Amazon Rain Forest Classification Using J-ERS-1 SAR Data
NASA Technical Reports Server (NTRS)
Freeman, A.; Kramer, C.; Alves, M.; Chapman, B.
1994-01-01
The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.
Six years of land subsidence in shanghai revealed by JERS-1 SAR data
Damoah-Afari, P.; Ding, X.-L.; Li, Z.; Lu, Z.; Omura, M.
2008-01-01
Differential interferometric synthetic aperture radar (SAR) (DInSAR) has proven to be very useful in mapping and monitoring land subsidence in many regions of the world. Shanghai, China's largest city, is one of such areas suffering from land subsidence as a result of severe withdrawal of groundwater for different usages. DInSAR application in Shanghai with the C-band European Remote Sensing 1 & 2 (ERS-1/2) SAR data has been difficult mainly due to the problem of decorrelation of InSAR pairs with temporal baselines larger than 10 months. To overcome the coherence loss of C-band InSAR data, we used eight L-band Japanese Earth Resource Satellite (JERS-1) SAR data acquired during 2 October 1992 to 15 July 1998 to study land subsidence phenomenon in Shanghai. Three of the images were used to produce two separate digital elevation models (DEMs) of the study area to remove topographic fringes from the interferograms used for subsidence mapping. Six interferograms were used to generate 2 different time series of deformation maps over Shanghai. The cumulative subsidence map generated from each of the time series is in agreement with the land subsidence measurements of Shanghai city from 1990-1998, produced from other survey methods. ?? 2007 IEEE.
Sea-Ice Feature Mapping using JERS-1 Imagery
NASA Technical Reports Server (NTRS)
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.
NASA Technical Reports Server (NTRS)
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.
Global Boreal Forest Mapping with JERS-1: North America
NASA Technical Reports Server (NTRS)
Williams, Cynthia L.; McDonald, Kyle; Chapman, Bruce
2000-01-01
Collaborative effort is underway to map boreal forests worldwide using L-band, single polarization Synthetic Aperture Radar (SAR) imagery from the Japanese Earth Resources (JERS-1) satellite. Final products of the North American Boreal Forest Mapping Project will include two continental scale radar mosaics and supplementary multitemporal mosaics for Alaska, central Canada, and eastern Canada. For selected sites, we are also producing local scale (100 km x 100 km) and regional scale maps (1000 km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web. Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR Facility.
NASA Technical Reports Server (NTRS)
Fielding, E. J.; Fujiwara, Satoshi; Hensley, S.; Rosen, P. A.; Tobita, Mikio; Shimada, Masanobu
1996-01-01
A large (M&subw;=7.0) earthquake on May 27, 1995 completely destroyed the town of Neftegorsk in the northern part of Sakhalin Island and caused more than 2000 human deaths. The shallow, right-lateral, strick-slip earthquake resulted in extensive surface ruptures and up to 7 m of horizontal displacement as reported by field workers. The sourthern part of the mainshock epicenter zone was imaged by the JERS-1 SAR (synthetic aperature radar) one month (April 28) before and two weeks after (June 11) the mainshock. Despite drastically changed surface conditions in the 44 days between the two images, due primarily to spring thaw, we obtained reasonably good interferometric correlation with the L-band (24 cm) SAR pair. The interoferogram records the distribution of deformation reflecting displacement during both the mainshock and aftershocks. The ability to map the deformation pattern can aid the assessment and mitigation of damage.
NASA Astrophysics Data System (ADS)
Ji, Lingyun; Wang, Qingliang; Xu, Jing; Ji, Cunwei
2017-03-01
On July 11, 1995, an Mw 6.8 earthquake struck eastern Myanmar near the Chinese border; hereafter referred to as the 1995 Myanmar-China earthquake. Coseismic surface displacements associated with this event are identified from JERS-1 (Japanese Earth Resources Satellite-1) SAR (Synthetic Aperture Radar) images. The largest relative displacement reached 60 cm in the line-of-sight direction. We speculate that a previously unrecognized dextral strike-slip subvertical fault striking NW-SE was responsible for this event. The coseismic slip distribution on the fault planes is inverted based on the InSAR-derived deformation. The results indicate that the fault slip was confined to two lobes. The maximum slip reached approximately 2.5 m at a depth of 5 km in the northwestern part of the focal region. The inverted geodetic moment was approximately Mw = 6.69, which is consistent with seismological results. The 1995 Myanmar-China earthquake is one of the largest recorded earthquakes that has occurred around the "bookshelf faulting" system between the Sagaing fault in Myanmar and the Red River fault in southwestern China.
Modeling of February 1993 Intrusion Seen by JERS-1 Satellite, Kilauea Volcano, Hawaii
NASA Astrophysics Data System (ADS)
Moore, S.; Wauthier, C.; Fukushima, Y.; Poland, M. P.
2016-12-01
Interferometric Synthetic Aperture Radar (InSAR) is a valuable means of remotely assessing deformation on the surface of the earth. At Kilauea Volcano, Hawai'i many InSAR deformation maps (interferograms) have been studied in recent years to monitor deformation on the volcano. In February 1993, a diking event occurred that could be one of the first intrusions seen by InSAR satellites at Kilauea. This event has not received much attention due to little geodetic data spanning the event. Between October 1992 and March 1993, SAR images from the JERS-1 satellite captured 30 centimeters of surface deformation occurring along the East Rift Zone (ERZ) near Makaopuhi crater. Seismic activity was similar to other intrusions with more than 5,000 shallow (<5 km) earthquakes occurred in the area between the summit caldera and Makaopuhi crater from February 7-9, 1993 [Okubo & Nakata, 2003]. We used simple analytical half-space solutions (e.g., Mogi [1958], Okada [1992)]), as well as a more complex and mechanically robust numerical approach (3D-MBEM [Cayol and Cornet, 1997]) to model deformation sources active between October 1992 and March 1993. Non-linear inversions of the JERS-1 Interferogram show that the most likely source to account for the February 1993 observed deformation is a subvertical rectangular dike with an opening of 1.5 m reaching depths of 1.5 to 3 km.
Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc
2009-01-01
Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C-band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr(-1) was measured.
Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc
2009-01-01
Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured. PMID:22389620
Crustal Deformation of Long Valley Caldera, Eastern California, Inferred from L-Band InSAR
NASA Astrophysics Data System (ADS)
Tanaka, Akiko
2008-11-01
SAR interferometric analyses using JERS-1/SAR and ALOS/PALSAR images of Long Valley caldera are performed. JERS-1/SAR interferogram (June 1993-August 1996) shows a small region of subsidence associated the Casa Diablo geothermal power plant, which is superimposed on a broad scale uplift/expansion of the resurgent dome. ALOS/PALSAR interferograms show no deformation of the resurgent dome as expected. However, it may show a small region of subsidence associated the Casa Diablo geothermal power plant.
NASA Technical Reports Server (NTRS)
Thomas, Nathan; Lucas, Richard; Itoh, Takuya; Simard, Marc; Fatoyinbo, Lucas; Bunting, Peter; Rosenqvist, Ake
2014-01-01
Between 2007 and 2010, Japan's Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) captured dual polarization HH and HV data across the tropics and sub-tropics. A pan tropical dataset of Japanese Earth Resources Satellite (JERS-1) SAR (HH) data was also acquired between 1995 and 1998. The provision of these comparable cloud-free datasets provided an opportunity for observing changes in the extent of coastal mangroves over more than a decade. Focusing on nine sites distributed through the tropics, this paper demonstrates how these data can be used to backdate and update existing baseline maps of mangrove extent. The benefits of integrating dense timeseries of Landsat sensor data for both validating assessments of change and determining the causes of change are outlined. The approach is evaluated for wider application across the geographical range of mangroves in order to advance the development of JAXA's Global Mangrove Watch (GMW) program.
NASA Technical Reports Server (NTRS)
Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika
1999-01-01
In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.
The Alaska SAR processor - Operations and control
NASA Technical Reports Server (NTRS)
Carande, Richard E.
1989-01-01
The Alaska SAR (synthetic-aperture radar) Facility (ASF) will be capable of receiving, processing, archiving, and producing a variety of SAR image products from three satellite-borne SARs: E-ERS-1 (ESA), J-ERS-1 (NASDA) and Radarsat (Canada). Crucial to the success of the ASF is the Alaska SAR processor (ASP), which will be capable of processing over 200 100-km x 100-km (Seasat-like) frames per day from the raw SAR data, at a ground resolution of about 30 m x 30 m. The processed imagery is of high geometric and radiometric accuracy, and is geolocated to within 500 m. Special-purpose hardware has been designed to execute a SAR processing algorithm to achieve this performance. This hardware is currently undergoing acceptance testing for delivery to the University of Alaska. Particular attention has been devoted to making the operations semi-automated and to providing a friendly operator interface via a computer workstation. The operations and control of the Alaska SAR processor are described.
MACSIGMA0 - MACINTOSH TOOL FOR ANALYZING JPL AIRSAR, ERS-1, JERS-1, AND MAGELLAN MIDR DATA
NASA Technical Reports Server (NTRS)
Norikane, L.
1994-01-01
MacSigma0 is an interactive tool for the Macintosh which allows you to display and make computations from radar data collected by the following sensors: the JPL AIRSAR, ERS-1, JERS-1, and Magellan. The JPL AIRSAR system is a multi-polarimetric airborne synthetic aperture radar developed and operated by the Jet Propulsion Laboratory. It includes the single-frequency L-band sensor mounted on the NASA CV990 aircraft and its replacement, the multi-frequency P-, L-, and C-band sensors mounted on the NASA DC-8. MacSigma0 works with data in the standard JPL AIRSAR output product format, the compressed Stokes matrix format. ERS-1 and JERS-1 are single-frequency, single-polarization spaceborne synthetic aperture radars launched by the European Space Agency and NASDA respectively. To be usable by MacSigma0, The data must have been processed at the Alaska SAR Facility and must be in the "low-resolution" format. Magellan is a spacecraft mission to map the surface of Venus with imaging radar. The project is managed by the Jet Propulsion Laboratory. The spacecraft carries a single-frequency, single-polarization synthetic aperture radar. MacSigma0 works with framelets of the standard MIDR CD-ROM data products. MacSigma0 provides four basic functions: synthesis of images (if necessary), statistical analysis of selected areas, analysis of corner reflectors as a calibration measure (if appropriate and possible), and informative mouse tracking. For instance, the JPL AIRSAR data can be used to synthesize a variety of images such as a total power image. The total power image displays the sum of the polarized and unpolarized components of the backscatter for each pixel. Other images which can be synthesized are HH, HV, VV, RL, RR, HHVV*, HHHV*, HVVV*, HHVV* phase and correlation coefficient images. For the complex and phase images, phase is displayed using color and magnitude is displayed using intensity. MacSigma0 can also be used to compute statistics from within a selected area. The
Data Recipes: Easy-to-Follow Instructions for Using SAR Data
NASA Astrophysics Data System (ADS)
Stoner, C.; Laurencelle, J. C.; Drew, L.; Myers, A.
2016-12-01
To make synthetic aperture radar (SAR) data more user friendly, the Alaska Satellite Facility DAAC has created a growing library of online data recipes. The ASF DAAC offers SAR data from more than a dozen datasets, increasingly used by researchers for applications as varied as mapping wetlands, analyzing volcanic eruptions, measuring subsidence, following sea-ice movements, and tracking the paths of oil spills into sensitive marshes. Yet because learning how to use SAR data can seem intimidating or difficult, many researchers in relevant Earth sciences never access ASF's 25 year, 2.5 petabyte archive of day/night all-weather earth images. The data recipes help address this issue. With varied combinations of written instructions, scripts, pictures, and videos, the recipes give users step-by-step instructions for accomplishing discrete tasks. Recipe difficulty is rated and labeled from "Easier" to "More Advanced" with ski-slope type symbols. Recipe examples include creating a regional inundation map; radiometrically terrain correcting Sentinel-1A data using either a GUI or a script; viewing RTC power images in a GIS environment; and radiometrically terrain correcting ERS-1, ERS-2, JERS-1, RADARSAT-1, and ALOS PALSAR images using ASF MapReady software.
Extraction of Coastlines with Fuzzy Approach Using SENTINEL-1 SAR Image
NASA Astrophysics Data System (ADS)
Demir, N.; Kaynarca, M.; Oy, S.
2016-06-01
Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS) Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the LIDAR points of
Composite SAR imaging using sequential joint sparsity
NASA Astrophysics Data System (ADS)
Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.
2017-06-01
This paper investigates accurate and efficient ℓ1 regularization methods for generating synthetic aperture radar (SAR) images. Although ℓ1 regularization algorithms are already employed in SAR imaging, practical and efficient implementation in terms of real time imaging remain a challenge. Here we demonstrate that fast numerical operators can be used to robustly implement ℓ1 regularization methods that are as or more efficient than traditional approaches such as back projection, while providing superior image quality. In particular, we develop a sequential joint sparsity model for composite SAR imaging which naturally combines the joint sparsity methodology with composite SAR. Our technique, which can be implemented using standard, fractional, or higher order total variation regularization, is able to reduce the effects of speckle and other noisy artifacts with little additional computational cost. Finally we show that generalizing total variation regularization to non-integer and higher orders provides improved flexibility and robustness for SAR imaging.
MREG V1.1 : a multi-scale image registration algorithm for SAR applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eichel, Paul H.
2013-08-01
MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962more » leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.« less
Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems
NASA Technical Reports Server (NTRS)
Saatchi, Sassan; Moghaddam, Mahta
1995-01-01
In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.
Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic
NASA Technical Reports Server (NTRS)
Saatchi, Sassan S.; Nelson, Bruce; Podest, Erika; Holt, John
2000-01-01
In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.
Segmentation of oil spills in SAR images by using discriminant cuts
NASA Astrophysics Data System (ADS)
Ding, Xianwen; Zou, Xiaolin
2018-02-01
The discriminant cut is used to segment the oil spills in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in SAR images. The real SAR images, i.e. ALOS-1 PALSAR and Sentinel-1 SAR images were collected and used to validate the accuracy of the proposed approach for oil spill segmentation in SAR images. The accuracy of the proposed approach is higher than that of the fuzzy C-means classification method.
Method for removing RFI from SAR images
Doerry, Armin W.
2003-08-19
A method of removing RFI from a SAR by comparing two SAR images on a pixel by pixel basis and selecting the pixel with the lower magnitude to form a composite image. One SAR image is the conventional image produced by the SAR. The other image is created from phase-history data which has been filtered to have the frequency bands containing the RFI removed.
SAR imaging - Seeing the unseen
NASA Technical Reports Server (NTRS)
Kobrick, M.
1982-01-01
The functional abilities and operations of synthetic aperture radar (SAR) are described. SAR employs long wavelength radio waves in bursts, imaging a target by 'listening' to the small frequency changes that result from the Doppler shift due to the relative motion of the imaging craft and the motions of the target. The time delay of the signal return allows a determination of the location of the target, leading to the build up of a two-dimensional image. The uses of both Doppler shifts and time delay enable detailed imagery which is independent of distance. The synthetic aperture part of the name of SAR derives from the beaming of multiple pulses, which result in a picture that is effectively the same as using a large antenna. Mechanisms contributing to the fineness of SAR images are outlined.
NASA Astrophysics Data System (ADS)
Iisaka, Joji; Sakurai-Amano, Takako
1994-08-01
This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.
Spaceborne SAR Imaging Algorithm for Coherence Optimized.
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.
Spaceborne SAR Imaging Algorithm for Coherence Optimized
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
SAR image registration based on Susan algorithm
NASA Astrophysics Data System (ADS)
Wang, Chun-bo; Fu, Shao-hua; Wei, Zhong-yi
2011-10-01
Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.
Colorizing SENTINEL-1 SAR Images Using a Variational Autoencoder Conditioned on SENTINEL-2 Imagery
NASA Astrophysics Data System (ADS)
Schmitt, M.; Hughes, L. H.; Körner, M.; Zhu, X. X.
2018-05-01
In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner.
Image based SAR product simulation for analysis
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
Liu, Chunhui; Zhang, Duona; Zhao, Xintao
2018-03-01
Saliency detection in synthetic aperture radar (SAR) images is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR images. We extract four features of the SAR image, which include the intensity, orientation, uniqueness, and global contrast, as the input of the MSD model. The saliency map is generated by the multitask sparsity pursuit, which integrates the multiple features collaboratively. Detection of different scale features is also taken into consideration. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps obtained by the MSD model, we apply the saliency map of the SAR image to the SAR and color optical image fusion. The experimental results of real data show that the saliency map obtained by the MSD model helps to improve the fusion effect, and the salient areas in the SAR image can be highlighted in the fusion results.
Controlling Data Collection to Support SAR Image Rotation
Doerry, Armin W.; Cordaro, J. Thomas; Burns, Bryan L.
2008-10-14
A desired rotation of a synthetic aperture radar (SAR) image can be facilitated by adjusting a SAR data collection operation based on the desired rotation. The SAR data collected by the adjusted SAR data collection operation can be efficiently exploited to form therefrom a SAR image having the desired rotational orientation.
Registration of interferometric SAR images
NASA Technical Reports Server (NTRS)
Lin, Qian; Vesecky, John F.; Zebker, Howard A.
1992-01-01
Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.
InSAR detects possible thaw settlement in the Alaskan Arctic Coastal Plain
Rykhus, Russell P.; Lu, Zhong
2008-01-01
Satellite interferometric synthetic aperture radar (InSAR) has proven to be an effective tool for monitoring surface deformation from volcanoes, earthquakes, landslides, and groundwater withdrawal. This paper seeks to expand the list of applications of InSAR data to include monitoring subsidence possibly associated with thaw settlement over the Alaskan Arctic Coastal Plain. To test our hypothesis that InSAR data are sufficiently sensitive to detect subsidence associated with thaw settlement, we acquired all Japanese Earth Resources Satellite-1 (JERS-1) L-band data available for the summers of 1996, 1997, and 1998 over two sites on the Alaska North Slope. The least amount of subsidence for both study sites was detected in the interferograms covering the summer of 1996 (2-3 cm), interferograms from 1997 and 1998 revealed that about 3 cm of subsidence occurred at the northern Cache One Lake site, and about 5 cm of subsidence was detected at the southern Kaparuk River site. These preliminary results illustrate the capacity of the L-band (24 cm) wavelength JERS-1 radar data to penetrate the short Arctic vegetation to monitor subsidence possibly associated with thaw settlement of the active layer and (or) other hydrologic changes over relatively large areas.
Automatic Coregistration for Multiview SAR Images in Urban Areas
NASA Astrophysics Data System (ADS)
Xiang, Y.; Kang, W.; Wang, F.; You, H.
