion, neurophysiological evidence from brain lesion studies (e.g., from patients with brain lesions resulting in a loss of mental imagery but not a corresponding loss of perception and vice versa indicates that there are functional and anatomical dissociations between mental imagery and perception. Assuming that the mental imagery and perception do not overlap, at least, to the extent traditionally assumed, then the question arises as to what exactly mental imagery is and whether it parallels perception by proceeding via several functionally distinct mechanisms. In this review, we argue that even though there may not be a shared mechanism underlying vision for perception and conscious imagery, there is an overlap between the mechanisms underlying vision for action and unconscious visual imagery. On the basis of these findings, we propose a modification of Kosslyn’s model of imagery that accommodates unconscious imagination and explore possible explanations of the quasi-pictorial phenomenology of conscious visual imagery in light of the fact that its underlying neural substrates and mechanisms typically are distinct from those of visual experience.

Backscatter Analysis Using Multi-Temporal SENTINEL-1 SAR Data for Crop Growth of Maize in Konya Basin, Turkey

Science.gov (United States)

Abdikan, S.; Sekertekin, A.; Ustunern, M.; Balik Sanli, F.; Nasirzadehdizaji, R.

2018-04-01

Temporal monitoring of crop types is essential for the sustainable management of agricultural activities on both national and global levels. As a practical and efficient tool, remote sensing is widely used in such applications. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to investigate the performance of the sensor backscatter image on crop monitoring. Multi-temporal C-band VV and VH polarized SAR images were acquired simultaneously by in-situ measurements which was conducted at Konya basin, central Anatolia Turkey. During the measurements, plant height of maize plant was collected and relationship between backscatter values and plant height was analysed. The maize growth development was described under Biologische Bundesanstalt, bundessortenamt und CHemische industrie (BBCH). Under BBCH stages, the test site was classified as leaf development, stem elongation, heading and flowering in general. The correlation coefficient values indicated high correlation for both polarimetry during the early stages of the plant, while late stages indicated lower values in both polarimetry. As a last step, multi-temporal coverage of crop fields was analysed to map seasonal land use. To this aim, object based image classification was applied following image segmentation. About 80 % accuracies of land use maps were created in this experiment. As preliminary results, it is concluded that Sentinel-1 data provides beneficial information about plant growth. Dual-polarized Sentinel-1 data has high potential for multi-temporal analyses for agriculture monitoring and reliable mapping.

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

Directory of Open Access Journals (Sweden)

Zhen Xu

2018-03-01

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

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.

Pulse-based internal calibration of polarimetric SAR

DEFF Research Database (Denmark)

Dall, Jørgen; Skou, Niels; Christensen, Erik Lintz

1994-01-01

Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops and devel......Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops...

Multi-look polarimetric SAR image filtering using simulated annealing

DEFF Research Database (Denmark)

Schou, Jesper

2000-01-01

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

The integration of Human Factors (HF) in the SAR process training course text

International Nuclear Information System (INIS)

Ryan, T.G.

1995-03-01

This text provides the technical basis for a two-day course on human factors (HF), as applied to the Safety Analysis Report (SAR) process. The overall objective of this text and course is to: provide the participant with a working knowledge of human factors-related requirements, suggestions for doing a human safety analysis applying a graded approach, and an ability to demonstrate using the results of the human safety analysis, that human factors elements as defined by DOE (human factors engineering, procedures, training, oversight, staffing, qualifications), can support wherever necessary, nuclear safety commitments in the SAR. More specifically, the objectives of the text and course are: (1) To provide the SAR preparer with general guidelines for doing HE within the context of a graded approach for the SAR; (2) To sensitize DOE facility managers and staff, safety analysts and SAR preparers, independent reviewers, and DOE reviewers and regulators, to DOE Order 5480.23 requirements for HE in the SAR; (3) To provide managers, analysts, reviewers and regulators with a working knowledge of HE concepts and techniques within the context of a graded approach for the SAR, and (4) To provide SAR managers and DOE reviewers and regulators with general guidelines for monitoring and coordinating the work of preparers of HE inputs throughout the SAR process, and for making decisions regarding the safety relevance of HE inputs to the SAR. As a ready reference for implementing the human factors requirements of DOE Order 5480.22 and DOE Standard 3009-94, this course text and accompanying two-day course are intended for all persons who are involved in the SAR

The integration of Human Factors (HF) in the SAR process training course text

Energy Technology Data Exchange (ETDEWEB)

Ryan, T.G.

1995-03-01

This text provides the technical basis for a two-day course on human factors (HF), as applied to the Safety Analysis Report (SAR) process. The overall objective of this text and course is to: provide the participant with a working knowledge of human factors-related requirements, suggestions for doing a human safety analysis applying a graded approach, and an ability to demonstrate using the results of the human safety analysis, that human factors elements as defined by DOE (human factors engineering, procedures, training, oversight, staffing, qualifications), can support wherever necessary, nuclear safety commitments in the SAR. More specifically, the objectives of the text and course are: (1) To provide the SAR preparer with general guidelines for doing HE within the context of a graded approach for the SAR; (2) To sensitize DOE facility managers and staff, safety analysts and SAR preparers, independent reviewers, and DOE reviewers and regulators, to DOE Order 5480.23 requirements for HE in the SAR; (3) To provide managers, analysts, reviewers and regulators with a working knowledge of HE concepts and techniques within the context of a graded approach for the SAR, and (4) To provide SAR managers and DOE reviewers and regulators with general guidelines for monitoring and coordinating the work of preparers of HE inputs throughout the SAR process, and for making decisions regarding the safety relevance of HE inputs to the SAR. As a ready reference for implementing the human factors requirements of DOE Order 5480.22 and DOE Standard 3009-94, this course text and accompanying two-day course are intended for all persons who are involved in the SAR.

Fusion method of SAR and optical images for urban object extraction

Science.gov (United States)

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

2007-11-01

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

SIMULATION OF SHIP GENERATED TURBULENT AND VORTICAL WAKE IMAGING BY SAR

Institute of Scientific and Technical Information of China (English)

Wang Aiming; Zhu Minhui

2004-01-01

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

Risk factors for chronic post-traumatic stress disorder (PTSD) in SARS survivors.

Science.gov (United States)

Mak, Ivan Wing Chit; Chu, Chung Ming; Pan, Pey Chyou; Yiu, Michael Gar Chung; Ho, Suzanne C; Chan, Veronica Lee

2010-01-01

Post-traumatic stress disorder (PTSD) is one of the most prevalent long-term psychiatric diagnoses among survivors of severe acute respiratory syndrome (SARS). The objective of this study was to identify the predictors of chronic PTSD in SARS survivors. PTSD at 30 months after the SARS outbreak was assessed by the Structured Clinical Interview for the DSM-IV. Survivors' demographic data, medical information and psychosocial variables were collected for risk factor analysis. Multivariate logistic regression analysis showed that female gender as well as the presence of chronic medical illnesses diagnosed before the onset of SARS and avascular necrosis were independent predictors of PTSD at 30 months post-SARS. Associated factors included higher-chance external locus of control, higher functional disability and higher average pain intensity. The study of PTSD at 30 months post-SARS showed that the predictive value of acute medical variables may fade out. Our findings do not support some prior hypotheses that the use of high dose corticosteroids is protective against the development of PTSD. On the contrary, the adversity both before and after the SARS outbreak may be more important in hindering recovery from PTSD. The risk factor analysis can not only improve the detection of hidden psychiatric complications but also provide insight for the possible model of care delivery for the SARS survivors. With the complex interaction of the biopsychosocial challenges of SARS, an integrated multidisciplinary clinic setting may be a superior approach in the long-term management of complicated PTSD cases. Copyright © 2010 Elsevier Inc. All rights reserved.

SAR Cross-Ambiguities in SAOCOM-CS Large Baseline Bistatic Configuration

OpenAIRE

Bordoni, Federica; Rodriguez-Cassola, Marc; Younis, Marwan; Prats-Iraola, Pau; Lopez-Dekker, Paco; Krieger, Gerhard

2016-01-01

The evaluation of the ambiguous signal level, the Ambiguity-to-Signal Ratio (ASR), plays a key role in the Synthetic Aperture Radar (SAR) design and performance prediction. In conventional SAR acquisition scenarios, the computation of the ASR is based on the evaluation of the range and azimuth ambiguous contributes. Though appealing for its simplicity, this approach could be inaccurate in case of complex SAR acquisition geometries. In this paper we focus on the ASR performance of the SAOCOM-...

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

NARCIS (Netherlands)

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

2003-01-01

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

Imagery encoding and false recognition errors: Examining the role of imagery process and imagery content on source misattributions.

Science.gov (United States)

Foley, Mary Ann; Foy, Jeffrey; Schlemmer, Emily; Belser-Ehrlich, Janna

2010-11-01

Imagery encoding effects on source-monitoring errors were explored using the Deese-Roediger-McDermott paradigm in two experiments. While viewing thematically related lists embedded in mixed picture/word presentations, participants were asked to generate images of objects or words (Experiment 1) or to simply name the items (Experiment 2). An encoding task intended to induce spontaneous images served as a control for the explicit imagery instruction conditions (Experiment 1). On the picture/word source-monitoring tests, participants were much more likely to report "seeing" a picture of an item presented as a word than the converse particularly when images were induced spontaneously. However, this picture misattribution error was reversed after generating images of words (Experiment 1) and was eliminated after simply labelling the items (Experiment 2). Thus source misattributions were sensitive to the processes giving rise to imagery experiences (spontaneous vs deliberate), the kinds of images generated (object vs word images), and the ways in which materials were presented (as pictures vs words).

Bats and SARS

Centers for Disease Control (CDC) Podcasts

2006-11-08

Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.  Created: 11/8/2006 by Emerging Infectious Diseases.   Date Released: 11/17/2006.