2017-09-01
Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.
NASA Astrophysics Data System (ADS)
Garzelli, Andrea; Zoppetti, Claudia; Pinelli, Gianpaolo
2017-10-01
Coastline detection in synthetic aperture radar (SAR) images is crucial in many application fields, from coastal erosion monitoring to navigation, from damage assessment to security planning for port facilities. The backscattering difference between land and sea is not always documented in SAR imagery, due to the severe speckle noise, especially in 1-look data with high spatial resolution, high sea state, or complex coastal environments. This paper presents an unsupervised, computationally efficient solution to extract the coastline acquired by only one single-polarization 1-look SAR image. Extensive tests on Spotlight COSMO-SkyMed images of complex coastal environments and objective assessment demonstrate the validity of the proposed procedure which is compared to state-of-the-art methods through visual results and with an objective evaluation of the distance between the detected and the true coastline provided by regional authorities.
NASA Technical Reports Server (NTRS)
Hasselmann, Klaus; Hasselmann, Susanne; Bauer, Eva; Bruening, Claus; Lehner, Susanne; Graber, Hans; Lionello, Piero
1988-01-01
The applicability of ERS-1 wind and wave data for wave models was studied using the WAM third generation wave model and SEASAT altimeter, scatterometer and SAR data. A series of global wave hindcasts is made for the surface stress and surface wind fields by assimilation of scatterometer data for the full 96-day SEASAT and also for two wind field analyses for shorter periods by assimilation with the higher resolution ECMWF T63 model and by subjective analysis methods. It is found that wave models respond very sensitively to inconsistencies in wind field analyses and therefore provide a valuable data validation tool. Comparisons between SEASAT SAR image spectra and theoretical SAR spectra derived from the hindcast wave spectra by Monte Carlo simulations yield good overall agreement for 32 cases representing a wide variety of wave conditions. It is concluded that SAR wave imaging is sufficiently well understood to apply SAR image spectra with confidence for wave studies if supported by realistic wave models and theoretical computations of the strongly nonlinear mapping of the wave spectrum into the SAR image spectrum. A closed nonlinear integral expression for this spectral mapping relation is derived which avoids the inherent statistical errors of Monte Carlo computations and may prove to be more efficient numerically.
Ship Detection in SAR Image Based on the Alpha-stable Distribution
Wang, Changcheng; Liao, Mingsheng; Li, Xiaofeng
2008-01-01
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alpha-stable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. PMID:27873794
Applications of independent component analysis in SAR images
NASA Astrophysics Data System (ADS)
Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping
2009-07-01
The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.
Relevant Scatterers Characterization in SAR Images
NASA Astrophysics Data System (ADS)
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.
Combined DEM Extration Method from StereoSAR and InSAR
NASA Astrophysics Data System (ADS)
Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.
2015-06-01
A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.
Calibration of a polarimetric imaging SAR
NASA Technical Reports Server (NTRS)
Sarabandi, K.; Pierce, L. E.; Ulaby, F. T.
1991-01-01
Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.
SAR/LANDSAT image registration study
NASA Technical Reports Server (NTRS)
Murphrey, S. W. (Principal Investigator)
1978-01-01
The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.
Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images
NASA Astrophysics Data System (ADS)
Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.
2017-09-01
Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.
Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern
Doerry, Armin W.
2013-04-30
Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.
Bistatic SAR: Signal Processing and Image Formation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wahl, Daniel E.; Yocky, David A.
This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013more » on Kirtland Air Force Base, New Mexico.« less
Sparsity-driven coupled imaging and autofocusing for interferometric SAR
NASA Astrophysics Data System (ADS)
Zengin, Oǧuzcan; Khwaja, Ahmed Shaharyar; ćetin, Müjdat
2018-04-01
We propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan et al. proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods.
Moran, S.C.; Kwoun, O.; Masterlark, Timothy; Lu, Z.
2006-01-01
Shishaldin Volcano, a large, frequently active basaltic-andesite volcano located on Unimak Island in the Aleutian Arc of Alaska, had a minor eruption in 1995–1996 and a VEI 3 sub-Plinian basaltic eruption in 1999. We used 21 synthetic aperture radar images acquired by ERS-1, ERS-2, JERS-1, and RADARSAT-1 satellites to construct 12 coherent interferograms that span most of the 1993–2003 time interval. All interferograms lack coherence within ∼5 km of the summit, primarily due to persistent snow and ice cover on the edifice. Remarkably, in the 5–15 km distance range where interferograms are coherent, the InSAR images show no intrusion- or withdrawal-related deformation at Shishaldin during this entire time period. However, several InSAR images do show deformation associated with a shallow ML 5.2 earthquake located ∼14 km west of Shishaldin that occurred 6 weeks before the 1999 eruption. We use a theoretical model to predict deformation magnitudes due to a volumetric expansion source having a volume equivalent to the 1999 erupted volume, and find that deformation magnitudes for sources shallower than 10 km are within the expected detection capabilities for interferograms generated from C-band ERS 1/2 and RADARSAT-1 synthetic aperture radar images. We also find that InSAR images cannot resolve relatively shallow deformation sources (1–2 km below sea level) due to spatial gaps in the InSAR images caused by lost coherence. The lack of any deformation, particularly for the 1999 eruption, leads us to speculate that magma feeding eruptions at the summit moves rapidly (at least 80m/day) from > 10 km depth, and that the intrusion–eruption cycle at Shishaldin does not produce significant permanent deformation at the surface.
NASA Astrophysics Data System (ADS)
He, G.; Xia, Z.; Chen, H.; Li, K.; Zhao, Z.; Guo, Y.; Feng, P.
2018-04-01
Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.
Final Report (O1-ERD-051) Dynamic InSAR: Imaging Seismic Waves Remotely from Space
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vincent, P; Rodgers, A; Dodge, D
2003-02-07
The purpose of this LDRD project was to determine the feasibility of using InSAR (interferometric synthetic aperture radar) to image seismic waves remotely from space. If shown to be feasible, the long-term goal of this project would be to influence future SAR satellite missions and airborne SAR platforms to include a this new capability. This final report summarizes the accomplishments of the originally-planned 2-year project that was cut short to 1 year plus 2 months due to a funding priority change that occurred in the aftermath of the September 11th tragedy. The LDRD-ER project ''Dynamic InSAR: Imaging Seismic Waves frommore » Space'' (01-ERD-051) began in October, (FY01) and ended in December (FY02). Consequently, most of the results and conclusions for this project are represented in the FY0l Annual Report. Nonetheless, additional conclusions and insights regarding the progress of this work are included in this report. In should be noted that this work was restarted and received additional funding under the NA-22 DOE Nonproliferation Program in FY03.« less
Coastline detection with time series of SAR images
NASA Astrophysics Data System (ADS)
Ao, Dongyang; Dumitru, Octavian; Schwarz, Gottfried; Datcu, Mihai
2017-10-01
For maritime remote sensing, coastline detection is a vital task. With continuous coastline detection results from satellite image time series, the actual shoreline, the sea level, and environmental parameters can be observed to support coastal management and disaster warning. Established coastline detection methods are often based on SAR images and wellknown image processing approaches. These methods involve a lot of complicated data processing, which is a big challenge for remote sensing time series. Additionally, a number of SAR satellites operating with polarimetric capabilities have been launched in recent years, and many investigations of target characteristics in radar polarization have been performed. In this paper, a fast and efficient coastline detection method is proposed which comprises three steps. First, we calculate a modified correlation coefficient of two SAR images of different polarization. This coefficient differs from the traditional computation where normalization is needed. Through this modified approach, the separation between sea and land becomes more prominent. Second, we set a histogram-based threshold to distinguish between sea and land within the given image. The histogram is derived from the statistical distribution of the polarized SAR image pixel amplitudes. Third, we extract continuous coastlines using a Canny image edge detector that is rather immune to speckle noise. Finally, the individual coastlines derived from time series of .SAR images can be checked for changes.
Direct Geolocation of TerraSAR-X Spotlight Mode Image and Error Correction
NASA Astrophysics Data System (ADS)
Zhou, Xiao; Zeng, Qiming; Jiao, Jian; Zhang, Jingfa; Gong, Lixia
2013-01-01
The GERMAN TerraSAR-X mission was launched in June 2007, operating a versatile new-generation SAR sensor in X-band. Its Spotlight mode providing SAR images at very high resolution of about 1m. The product’s specified 3-D geolocation accuracy is tightened to 1m according to the official technical report. However, this accuracy is able to be achieved relies on not only robust mathematical basis of SAR geolocation, but also well knowledge of error sources and their correction. The research focuses on geolocation of TerraSAR-X spotlight image. Mathematical model and resolving algorithms have been analyzed. Several error sources have been researched and corrected especially. The effectiveness and accuracy of the research was verified by the experiment results.
Speckle noise reduction in SAR images ship detection
NASA Astrophysics Data System (ADS)
Yuan, Ji; Wu, Bin; Yuan, Yuan; Huang, Qingqing; Chen, Jingbo; Ren, Lin
2012-09-01
At present, there are two types of method to detect ships in SAR images. One is a direct detection type, detecting ships directly. The other is an indirect detection type. That is, it firstly detects ship wakes, and then seeks ships around wakes. The two types all effect by speckle noise. In order to improve the accuracy of ship detection and get accurate ship and ship wakes parameters, such as ship length, ship width, ship area, the angle of ship wakes and ship outline from SAR images, it is extremely necessary to remove speckle noise in SAR images before data used in various SAR images ship detection. The use of speckle noise reduction filter depends on the specification for a particular application. Some common filters are widely used in speckle noise reduction, such as the mean filter, the median filter, the lee filter, the enhanced lee filter, the Kuan filter, the frost filter, the enhanced frost filter and gamma filter, but these filters represent some disadvantages in SAR image ship detection because of the various types of ship. Therefore, a mathematical function known as the wavelet transform and multi-resolution analysis were used to localize an SAR ocean image into different frequency components or useful subbands, and effectively reduce the speckle in the subbands according to the local statistics within the bands. Finally, the analysis of the statistical results are presented, which demonstrates the advantages and disadvantages of using wavelet shrinkage techniques over standard speckle filters.
NASA Technical Reports Server (NTRS)
Chang, C. Y.; Kwok, R.; Curlander, J. C.
1987-01-01
Five coding techniques in the spatial and transform domains have been evaluated for SAR image compression: linear three-point predictor (LTPP), block truncation coding (BTC), microadaptive picture sequencing (MAPS), adaptive discrete cosine transform (ADCT), and adaptive Hadamard transform (AHT). These techniques have been tested with Seasat data. Both LTPP and BTC spatial domain coding techniques provide very good performance at rates of 1-2 bits/pixel. The two transform techniques, ADCT and AHT, demonstrate the capability to compress the SAR imagery to less than 0.5 bits/pixel without visible artifacts. Tradeoffs such as the rate distortion performance, the computational complexity, the algorithm flexibility, and the controllability of compression ratios are also discussed.
Watershed identification of polygonal patterns in noisy SAR images.
Moreels, Pierre; Smrekar, Suzanne E
2003-01-01
This paper describes a new approach to pattern recognition in synthetic aperture radar (SAR) images. A visual analysis of the images provided by NASA's Magellan mission to Venus has revealed a number of zones showing polygonal-shaped faults on the surface of the planet. The goal of the paper is to provide a method to automate the identification of such zones. The high level of noise in SAR images and its multiplicative nature make automated image analysis difficult and conventional edge detectors, like those based on gradient images, inefficient. We present a scheme based on an improved watershed algorithm and a two-scale analysis. The method extracts potential edges in the SAR image, analyzes the patterns obtained, and decides whether or not the image contains a "polygon area". This scheme can also be applied to other SAR or visual images, for instance in observation of Mars and Jupiter's satellite Europa.
Pre-Processes for Urban Areas Detection in SAR Images
NASA Astrophysics Data System (ADS)
Altay Açar, S.; Bayır, Ş.
2017-11-01
In this study, pre-processes for urban areas detection in synthetic aperture radar (SAR) images are examined. These pre-processes are image smoothing, thresholding and white coloured regions determination. Image smoothing is carried out to remove noises then thresholding is applied to obtain binary image. Finally, candidate urban areas are detected by using white coloured regions determination. All pre-processes are applied by utilizing the developed software. Two different SAR images which are acquired by TerraSAR-X are used in experimental study. Obtained results are shown visually.
SAR image dataset of military ground targets with multiple poses for ATR
NASA Astrophysics Data System (ADS)
Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc
2017-10-01
Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.
Space Radar Image of West Texas - SAR scan
NASA Technical Reports Server (NTRS)
1999-01-01
This radar image of the Midland/Odessa region of West Texas, demonstrates an experimental technique, called ScanSAR, that allows scientists to rapidly image large areas of the Earth's surface. The large image covers an area 245 kilometers by 225 kilometers (152 miles by 139 miles). It was obtained by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying aboard the space shuttle Endeavour on October 5, 1994. The smaller inset image is a standard SIR-C image showing a portion of the same area, 100 kilometers by 57 kilometers (62 miles by 35 miles) and was taken during the first flight of SIR-C on April 14, 1994. The bright spots on the right side of the image are the cities of Odessa (left) and Midland (right), Texas. The Pecos River runs from the top center to the bottom center of the image. Along the left side of the image are, from top to bottom, parts of the Guadalupe, Davis and Santiago Mountains. North is toward the upper right. Unlike conventional radar imaging, in which a radar continuously illuminates a single ground swath as the space shuttle passes over the terrain, a Scansar radar illuminates several adjacent ground swaths almost simultaneously, by 'scanning' the radar beam across a large area in a rapid sequence. The adjacent swaths, typically about 50 km (31 miles) wide, are then merged during ground processing to produce a single large scene. Illumination for this L-band scene is from the top of the image. The beams were scanned from the top of the scene to the bottom, as the shuttle flew from left to right. This scene was acquired in about 30 seconds. A normal SIR-C image is acquired in about 13 seconds. The ScanSAR mode will likely be used on future radar sensors to construct regional and possibly global radar images and topographic maps. The ScanSAR processor is being designed for 1996 implementation at NASA's Alaska SAR Facility, located at the University of Alaska Fairbanks, and will produce digital images from the
Polarimetric SAR image classification based on discriminative dictionary learning model
NASA Astrophysics Data System (ADS)
Sang, Cheng Wei; Sun, Hong
2018-03-01
Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.
Research on Airborne SAR Imaging Based on Esc Algorithm
NASA Astrophysics Data System (ADS)
Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.
2017-09-01
Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.
SAR imaging of vortex ship wakes. Volume 3: An overview of pre-ERS-1 observations and models
NASA Astrophysics Data System (ADS)
Skoeelv, Aage; Wahl, Terje
1991-05-01
The visibility of dark turbulent wakes in Synthetic Aperture Radar (SAR) imagery is focused upon. An overview of various wake observations prior to ERS-1 is given. This includes images from Seasat and airborne SAR as well as photographic observations. Different turbulent wake models and simulation, schemes are reviewed. The requirements for a complete turbulent wake model are discussed, and from results available, some conclusions are drawn with respect to possible ERS-1 applications.
Synthetic aperture design for increased SAR image rate
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.
Guided SAR image despeckling with probabilistic non local weights
NASA Astrophysics Data System (ADS)
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.
Analysis of Multipath Pixels in SAR Images
NASA Astrophysics Data System (ADS)
Zhao, J. W.; Wu, J. C.; Ding, X. L.; Zhang, L.; Hu, F. M.
2016-06-01
As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings) and the physical parameters of the surface (roughness, correlation length, permittivity)which determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.
NASA Astrophysics Data System (ADS)
Liu, F.; Chen, T.; He, J.; Wen, Q.; Yu, F.; Gu, X.; Wang, Z.
2018-04-01
In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.
Advanced InSAR imaging for dune mapping
NASA Astrophysics Data System (ADS)
Havivi, Shiran; August, Yitzhak; Blumberg, Dan G.; Rotman, Stanley R.
2015-04-01
Aeolian morphologies are formed in the presence of sufficient wind energy and available particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970's, remote sensing imagery both optical and radar, are used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of Aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two images or more. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This research aims to demonstrate how interferometric decorrelation, or, coherence change detection, can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the Nitzanim coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically and
Structural Information Detection Based Filter for GF-3 SAR Images
NASA Astrophysics Data System (ADS)
Sun, Z.; Song, Y.
2018-04-01
GF-3 satellite with high resolution, large swath, multi-imaging mode, long service life and other characteristics, can achieve allweather and all day monitoring for global land and ocean. It has become the highest resolution satellite system in the world with the C-band multi-polarized synthetic aperture radar (SAR) satellite. However, due to the coherent imaging system, speckle appears in GF-3 SAR images, and it hinders the understanding and interpretation of images seriously. Therefore, the processing of SAR images has big challenges owing to the appearance of speckle. The high-resolution SAR images produced by the GF-3 satellite are rich in information and have obvious feature structures such as points, edges, lines and so on. The traditional filters such as Lee filter and Gamma MAP filter are not appropriate for the GF-3 SAR images since they ignore the structural information of images. In this paper, the structural information detection based filter is constructed, successively including the point target detection in the smallest window, the adaptive windowing method based on regional characteristics, and the most homogeneous sub-window selection. The despeckling experiments on GF-3 SAR images demonstrate that compared with the traditional filters, the proposed structural information detection based filter can well preserve the points, edges and lines as well as smooth the speckle more sufficiently.
High Resolution SAR Imaging Employing Geometric Features for Extracting Seismic Damage of Buildings
NASA Astrophysics Data System (ADS)
Cui, L. P.; Wang, X. P.; Dou, A. X.; Ding, X.
2018-04-01
Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover & bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.
SAR imaging and hydrodynamic analysis of ocean bottom topographic waves
NASA Astrophysics Data System (ADS)
Zheng, Quanan; Li, Li; Guo, Xiaogang; Ge, Yong; Zhu, Dayong; Li, Chunyan
2006-09-01
The satellite synthetic aperture radar (SAR) images display wave-like patterns of the ocean bottom topographic features at the south outlet of Taiwan Strait (TS). Field measurements indicate that the most TS water body is vertically stratified. However, SAR imaging models available were developed for homogeneous waters. Hence explaining SAR imaging mechanisms of bottom features in a stratified ocean is beyond the scope of those models. In order to explore these mechanisms and to determine the quantitative relations between the SAR imagery and the bottom features, a two-dimensional, three-layer ocean model with sinusoidal bottom topographic features is developed. Analytical solutions and inferences of the momentum equations of the ocean model lead to the following conditions. (1) In the lower layer, the topography-induced waves (topographic waves hereafter) exist in the form of stationary waves, which satisfy a lower boundary resonance condition σ = kC0, here σ is an angular frequency of the stationary waves, k is a wavenumber of bottom topographic corrugation, and C0 is a background current speed. (2) As internal waves, the topographic waves may propagate vertically to the upper layer with an unchanged wavenumber k, if a frequency relation N3 < σ < N2 is satisfied, here N2 and N3 are the Brunt-Wäisälä frequencies of middle layer and upper layer, respectively. (3) The topographic waves are extremely amplified if an upper layer resonance condition is satisfied. The SAR image of topographic waves is derived on the basis of current-modulated small wave spectra. The results indicate that the topographic waves on SAR images have the same wavelength of bottom topographic corrugation, and the imagery brightness peaks are either inphase or antiphase with respect to the topographic corrugation, depending on a sign of a coupling factor. These theoretical predictions are verified by field observations. The results of this study provide a physical basis for quantitative
Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features
NASA Astrophysics Data System (ADS)
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.