Mental Imagery in Depression: Phenomenology, Potential Mechanisms, and Treatment Implications.

Science.gov (United States)

Holmes, Emily A; Blackwell, Simon E; Burnett Heyes, Stephanie; Renner, Fritz; Raes, Filip

2016-01-01

Mental imagery is an experience like perception in the absence of a percept. It is a ubiquitous feature of human cognition, yet it has been relatively neglected in the etiology, maintenance, and treatment of depression. Imagery abnormalities in depression include an excess of intrusive negative mental imagery; impoverished positive imagery; bias for observer perspective imagery; and overgeneral memory, in which specific imagery is lacking. We consider the contribution of imagery dysfunctions to depressive psychopathology and implications for cognitive behavioral interventions. Treatment advances capitalizing on the representational format of imagery (as opposed to its content) are reviewed, including imagery rescripting, positive imagery generation, and memory specificity training. Consideration of mental imagery can contribute to clinical assessment and imagery-focused psychological therapeutic techniques and promote investigation of underlying mechanisms for treatment innovation. Research into mental imagery in depression is at an early stage. Work that bridges clinical psychology and neuroscience in the investigation of imagery-related mechanisms is recommended.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

Science.gov (United States)

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

2017-09-01

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

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

Directory of Open Access Journals (Sweden)

Zhiqiang Zhao

2018-06-01

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

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

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

Xu, Xin; Gui, Rong; Pu, Fangling

2018-01-01

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

Agency Video, Audio and Imagery Library

Science.gov (United States)

Grubbs, Rodney

2015-01-01

The purpose of this presentation was to inform the ISS International Partners of the new NASA Agency Video, Audio and Imagery Library (AVAIL) website. AVAIL is a new resource for the public to search for and download NASA-related imagery, and is not intended to replace the current process by which the International Partners receive their Space Station imagery products.

Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

Directory of Open Access Journals (Sweden)

Sang-Hoon Hong

2015-07-01

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

SAR11 Bacteria: The Most Abundant Plankton in the Oceans.

Science.gov (United States)

Giovannoni, Stephen J

2017-01-03

SAR11 is a group of small, carbon-oxidizing bacteria that reach a global estimated population size of 2.4×10 28 cells-approximately 25% of all plankton. They are found throughout the oceans but reach their largest numbers in stratified, oligotrophic gyres, which are an expanding habitat in the warming oceans. SAR11 likely had a Precambrian origin and, over geological time, evolved into the niche of harvesting labile, low-molecular-weight dissolved organic matter (DOM). SAR11 cells are minimal in size and complexity, a phenomenon known as streamlining that is thought to benefit them by lowering the material costs of replication and maximizing transport functions that are essential to competition at ultralow nutrient concentrations. One of the surprises in SAR11 metabolism is their ability to both oxidize and produce a variety of volatile organic compounds that can diffuse into the atmosphere. SAR11 cells divide slowly and lack many forms of regulation commonly used by bacterial cells to adjust to changing environmental conditions. As a result of genome reduction, they require an unusual range of nutrients, which leads to complex biochemical interactions with other plankton. The study of SAR11 is providing insight into the biogeochemistry of labile DOM and is affecting microbiology beyond marine science by providing a model for understanding the evolution and function of streamlined cells.

Motion/imagery secure cloud enterprise architecture analysis

Science.gov (United States)

DeLay, John L.

2012-06-01

Cloud computing with storage virtualization and new service-oriented architectures brings a new perspective to the aspect of a distributed motion imagery and persistent surveillance enterprise. Our existing research is focused mainly on content management, distributed analytics, WAN distributed cloud networking performance issues of cloud based technologies. The potential of leveraging cloud based technologies for hosting motion imagery, imagery and analytics workflows for DOD and security applications is relatively unexplored. This paper will examine technologies for managing, storing, processing and disseminating motion imagery and imagery within a distributed network environment. Finally, we propose areas for future research in the area of distributed cloud content management enterprises.

Multi-temporal and Dual-polarization Interferometric SAR for Land Cover Type Classification

Directory of Open Access Journals (Sweden)

WANG Xinshuang

2015-05-01

Full Text Available In order to study SAR land cover classification method, this paper uses the multi-dimensional combination of temporal,polarization and InSAR data. The area covered by space borne data of ALOS PALSAR in Xunke County,Heilongjiang Province was chosen as test site. A land cover classification technique of SVM based on multi-temporal, multi-polarization and InSAR data had been proposed, using the sensitivity to land cover type of multi-temporal, multi-polarization SAR data and InSAR measurements, and combing time series characteristic of backscatter coefficient and correlation coefficient to identify ground objects. The results showed the problem of confusion between forest land and urban construction land can be nicely solved, using the correlation coefficient between HH and HV, and also combing the selected temporal, polarization and InSAR characteristics. The land cover classification result with higher accuracy is gotten using the classification algorithm proposed in this paper.

New free Danish online (Q)SAR predictions database with >600,000 substances

DEFF Research Database (Denmark)

Wedebye, Eva Bay; Dybdahl, Marianne; Reffstrup, Trine Klein

Since 2005 the Danish (Q)SAR Database has been freely available on the Internet. It is a tool that allows single chemical substance profiling and screenings based on predicted hazard information. The database is also included in the OECD (Q)SAR Application Toolbox which is used worldwide...... by regulators and industry. A lot of progress in (Q)SAR model development, application and documentation has been made since the publication in 2005. A new and completely rebuild online (Q)SAR predictions database was therefore published in November 2015 at http://qsar.food.dtu.dk. The number of chemicals...... in the database has been expanded from 185,000 to >600,000. As far as possible all organic single constituent substances that were pre-registered under REACH have been included in the new structure set. The new Danish (Q)SAR Database includes estimates from more than 200 (Q)SARs covering a wide range of hazardous...

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

Science.gov (United States)

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

2017-12-01

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

Comparing satellite SAR and wind farm wake models

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Vincent, P.; Husson, R.

2015-01-01

. These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting...... (WRF) model in high resolution and WRF with coupled microscale parametrization....

Genomic characterization of two novel SAR11 isolates from the Red Sea, including the first strain of the SAR11 Ib clade.

Science.gov (United States)

Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Blom, Jochen; Alam, Intikhab; Bajic, Vladimir B; Stingl, Ulrich

2017-07-01

The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea: one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

TOWARDS CHANGE DETECTION IN URBAN AREA BY SAR INTERFEROMETRY AND RADARGRAMMETRY

Directory of Open Access Journals (Sweden)

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.

Imagery mismatch negativity in musicians.

Science.gov (United States)

Herholz, Sibylle C; Lappe, Claudia; Knief, Arne; Pantev, Christo

2009-07-01

The present study investigated musical imagery in musicians and nonmusicians by means of magnetoencephalography (MEG). We used a new paradigm in which subjects had to continue familiar melodies in their mind and then judged if a further presented tone was a correct continuation of the melody. Incorrect tones elicited an imagery mismatch negativity (iMMN) in musicians but not in nonmusicians. This finding suggests that the MMN component can be based on an imagined instead of a sensory memory trace and that imagery of music is modulated by musical expertise.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Vegetation Parameter Extraction Using Dual Baseline Polarimetric SAR Interferometry Data

Science.gov (United States)

Zhang, H.; Wang, C.; Chen, X.; Tang, Y.

2009-04-01

For vegetation parameter inversion, the single baseline polarimetric SAR interferometry (POLinSAR) technique, such as the three-stage method and the ESPRIT algorithm, is limited by the observed data with the minimum ground to volume amplitude ration, which effects the estimation of the effective phase center for the vegetation canopy or the surface, and thus results in the underestimated vegetation height. In order to remove this effect of the single baseline inversion techniques in some extend, another baseline POLinSAR data is added on vegetation parameter estimation in this paper, and a dual baseline POLinSAR technique for the extraction of the vegetation parameter is investigated and improved to reduce the dynamic bias for the vegetation parameter estimation. Finally, the simulated data and real data are used to validate this dual baseline technique.

Sensory Substitution and Multimodal Mental Imagery.

Science.gov (United States)

Nanay, Bence

2017-09-01

Many philosophers use findings about sensory substitution devices in the grand debate about how we should individuate the senses. The big question is this: Is "vision" assisted by (tactile) sensory substitution really vision? Or is it tactile perception? Or some sui generis novel form of perception? My claim is that sensory substitution assisted "vision" is neither vision nor tactile perception, because it is not perception at all. It is mental imagery: visual mental imagery triggered by tactile sensory stimulation. But it is a special form of mental imagery that is triggered by corresponding sensory stimulation in a different sense modality, which I call "multimodal mental imagery."

Offshore winds from a new generation of European satellites

DEFF Research Database (Denmark)

Badger, Merete; Karagali, Ioanna; Ahsbahs, Tobias Torben

at sea. All are important for the planning, operation, and maintenance of offshore wind farms. Typical shortcomings of SAR-based wind fields include a low sampling frequency and a need for advanced data processing in order to retrieve the wind speed at 10 m above sea level. A new generation of European...... satellites and services could lower these barriers for applications in wind energy significantly. The Sentinel-1 A/B missions by the European Space Agency (ESA) deliver C-band SAR observations at an unprecedented coverage and spatial resolution. Over the seas of Europe, approximately 200 new acquisitions...... of Europe over time. The accuracy of this new product is currently under investigation. TerraSAR-X is an X-band SAR mission by the German Aerospace Center (DLR). It offers very high-resolution imagery, which may be used for detailed studies of e.g. wind farm wakes. TerraSAR-X imagery is acquired on...