Estimating IMU heading error from SAR images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Doerry, Armin Walter
Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.
SAR imaging of ocean waves - Theory
NASA Technical Reports Server (NTRS)
Jain, A.
1981-01-01
A SAR imaging integral for a rough surface is derived. Aspects of distributed target imaging and questions of ocean-wave imaging are considered. A description is presented of the results of analyses which are performed on aircraft and a spacecraft data in order to gain an understanding of the SAR imaging of ocean waves. The analyzed data illustrate the effect of radar resolution on the images of azimuthally traveling waves, the dependence of image distortion on the angle which the waves make with the radar flight path, and the dependence of the focusing parameter of the radar matched filter on the ocean wave period for azimuthally traveling waves. A dependence of ocean-wave modulation on significant wave height is also observed. The observed dependence of the modulations of azimuth waves on radar resolution is in contradiction to the hypothesis that these modulations are caused mainly by velocity bunching.
A Wavelet Polarization Decomposition Net Model for Polarimetric SAR Image Classification
NASA Astrophysics Data System (ADS)
He, Chu; Ou, Dan; Yang, Teng; Wu, Kun; Liao, Mingsheng; Chen, Erxue
2014-11-01
In this paper, a deep model based on wavelet texture has been proposed for Polarimetric Synthetic Aperture Radar (PolSAR) image classification inspired by recent successful deep learning method. Our model is supposed to learn powerful and informative representations to improve the generalization ability for the complex scene classification tasks. Given the influence of speckle noise in Polarimetric SAR image, wavelet polarization decomposition is applied first to obtain basic and discriminative texture features which are then embedded into a Deep Neural Network (DNN) in order to compose multi-layer higher representations. We demonstrate that the model can produce a powerful representation which can capture some untraceable information from Polarimetric SAR images and show a promising achievement in comparison with other traditional SAR image classification methods for the SAR image dataset.
Chinese HJ-1C SAR And Its Wind Mapping Capability
NASA Astrophysics Data System (ADS)
Huang, Weigen; Chen, Fengfeng; Yang, Jingsong; Fu, Bin; Chen, Peng; Zhang, Chan
2010-04-01
Chinese Huan Jing (HJ)-1C synthetic aperture radar (SAR) satellite has been planed to be launched in 2010. HJ-1C satellite will fly in a sun-synchronous polar orbit of 500-km altitude. SAR will be the only sensor on board the satellite. It operates in S band with VV polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. There are two selectable SAR modes of operation, which are fine resolution beams and standard beams respectively. The sea surface wind mapping capability of the SAR has been examined using M4S radar imaging model developed by Romeiser. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat ASAR. It shows that HJ-1C SAR is as good as Envisat ASAR at sea surface wind mapping.
Multitemporal Observations of Sugarcane by TerraSAR-X Images
Baghdadi, Nicolas; Cresson, Rémi; Todoroff, Pierre; Moinet, Soizic
2010-01-01
The objective of this study is to investigate the potential of TerraSAR-X (X-band) in monitoring sugarcane growth on Reunion Island (located in the Indian Ocean). Multi-temporal TerraSAR data acquired at various incidence angles (17°, 31°, 37°, 47°, 58°) and polarizations (HH, HV, VV) were analyzed in order to study the behaviour of SAR (synthetic aperture radar) signal as a function of sugarcane height and NDVI (Normalized Difference Vegetation Index). The potential of TerraSAR for mapping the sugarcane harvest was also studied. Radar signal increased quickly with crop height until a threshold height, which depended on polarization and incidence angle. Beyond this threshold, the signal increased only slightly, remained constant, or even decreased. The threshold height is slightly higher with cross polarization and higher incidence angles (47° in comparison with 17° and 31°). Results also showed that the co-polarizations channels (HH and VV) were well correlated. High correlation between SAR signal and NDVI calculated from SPOT-4/5 images was observed. TerraSAR data showed that after strong rains the soil contribution to the backscattering of sugarcane fields can be important for canes with heights of terminal visible dewlap (htvd) less than 50 cm (total cane heights around 155 cm). This increase in radar signal after strong rains could involve an ambiguity between young and mature canes. Indeed, the radar signal on TerraSAR images acquired in wet soil conditions could be of the same order for fields recently harvested and mature sugarcane fields, making difficult the detection of cuts. Finally, TerraSAR data at high spatial resolution were shown to be useful for monitoring sugarcane harvest when the fields are of small size or when the cut is spread out in time. The comparison between incidence angles of 17°, 37° and 58° shows that 37° is more suitable to monitor the sugarcane harvest. The cut is easily detectable on TerraSAR images for data acquired
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks
Xu, Xin; Gui, Rong; Pu, Fangling
2018-01-01
Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.
Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling
2018-03-03
Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.
Fusion method of SAR and optical images for urban object extraction
NASA Astrophysics Data System (ADS)
Jia, Yonghong; Blum, Rick S.; Li, Fangfang
2007-11-01
A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.
Reducing Speckle In One-Look SAR Images
NASA Technical Reports Server (NTRS)
Nathan, K. S.; Curlander, J. C.
1990-01-01
Local-adaptive-filter algorithm incorporated into digital processing of synthetic-aperture-radar (SAR) echo data to reduce speckle in resulting imagery. Involves use of image statistics in vicinity of each picture element, in conjunction with original intensity of element, to estimate brightness more nearly proportional to true radar reflectance of corresponding target. Increases ratio of signal to speckle noise without substantial degradation of resolution common to multilook SAR images. Adapts to local variations of statistics within scene, preserving subtle details. Computationally simple. Lends itself to parallel processing of different segments of image, making possible increased throughput.
NASA Technical Reports Server (NTRS)
Carsey, F. D.; Weeks, W.
1988-01-01
The Alaska SAR Facility (ASF) program for the acquisition and processing of data from the ESA ERS-1, the NASDA ERS-1, and Radarsat and to carry out a program of science investigations using the data is introduced. Agreements for data acquisition and analysis are in place except for the agreement between NASA and Radarsat which is in negotiation. The ASF baseline system, consisting of the Receiving Ground System, the SAR Processor System and the Archive and Operations System, passed critical design review and is fully in implementation phase. Augments to the baseline system for systems to perform geophysical processing and for processing of J-ERS-1 optical data are in the design and implementation phase. The ASF provides a very effective vehicle with which to prepare for the Earth Observing System (EOS) in that it will aid the development of systems and technologies for handling the data volumes produced by the systems of the next decades, and it will also supply some of the data types that will be produced by EOS.
Analysis of ROC on chest direct digital radiography (DR) after image processing in diagnosis of SARS
NASA Astrophysics Data System (ADS)
Lv, Guozheng; Lan, Rihui; Zeng, Qingsi; Zheng, Zhong
2004-05-01
The Severe Acute Respiratory Syndrome (SARS, also called Infectious Atypical Pneumonia), which initially broke out in late 2002, has threatened the public"s health seriously. How to confirm the patients contracting SARS becomes an urgent issue in diagnosis. This paper intends to evaluate the importance of Image Processing in the diagnosis on SARS at the early stage. Receiver Operating Characteristics (ROC) analysis has been employed in this study to compare the value of DR images in the diagnosis of SARS patients before and after image processing by Symphony Software supplied by E-Com Technology Ltd., and DR image study of 72 confirmed or suspected SARS patients were reviewed respectively. All the images taken from the studied patients were processed by Symphony. Both the original and processed images were taken into ROC analysis, based on which the ROC graph for each group of images has been produced as described below: For processed images: a = 1.9745, b = 1.4275, SA = 0.8714; For original images: a = 0.9066, b = 0.8310, SA = 0.7572; (a - intercept, b - slop, SA - Area below the curve). The result shows significant difference between the original images and processed images (P<0.01). In summary, the images processed by Symphony are superior to the original ones in detecting the opacity lesion, and increases the accuracy of SARS diagnosis.
Mining Land Subsidence Monitoring Using SENTINEL-1 SAR Data
NASA Astrophysics Data System (ADS)
Yuan, W.; Wang, Q.; Fan, J.; Li, H.
2017-09-01
In this paper, DInSAR technique was used to monitor land subsidence in mining area. The study area was selected in the coal mine area located in Yuanbaoshan District, Chifeng City, and Sentinel-1 data were used to carry out DInSAR techniqu. We analyzed the interferometric results by Sentinel-1 data from December 2015 to May 2016. Through the comparison of the results of DInSAR technique and the location of the mine on the optical images, it is shown that DInSAR technique can be used to effectively monitor the land subsidence caused by underground mining, and it is an effective tool for law enforcement of over-mining.
Arctic coastal polynya observations with ERS-1 SAR and DMSP SSM/I
NASA Technical Reports Server (NTRS)
Cavalieri, D. J.; Onstott, R. G.
1993-01-01
Work to improve the characterization of the distribution of new and young sea ice types and open water amount within Arctic coastal polynyas through the combined use of ERS-1 SAR (Synthetic Aperture Radar) and DMSP SSM/I (Defense Meteorological Satellite Program Special Sensor Microwave/Imager) data is described. Two St. Lawrence Island polynya events are studied using low resolution, geocoded SAR images and coincident SSM/I data. The SAR images are analyzed in terms of polarization and spectral gradient ratios. Results of the combined analysis show that the SAR ice type classification is consistent with that from SSM/I and that the combined use of SAR and SSM/I can improve the characterization of thin ice better than either data set can do alone.
Space Radar Image of West Texas - SAR Scan
1999-04-15
This radar image of the Midland/Odessa region of West Texas, demonstrates an experimental technique, called ScanSAR, that allows scientists to rapidly image large areas of the Earth's surface. The large image covers an area 245 kilometers by 225 kilometers (152 miles by 139 miles). It was obtained by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying aboard the space shuttle Endeavour on October 5, 1994. The smaller inset image is a standard SIR-C image showing a portion of the same area, 100 kilometers by 57 kilometers (62 miles by 35 miles) and was taken during the first flight of SIR-C on April 14, 1994. The bright spots on the right side of the image are the cities of Odessa (left) and Midland (right), Texas. The Pecos River runs from the top center to the bottom center of the image. Along the left side of the image are, from top to bottom, parts of the Guadalupe, Davis and Santiago Mountains. North is toward the upper right. Unlike conventional radar imaging, in which a radar continuously illuminates a single ground swath as the space shuttle passes over the terrain, a Scansar radar illuminates several adjacent ground swaths almost simultaneously, by "scanning" the radar beam across a large area in a rapid sequence. The adjacent swaths, typically about 50 km (31 miles) wide, are then merged during ground processing to produce a single large scene. Illumination for this L-band scene is from the top of the image. The beams were scanned from the top of the scene to the bottom, as the shuttle flew from left to right. This scene was acquired in about 30 seconds. A normal SIR-C image is acquired in about 13 seconds. The ScanSAR mode will likely be used on future radar sensors to construct regional and possibly global radar images and topographic maps. The ScanSAR processor is being designed for 1996 implementation at NASA's Alaska SAR Facility, located at the University of Alaska Fairbanks, and will produce digital images from the
Wavelet Filter Banks for Super-Resolution SAR Imaging
NASA Technical Reports Server (NTRS)
Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess
2011-01-01
This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.
Use of SAR data to study active volcanoes in Alaska
Dean, K.G.; Engle, K.; Lu, Z.; Eichelberger, J.; Near, T.; Doukas, M.
1996-01-01
Synthetic Aperture Radar (SAR) data of the Westdahl, Veniaminof, and Novarupta volcanoes in the Aleutian Arc of Alaska were analysed to investigate recent surface volcanic processes. These studies support ongoing monitoring and research by the Alaska Volcano Observatory (AVO) in the North Pacific Ocean Region. Landforms and possible crustal deformation before, during, or after eruptions were detected and analysed using data from the European Remote Sensing Satellites (ERS), the Japanese Earth Resources Satellite (JERS) and the US Seasat platforms. Field observations collected by scientists from the AVO were used to verify the results from the analysis of SAR data.
NASA Technical Reports Server (NTRS)
Drinkwater, M.; Early, D.; Long, D.
1994-01-01
Coregistered ERS-1 SAR and Scatterometer data are presented for the Weddell Sea, Antarctica. Calibrated image backscatter statistics are extracted from data acquired in regions where surface measurements were made during two extensive international Weddell Sea experiments in 1992. Changes in summer ice-surface conditions, due to temperature and wind, are shown to have a large impact on observed microwave backscatter values. Winter calibrated backscatter distributions are also investigated as a way of describing ice thickness conditions in different location during winter. Coregistered SAR and EScat data over a manned drifting ice station are used to illustrate the seasonal signature changes occurring during the fall freeze-up transition.
G0-WISHART Distribution Based Classification from Polarimetric SAR Images
NASA Astrophysics Data System (ADS)
Hu, G. C.; Zhao, Q. H.
2017-09-01
Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.
NASA Astrophysics Data System (ADS)
Furuya, M.
2003-12-01
Miyakejima volcano is a basaltic strato volcano island on the eastern edge of the Philippine Sea Plate, and was undergoing a number of eruption activities over the past centuries. In July-August 2000, the Miyakejima volcano underwent a caldera collapse, prompting many modern geodetic and geophysical measurements (e.g., Geshi et al. 2002; Furuya et al. 2003). The observation results on the pre-caldera-collapse stages are, however, limitted. Were there any precursory secular subsidence before the collapse? Though Miyazaki (1990) reported a secular subsidence at the Miyakejima, using leveling technique, there are no documented reports, to my knowledge, which employed radar interferometry to examine the ground displacements at Miyakejima. Here I will report on the results derived from the radar interferometry at Miyakejima volcano. I chose JERS-1 data (L-band HH) for the analysis, so that I could get rid of the loss of coherence; most of the Miyakejima is covered with vegetation. To remove the topographic fringes as well as to re-estimate the spatial baseline data (Rosen et al. 1996), I employed 10-meter resolution digital elevation map derived by Geographical Survey Institute, Japan. I could generate 24 differential interferograms at the time of writing this text. However, I do not yet recognize any significant "signals" that can be discriminated with the atmospheric "noise". There appears to be no specific subsidence pattern, which are detected in a number of other volcanos in the world (e.g., Lu et al. 2002; Yarai et al. 2002; Okuyama et al. 2002). I am going to show a stacked interferogram like that in Fujiwara et al. (1998) and to examine the existence of volcanic signals.
A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions
Huang, Shiqi; Huang, Wenzhun; Zhang, Ting
2016-01-01
The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application. PMID:27924935
A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions.
Huang, Shiqi; Huang, Wenzhun; Zhang, Ting
2016-12-07
The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.
SAR image classification based on CNN in real and simulation datasets
NASA Astrophysics Data System (ADS)
Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin
2018-04-01
Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.
Superresolution SAR Imaging Algorithm Based on Mvm and Weighted Norm Extrapolation
NASA Astrophysics Data System (ADS)
Zhang, P.; Chen, Q.; Li, Z.; Tang, Z.; Liu, J.; Zhao, L.
2013-08-01
In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.
Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin
2016-04-07
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing
Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin
2016-01-01
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606
An Improved Method of AGM for High Precision Geolocation of SAR Images
NASA Astrophysics Data System (ADS)
Zhou, G.; He, C.; Yue, T.; Huang, W.; Huang, Y.; Li, X.; Chen, Y.
2018-05-01
In order to take full advantage of SAR images, it is necessary to obtain the high precision location of the image. During the geometric correction process of images, to ensure the accuracy of image geometric correction and extract the effective mapping information from the images, precise image geolocation is important. This paper presents an improved analytical geolocation method (IAGM) that determine the high precision geolocation of each pixel in a digital SAR image. This method is based on analytical geolocation method (AGM) proposed by X. K. Yuan aiming at realizing the solution of RD model. Tests will be conducted using RADARSAT-2 SAR image. Comparing the predicted feature geolocation with the position as determined by high precision orthophoto, results indicate an accuracy of 50m is attainable with this method. Error sources will be analyzed and some recommendations about improving image location accuracy in future spaceborne SAR's will be given.
Using ERS-2 SAR images for routine observation of marine pollution in European coastal waters.
Gade, M; Alpers, W
1999-09-30
More than 660 synthetic aperture radar (SAR) images acquired over the southern Baltic Sea, the North Sea, and the Gulf of Lion in the Mediterranean Sea by the Second European Remote Sensing Satellite (ERS-2) have been analyzed since December 1996 with respect to radar signatures of marine pollution and other phenomena causing similar signatures. First results of our analysis reveal that the seas are most polluted along the main shipping routes. The sizes of the detected oil spills vary between < 0.1 km2 and > 56 km2. SAR images acquired during descending (morning) and ascending (evening) satellite passes show different percentages of oil pollution, because most of this pollution occurs during night time and is still visible on the SAR images acquired in the morning time. Moreover, we found a higher amount of oil spills on SAR images acquired during summer (April-September) than on SAR images acquired during winter (October-March). We attribute this finding to the higher mean wind speed encountered in all three test areas during winter. By using an ERS-2 SAR image of the North Sea test area we show how the reduction of the normalized radar backscattering cross section (NRCS) by an oil spill depends on wind speed.
Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network
NASA Astrophysics Data System (ADS)
Zhang, J.; Zhang, J.; Zhao, Z.
2018-04-01
Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.
A discussion on the use of X-band SAR images in marine applications
NASA Astrophysics Data System (ADS)
Schiavulli, D.; Sorrentino, A.; Migliaccio, M.