An Assessment of Alternative Synthetic Aperture Radar Display Formats: Orientation and Situational Awareness

National Research Council Canada - National Science Library

Kuperman, Gilbert

1998-01-01

...) display of SAR overlaid on corresponding DTM data. Eight imagery analysts (IAs), assigned to the Israeli Ground Corps Command Imagery Analysis Unit and to the Israel Air Force, and two weapon system officers (WSOs...

Exploring cloud and big data components for SAR archiving and analysis

Science.gov (United States)

Baker, S.; Crosby, C. J.; Meertens, C.; Phillips, D.

2017-12-01

Under the Geodesy Advancing Geoscience and EarthScope (GAGE) NSF Cooperative Agreement, UNAVCO has seen the volume of the SAR Data Archive grow at a substantial rate, from 2 TB in Y1 and 5 TB in Y2 to 41 TB in Y3 primarily due to WInSAR PI proposal management of ALOS-­2/JAXA (Japan Aerospace Exploration Agency) data and to a lesser extent Supersites and other data collections. JAXA provides a fixed number of scenes per year for each PI, and some data files are 50­-60GB each, which accounts for the large volume of data. In total, over 100TB of SAR data are in the WInSAR/UNAVCO archive and a large portion of these are available unrestricted for WInSAR members. In addition to the existing data, newer data streams from the Sentinel-1 and NISAR missions will require efficient processing pipelines and easily scalable infrastructure to handle processed results. With these growing data sizes and space concerns, the SAR archive operations migrated to the Texas Advanced Computing Center (TACC) via an NSF XSEDE proposal in spring 2017. Data are stored on an HPC system while data operations are running on Jetstream virtual machines within the same datacenter. In addition to the production data operations, testing was done in early 2017 with container based InSAR processing analysis using JupyterHub and Docker images deployed on a VM cluster on Jetstream. The JupyterHub environment is well suited for short courses and other training opportunities for the community such as labs for university courses on InSAR. UNAVCO is also exploring new processing methodologies using DC/OS (the datacenter operating system) for batch and stream processing workflows and time series analysis with Big Data open source components like the Spark, Mesos, Akka, Cassandra, Kafka (SMACK) stack. The comparison of the different methodologies will provide insight into the pros and cons for each and help the SAR community with decisions about infrastructure and software requirements to meet their research

Calibration of SAR probes in waveguide at 900 MHz

International Nuclear Information System (INIS)

Jokela, K.; Puranen, L.; Hyysalo, P.

1998-01-01

The radiation safety tests for hand-held mobile phones require precise calibration of the small electric field probes used for the measurement of SAR in phantoms simulating the human body. In this study a calibration based on a rectangular waveguide was developed for SAR calibrations at 900 MHz

Project PHARUS: Towards a polarimetric C-band airborne SAR

NARCIS (Netherlands)

Hoogeboom, P.; Koomen, P.J.; Otten, M.P.G.; Pouwels, H.; Snoeij, P.

1989-01-01

A few years ago three institutes in the Netherlands developed a plan to design and build a polarimetric C-band aircraft SAR system of a novel design, called PHARUS (PHased Array Universal SAR), meant as a replacement for our current digital SLAR system. These institutes are the Physics and

A question of intention in motor imagery.

Science.gov (United States)

Gabbard, Carl; Cordova, Alberto; Lee, Sunghan

2009-03-01

We examined the question-is the intention of completing a simulated motor action the same as the intention used in processing overt actions? Participants used motor imagery to estimate distance reachability in two conditions: Imagery-Only (IO) and Imagery-Execution (IE). With IO (red target) only a verbal estimate using imagery was given. With IE (green target) participants knew that they would actually reach after giving a verbal estimate and be judged on accuracy. After measuring actual maximum reach, used for the comparison, imagery targets were randomly presented across peripersonal- (within reach) and extrapersonal (beyond reach) space. Results indicated no difference in overall accuracy by condition, however, there was a significant distinction by space; participants were more accurate in peripersonal space. Although more research is needed, these findings support an increasing body of evidence suggesting that the neurocognitive processes (in this case, intention) driving motor imagery and overt actions are similar.

Immune responses against SARS-coronavirus nucleocapsid protein induced by DNA vaccine

International Nuclear Information System (INIS)

Zhao Ping; Cao Jie; Zhao Lanjuan; Qin Zhaolin; Ke Jinshan; Pan Wei; Ren Hao; Yu Jianguo; Qi Zhongtian

2005-01-01

The nucleocapsid (N) protein of SARS-coronavirus (SARS-CoV) is the key protein for the formation of the helical nucleocapsid during virion assembly. This protein is believed to be more conserved than other proteins of the virus, such as spike and membrane glycoprotein. In this study, the N protein of SARS-CoV was expressed in Escherichia coli DH5α and identified with pooled sera from patients in the convalescence phase of SARS. A plasmid pCI-N, encoding the full-length N gene of SARS-CoV, was constructed. Expression of the N protein was observed in COS1 cells following transfection with pCI-N. The immune responses induced by intramuscular immunization with pCI-N were evaluated in a murine model. Serum anti-N immunoglobulins and splenocytes proliferative responses against N protein were observed in immunized BALB/c mice. The major immunoglobulin G subclass recognizing N protein was immunoglobulin G2a, and stimulated splenocytes secreted high levels of gamma interferon and IL-2 in response to N protein. More importantly, the immunized mice produced strong delayed-type hypersensitivity (DTH) and CD8 + CTL responses to N protein. The study shows that N protein of SARS-CoV not only is an important B cell immunogen, but also can elicit broad-based cellular immune responses. The results indicate that the N protein may be of potential value in vaccine development for specific prophylaxis and treatment against SARS

The Sport Imagery Questionnaire for Children (SIQ-C)

Science.gov (United States)

Hall, C. R.; Munroe-Chandler, K. J.; Fishburne, G. J.; Hall, N. D.

2009-01-01

Athletes of all ages report using imagery extensively to enhance their sport performance. The Sport Imagery Questionnaire (Hall, Mack, Paivio, & Hausenblas, 1998) was developed to assess cognitive and motivational imagery used by adult athletes. No such instrument currently exists to measure the use of imagery by young athletes. The aim of the…

From genome to antivirals: SARS as a test tube.

Science.gov (United States)

Kliger, Yossef; Levanon, Erez Y; Gerber, Doron

2005-03-01

The severe acute respiratory syndrome (SARS) epidemic brought into the spotlight the need for rapid development of effective anti-viral drugs against newly emerging viruses. Researchers have leveraged the 20-year battle against AIDS into a variety of possible treatments for SARS. Most prominently, based solely on viral genome information, silencers of viral genes, viral-enzyme blockers and viral-entry inhibitors were suggested as potential therapeutic agents for SARS. In particular, inhibitors of viral entry, comprising therapeutic peptides, were based on the recently launched anti-HIV drug enfuvirtide. This could represent one of the most direct routes from genome sequencing to the discovery of antiviral drugs.

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

Science.gov (United States)

Wang, Yan; Du, Lan; Dai, Hui

2018-01-01

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

Investigation of the Capability of Compact Polarimetric SAR Interferometry to Estimate Forest Height

Science.gov (United States)

Zhang, Hong; Xie, Lei; Wang, Chao; Chen, Jiehong

2013-08-01

The main objective of this paper is to investigate the capability of compact Polarimetric SAR Interferometry (C-PolInSAR) on forest height estimation. For this, the pseudo fully polarimetric interferomteric (F-PolInSAR) covariance matrix is firstly reconstructed, then the three- stage inversion algorithm, hybrid algorithm, Music and Capon algorithm are applied to both C-PolInSAR covariance matrix and pseudo F-PolInSAR covariance matrix. The availability of forest height estimation is demonstrated using L-band data generated by simulator PolSARProSim and X-band airborne data acquired by East China Research Institute of Electronic Engineering, China Electronics Technology Group Corporation.

Information theoretic bounds for compressed sensing in SAR imaging

International Nuclear Information System (INIS)

Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

2014-01-01

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

Pixel Classification of SAR ice images using ANFIS-PSO Classifier

Directory of Open Access Journals (Sweden)

G. Vasumathi

2016-12-01

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

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

Directory of Open Access Journals (Sweden)

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.

Latitudinal dynamics of SAR-arcs relative to the local time

International Nuclear Information System (INIS)

Alekseev, V.N.; Ievenko, I.B.

1991-01-01

In November-December, 1988, January-April, 1989-1990, at the Maymaga station in Yakutia according to spectrophotometric data 47 events of the occurrence of red stable middle-latitudinal arcs (SAR-arcs) were recorded. On the basis of these data the latitudinal dynamics of SAR-arcs was studied depending on the local time and geomagnetic disturbance level. The uniform equatorial shift of SAR arcs in the night time is noticed, and a sharp increase of the speed of this motion can be caused by the nonstationary character of the magnetospheric activity

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

Science.gov (United States)

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

1991-01-01

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

Wind mapping offshore in coastal Mediterranean area using SAR images

DEFF Research Database (Denmark)

Calaudi, Rosamaria; Arena, Felice; Badger, Merete

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

LTE modem power consumption, SAR and RF signal strength emulation

DEFF Research Database (Denmark)

Musiige, Deogratius; Vincent, Laulagnet; Anton, François

2012-01-01

This paper presents a new methodology for emulating the LTE modem power consumption, emitted SAR and RF signal strength when transmitting an LTE signal. The inputs of the methodology are: modem logical/protocol commands, time advance, near-field specifier, and antenna characteristics. The power...... emulation model(s) are computed by a two layer 451 neural network based on physical power measurements. SAR is emulated by polynomial interpolation models based on FDTD simulations. The accuracies of the mathematical function approximations for the emulation models of power and SAR are 5.19% and 3...

Blood donors--Serious adverse reactions (SAR) 2010-2014 EFS Châteauroux, France.