2012-10-01
The Synthetic Aperture Radar (SAR) is able to generate images of the sea surface that can be exploited to extract geophysical information of environmental interest. In order to enhance the operational use of these data in the marine applications the revisit time is to be improved. This goal can be achieved by using SAR virtual or real constellations and/or exploiting new antenna technologies that allow huge swath and fine resolution. Within this framework, the presence of the Italian and German X-band SAR constellations is of special interest while the new SAR technologies are not nowadays operated. Although SAR images are considered to be independent of weather conditions, this is only partially true at higher frequencies, e.g. X-band. In fact, observations can present signature corresponding to high intensity precipitating clouds, i.e. rain cells. Further, ScanSAR images may be characterized by the presence of processing artifacts, called scalloping, that corrupt image interpretation. In this paper we review these key facts that are at the basis of an effective use of X-band SAR images for marine applications.
a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image
NASA Astrophysics Data System (ADS)
Li, L.; Yang, H.; Chen, Q.; Liu, X.
2018-04-01
Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.
Pseudo-color coding method for high-dynamic single-polarization SAR images
NASA Astrophysics Data System (ADS)
Feng, Zicheng; Liu, Xiaolin; Pei, Bingzhi
2018-04-01
A raw synthetic aperture radar (SAR) image usually has a 16-bit or higher bit depth, which cannot be directly visualized on 8-bit displays. In this study, we propose a pseudo-color coding method for high-dynamic singlepolarization SAR images. The method considers the characteristics of both SAR images and human perception. In HSI (hue, saturation and intensity) color space, the method carries out high-dynamic range tone mapping and pseudo-color processing simultaneously in order to avoid loss of details and to improve object identifiability. It is a highly efficient global algorithm.
Speckle noise reduction of 1-look SAR imagery
NASA Technical Reports Server (NTRS)
Nathan, Krishna S.; Curlander, John C.
1987-01-01
Speckle noise is inherent to synthetic aperture radar (SAR) imagery. Since the degradation of the image due to this noise results in uncertainties in the interpretation of the scene and in a loss of apparent resolution, it is desirable to filter the image to reduce this noise. In this paper, an adaptive algorithm based on the calculation of the local statistics around a pixel is applied to 1-look SAR imagery. The filter adapts to the nonstationarity of the image statistics since the size of the blocks is very small compared to that of the image. The performance of the filter is measured in terms of the equivalent number of looks (ENL) of the filtered image and the resulting resolution degradation. The results are compared to those obtained from different techniques applied to similar data. The local adaptive filter (LAF) significantly increases the ENL of the final image. The associated loss of resolution is also lower than that for other commonly used speckle reduction techniques.
Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations
NASA Astrophysics Data System (ADS)
Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian
2018-04-01
Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.
Phase information contained in meter-scale SAR images
NASA Astrophysics Data System (ADS)
Datcu, Mihai; Schwarz, Gottfried; Soccorsi, Matteo; Chaabouni, Houda
2007-10-01
The properties of single look complex SAR satellite images have already been analyzed by many investigators. A common belief is that, apart from inverse SAR methods or polarimetric applications, no information can be gained from the phase of each pixel. This belief is based on the assumption that we obtain uniformly distributed random phases when a sufficient number of small-scale scatterers are mixed in each image pixel. However, the random phase assumption does no longer hold for typical high resolution urban remote sensing scenes, when a limited number of prominent human-made scatterers with near-regular shape and sub-meter size lead to correlated phase patterns. If the pixel size shrinks to a critical threshold of about 1 meter, the reflectance of built-up urban scenes becomes dominated by typical metal reflectors, corner-like structures, and multiple scattering. The resulting phases are hard to model, but one can try to classify a scene based on the phase characteristics of neighboring image pixels. We provide a "cooking recipe" of how to analyze existing phase patterns that extend over neighboring pixels.
Ground Deformation near active faults in the Kinki district, southwest Japan, detected by InSAR
NASA Astrophysics Data System (ADS)
Hashimoto, M.; Ozawa, T.
2016-12-01
The Kinki district, southwest Japan, consists of ranges and plains between which active faults reside. The Osaka plain is in the middle of this district and is surrounded by the Rokko, Arima-Takatsuki, Ikoma, Kongo and Median Tectonic Line fault zones in the clockwise order. These faults are considered to be capable to generate earthquakes of larger magnitude than 7. The 1995 Kobe earthquake is the most recent activity of the Rokko fault (NE-SW trending dextral fault). Therefore the monitoring of ground deformation with high spatial resolution is essential to evaluate seismic hazards in this area. We collected and analyzed available SAR images such as ERS-1/2, Envisat, JERS-1, TerraSAR-X, ALOS/PALSAR and ALOS-2/PALSAR-2 to reveal ground deformation during these 20 years. We made DInSAR and PSInSAR analyses of these images using ASTER-GDEM ver.2. We detected three spots of subsidence along the Arima-Takatsuki fault (ENE-WSW trending dextral fault, east neighbor of the Rokko fault) after the Kobe earthquake, which continued up to 2010. Two of them started right after the Kobe earthquake, while the easternmost one was observed after 2000. However, we did not find them in the interferograms of ALOS-2/PALSAR-2 acquired during 2014 - 2016. Marginal uplift was recognized along the eastern part of the Rokko fault. PS-InSAR results of ALOS/PALSAR also revealed slight uplift north of the Rokko Mountain that uplift by 20 cm coseismically. These observations suggest that the Rokko Mountain might have uplifted during the postseismic period. We found subsidence on the eastern frank of the Kongo Mountain, where the Kongo fault (N-S trending reverse fault) exits. In the southern neighbor of the Median Tectonic Line (ENE-WSW trending dextral fault), uplift of > 5 mm/yr was found by Envisat and ALOS/PALSAR images. This area is shifted westward by 4 mm/yr as well. Since this area is located east of a seismically active area in the northwestern Wakayama prefecture, this deformation
The Grand Banks ERS-1 SAR wave spectra validation experiment
NASA Technical Reports Server (NTRS)
Vachon, P. W.; Dobson, F. W.; Smith, S. D.; Anderson, R. J.; Buckley, J. R.; Allingham, M.; Vandemark, D.; Walsh, E. J.; Khandekar, M.; Lalbeharry, R.
1993-01-01
As part of the ERS-1 validation program, the ERS-1 Synthetic Aperture Radar (SAR) wave spectra validation experiment was carried out over the Grand Banks of Newfoundland (Canada) in Nov. 1991. The principal objective of the experiment was to obtain complete sets of wind and wave data from a variety of calibrated instruments to validate SAR measurements of ocean wave spectra. The field program activities are described and the rather complex wind and wave conditions which were observed are summarized. Spectral comparisons with ERS-1 SAR image spectra are provided. The ERS-1 SAR is shown to have measured swell and range traveling wind seas, but did not measure azimuth traveling wind seas at any time during the experiment. Results of velocity bunching forward mapping and new measurements of the relationship between wind stress and sea state are also shown.
SAR image segmentation using skeleton-based fuzzy clustering
NASA Astrophysics Data System (ADS)
Cao, Yun Yi; Chen, Yan Qiu
2003-06-01
SAR image segmentation can be converted to a clustering problem in which pixels or small patches are grouped together based on local feature information. In this paper, we present a novel framework for segmentation. The segmentation goal is achieved by unsupervised clustering upon characteristic descriptors extracted from local patches. The mixture model of characteristic descriptor, which combines intensity and texture feature, is investigated. The unsupervised algorithm is derived from the recently proposed Skeleton-Based Data Labeling method. Skeletons are constructed as prototypes of clusters to represent arbitrary latent structures in image data. Segmentation using Skeleton-Based Fuzzy Clustering is able to detect the types of surfaces appeared in SAR images automatically without any user input.
Flight path-driven mitigation of wavefront curvature effects in SAR images
Doerry, Armin W [Albuquerque, NM
2009-06-23
A wavefront curvature effect associated with a complex image produced by a synthetic aperture radar (SAR) can be mitigated based on which of a plurality of possible flight paths is taken by the SAR when capturing the image. The mitigation can be performed differently for different ones of the flight paths.
Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models
NASA Astrophysics Data System (ADS)
La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole
2016-08-01
Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).
Investigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong
NASA Astrophysics Data System (ADS)
Zhu, Wu; Ding, Xiao-Li; Jung, Hyung-Sup; Zhang, Qin; Zhang, Bo-Chen; Qu, Wei
2016-08-01
Synthetic Aperture Radar Interferometry (InSAR) has demonstrated its potential for high-density spatial mapping of ground displacement associated with earthquakes, volcanoes, and other geologic processes. However, this technique may be affected by the ionosphere, which can result in the distortions of Synthetic Aperture Radar (SAR) images, phases, and polarization. Moreover, ionospheric effect has become and is becoming further significant with the increasing interest in low-frequency SAR systems, limiting the further development of InSAR technique. Although some research has been carried out, thorough analysis of ionospheric influence on true SAR imagery is still limited. Based on this background, this study performs a thorough investigation of ionospheric effect on InSAR through processing L-band ALOS-1/PALSAR-1 images and dual-frequency Global Positioning System (GPS) data over Hong Kong, where the phenomenon of ionospheric irregularities often occurs. The result shows that the small-scale ionospheric irregularities can cause the azimuth pixel shifts and phase advance errors on interferograms. Meanwhile, it is found that these two effects result in the stripe-shaped features in InSAR images. The direction of the stripe-shaped effects keep approximately constant in space for our InSAR dataset. Moreover, the GPS-derived rate of total electron content change index (ROTI), an index to reflect the level of ionospheric disturbances, may be a useful indicator for predicting the ionospheric effect for SAR images. This finding can help us evaluate the quality of SAR images when considering the ionospheric effect.
Tie Points Extraction for SAR Images Based on Differential Constraints
NASA Astrophysics Data System (ADS)
Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.
2018-04-01
Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.
Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps
NASA Astrophysics Data System (ADS)
Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.
2018-04-01
Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.
A comparative study on methods of improving SCR for ship detection in SAR image
NASA Astrophysics Data System (ADS)
Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li
2017-10-01
Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.
Zheng, Minxue; Fukuyama, Kaoru; Sanga-Ngoie, Kazadi
2013-12-31
Spatial variation and temporal changes in ground subsidence over the Nobi Plain, Central Japan, are assessed using GIS techniques and ground level measurements data taken over this area since the 1970s. Notwithstanding the general slowing trend observed in ground subsidence over the plains, we have detected ground rise at some locations, more likely due to the ground expansion because of recovering groundwater levels and the tilting of the Nobi land mass. The problem of non-availability of upper-air meteorological information, especially the 3-dimensional water vapor distribution, during the JERS-1 observational period (1992-1998) was solved by applying the AWC (analog weather charts) method onto the high-precision GPV-MSM (Grid Point Value of Meso-Scale Model) water-vapor data to find the latter's matching meteorological data. From the selected JERS-1 interferometry pair and the matching GPV-MSM meteorological data, the atmospheric path delay generated by water vapor inhomogeneity was then quantitatively evaluated. A highly uniform spatial distribution of the atmospheric delay, with a maximum deviation of approximately 38 mm in its horizontal distribution was found over the Plain. This confirms the effectiveness of using GPV-MSM data for SAR differential interferometric analysis, and sheds thus some new light on the possibility of improving InSAR analysis results for land subsidence applications.
Zheng, Minxue; Fukuyama, Kaoru; Sanga-Ngoie, Kazadi
2014-01-01
Spatial variation and temporal changes in ground subsidence over the Nobi Plain, Central Japan, are assessed using GIS techniques and ground level measurements data taken over this area since the 1970s. Notwithstanding the general slowing trend observed in ground subsidence over the plains, we have detected ground rise at some locations, more likely due to the ground expansion because of recovering groundwater levels and the tilting of the Nobi land mass. The problem of non-availability of upper-air meteorological information, especially the 3-dimensional water vapor distribution, during the JERS-1 observational period (1992–1998) was solved by applying the AWC (analog weather charts) method onto the high-precision GPV-MSM (Grid Point Value of Meso-Scale Model) water-vapor data to find the latter's matching meteorological data. From the selected JERS-1 interferometry pair and the matching GPV-MSM meteorological data, the atmospheric path delay generated by water vapor inhomogeneity was then quantitatively evaluated. A highly uniform spatial distribution of the atmospheric delay, with a maximum deviation of approximately 38 mm in its horizontal distribution was found over the Plain. This confirms the effectiveness of using GPV-MSM data for SAR differential interferometric analysis, and sheds thus some new light on the possibility of improving InSAR analysis results for land subsidence applications. PMID:24385028
Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points - A Review.
Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli
2009-01-01
Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.
Separated Component-Based Restoration of Speckled SAR Images
2013-01-01
unsupervised change detection from SAR amplitude imagery,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 10, pp. 2972–2982, Oct. 2006. [5] F. Argenti , T...Sens., vol. 40, no. 10, pp. 2196–2212, Oct. 2002. [13] F. Argenti and L. Alparone, “Speckle removal from SAR images in the undecimated wavelet domain...iterative thresh- olding algorithm for linear inverse problems with a sparsity con- straint,” Commun . Pure Appl. Math., vol. 57, no. 11, pp. 1413
Spacecraft on-board SAR image generation for EOS-type missions
NASA Technical Reports Server (NTRS)
Liu, K. Y.; Arens, W. E.; Assal, H. M.; Vesecky, J. F.
1987-01-01
Spacecraft on-board synthetic aperture radar (SAR) image generation is an extremely difficult problem because of the requirements for high computational rates (usually on the order of Giga-operations per second), high reliability (some missions last up to 10 years), and low power dissipation and mass (typically less than 500 watts and 100 Kilograms). Recently, a JPL study was performed to assess the feasibility of on-board SAR image generation for EOS-type missions. This paper summarizes the results of that study. Specifically, it proposes a processor architecture using a VLSI time-domain parallel array for azimuth correlation. Using available space qualifiable technology to implement the proposed architecture, an on-board SAR processor having acceptable power and mass characteristics appears feasible for EOS-type applications.
Wavelet Analysis of SAR Images for Coastal Monitoring
NASA Technical Reports Server (NTRS)
Liu, Antony K.; Wu, Sunny Y.; Tseng, William Y.; Pichel, William G.
1998-01-01
The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.
An automatic target recognition system based on SAR image
NASA Astrophysics Data System (ADS)
Li, Qinfu; Wang, Jinquan; Zhao, Bo; Luo, Furen; Xu, Xiaojian
2009-10-01
In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR research. To establish an integral and available system, the processing of SAR image was divided into four main stages which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.
Sea bottom topography imaging with SAR
NASA Technical Reports Server (NTRS)
Vanderkooij, M. W. A.; Wensink, G. J.; Vogelzang, J.
1992-01-01
It is well known that under favorable meteorological and hydrodynamical conditions the bottom topography of shallow seas can be mapped with airborne or spaceborne imaging radar. This phenomenon was observed for the first time in 1969 by de Loor and co-workers in Q-band Side Looking Airborne Radar (SLAR) imagery of sandwaves in the North Sea. It is now generally accepted that the imaging mechanism consists of three steps: (1) interaction between (tidal) current and bottom topography causes spatial modulations in the surface current velocity; (2) modulations in the surface current velocity give rise to variations in the spectrum of wind-generated waves, as described by the action balance equation; and (3) variations in the wave spectrum show up as intensity modulations in radar imagery. In order to predict radar backscatter modulations caused by sandwaves, an imaging model, covering the three steps, was developed by the Dutch Sea Bottom Topography Group. This model and some model results will be shown. On 16 Aug. 1989 an experiment was performed with the polarimetric P-, L-, and C-band synthetic aperture radar (SAR) of NASA/JPL. One scene was recorded in SAR mode. On 12 Jul. 1991 another three scenes were recorded, of which one was in the ATI-mode (Along-Track Interferometer). These experiments took place in the test area of the Sea Bottom Topography Group, 30 km off the Dutch coast, where the bottom topography is dominated by sand waves. In-situ data were gathered by a ship in the test area and on 'Measuring Platform Noordwijk', 20 km from the center of the test area. The radar images made during the experiment were compared with digitized maps of the bottom. Furthermore, the profiles of radar backscatter modulation were compared with the results of the model. During the workshop some preliminary results of the ATI measurements will be shown.
On the appropriate feature for general SAR image registration
NASA Astrophysics Data System (ADS)
Li, Dong; Zhang, Yunhua
2012-09-01
An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed, the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation, and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for general SAR image registration.
On the Implementation of a Land Cover Classification System for SAR Images Using Khoros
NASA Technical Reports Server (NTRS)
Medina Revera, Edwin J.; Espinosa, Ramon Vasquez
1997-01-01
The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.
Change detection of polarimetric SAR images based on the KummerU Distribution
NASA Astrophysics Data System (ADS)
Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping
2014-11-01
In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.
NASA Astrophysics Data System (ADS)
Crosetto, M.; Budillon, A.; Johnsy, A.; Schirinzi, G.; Devanthéry, N.; Monserrat, O.; Cuevas-González, M.
2018-04-01
A lot of research and development has been devoted to the exploitation of satellite SAR images for deformation measurement and monitoring purposes since Differential Interferometric Synthetic Apertura Radar (InSAR) was first described in 1989. In this work, we consider two main classes of advanced DInSAR techniques: Persistent Scatterer Interferometry and Tomographic SAR. Both techniques make use of multiple SAR images acquired over the same site and advanced procedures to separate the deformation component from the other phase components, such as the residual topographic component, the atmospheric component, the thermal expansion component and the phase noise. TomoSAR offers the advantage of detecting either single scatterers presenting stable proprieties over time (Persistent Scatterers) and multiple scatterers interfering within the same range-azimuth resolution cell, a significant improvement for urban areas monitoring. This paper addresses a preliminary inter-comparison of the results of both techniques, for a test site located in the metropolitan area of Barcelona (Spain), where interferometric Sentinel-1 data were analysed.
Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling.
Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng
2016-07-14
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath.
Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling
Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng
2016-01-01
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974
Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region
Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao
2017-01-01
Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure–up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data. PMID:28587066
3D Tomographic SAR Imaging in Densely Vegetated Mountainous Rural Areas in China and Sweden
NASA Astrophysics Data System (ADS)
Feng, L.; Muller, J. P., , Prof
2017-12-01
3D SAR Tomography (TomoSAR) and 4D SAR Differential Tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to unscramble complex scenes with multiple scatterers mapped into the same SAR cell. In addition to this 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas, and recent cryospheric ice investigations, emerging tomographic remote sensing applications include forest applications, e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to develop solutions for temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China and L and P band airborne SAR data (BioSAR 2008 - ESA) in the Krycklan river catchment, Northern Sweden. The new TanDEM-X 12m DEM is used to assist co - registration of all the data stacks over China first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract
SAR image formation with azimuth interpolation after azimuth transform
Doerry,; Armin W. , Martin; Grant D. , Holzrichter; Michael, W [Albuquerque, NM
2008-07-08
Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.
Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review
Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli
2009-01-01
Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram. PMID:22399966
Significant wave heights from Sentinel-1 SAR: Validation and applications
NASA Astrophysics Data System (ADS)
Stopa, J. E.; Mouche, A.
2017-03-01
Two empirical algorithms are developed for wave mode images measured from the synthetic aperture radar aboard Sentinel-1 A. The first method, called CWAVE_S1A, is an extension of previous efforts developed for ERS2 and the second method, called Fnn, uses the azimuth cutoff among other parameters to estimate significant wave heights (Hs) and average wave periods without using a modulation transfer function. Neural networks are trained using colocated data generated from WAVEWATCH III and independently verified with data from altimeters and in situ buoys. We use neural networks to relate the nonlinear relationships between the input SAR image parameters and output geophysical wave parameters. CWAVE_S1A performs well and has reduced precision compared to Fnn with Hs root mean square errors within 0.5 and 0.6 m, respectively. The developed neural networks extend the SAR's ability to retrieve useful wave information under a large range of environmental conditions including extratropical and tropical cyclones in which Hs estimation is traditionally challenging.
Large Scale Assessment of Radio Frequency Interference Signatures in L-band SAR Data
NASA Astrophysics Data System (ADS)
Meyer, F. J.; Nicoll, J.
2011-12-01
Imagery of L-band Synthetic Aperture Radar (SAR) systems such as the PALSAR sensor on board the Advanced Land Observing Satellite (ALOS) has proven to be a valuable tool for observing environmental changes around the globe. Besides offering 24/7 operability, the L-band frequency provides improved interferometric coherence, and L-band polarimetric data has shown great potential for vegetation monitoring, sea ice classification, and the observation of glaciers and ice sheets. To maximize the benefit of missions such as ALOS PALSAR for environmental monitoring, data consistency and calibration are vital. Unfortunately, radio frequency interference (RFI) signatures from ground-based radar systems regularly impair L-band SAR data quality and consistency. With this study we present a large-scale analysis of typical RFI signatures that are regularly observed in L-band SAR data over the Americas. Through a study of the vast archive of L-band SAR data in the US Government Research Consortium (USGRC) data pool at the Alaska Satellite Facility (ASF) we were able to address the following research goals: 1. Assessment of RFI Signatures in L-band SAR data and their Effects on SAR Data Quality: An analysis of time-frequency properties of RFI signatures in L-band SAR data of the USGRC data pool is presented. It is shown that RFI-filtering algorithms implemented in the operational ALOS PALSAR processor are not sufficient to remove all RFI-related artifacts. In examples, the deleterious effects of RFI on SAR image quality, polarimetric signature, SAR phase, and interferometric coherence are presented. 2. Large-Scale Assessment of Severity, Spatial Distribution, and Temporal Variation of RFI Signatures in L-band SAR data: L-band SAR data in the USGRC data pool were screened for RFI using a custom algorithm. Per SAR frame, the algorithm creates geocoded frame bounding boxes that are color-coded according to RFI intensity and converted to KML files for analysis in Google Earth. From
Doerry, Armin W.; Heard, Freddie E.; Cordaro, J. Thomas
2010-07-20
Motion measurement errors that extend beyond the range resolution of a synthetic aperture radar (SAR) can be corrected by effectively decreasing the range resolution of the SAR in order to permit measurement of the error. Range profiles can be compared across the slow-time dimension of the input data in order to estimate the error. Once the error has been determined, appropriate frequency and phase correction can be applied to the uncompressed input data, after which range and azimuth compression can be performed to produce a desired SAR image.
The artificial object detection and current velocity measurement using SAR ocean surface images
NASA Astrophysics Data System (ADS)
Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey
2017-10-01
Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.
NASA Technical Reports Server (NTRS)
Steffen, Konrad; Heinrichs, John
1994-01-01
Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.
Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.
Guo, Hao; Wu, Danni; An, Jubai
2017-08-09
Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.
Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN
An, Jubai
2017-01-01
Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features. PMID:28792477
Advanced Interferometric Synthetic Aperture Imaging Radar (InSAR) for Dune Mapping
NASA Astrophysics Data System (ADS)
Havivi, Shiran; Amir, Doron; Schvartzman, Ilan; August, Yitzhak; Mamman, Shimrit; Rotman, Stanely R.; Blumberg, Dan G.
2016-04-01
Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of
Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD
NASA Astrophysics Data System (ADS)
Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun
2017-12-01
This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.
Autofocus algorithm for curvilinear SAR imaging
NASA Astrophysics Data System (ADS)
Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.
2012-05-01
We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.
Titan Topography: A Comparison Between Cassini Altimeter and SAR Imaging from Two Titan Flybys
NASA Astrophysics Data System (ADS)
Gim, Y.; Stiles, B.; Callahan, P. S.; Johnson, W. T.; Hensley, S.; Hamilton, G.; West, R.; Alberti, G.; Flamini, E.; Lorenz, R. D.; Zebker, H. A.; Cassini RADAR Team
2007-12-01
The Cassini RADAR has collected twelve altimeter data sets of Titan since the beginning of the Saturn Tour in 2004. Most of the altimeter measurements were made at high altitudes, from 4,000 km to 15,000 km, resulting in low spatial resolutions due to beam footprint sizes larger than 20 km, as well as short ground tracks less than 600 km. One flyby (T30) was dedicated to altimeter data collection from 15,000 km to the closest approach altitude of 950 km. This produced a beam footprint size of 6 km at the lowest altitude and an altimeter ground track of about 3,500 km covering Titan's surface from near the equator to high latitude areas near Titan's north pole. More importantly, the ground track is located inside the SAR swath viewed from an earlier Titan flyby (T28). This provides a rare opportunity to investigate Titan topography with a relatively high spatial resolution and compare nadir-looking altimeter data with side-looking SAR imaging. From altimeter data, we have measured the mean Titan radius of 2575.1 km +/- 0.1 km and observed rather complex topographical variations over a short distance. By comparing altimeter data and SAR images at altitudes below 2,000 km, we have found that there is a strong correlation between SAR brightness and altimeter waveform; SAR dark areas correspond to strong and sharp altimeter waveforms while SAR bright areas correspond to weak and diffused altimeter waveforms. The research described here was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location
NASA Astrophysics Data System (ADS)
Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman
2018-04-01
Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.
NASA Astrophysics Data System (ADS)
Wang, P.; Xing, C.
2018-04-01
In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D) plane coordinate system with the common three-dimensional (3D) terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.
Fast iterative censoring CFAR algorithm for ship detection from SAR images
NASA Astrophysics Data System (ADS)
Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng
2017-11-01
Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.
NASA Technical Reports Server (NTRS)
Evans, Diane L. (Editor); Plaut, Jeffrey (Editor)
1996-01-01
The Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) is the most advanced imaging radar system to fly in Earth orbit. Carried in the cargo bay of the Space Shuttle Endeavour in April and October of 1994, SIR-C/X-SAR simultaneously recorded SAR data at three wavelengths (L-, C-, and X-bands; 23.5, 5.8, and 3.1 cm, respectively). The SIR-C/X-SAR Science Team consists of 53 investigator teams from more than a dozen countries. Science investigations were undertaken in the fields of ecology, hydrology, ecology, and oceanography. This report contains 44 investigator team reports and several additional reports from coinvestigators and other researchers.
Processor architecture for airborne SAR systems
NASA Technical Reports Server (NTRS)
Glass, C. M.
1983-01-01
Digital processors for spaceborne imaging radars and application of the technology developed for airborne SAR systems are considered. Transferring algorithms and implementation techniques from airborne to spaceborne SAR processors offers obvious advantages. The following topics are discussed: (1) a quantification of the differences in processing algorithms for airborne and spaceborne SARs; and (2) an overview of three processors for airborne SAR systems.
SAR and scan-time optimized 3D whole-brain double inversion recovery imaging at 7T.
Pracht, Eberhard D; Feiweier, Thorsten; Ehses, Philipp; Brenner, Daniel; Roebroeck, Alard; Weber, Bernd; Stöcker, Tony
2018-05-01
The aim of this project was to implement an ultra-high field (UHF) optimized double inversion recovery (DIR) sequence for gray matter (GM) imaging, enabling whole brain coverage in short acquisition times ( ≈5 min, image resolution 1 mm 3 ). A 3D variable flip angle DIR turbo spin echo (TSE) sequence was optimized for UHF application. We implemented an improved, fast, and specific absorption rate (SAR) efficient TSE imaging module, utilizing improved reordering. The DIR preparation was tailored to UHF application. Additionally, fat artifacts were minimized by employing water excitation instead of fat saturation. GM images, covering the whole brain, were acquired in 7 min scan time at 1 mm isotropic resolution. SAR issues were overcome by using a dedicated flip angle calculation considering SAR and SNR efficiency. Furthermore, UHF related artifacts were minimized. The suggested sequence is suitable to generate GM images with whole-brain coverage at UHF. Due to the short total acquisition times and overall robustness, this approach can potentially enable DIR application in a routine setting and enhance lesion detection in neurological diseases. Magn Reson Med 79:2620-2628, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
First Image Products from EcoSAR - Osa Peninsula, Costa Rica
NASA Technical Reports Server (NTRS)
Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon
2016-01-01
Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.
Comparative Study of Speckle Filtering Methods in PolSAR Radar Images
NASA Astrophysics Data System (ADS)
Boutarfa, S.; Bouchemakh, L.; Smara, Y.
2015-04-01
Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria
SAR Image Change Detection Based on Fuzzy Markov Random Field Model
NASA Astrophysics Data System (ADS)
Zhao, J.; Huang, G.; Zhao, Z.
2018-04-01
Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels. So the change detection results are susceptible to image noise, and the detection effect is not ideal. Markov Random Field (MRF) can make full use of the spatial dependence of image pixels and improve detection accuracy. When segmenting the difference image, different categories of regions have a high degree of similarity at the junction of them. It is difficult to clearly distinguish the labels of the pixels near the boundaries of the judgment area. In the traditional MRF method, each pixel is given a hard label during iteration. So MRF is a hard decision in the process, and it will cause loss of information. This paper applies the combination of fuzzy theory and MRF to the change detection of SAR images. The experimental results show that the proposed method has better detection effect than the traditional MRF method.
NASA Astrophysics Data System (ADS)
Zhao, Xia; Wang, Guang-xin
2008-12-01
Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.
SAR image change detection using watershed and spectral clustering
NASA Astrophysics Data System (ADS)
Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie
2011-12-01
A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.
Extraction of lead and ridge characteristics from SAR images of sea ice
NASA Technical Reports Server (NTRS)
Vesecky, John F.; Smith, Martha P.; Samadani, Ramin
1990-01-01
Image-processing techniques for extracting the characteristics of lead and pressure ridge features in SAR images of sea ice are reported. The methods are applied to a SAR image of the Beaufort Sea collected from the Seasat satellite on October 3, 1978. Estimates of lead and ridge statistics are made, e.g., lead and ridge density (number of lead or ridge pixels per unit area of image) and the distribution of lead area and orientation as well as ridge length and orientation. The information derived is useful in both ice science and polar operations for such applications as albedo and heat and momentum transfer estimates, as well as ship routing and offshore engineering.
Lu, Z.; Kwoun, Oh-Ig
2008-01-01
Detailed analysis of C-band European Remote Sensing 1 and 2 (ERS-1/ERS-2) and Radarsat-1 interferometric synthetic aperture radar (InSAR) imagery was conducted to study water-level changes of coastal wetlands of southeastern Louisiana. Radar backscattering and InSAR coherence suggest that the dominant radar backscattering mechanism for swamp forest and saline marsh is double-bounce backscattering, implying that InSAR images can be used to estimate water-level changes with unprecedented spatial details. On the one hand, InSAR images suggest that water-level changes over the study site can be dynamic and spatially heterogeneous and cannot be represented by readings from sparsely distributed gauge stations. On the other hand, InSAR phase measurements are disconnected by structures and other barriers and require absolute water-level measurements from gauge stations or other sources to convert InSAR phase values to absolute water-level changes. ?? 2006 IEEE.
Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model
NASA Astrophysics Data System (ADS)
Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Eerdenbrugh, Katrien Van; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; Baets, Bernard De; Bates, Paul D.; Verhoest, Niko E. C.
2017-02-01
Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modelled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.
Impact of the Timing of a SAR Image Acquisition on the Calibration of a Flood Inundation Model
NASA Technical Reports Server (NTRS)
Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Van Eerdenbrugh, Katrien; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; De Baets, Bernard;
2016-01-01
Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modeled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.
An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery
Leng, Xiangguang; Ji, Kefeng; Zhou, Shilin; Xing, Xiangwei; Zou, Huanxin
2016-01-01
With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way. PMID:27563902
Spaceborne imaging radar research in the 90's
NASA Technical Reports Server (NTRS)
Elachi, Charles
1986-01-01
The imaging radar experiments on SEASAT and on the space shuttle (SIR-A and SIR-B) have led to a wide interest in the use of spaceborne imaging radars in Earth and planetary sciences. The radar sensors provide unique and complimentary information to what is acquired with visible and infrared imagers. This includes subsurface imaging in arid regions, all weather observation of ocean surface dynamic phenomena, structural mapping, soil moisture mapping, stereo imaging and resulting topographic mapping. However, experiments up to now have exploited only a very limited range of the generic capability of radar sensors. With planned sensor developments in the late 80's and early 90's, a quantum jump will be made in our ability to fully exploit the potential of these sensors. These developments include: multiparameter research sensors such as SIR-C and X-SAR, long-term and global monitoring sensors such as ERS-1, JERS-1, EOS, Radarsat, GLORI and the spaceborne sounder, planetary mapping sensors such as the Magellan and Cassini/Titan mappers, topographic three-dimensional imagers such as the scanning radar altimeter and three-dimensional rain mapping. These sensors and their associated research are briefly described.
Theory and measure of certain image norms in SAR
NASA Technical Reports Server (NTRS)
Raney, R. K.
1984-01-01
The principal properties of synthetic aperture radar SAR imagery of point and distributed objects are summarized. Against this background, the response of a SAR (Synthetic Aperture Radar) to the moving surface of the sea is considered. Certain conclusions are drawn as to the mechanism of interaction between microwaves and the sea surface. Focus and speckle spectral tests may be used on selected SAR imagery for areas of the ocean. The fine structure of the sea imagery is sensitive to processor focus and adjustment. The ocean reflectivity mechanism must include point like scatterers of sufficient radar cross section to dominate the return from certain individual resolution elements. Both specular and diffuse scattering mechanisms are observed together, to varying degree. The effect is sea state dependent. Several experiments are proposed based on imaging theory that could assist in the investigation of reflectivity mechanisms.
Target discrimination method for SAR images based on semisupervised co-training
NASA Astrophysics Data System (ADS)
Wang, Yan; Du, Lan; Dai, Hui
2018-01-01
Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.
Mathematical modeling and SAR simulation multifunction SAR technology efforts
NASA Technical Reports Server (NTRS)
Griffin, C. R.; Estes, J. M.
1981-01-01
The orbital SAR (synthetic aperture radar) simulation data was used in several simulation efforts directed toward advanced SAR development. Efforts toward simulating an operational radar, simulation of antenna polarization effects, and simulation of SAR images at serveral different wavelengths are discussed. Avenues for improvements in the orbital SAR simulation and its application to the development of advanced digital radar data processing schemes are indicated.
SAR Reduction in 7T C-Spine Imaging Using a “Dark Modes” Transmit Array Strategy
Eryaman, Yigitcan; Guerin, Bastien; Keil, Boris; Mareyam, Azma; Herraiz, Joaquin L.; Kosior, Robert K.; Martin, Adrian; Torrado-Carvajal, Angel; Malpica, Norberto; Hernandez-Tamames, Juan A.; Schiavi, Emanuele; Adalsteinsson, Elfar; Wald, Lawrence L.
2016-01-01
Purpose Local specific absorption rate (SAR) limits many applications of parallel transmit (pTx) in ultra high-field imaging. In this Note, we introduce the use of an array element, which is intentionally inefficient at generating spin excitation (a “dark mode”) to attempt a partial cancellation of the electric field from those elements that do generate excitation. We show that adding dipole elements oriented orthogonal to their conventional orientation to a linear array of conventional loop elements can lower the local SAR hotspot in a C-spine array at 7 T. Methods We model electromagnetic fields in a head/torso model to calculate SAR and excitation B1+ patterns generated by conventional loop arrays and loop arrays with added electric dipole elements. We utilize the dark modes that are generated by the intentional and inefficient orientation of dipole elements in order to reduce peak 10g local SAR while maintaining excitation fidelity. Results For B1+ shimming in the spine, the addition of dipole elements did not significantly alter the B1+ spatial pattern but reduced local SAR by 36%. Conclusion The dipole elements provide a sufficiently complimentary B1+ and electric field pattern to the loop array that can be exploited by the radiofrequency shimming algorithm to reduce local SAR. PMID:24753012
NASA Astrophysics Data System (ADS)
Yague-Martinez, N.; Fielding, E. J.; Haghshenas-Haghighi, M.; Cong, X.; Motagh, M.
2014-12-01
This presentation will address the 24 September 2013 Mw 7.7 Balochistan Earthquake in western Pakistan from the point of view of interferometric processing algorithms of wide-swath TerraSAR-X ScanSAR images. The algorithms are also valid for TOPS acquisition mode, the operational mode of the Sentinel-1A ESA satellite that was successfully launched in April 2014. Spectral properties of burst-mode data and an overview of the interferometric processing steps of burst-mode acquisitions, emphasizing the importance of the co-registration stage, will be provided. A co-registration approach based on incoherent cross-correlation will be presented and applied to seismic scenarios. Moreover geodynamic corrections due to differential atmospheric path delay and differential solid Earth tides are considered to achieve accuracy in the order of several centimeters. We previously derived a 3D displacement map using cross-correlation techniques applied to optical images from Landsat-8 satellite and TerraSAR-X ScanSAR amplitude images. The Landsat-8 cross-correlation measurements cover two horizontal directions, and the TerraSAR-X displacements include both horizontal along-track and slant-range (radar line-of-sight) measurements that are sensitive to vertical and horizontal deformation. It will be justified that the co-seismic displacement map from TerraSAR-X ScanSAR data may be contaminated by postseismic deformation due to the fact that the post-seismic acquisition took place one month after the main shock, confirmed in part by a TerraSAR-X stripmap interferogram (processed with conventional InSAR) covering part of the area starting on 27 September 2013. We have arranged the acquisition of a burst-synchronized stack of TerraSAR-X ScanSAR images over the affected area after the earthquake. It will be possible to apply interferometry to these data to measure the lower magnitude of the expected postseismic displacements. The processing of single interferograms will be discussed. A
Synthetic Aperture Radar (SAR) data processing
NASA Technical Reports Server (NTRS)
Beckner, F. L.; Ahr, H. A.; Ausherman, D. A.; Cutrona, L. J.; Francisco, S.; Harrison, R. E.; Heuser, J. S.; Jordan, R. L.; Justus, J.; Manning, B.
1978-01-01
The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.
Contextual descriptors and neural networks for scene analysis in VHR SAR images
NASA Astrophysics Data System (ADS)
Del Frate, Fabio; Picchiani, Matteo; Falasco, Alessia; Schiavon, Giovanni
2016-10-01
The development of SAR technology during the last decade has made it possible to collect a huge amount of data over many regions of the world. In particular, the availability of SAR images from different sensors, with metric or sub-metric spatial resolution, offers novel opportunities in different fields as land cover, urban monitoring, soil consumption etc. On the other hand, automatic approaches become crucial for the exploitation of such a huge amount of information. In such a scenario, especially if single polarization images are considered, the main issue is to select appropriate contextual descriptors, since the backscattering coefficient of a single pixel may not be sufficient to classify an object on the scene. In this paper a comparison among three different approaches for contextual features definition is presented so as to design optimum procedures for VHR SAR scene understanding. The first approach is based on Gray Level Co- Occurrence Matrix since it is widely accepted and several studies have used it for land cover classification with SAR data. The second approach is based on the Fourier spectra and it has been already proposed with positive results for this kind of problems, the third one is based on Auto-associative Neural Networks which have been already proven effective for features extraction from polarimetric SAR images. The three methods are evaluated in terms of the accuracy of the classified scene when the features extracted using each method are considered as input to a neural network classificator and applied on different Cosmo-SkyMed spotlight products.
Generalized interpretation scheme for arbitrary HR InSAR image pairs
NASA Astrophysics Data System (ADS)
Boldt, Markus; Thiele, Antje; Schulz, Karsten
2013-10-01
Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.
DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI
NASA Astrophysics Data System (ADS)
He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun
2009-10-01
The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.
Ship Detection from Ocean SAR Image Based on Local Contrast Variance Weighted Information Entropy
Huang, Yulin; Pei, Jifang; Zhang, Qian; Gu, Qin; Yang, Jianyu
2018-01-01
Ship detection from synthetic aperture radar (SAR) images is one of the crucial issues in maritime surveillance. However, due to the varying ocean waves and the strong echo of the sea surface, it is very difficult to detect ships from heterogeneous and strong clutter backgrounds. In this paper, an innovative ship detection method is proposed to effectively distinguish the vessels from complex backgrounds from a SAR image. First, the input SAR image is pre-screened by the maximally-stable extremal region (MSER) method, which can obtain the ship candidate regions with low computational complexity. Then, the proposed local contrast variance weighted information entropy (LCVWIE) is adopted to evaluate the complexity of those candidate regions and the dissimilarity between the candidate regions with their neighborhoods. Finally, the LCVWIE values of the candidate regions are compared with an adaptive threshold to obtain the final detection result. Experimental results based on measured ocean SAR images have shown that the proposed method can obtain stable detection performance both in strong clutter and heterogeneous backgrounds. Meanwhile, it has a low computational complexity compared with some existing detection methods. PMID:29652863
Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortel, Pierre-François; Liu, Jiaen
2014-01-01
Elevated Specific Absorption Rate (SAR) associated with increased main magnetic field strength remains as a major safety concern in ultra-high-field (UHF) Magnetic Resonance Imaging (MRI) applications. The calculation of local SAR requires the knowledge of the electric field induced by radiofrequency (RF) excitation, and the local electrical properties of tissues. Since electric field distribution cannot be directly mapped in conventional MR measurements, SAR estimation is usually performed using numerical model-based electromagnetic simulations which, however, are highly time consuming and cannot account for the specific anatomy and tissue properties of the subject undergoing a scan. In the present study, starting from the measurable RF magnetic fields (B1) in MRI, we conducted a series of mathematical deduction to estimate the local, voxel-wise and subject-specific SAR for each single coil element using a multi-channel transceiver array coil. We first evaluated the feasibility of this approach in numerical simulations including two different human head models. We further conducted experimental study in a physical phantom and in two human subjects at 7T using a multi-channel transceiver head coil. Accuracy of the results is discussed in the context of predicting local SAR in the human brain at UHF MRI using multi-channel RF transmission. PMID:23508259
Estimating Velocities of Glaciers Using Sentinel-1 SAR Imagery
NASA Astrophysics Data System (ADS)
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.
SAR Image Simulation of Ship Targets Based on Multi-Path Scattering
NASA Astrophysics Data System (ADS)
Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.
2018-04-01
Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.
Investigation of Joint Visibility Between SAR and Optical Images of Urban Environments
NASA Astrophysics Data System (ADS)
Hughes, L. H.; Auer, S.; Schmitt, M.
2018-05-01
In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.
NASA Technical Reports Server (NTRS)
Premkumar, A. B.; Purviance, J. E.
1990-01-01
A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.
Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong
2018-01-31
Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.
Zhou, Rui; Hu, Yuxin; Qi, Yaolong
2018-01-01
Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm. PMID:29385059
A novel framework for change detection in bi-temporal polarimetric SAR images
NASA Astrophysics Data System (ADS)
Pirrone, Davide; Bovolo, Francesca; Bruzzone, Lorenzo
2016-10-01
Last years have seen relevant increase of polarimetric Synthetic Aperture Radar (SAR) data availability, thanks to satellite sensors like Sentinel-1 or ALOS-2 PALSAR-2. The augmented information lying in the additional polarimetric channels represents a possibility for better discriminate different classes of changes in change detection (CD) applications. This work aims at proposing a framework for CD in multi-temporal multi-polarization SAR data. The framework includes both a tool for an effective visual representation of the change information and a method for extracting the multiple-change information. Both components are designed to effectively handle the multi-dimensionality of polarimetric data. In the novel representation, multi-temporal intensity SAR data are employed to compute a polarimetric log-ratio. The multitemporal information of the polarimetric log-ratio image is represented in a multi-dimensional features space, where changes are highlighted in terms of magnitude and direction. This representation is employed to design a novel unsupervised multi-class CD approach. This approach considers a sequential two-step analysis of the magnitude and the direction information for separating non-changed and changed samples. The proposed approach has been validated on a pair of Sentinel-1 data acquired before and after the flood in Tamil-Nadu in 2015. Preliminary results demonstrate that the representation tool is effective and that the use of polarimetric SAR data is promising in multi-class change detection applications.
5. SWITCH TOWER AND JUNCTION OF S.A.R. #1 & S.A.R. ...
5. SWITCH TOWER AND JUNCTION OF S.A.R. #1 & S.A.R. #2 TRANSMISSION LINES, MARCH 7, 1916. SCE drawing no. 4932. - Santa Ana River Hydroelectric System, Transmission Lines, Redlands, San Bernardino County, CA
NASA Astrophysics Data System (ADS)
Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.; Bates, P. D.
2015-12-01
Synthetic Aperture Radar (SAR) satellites are capable of all-weather day and night observations that can discriminate between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR satellite data to improve our understanding of water processes, in particular for fluvial flood inundation mechanisms. Past studies prove that integrating SAR derived data with hydraulic models can improve simulations of flooding. However while much of this work focusses on improving model channel roughness values or inflows in ungauged catchments, improvement of model bathymetry is often overlooked. The provision of good bathymetric data is critical to the performance of hydraulic models but there are only a small number of ways to obtain bathymetry information where no direct measurements exist. Spatially distributed river depths are also rarely available. We present a methodology for calibration of model average channel depth and roughness parameters concurrently using SAR images of flood extent and a Sub-Grid model utilising hydraulic geometry concepts. The methodology uses real data from the European Space Agency's archive of ENVISAT[1] Wide Swath Mode images of the River Severn between Worcester and Tewkesbury during flood peaks between 2007 and 2010. Historic ENVISAT WSM images are currently free and easy to access from archive but the methodology can be applied with any available SAR data. The approach makes use of the SAR image processing algorithm of Giustarini[2] et al. (2013) to generate binary flood maps. A unique feature of the calibration methodology is to also use parameter 'identifiability' to locate the parameters with higher accuracy from a pre-assigned range (adopting the DYNIA method proposed by Wagener[3] et al., 2003). [1] https://gpod.eo.esa.int/services/ [2] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote
NASA Astrophysics Data System (ADS)
Zhang, K.; Han, B.; Mansaray, L. R.; Xu, X.; Guo, Q.; Jingfeng, H.
2017-12-01
Synthetic aperture radar (SAR) instruments on board satellites are valuable for high-resolution wind field mapping, especially for coastal studies. Since the launch of Sentinel-1A on April 3, 2014, followed by Sentinel-1B on April 25, 2016, large amount of C-band SAR data have been added to a growing accumulation of SAR datasets (ERS-1/2, RADARSAT-1/2, ENVISAT). These new developments are of great significance for a wide range of applications in coastal sea areas, especially for high spatial resolution wind resource assessment, in which the accuracy of retrieved wind fields is extremely crucial. Recently, it is reported that wind speeds can also be retrieved from C-band cross-polarized SAR images, which is an important complement to wind speed retrieval from co-polarization. However, there is no consensus on the optimal resolution for wind speed retrieval from cross-polarized SAR images. This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized SAR images. Firstly, for wind speeds retrieved from VV-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Secondly, the most suitable C-band cross-polarized ocean (C-2PO) model was selected between two C-2POs for the VH-polarized image dataset. Then, the VH-wind speeds retrieved by the selected C-2PO were compared with the VV-polarized sea surface wind speeds retrieved using the optimal CMOD, which served as reference, at different spatial resolutions. Results show that the VH-polarized wind speed retrieval accuracy increases rapidly with the decrease in spatial resolutions from 100 m to 1000 m, with a drop in RMSE of 42%. However, the improvement in wind speed retrieval accuracy levels off with spatial resolutions decreasing from 1000 m to 5000 m. This demonstrates that the pixel spacing of 1 km may be the compromising choice for the tradeoff between the spatial
Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model
NASA Astrophysics Data System (ADS)
Li, X. L.; Zhao, Q. H.; Li, Y.
2017-09-01
Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.
Aircraft Segmentation in SAR Images Based on Improved Active Shape Model
NASA Astrophysics Data System (ADS)
Zhang, X.; Xiong, B.; Kuang, G.
2018-04-01
In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.
NASA Astrophysics Data System (ADS)
Sato, H. P.; Nakajima, H.; Nakano, T.; Daimaru, H.
2014-12-01
Synthetic Aperture Radar (SAR) is the technique to obtain ground surface images using microwave that is emitted from and received on the antenna. The Kuchi-Sakamoto area, 2.2 km2 in precipitous mountains, central Japan, has suffered from frequent landslides, and slow landslide surface deformation has been monitored by on-site extensometer; however, such the monitoring method cannot detect the deformation in the whole area. Because satellite InSAR is effective tool to monitor slow landslide suface deformation, it is a promising tool for detecting precursor deformation and preparing effective measures against serious landslide disasters. In this study Advanced Land Observing Satellite (ALOS) / Phased Array type L-band SAR (PALSAR) data were used, and InSAR images were produced from the PALSAR data that were observed between 5 Sep 2008 and 21 Oct 2008 (from descending orbit) and between 20 Jul 2008 and 7 Sep 2009 (from ascending orbit). InSAR image from descending orbit was found to detect clear precursor landslide surface deformation on a slope; however, InSAR image on ascending orbit did not always detect clear precursor deformation. It is thought to be related with atmospheric moisture condition, length of observation baseline and so on. Furthermore, after phase unwrapping on InSAR images, 2.5-dimensional deformation was analized. This analysis needed both ascending and descending InSAR images and culculated quasi east-west deformation component (Figs. (a) and (b)) and quasi up-down deformation component (Figs. (c) and (d)). The resulting 2.5D calculation gave westward deformation and mixture of upward and downward deformations on the precursor landslide surface deformation slope (blue circles in Figs. (c) and (d)), where remarkable disrupted deep landslide occurred during Nov 2012 and 25 Jun 2013, judging from result of airborne LiDAR survey and field survey; the occurrence date is not precisely identified. The figure remains the issue that eliminating "real
Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis
NASA Astrophysics Data System (ADS)
Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu
2016-07-01
Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.
Argenti, Fabrizio; Bianchi, Tiziano; Alparone, Luciano
2006-11-01
In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori MIAP) estimation is proposed. Such a method relies on the assumption that the probability density function (pdf) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG pdf are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed pdf model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.
Evaluation of RISAT-1 SAR data for tropical forestry applications
NASA Astrophysics Data System (ADS)
Padalia, Hitendra; Yadav, Sadhana
2017-01-01
India launched C band (5.35 GHz) RISAT-1 (Radar Imaging Satellite-1) on 26th April, 2012, equipped with the capability to image the Earth at multiple-resolutions and -polarizations. In this study the potential of Fine Resolution Strip (FRS) modes of RISAT-1 was evaluated for characterization and classification forests and estimation of biomass of early growth stages. The study was carried out at the two sites located in the foothills of western Himalaya, India. The pre-processing and classification of FRS-1 SAR data was performed using PolSAR Pro ver. 5.0 software. The scattering mechanisms derived from m-chi decomposition of FRS-1 RH/RV data were found physically meaningful for the characterization of various surface features types. The forest and land use type classification of the study area was developed applying Support Vector Machine (SVM) algorithm on FRS-1 derived appropriate polarimetric features. The biomass of early growth stages of Eucalyptus (up to 60 ton/ha) was estimated developing a multi-linear regression model using C band σ0 HV and σ0 HH backscatter information. The study outcomes has promise for wider application of RISAT-1 data for forest cover monitoring, especially for the tropical regions.
NASA Astrophysics Data System (ADS)
Zhang, L.; Wu, J.; Shi, F.
2017-09-01
After the 2010, Mw7.1, Yushu earthquake, many researchers have conducted detail investigations of the surface rupture zone by optical image interpretation, field surveying and inversion of seismic waves. However, how larger of the crustal deformation area caused by the earthquake and the quantitative co-seismic displacements are still not available. In this paper, we first take advantage of D-InSAR, MAI, and optical image matching methods to determine the whole co-seismic displacement fields. Two PALSAR images and two SPOT5 images before and after the earthquake are processed and the co-seismic displacements at the surface rupture zone and far field are obtained. The results are consistent with the field investigations, which illustrates the rationality of the application of optical image matching technology in the earthquake.
Time domain SAR raw data simulation using CST and image focusing of 3D objects
NASA Astrophysics Data System (ADS)
Saeed, Adnan; Hellwich, Olaf
2017-10-01
This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.
1. DOMESTIC WATER SUPPLY TREATMENT HOUSE, ON PENSTOCK ABOVE SAR1. ...
1. DOMESTIC WATER SUPPLY TREATMENT HOUSE, ON PENSTOCK ABOVE SAR-1. VIEW TO NORTWEST. - Santa Ana River Hydroelectric System, SAR-1 Domestic Water Supply Treatment House, Redlands, San Bernardino County, CA
Monitoring Seawall Deformation With Repeat-Track Space-Borne SAR Images
NASA Astrophysics Data System (ADS)
Pei, Yuanyuan; Wan, Qing; Wei, Lianhuan; Fang, Zhilei; Liao, Mingsheng
2010-10-01
Seawalls are constructed to protect coastal cities from typhoon, flood and sea tide. It is necessary to monitor the deformation of seawalls in real time. Repeat-track space-borne SAR images are useful for environment monitoring, especially ground deformation monitoring. Shanghai sits on the Yangtze River Delta on China's eastern coast. Each year, the city is hit by typhoons from Pacific Ocean and threatened by the flood of the Yangtze River. PS-InSAR technique is carried out to monitor the deformation of the seawalls. Experiment exhibits that the seawalls around Pudong airport and Lingang town suffered serious deformation.
Fast Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode
Liu, Lei; Qiu, Xiaolan; Lei, Bin
2017-01-01
This study aims to detect vessels with lengths ranging from about 70 to 300 m, in Gaofen-3 (GF-3) SAR images with ultrafine strip-map (UFS) mode as fast as possible. Based on the analysis of the characteristics of vessels in GF-3 SAR imagery, an effective vessel detection method is proposed in this paper. Firstly, the iterative constant false alarm rate (CFAR) method is employed to detect the potential ship pixels. Secondly, the mean-shift operation is applied on each potential ship pixel to identify the candidate target region. During the mean-shift process, we maintain a selection matrix recording which pixels can be taken, and these pixels are called as the valid points of the candidate target. The l1 norm regression is used to extract the principal axis and detect the valid points. Finally, two kinds of false alarms, the bright line and the azimuth ambiguity, are removed by comparing the valid area of the candidate target with a pre-defined value and computing the displacement between the true target and the corresponding replicas respectively. Experimental results on three GF-3 SAR images with UFS mode demonstrate the effectiveness and efficiency of the proposed method. PMID:28678197
Regional Glacier Mapping by Combination of Dense Optical and SAR Satellite Image Time-Series
NASA Astrophysics Data System (ADS)
Winsvold, S. H.; Kääb, A.; Andreassen, L. M.; Nuth, C.; Schellenberger, T.; van Pelt, W.
2016-12-01
Near-future dense time series from both SAR (Sentinel-1A and B) and optical satellite sensors (Landsat 8, Sentinel-2A and B) will promote new multisensory time series applications for glacier mapping. We assess such combinations of optical and SAR data among others by 1) using SAR data to supplement optical time series that suffer from heavy cloud cover (chronological gap-filling), 2) merging the two data types based on stack statistics (Std.dev, Mean, Max. etc.), or 3) better explaining glacier facies patterns in SAR data using optical satellite images. As one example, summer SAR backscatter time series have been largely unexplored and even neglected in many glaciological studies due to the high content of liquid melt water on the ice surface and its intrusion in the upper part of the snow and firn. This water content causes strong specular scattering and absorption of the radar signal, and little energy is scattered back to the SAR sensor. We find in many scenes of a Sentinel-1 time series a significant temporal backscatter difference between the glacier ice surface and the seasonal snow as it melts up glacier. Even though both surfaces have typically wet conditions, we suggest that the backscatter difference is due to different roughness lengths of the two surfaces. Higher backscatter is found on the ice surface in the ablation area compared to the firn/seasonal snow surface. We find and present also other backscatter patterns in the Sentinel-1 time series related to glacier facies and weather events. For the Ny Ålesund area, Svalbard we use Radarsat-2 time series to explore the glacier backscatter conditions in a > 5 year period, discussing distinct temporal signals from among others refreezing of the firn in late autumn, or temporal lakes. All these examples are analyzed using the above 3 methods. By this multi-temporal and multi-sensor approach we also explore and describe the possible connection between combined SAR/optical time series and surface mass
NASA Astrophysics Data System (ADS)
da Silva, Jose C. B.; Magalhaes, J. M.; Buijsman, M. C.; Garcia, C. A. E.