Science.gov (United States)

Riga, A; Sapey, T; Bacanu, M; Py, J-Y; Dehaut, F

2015-06-01

In 2013, the national French incidence of serious adverse reactions (SAR) was 155.7 per 100,000 donations and 82% of SAR were grade 2 (French classification of SAR related to blood donors) The purpose of our study was to describe the profile of blood donator candidate which had a SAR in our center. The study contains all the SAR superior to grade 1 occurred on the site EFS Châteauroux (site and mobile blood collection) from January 2010 to October 31, 2014. We analyzed 37 parameters from the e-fit files (e-site French blood vigilance) and In-log software. We identified 82 SAR for 72,553 blood donations (incidence: 113.02 SAR per 100,000 donations). Forty-one men and 41 women, middle age 39 years (18-66). Average height: 1.68 m (1.49-1.85); average weight: 68 kg (50-98); body mass index (kg/m(2)): 24,13(18.6-31.9). All donors were Caucasian and 30% unemployed. We found 74 vasovagal syncope (VVS), 5 hematomas, 2 arterial injuries and an adverse reaction to citrate. In 90%, the SAR was immediate and of grade 2 in 85% of cases. Thirty-seven percent of SAR were first donation in connection with whole blood in 87% of cases. Regarding the seniority of donors, the number of average donations (whole blood, plasma, platelets) was 16.5. An SAR determined the stop of blood donation in 65% of cases with nearly 80% stoppage if it was a first donation. Seventy-three percent of SAR as a VVS took place during blood collection or within 5 minutes following the end of the donation. Sixty-one percent were men. Forty-four percent of cases were a first donation and 83% occurred in mobile blood collection. Average age was 36 years. The result was a permanent stop of all type of donations in 76% of cases. Twenty-seven percent of SAR as a VVS took place beyond 5 minutes after the end of the donation. Seventy-five percent were women. Thirty percent of cases were a first donation and 95% of SAR occurred in mobile blood collection. Average age was 42 years. The result was a permanent stop of

Performance improvements from imagery:evidence that internal visual imagery is superior to external visual imagery for slalom performance

Directory of Open Access Journals (Sweden)

Nichola eCallow

2013-10-01

Full Text Available We report three experiments investigating the hypothesis that use of internal visual imagery (IVI would be superior to external visual imagery (EVI for the performance of different slalom-based motor tasks. In Experiment 1, three groups of participants (IVI, EVI, and a control group performed a driving-simulation slalom task. The IVI group achieved significantly quicker lap times than EVI and the control group. In Experiment 2, participants performed a downhill running slalom task under both IVI and EVI conditions. Performance was again quickest in the IVI compared to EVI condition, with no differences in accuracy. Experiment 3 used the same group design as Experiment 1, but with participants performing a downhill ski-slalom task. Results revealed the IVI group to be significantly more accurate than the control group, with no significant differences in time taken to complete the task. These results support the beneficial effects of IVI for slalom-based tasks, and significantly advances our knowledge related to the differential effects of visual imagery perspectives on motor performance.

The planned Alaska SAR Facility - An overview

Science.gov (United States)

Carsey, Frank; Weeks, Wilford

1987-01-01

The Alaska SAR Facility (ASF) is described in an overview fashion. The facility consists of three major components, a Receiving Ground System, a SAR Processing System and an Analysis and Archiving System; the ASF Program also has a Science Working Team and the requisite management and operations systems. The ASF is now an approved and fully funded activity; detailed requirements and science background are presented for the facility to be implemented for data from the European ERS-1, the Japanese ERS-1 and Radarsat.

Satellite sar detection of hurricane helene (2006)

DEFF Research Database (Denmark)

Ju, Lian; Cheng, Yongcun; Xu, Qing

2013-01-01

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

Geologic mapping in Greenland with polarimetric SAR

DEFF Research Database (Denmark)

Dall, Jørgen; Madsen, Søren Nørvang; Brooks, C. K.

1995-01-01

The application of synthetic aperture radar (SAR) for geologic mapping in Greenland is investigated by the Danish Center for Remote Sensing (DCRS) in co-operation with the Danish Lithosphere Centre (DLC). In 1994 a pilot project was conducted in East Greenland. The Danish airborne SAR, EMISAR...... mapping is complicated by an extreme topography leading to massive shadowing, foreshortening and layover. An artifact characterised by high cross-polarisation is observed behind many sharp mountain ridges. A multi-reflection hypothesis has been investigated without finding the ultimate proof...

RADARSAT-1 Image Quality Excellence in the Extended Mission

National Research Council Canada - National Science Library

Srivastava, S. K; Cote, S; Le Dantec, P; Hawkins, R. K

2005-01-01

... after its launch on November 4, 1995. Both single beams and ScanSAR imagery are still monitored routinely for radiometric calibration performance based on images of the Amazon Rainforest, and for image quality performance using imagery...

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

Science.gov (United States)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Selective effect of physical fatigue on motor imagery accuracy.