2016-08-01
Mode-2 internal waves are usually not as energetic as larger mode-1 Internal Solitary Waves (ISWs), but they have attracted a great deal of attention in recent years because they have been identified as playing a significant role in mixing shelf waters [1]. This mixing is particularly effective for mode-2 ISWs because the location of these waves in the middle of the pycnocline plays an important role in eroding the barrier between the base of the surface mixed layer and the stratified deep layer below. An urgent problem in physical oceanography is therefore to account for the magnitude and distribution of ISW-driven mixing, including mode-2 ISWs. Several generation mechanisms of mode-2 ISWs have been identified. These include: (1) mode-1 ISWs propagating onshore (shoaling) and entering the breaking instability stage, or propagating over a steep sill; (2) a mode-1 ISW propagating offshore (antishoaling) over steep slopes of the shelf break, and undergoing modal transformation; (3) intrusion of the whole head of a gravity current into a three-layer fluid; (4) impingement of an internal tidal beam on the pycnocline, itself emanating from critical bathymetry; (5) nonlinear disintegration of internal tide modes; (6) lee wave mechanism. In this paper we provide methods to identify internal wave features denominated "Wave Tails" in SAR images of the ocean surface, which are many times associated with second mode internal waves. The SAR case studies that are presented portray evidence of the aforementioned generation mechanisms, and we further discuss possible methods to discriminate between the various types of mode-2 ISWs in SAR images, that emerge from these physical mechanisms. Some of the SAR images correspond to numerical simulations with the MITgcm in fully nonlinear and nonhydrostatic mode and in a 2D configuration with realistic stratification, bathymetry and other environmental conditions.Results of a global survey with some of these observations are presented
NASA Astrophysics Data System (ADS)
Dai, K. R.; Liu, G. X.; Yu, B.; Jia, H. G.; Ma, D. Y.; Wang, X. W.
2013-10-01
A High Speed Railway goes across Wuqing district of Tianjin, China. Historical studies showed that the land subsidence of this area was very serious, which would give rise to huge security risk to the high speed railway. For detecting the detailed subsidence related to the high speed railway, we use the multi-temporal InSAR (MT-InSAR) technique to extract regional scale subsidence of Wuqing district. Take it into consideration that Wuqing district is a suburban region with large area of low coherence farmland, we select the temporarily coherent point InSAR (TCP-InSAR) approach for MT-InSAR analysis. The TCP-InSAR is a potential approach for detecting land subsidence in low coherence areas as it can identify and analysis coherent points between just two images and can acquire a reliable solution without conventional phase unwrapping. This paper extended the TCP-InSAR with use of ultrashort spatial baseline (USB) interferograms. As thetopographic effects are negligible in the USB interferograms, an external digital elevation model (DEM) is no longer needed in interferometric processing, and the parameters needed to be estimated were simplified at the same time. With use of 17 TerraSAR-X (TSX) images acquired from 2009 to 2010 over Wuqing district, the annual subsidence rates along the high speed railway were derived by the USB-TCPInSAR approach. Two subsidence funnels were found at ShuangJie town and around Wuqing Station with subsidence rate of -17 ∼ -27 mm/year and -7 ∼ -17 mm/year, respectively. The subsidence rates derived by USB-TCPInSAR were compared with those derived by the conventional TCP-InSAR that uses an external DEM for differential interferometry. The mean and the standard deviation of the differences between two types of results at 370697 TCPs are -4.43 × 10-6 mm/year and ±1.4673 mm/year, respectively. Further comparison with the subsidence results mentioned in several other studies were made, which shows good consistencies. The results
NASA Astrophysics Data System (ADS)
Zhang, Xi; Dierking, Wolfgang; Zhang, Jie; Meng, Junmin; Lang, Haitao
2016-07-01
In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric (CP) synthetic aperture radar (SAR) images. The parameter is denoted as the "CP ratio". In model simulations we investigated the sensitivity of the CP ratio to the dielectric constant, ice thickness, ice surface roughness, and radar incidence angle. From the results of the simulations we deduced optimal sea ice conditions and radar incidence angles for the ice thickness retrieval. C-band SAR data acquired over the Labrador Sea in circular transmit and linear receive (CTLR) mode were generated from RADARSAT-2 quad-polarization images. In comparison with results from helicopter-borne measurements, we tested different empirical equations for the retrieval of ice thickness. An exponential fit between the CP ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region, we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.94 for the retrieval procedure when applying it to level ice between 0.1 and 0.8 m thick.
Analysing surface deformation in Surabaya from sentinel-1A data using DInSAR method
NASA Astrophysics Data System (ADS)
Anjasmara, Ira Mutiara; Yusfania, Meiriska; Kurniawan, Akbar; Resmi, Awalina L. C.; Kurniawan, Roni
2017-07-01
The rapid population growth and increasing industrial space in the urban area of Surabaya have caused an excessive ground water use and load of infrastructures. This condition triggers surface deformation, especially the vertical deformation (subsidence or uplift), in Surabaya and its surroundings. The presence of dynamic processes of the Earth and geological form of Surabaya area can also fasten the rate of the surface deformation. In this research, Differential Interferometry Synthetic Aperture Radar (DInSAR) method is chosen to infer the surface deformation over Surabaya area. The DInSAR processing utilized Sentinel 1A satellite images from May 2015 to September 2016 using two-pass interferometric. Two-pass interferometric method is a method that uses two SAR imageries and Digital Elevation Model (DEM). The results from four pairs of DInSAR processing indicate the occurrence of surface deformation in the form of land subsidence and uplift based on the displacement Line of Sight (LOS) in Surabaya. The average rate of surface deformation from May 2015 to September 2016 varies from -3.52 mm/4months to +2.35 mm/4months. The subsidence mostly occurs along the coastal area. However, the result still contains errors from the processing of displacement, due to the value of coherence between the image, noise, geometric distortion of a radar signal and large baseline on image pair.
1. SAR1, SOUTHEAST AND SOUTHWEST ELEVATIONS, WITH SWITCH RACK AT ...
1. SAR-1, SOUTHEAST AND SOUTHWEST ELEVATIONS, WITH SWITCH RACK AT LEFT, AND SANTA ANA WELL #1 AND STONE RETAINING WALLS AT RIGHT. VIEW TO NORTH. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
ARF1 and SAR1 GTPases in Endomembrane Trafficking in Plants
Cevher-Keskin, Birsen
2013-01-01
Small GTPases largely control membrane traffic, which is essential for the survival of all eukaryotes. Among the small GTP-binding proteins, ARF1 (ADP-ribosylation factor 1) and SAR1 (Secretion-Associated RAS super family 1) are commonly conserved among all eukaryotes with respect to both their functional and sequential characteristics. The ARF1 and SAR1 GTP-binding proteins are involved in the formation and budding of vesicles throughout plant endomembrane systems. ARF1 has been shown to play a critical role in COPI (Coat Protein Complex I)-mediated retrograde trafficking in eukaryotic systems, whereas SAR1 GTPases are involved in intracellular COPII-mediated protein trafficking from the ER to the Golgi apparatus. This review offers a summary of vesicular trafficking with an emphasis on the ARF1 and SAR1 expression patterns at early growth stages and in the de-etiolation process. PMID:24013371
Ice/water Classification of Sentinel-1 Images
NASA Astrophysics Data System (ADS)
Korosov, Anton; Zakhvatkina, Natalia; Muckenhuber, Stefan
2015-04-01
Sea Ice monitoring and classification relies heavily on synthetic aperture radar (SAR) imagery. These sensors record data either only at horizontal polarization (RADARSAT-1) or vertically polarized (ERS-1 and ERS-2) or at dual polarization (Radarsat-2, Sentinel-1). Many algorithms have been developed to discriminate sea ice types and open water using single polarization images. Ice type classification, however, is still ambiguous in some cases. Sea ice classification in single polarization SAR images has been attempted using various methods since the beginning of the ERS programme. The robust classification using only SAR images that can provide useful results under varying sea ice types and open water tend to be not generally applicable in operational regime. The new generation SAR satellites have capability to deliver images in several polarizations. This gives improved possibility to develop sea ice classification algorithms. In this study we use data from Sentinel-1 at dual-polarization, i.e. HH (horizontally transmitted and horizontally received) and HV (horizontally transmitted, vertically received). This mode assembles wide SAR image from several narrower SAR beams, resulting to an image of 500 x 500 km with 50 m resolution. A non-linear scheme for classification of Sentinel-1 data has been developed. The processing allows to identify three classes: ice, calm water and rough water at 1 km spatial resolution. The raw sigma0 data in HH and HV polarization are first corrected for thermal and random noise by extracting the background thermal noise level and smoothing the image with several filters. At the next step texture characteristics are computed in a moving window using a Gray Level Co-occurence Matrix (GLCM). A neural network is applied at the last step for processing array of the most informative texture characteristics and ice/water classification. The main results are: * the most informative texture characteristics to be used for sea ice classification
Geodetic imaging of tectonic deformation with InSAR
NASA Astrophysics Data System (ADS)
Fattahi, Heresh
evaluated the rate of strain accumulation along the Chaman fault system (Chapter 5). I also evaluate the co-seismic and post-seismic displacement of a moderate M5.5 earthquake on the Ghazaband fault (Chapter 6). The developed methods to mitigate the systematic noise from InSAR time-series, significantly improve the accuracy of the InSAR displacement time-series and velocity. The approaches to evaluate the effect of the stochastic components of noise in InSAR displacement time-series enable us to obtain the variance-covariance matrix of the InSAR displacement time-series and to express their uncertainties. The effect of the topographic residuals in the InSAR range-change time-series is proportional to the perpendicular baseline history of the set of SAR acquisitions. The proposed method for topographic residual correction, efficiently corrects the displacement time-series. Evaluation of the uncertainty of velocity due to the orbital errors shows that for modern SAR satellites with precise orbits such as TerraSAR-X and Sentinel-1, the uncertainty of 0.2 mm/yr per 100 km and for older satellites with less accurate orbits such as ERS and Envisat, the uncertainty of 1.5 and 0.5mm/yr per 100 km, respectively are achievable. However, the uncertainty due to the orbital errors depends on the orbital uncertainties, the number and time span of SAR acquisitions. Contribution of the tropospheric delay to the InSAR range-change time-series can be subdivided to systematic (seasonal delay) and stochastic components. The systematic component biases the displacement times-series and velocity field as a function of the acquisition time and the non-seasonal component significantly contributes to the InSAR uncertainty. Both components are spatially correlated and therefore the covariance of noise between pixels should be considered for evaluating the uncertainty due to the random tropospheric delay. The relative velocity uncertainty due to the random tropospheric delay depends on the scatter of
Satellite SAR geocoding with refined RPC model
NASA Astrophysics Data System (ADS)
Zhang, Lu; Balz, Timo; Liao, Mingsheng
2012-04-01
Recent studies have proved that the Rational Polynomial Camera (RPC) model is able to act as a reliable replacement of the rigorous Range-Doppler (RD) model for the geometric processing of satellite SAR datasets. But its capability in absolute geolocation of SAR images has not been evaluated quantitatively. Therefore, in this article the problems of error analysis and refinement of SAR RPC model are primarily investigated to improve the absolute accuracy of SAR geolocation. Range propagation delay and azimuth timing error are identified as two major error sources for SAR geolocation. An approach based on SAR image simulation and real-to-simulated image matching is developed to estimate and correct these two errors. Afterwards a refined RPC model can be built from the error-corrected RD model and then used in satellite SAR geocoding. Three experiments with different settings are designed and conducted to comprehensively evaluate the accuracies of SAR geolocation with both ordinary and refined RPC models. All the experimental results demonstrate that with RPC model refinement the absolute location accuracies of geocoded SAR images can be improved significantly, particularly in Easting direction. In another experiment the computation efficiencies of SAR geocoding with both RD and RPC models are compared quantitatively. The results show that by using the RPC model such efficiency can be remarkably improved by at least 16 times. In addition the problem of DEM data selection for SAR image simulation in RPC model refinement is studied by a comparative experiment. The results reveal that the best choice should be using the proper DEM datasets of spatial resolution comparable to that of the SAR images.
Ubiquitous and continuous SAR imaging for natural hazards: present and future of remote sensing
NASA Astrophysics Data System (ADS)
Monti Guarnieri, Andrea; Rocca, Fabio
2017-04-01
Constellation of optical and SAR sensors have achieved unprecedented performances: dense constellation of cubesats - like the next constellation of 88 Dove satellites (Planet labs), launched simultaneously this February - reduce the revisit time to nearly daily. This brings great value to many domains, like the assessment of risk and damage in natural hazards, post-earthquake response, real time flood monitoring. The limits to optical imaging due to cloud coverage could then be removed with drones. Alternatively, decades of coherent exploitation of Synthetic Aperture Radars have demonstrated their unique capabilities in precise deformation monitoring, penetration in canopies and subsurfaces (glacier and deserts), 3D imaging of volumes, sensitivity to soil moisture and generation of water vapor maps. Thanks to these capabilities, for one, early warning was possible for a landslide at Bingham Canyon Mine (one of the largest in history), whereas monitoring of infrastructures, natural gas and carbon dioxide storage reservoirs, dams, mines is already an established business. Many of these applications are made possible by the Sentinel-1 SAR constellation, the first to provide systematic coherent acquisitions and free and open data. More than 50000 products are downloaded daily. Nonetheless, the present revisit times of this constellation (1-3 days), or the future 6 hours of Cosmo-SKYmed I and II constellations, will leave a gap that cannot be fruitfully exploited for early warning of landslides, real time mapping of flooding, hydrometeor forecasts, real-time regional alerts of collapse, continuous soil moisture mapping for precision farming. On the other side, the limited penetration capabilities of C-band (Sentinel-1) and X band (Cosmo, TerraSAR constellations) would not allow sufficient penetration to monitor volumes, like ice, sands and forests. In order to fill these gaps, two novel SAR systems are under study and will possibly appear in the next decades
Significant Wave Height under Hurricane Irma derived from SAR Sentinel-1 Data
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang
2018-04-01
To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.
The 2014 Napa Earthquake Imaged Through A Full Exploitation Of SAR Data
NASA Astrophysics Data System (ADS)
Castaldo, R.; Casu, F.; de Luca, C.; Solaro, G.
2014-12-01
We investigate the co-seismic surface deformation related to the earthquake occurred in Napa area (California) on August 24, 2014. To this aim, we exploit both the phase and the amplitude information of SAR data acquired in Stripmap mode by the Italian COSMO-SkyMed (CSK), the Canadian RADARSAT-2 (RS2), and the recently launched Europena Sentinel-1 satellites, to evaluate and analyze the induced surface displacements through the Differential SAR Interferometry (DInSAR) and Pixel-Offset (PO) techniques. In particular, the SAR images, acquired from descending orbits on 26 July and 27 August 2014 by CSK, and on 07 August and 31 August 2014 by Sentinel-1, as well as the ones acquired on 24 July and 10 September by RS2 from ascending passes were used to generate differential SAR interferograms encompassing the main seismic events. The related deformation map, obtained by performing a complex multi-look operation resulting in a pixel size of about 30 m by 30 m, reveals two main lobes of LOS displacement with a range change decrease of about 11 cm to the NE sector and about 7 cm of range change increase to the SE sector. Moreover, by benefiting from the sensor spatial resolutions (down to 3 meters for both CSK and Sentinel-1 satellites), the Pixel-Offset maps of the same data pairs have been also computed, thus permitting us to retrieve displacement information along the azimuth direction and better describing the deformation field. In order to retrieve the earthquake source location and its geometrical characteristics, the displacement maps were modeled by finite dislocation faults in an elastic and homogeneous half-space [Okada, 1985]. In particular, we searched for all the parameters free the fault by using a nonlinear inversion based on the Levenberg-Marquardt least-squares approach. The best fit solution, consists of a right -lateral NNW-SSE oriented fault. The comparison between the model results and the measured InSAR data show a good fit, with residue values
Robust Flood Monitoring Using Sentinel-1 SAR Time Series
NASA Astrophysics Data System (ADS)
DeVries, B.; Huang, C.; Armston, J.; Huang, W.
2017-12-01
The 2017 hurricane season in North and Central America has resulted in unprecedented levels of flooding that have affected millions of people and continue to impact communities across the region. The extent of casualties and damage to property incurred by these floods underscores the need for reliable systems to track flood location, timing and duration to aid response and recovery efforts. While a diverse range of data sources provide vital information on flood status in near real-time, only spaceborne Synthetic Aperture Radar (SAR) sensors can ensure wall-to-wall coverage over large areas, mostly independently of weather conditions or site accessibility. The European Space Agency's Sentinel-1 constellation represents the only SAR mission currently providing open access and systematic global coverage, allowing for a consistent stream of observations over flood-prone regions. Importantly, both the data and pre-processing software are freely available, enabling the development of improved methods, tools and data products to monitor floods in near real-time. We tracked flood onset and progression in Southeastern Texas, Southern Florida, and Puerto Rico using a novel approach based on temporal backscatter anomalies derived from times series of Sentinel-1 observations and historic baselines defined for each of the three sites. This approach was shown to provide a more objective measure of flood occurrence than the simple backscatter thresholds often employed in operational flood monitoring systems. Additionally, the use of temporal anomaly measures allowed us to partially overcome biases introduced by varying sensor view angles and image acquisition modes, allowing increased temporal resolution in areas where additional targeted observations are available. Our results demonstrate the distinct advantages offered by data from operational SAR missions such as Sentinel-1 and NASA's planned NISAR mission, and call attention to the continuing need for SAR Earth Observation
SAR image filtering based on the heavy-tailed Rayleigh model.
Achim, Alin; Kuruoğlu, Ercan E; Zerubia, Josiane
2006-09-01
Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori (MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the recently introduced heavy-tailed Rayleigh density function, which was derived based on the assumption that the real and imaginary parts of the received complex signal are best described using the alpha-stable family of distribution. We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the homomorphic MAP filter based on the heavy-tailed Rayleigh prior for the RCS is among the best for speckle removal.
Object recognition of real targets using modelled SAR images
NASA Astrophysics Data System (ADS)
Zherdev, D. A.
2017-12-01
In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).