Directory of Open Access Journals (Sweden)

Franck Di Rienzo

Full Text Available While the use of motor imagery (the mental representation of an action without overt execution during actual training sessions is usually recommended, experimental studies examining the effect of physical fatigue on subsequent motor imagery performance are sparse and yielded divergent findings. Here, we investigated whether physical fatigue occurring during an intense sport training session affected motor imagery ability. Twelve swimmers (nine males, mean age 15.5 years conducted a 45 min physically-fatiguing protocol where they swam from 70% to 100% of their maximal aerobic speed. We tested motor imagery ability immediately before and after fatigue state. Participants randomly imagined performing a swim turn using internal and external visual imagery. Self-reports ratings, imagery times and electrodermal responses, an index of alertness from the autonomic nervous system, were the dependent variables. Self-reports ratings indicated that participants did not encounter difficulty when performing motor imagery after fatigue. However, motor imagery times were significantly shortened during posttest compared to both pretest and actual turn times, thus indicating reduced timing accuracy. Looking at the selective effect of physical fatigue on external visual imagery did not reveal any difference before and after fatigue, whereas significantly shorter imagined times and electrodermal responses (respectively 15% and 48% decrease, p<0.001 were observed during the posttest for internal visual imagery. A significant correlation (r=0.64; p<0.05 was observed between motor imagery vividness (estimated through imagery questionnaire and autonomic responses during motor imagery after fatigue. These data support that unlike local muscle fatigue, physical fatigue occurring during intense sport training sessions is likely to affect motor imagery accuracy. These results might be explained by the updating of the internal representation of the motor sequence, due to

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

Science.gov (United States)

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

2018-05-01

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

New percepts via mental imagery?

Directory of Open Access Journals (Sweden)

Fred Walter Mast

2012-10-01

Full Text Available We are able to extract detailed information from mental images that we were not explicitly aware of during encoding. For example, we can discover a new figure when we rotate a previously seen image in our mind. However, such discoveries are not really new but just new interpretations. In two recent publications, we have shown that mental imagery can lead to perceptual learning (Tartaglia et al., 2009, 2012. Observers imagined the central line of a bisection stimulus for thousands of trials. This training enabled observers to perceive bisection offsets that were invisible before training. Hence, it seems that perceptual learning via mental imagery leads to new percepts. We will argue, however, that these new percepts can occur only within known models. In this sense, perceptual learning via mental imagery exceeds new discoveries in mental images. Still, the effects of mental imagery on perceptual learning are limited. Only perception can lead to really new perceptual experience.

Sentinel-3 SAR Altimetry Toolbox

Science.gov (United States)

Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

2015-04-01

The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage of ERS-2 and Envisat, and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the two Sentinels is expected to be launched in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission's data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth

InSAR observations of active volcanoes in Latin America

Science.gov (United States)

Morales Rivera, A. M.; Chaussard, E.; Amelung, F.

2012-12-01

Over the last decade satellite-based interferometric synthetic aperture radar (InSAR) has developed into a well-known technique to gauge the status of active volcanoes. The InSAR technique can detect the ascent of magma to shallow levels of the volcanic plumbing system because new arriving magma pressurizes the system. This is likely associated with the inflation of the volcanic edifice and the surroundings. Although the potential of InSAR to detect magma migration is well known, the principal limitation was that only for few volcanoes frequent observations were acquired. The ALOS-1 satellite of the Japanese Aerospace Exploration Agency (JAXA) acquired a global L-band data set of 15-20 acquisitions during 2006-2011. Here we use ALOS InSAR and Small Baseline (SB) time-series methods for a ground deformation survey of Latin America with emphasis on the northern Andes. We present time-dependent ground deformation data for the volcanoes in Colombia, Ecuador and Peru and interpret the observations in terms of the dynamics of the volcanic systems.

Assessing mental imagery in clinical psychology: A review of imagery measures and a guiding framework

Science.gov (United States)

Pearson, David G.; Deeprose, Catherine; Wallace-Hadrill, Sophie M.A.; Heyes, Stephanie Burnett; Holmes, Emily A.

2013-01-01

Mental imagery is an under-explored field in clinical psychology research but presents a topic of potential interest and relevance across many clinical disorders, including social phobia, schizophrenia, depression, and post-traumatic stress disorder. There is currently a lack of a guiding framework from which clinicians may select the domains or associated measures most likely to be of appropriate use in mental imagery research. We adopt an interdisciplinary approach and present a review of studies across experimental psychology and clinical psychology in order to highlight the key domains and measures most likely to be of relevance. This includes a consideration of methods for experimentally assessing the generation, maintenance, inspection and transformation of mental images; as well as subjective measures of characteristics such as image vividness and clarity. We present a guiding framework in which we propose that cognitive, subjective and clinical aspects of imagery should be explored in future research. The guiding framework aims to assist researchers in the selection of measures for assessing those aspects of mental imagery that are of most relevance to clinical psychology. We propose that a greater understanding of the role of mental imagery in clinical disorders will help drive forward advances in both theory and treatment. PMID:23123567

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