The geophysical processor system: Automated analysis of ERS-1 SAR imagery
NASA Technical Reports Server (NTRS)
Stern, Harry L.; Rothrock, D. Andrew; Kwok, Ronald; Holt, Benjamin
1994-01-01
The Geophysical Processor System (GPS) at the Alaska (U.S.) SAR (Synthetic Aperture Radar) Facility (ASF) uses ERS-1 SAR images as input to generate three types of products: sea ice motion, sea ice type, and ocean wave spectra. The GPS, operating automatically with minimal human intervention, delivers its output to the Archive and Catalog System (ACS) where scientists can search and order the products on line. The GPS has generated more than 10,000 products since it became operational in Feb. 1992, and continues to deliver 500 new products per month to the ACS. These products cover the Beaufort and Chukchi Seas and the western portion of the central Arctic Ocean. More geophysical processing systems are needed to handle the large volumes of data from current and future satellites. Images must be routinely and consistently analyzed to yield useful information for scientists. The current GPS is a good, working prototype on the way to more sophisticated systems.
NASA Astrophysics Data System (ADS)
Werninghaus, Rolf
2004-01-01
The TerraSAR-X is a German national SAR- satellite system for scientific and commercial applications. It is the continuation of the scientifically and technologically successful radar missions X-SAR (1994) and SRTM (2000) and will bring the national technology developments DESA and TOPAS into operational use. The space segment of TerraSAR-X is an advanced high-resolution X-Band radar satellite. The system design is based on a sound market analysis performed by Infoterra. The TerraSAR-X features an advanced high-resolution X-Band Synthetic Aperture Radar based on the active phased array technology which allows the operation in Spotlight-, Stripmap- and ScanSAR Mode with various polarizations. It combines the ability to acquire high resolution images for detailed analysis as well as wide swath images for overview applications. In addition, experimental modes like the Dual Receive Antenna Mode allow for full-polarimetric imaging as well as along track interferometry, i.e. moving target identification. The Ground Segment is optimized for flexible response to (scientific and commercial) User requests and fast image product turn-around times. The TerraSAR-X mission will serve two main goals. The first goal is to provide the strongly supportive scientific community with multi-mode X-Band SAR data. The broad spectrum of scientific application areas include Hydrology, Geology, Climatology, Oceanography, Environmental Monitoring and Disaster Monitoring as well as Cartography (DEM Generation) and Interferometry. The second goal is the establishment of a commercial EO-market in Europe which is driven by Infoterra. The commercial goal is the development of a sustainable EO-business so that the e.g. follow-on systems can be completely financed by industry from the profit. Due to its commercial potential, the TerraSAR-X project will be implemented based on a public-private partnership with the Astrium GmbH. This paper will describe first the mission objectives as well as the
Villanueva, Maite; Renzoni, Adriana; Monod, Antoinette; Barras, Christine; Rodriguez, Natalia; Kelley, William L.
2015-01-01
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. PMID:26275216
NASA Astrophysics Data System (ADS)
Shi, R.; Sun, Z.
2018-04-01
GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously. Recently, Shearlet is applied to the image processing with its best sparse representation. A new Shearlet-transform-based method is proposed in this paper based on the improved non-local means. Firstly, the logarithmic operation and the non-subsampled Shearlet transformation are applied to the GF-3 SAR image. Secondly, in order to solve the problems that the image details are smoothed overly and the weight distribution is affected by the speckle, a new non-local means is used for the transformed high frequency coefficient. Thirdly, the Shearlet reconstruction is carried out. Finally, the final filtered image is obtained by an exponential operation. Experimental results demonstrate that, compared with other despeckling methods, the proposed method can suppress the speckle effectively in homogeneous regions and has better capability of edge preserving.
NASA Astrophysics Data System (ADS)
Fielding, E. J.; Huang, M. H.; Liang, C.; Yue, H.; Agram, P. S.; Simons, M.; Fattahi, H.; Tung, H.; Hu, J. C.; Huang, C.
2016-12-01
We map complex fault ruptures of the February 2016 MeiNong earthquake in Taiwan and the April 2016 Kumamoto earthquake sequence in Japan by analysis of Synthetic Aperture Radar (SAR) data from the Copernicus Sentinel-1A (S1A) satellite operated by the European Space Agency and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japanese Aerospace Exploration Agency (JAXA). Our analysis shows that the MeiNong main rupture at lower crustal depth triggered slip on another fault at upper crustal depth and shallow slip on several faults in the upper few km. The Kumamoto earthquake sequence ruptured two major fault systems over two days and triggered shallow slip on a large number of shallow faults. We combine less precise analysis of large scale displacements from the SAR images of the two satellites by pixel offset tracking or sub-pixel correlation, including the along-track component of surface motion, with the more precise SAR interferometry (InSAR) measurements in the radar line-of-sight direction to estimate all three components of the surface displacement for the events. Data was processed with customized workflows based on modules in the InSAR Scientific Computing Environment (ISCE). Joint inversion of S1A and ALOS-2 InSAR, GPS, and strong motion seismograms for the Mw6.4 MeiNong earthquake shows that the main thrust rupture with N61°W strike and 15° dip at 15-20 km depth explains nearly all of the seismic waveforms but leaves a substantial uplift residual in the InSAR and GPS offsets estimated 4 hours after the earthquake. We model this residual with slip on a N8°E-trending thrust fault dipping 30° at depths between 5-10 km. This fault strike is parallel to surface faults and we interpret it as fault slip within a mid-crustal duplex that was triggered by the main rupture within 4 hours of the mainshock. In addition, InSAR shows sharp discontinuities at many locations that are likely due to shallow triggered slip, but the timing of
Image quality specification and maintenance for airborne SAR
NASA Astrophysics Data System (ADS)
Clinard, Mark S.
2004-08-01
Specification, verification, and maintenance of image quality over the lifecycle of an operational airborne SAR begin with the specification for the system itself. Verification of image quality-oriented specification compliance can be enhanced by including a specification requirement that a vendor provide appropriate imagery at the various phases of the system life cycle. The nature and content of the imagery appropriate for each stage of the process depends on the nature of the test, the economics of collection, and the availability of techniques to extract the desired information from the data. At the earliest lifecycle stages, Concept and Technology Development (CTD) and System Development and Demonstration (SDD), the test set could include simulated imagery to demonstrate the mathematical and engineering concepts being implemented thus allowing demonstration of compliance, in part, through simulation. For Initial Operational Test and Evaluation (IOT&E), imagery collected from precisely instrumented test ranges and targets of opportunity consisting of a priori or a posteriori ground-truthed cultural and natural features are of value to the analysis of product quality compliance. Regular monitoring of image quality is possible using operational imagery and automated metrics; more precise measurements can be performed with imagery of instrumented scenes, when available. A survey of image quality measurement techniques is presented along with a discussion of the challenges of managing an airborne SAR program with the scarce resources of time, money, and ground-truthed data. Recommendations are provided that should allow an improvement in the product quality specification and maintenance process with a minimal increase in resource demands on the customer, the vendor, the operational personnel, and the asset itself.
NASA Technical Reports Server (NTRS)
Schmullius, C.; Nithack, J.
1992-01-01
On July 12, the MAC Europe '91 (Multi-Sensor Airborne Campaign) took place over test site Oberpfaffenhofen. The DLR Institute of Radio-Frequency Technology participated with its C-VV, X-VV, and X-HH Experimental Synthetic Aperture Radar (E-SAR). The high resolution E-SAR images with a pixel size between 1 and 2 m and the polarimetric AIRSAR images were analyzed. Using both sensors in combination is a unique opportunity to evaluate SAR images in a frequency range from P- to X-band and to investigate polarimetric information.
Image synthesis for SAR system, calibration and processor design
NASA Technical Reports Server (NTRS)
Holtzman, J. C.; Abbott, J. L.; Kaupp, V. H.; Frost, V. S.
1978-01-01
The Point Scattering Method of simulating radar imagery rigorously models all aspects of the imaging radar phenomena. Its computational algorithms operate on a symbolic representation of the terrain test site to calculate such parameters as range, angle of incidence, resolution cell size, etc. Empirical backscatter data and elevation data are utilized to model the terrain. Additionally, the important geometrical/propagation effects such as shadow, foreshortening, layover, and local angle of incidence are rigorously treated. Applications of radar image simulation to a proposed calibrated SAR system are highlighted: soil moisture detection and vegetation discrimination.
Rabi cropped area forecasting of parts of Banaskatha District,Gujarat using MRS RISAT-1 SAR data
NASA Astrophysics Data System (ADS)
Parekh, R. A.; Mehta, R. L.; Vyas, A.
2016-10-01
Radar sensors can be used for large-scale vegetation mapping and monitoring using backscatter coefficients in different polarisations and wavelength bands. Due to cloud and haze interference, optical images are not always available at all phonological stages important for crop discrimination. Moreover, in cloud prone areas, exclusively SAR approach would provide operational solution. This paper presents the results of classifying the cropped and non cropped areas using multi-temporal SAR images. Dual polarised C- band RISAT MRS (Medium Resolution ScanSAR mode) data were acquired on 9thDec. 2012, 28thJan. 2013 and 22nd Feb. 2013 at 18m spatial resolution. Intensity images of two polarisations (HH, HV) were extracted and converted into backscattering coefficient images. Cross polarisation ratio (CPR) images and Radar fractional vegetation density index (RFDI) were created from the temporal data and integrated with the multi-temporal images. Signatures of cropped and un-cropped areas were used for maximum likelihood supervised classification. Separability in cropped and umcropped classes using different polarisation combinations and classification accuracy analysis was carried out. FCC (False Color Composite) prepared using best three SAR polarisations in the data set was compared with LISS-III (Linear Imaging Self-Scanning System-III) image. The acreage under rabi crops was estimated. The methodology developed was for rabi cropped area, due to availability of SAR data of rabi season. Though, the approach is more relevant for acreage estimation of kharif crops when frequent cloud cover condition prevails during monsoon season and optical sensors fail to deliver good quality images.
An Evaluation of ALOS Data in Disaster Applications
NASA Astrophysics Data System (ADS)
Igarashi, Tamotsu; Igarashi, Tamotsu; Furuta, Ryoich; Ono, Makoto
ALOS is the advanced land observing satellite, providing image data from onboard sensors; PRISM, AVNIR-2 and PALSAR. PRISM is the sensor of panchromatic stereo, high resolution three-line-scanner to characterize the earth surface. The accuracy of position in image and height of Digital Surface Model (DSM) are high, therefore the geographic information extraction is improved in the field of disaster applications with providing images of disaster area. Especially pan-sharpened 3D image composed with PRISM and the four-band visible near-infrared radiometer AVNIR-2 data is expected to provide information to understand the geographic and topographic feature. PALSAR is the advanced multi-functional synthetic aperture radar (SAR) operated in L-band, appropriate for the use of land surface feature characterization. PALSAR has many improvements from JERS-1/SAR, such as high sensitivity, having high resolution, polarimetric and scan SAR observation modes. PALSAR is also applicable for SAR interferometry processing. This paper describes the evaluation of ALOS data characteristic from the view point of disaster applications, through some exercise applications.
On The Spatial Homogeneity Of The Wave Spectra In Deep Water Employing ERS-2 SAR Precision Image
NASA Astrophysics Data System (ADS)
Violante-Carvalho, Nelson; Robinson, Ian; Gommenginger, Christine; Carvalho, Luiz Mariano; Goldstein, Brunno
2010-04-01
Using wave spectra extracted from image mode ERS-2 SAR, the spatial homogeneity of the wave field in deep water is investigated against directional buoy measurements. From the 100 x 100 km image, several small images of 6.4 x 6.4 km are selected and the wave spectra are computed. The locally disturbed wind velocity pat- tern, caused by the sheltering effect of large mountains near the coast, translates into the selected SAR image as regions of higher and lower wind speed. Assuming that a swell component is uniform over the whole image, SAR wave spectra retrieved from the sheltered and non-sheltered areas are intercompared. Any difference between them could be related to a possible interaction between wind sea and swell, since the wind sea part of the spectrum would be slightly different due to the different wind speeds. The results show that there is no significative variation, and apparently there is no clear difference in the swell spectra despite the different wind sea components.
NASA Astrophysics Data System (ADS)
Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe
2016-11-01
For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.
Battlefield radar imaging through airborne millimetric wave SAR (Synthetic Aperture Radar)
NASA Astrophysics Data System (ADS)
Carletti, U.; Daddio, E.; Farina, A.; Morabito, C.; Pangrazi, R.; Studer, F. A.
Airborne synthetic aperture radar (SAR), operating in the millimetric-wave (mmw) region, is discussed with reference to a battlefield surveillance application. The SAR system provides high resolution real-time imaging of the battlefield and moving target detection, under adverse environmental conditions (e.g., weather, dust, smoke, obscurants). The most relevant and original aspects of the system are the band of operation (i.e., mmw in lieu of the more traditional microwave region) and the use of an unmanned platform. The former implies reduced weight and size requirements, thus allowing use of small unmanned platforms. The latter enchances the system operational effectiveness by permitting accomplishment of recognition missions in depth beyond the FEBA. An overall system architecture based on the onboard sensor, the platform, the communication equipment, and a mobile ground station is described. The main areas of ongoing investigation are presented: the simulation of the end-to-end system, and the critical technological issues such as mmw antenna, transmitter, signal processor for image formation and platform attitude errors compensation and detection and imaging of moving targets.
Large Oil Spill Classification Using SAR Images Based on Spatial Histogram
NASA Astrophysics Data System (ADS)
Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.
2016-06-01
Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.
Dispersive Phase in the L-band InSAR Image Associated with Heavy Rain Episodes
NASA Astrophysics Data System (ADS)
Furuya, M.; Kinoshita, Y.
2017-12-01
Interferometric synthetic aperture radar (InSAR) is a powerful geodetic technique that allows us to detect ground displacements with unprecedented spatial resolution, and has been used to detect displacements due to earthquakes, volcanic eruptions, and glacier motion. In the meantime, due to the microwave propagation through ionosphere and troposphere, we often encounter non-negligible phase anomaly in InSAR data. Correcting for the ionsphere and troposphere is therefore a long-standing issue for high-precision geodetic measurements. However, if ground displacements are negligible, InSAR image can tell us the details of the atmosphere.Kinoshita and Furuya (2017, SOLA) detected phase anomaly in ALOS/PALSAR InSAR data associated with heavy rain over Niigata area, Japan, and performed numerical weathr model simulation to reproduce the anomaly; ALOS/PALSAR is a satellite-based L-band SAR sensor launched by JAXA in 2006 and terminated in 2011. The phase anomaly could be largely reproduced, using the output data from the weather model. However, we should note that numerical weather model outputs can only account for the non-dispersive effect in the phase anomaly. In case of severe weather event, we may expect dispersive effect that could be caused by the presence of free-electrons.In Global Navigation Satellite System (GNSS) positioning, dual frequency measurements allow us to separate the ionospheric dispersive component from tropospheric non-dispersive components. In contrast, SAR imaging is based on a single carrier frequency, and thus no operational ionospheric corrections have been performed in InSAR data analyses. Recently, Gomba et al (2016) detailed the processing strategy of split spectrum method (SSM) for InSAR, which splits the finite bandwidth of the range spectrum and virtually allows for dual-frequency measurements.We apply the L-band InSAR SSM to the heavy rain episodes, in which more than 50 mm/hour precipitations were reported. We report the presence of
NASA Astrophysics Data System (ADS)
Liang, J.; Liu, D.
2017-12-01
Emergency responses to floods require timely information on water extents that can be produced by satellite-based remote sensing. As SAR image can be acquired in adverse illumination and weather conditions, it is particularly suitable for delineating water extent during a flood event. Thresholding SAR imagery is one of the most widely used approaches to delineate water extent. However, most studies apply only one threshold to separate water and dry land without considering the complexity and variability of different dry land surface types in an image. This paper proposes a new thresholding method for SAR image to delineate water from other different land cover types. A probability distribution of SAR backscatter intensity is fitted for each land cover type including water before a flood event and the intersection between two distributions is regarded as a threshold to classify the two. To extract water, a set of thresholds are applied to several pairs of land cover types—water and urban or water and forest. The subsets are merged to form the water distribution for the SAR image during or after the flooding. Experiments show that this land cover based thresholding approach outperformed the traditional single thresholding by about 5% to 15%. This method has great application potential with the broadly acceptance of the thresholding based methods and availability of land cover data, especially for heterogeneous regions.
Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images
NASA Astrophysics Data System (ADS)
Yang, C. H.; Pang, Y.; Soergel, U.
2017-05-01
Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.
1km Soil Moisture from Downsampled Sentinel-1 SAR Data: Harnessing Assets and Overcoming Obstacles.
NASA Astrophysics Data System (ADS)
Bauer-Marschallinger, Bernhard; Cao, Senmao; Schaufler, Stefan; Paulik, Christoph; Naeimi, Vahid; Wagner, Wolfgang
2017-04-01
Radars onboard Earth observing satellites allow estimating Surface Soil Moisture (SSM) regularly and globally. The use of coarse-scale measurements from active or passive radars for SSM retrieval is well established and in operational use. Thanks to the Sentinel-1 mission, launched in 2014 and deploying Synthetic Aperture Radars (SAR), high-resolution radar imagery is routinely available at the scale of 20 meters, with a high revisit frequency of 3-6 days and with unprecedented radiometric accuracy. However, the direct exploitation of high-resolution SAR data for SSM retrieval is complicated by several problems: Small-scaled contributions to the radar backscatter from individual ground features often obscure the soil moisture signal, rendering common algorithms insensitive to SSM. Furthermore, the influence of vegetation dynamics on the radar signal is less understood than in the coarse-scale case, leading to biases during the vegetation period. Finally, the large data volumes of high-resolution remote sensing data present a great load on hardware systems. Consequently, a spatial resampling of the high-resolution SAR data to a 500 meters sampling is done, allowing the exploitation of information at 10 meter sampling, but reducing effectively the inherent uncertainties. The thereof retrieved 1km SSM product aims to describe the soil moisture dynamics at medium scale with high quality. We adopted the TU-Wien Change Detection algorithm to the Sentinel-1 data, which was already successfully used for retrieving SSM from ERS-1/2 and Envisat-ASAR observations. The adoption entails a new method for SAR image resampling, including a masking for pixels that do not carry soil moisture signals, preventing them to spread during downsampling. Furthermore, the observation angle between the radar sensors and the ground is treated in a different way, as Sentinel-1 sensors observe from fixed orbit paths (in contrast to other radar sensors). Here, a regression model is developed that
NASA Technical Reports Server (NTRS)
Lin, Qian; Allebach, Jan P.
1990-01-01
An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.
SAR processing using SHARC signal processing systems
NASA Astrophysics Data System (ADS)
Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.
1998-09-01
Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.
Marine Targets Detection in Pol-SAR Data
NASA Astrophysics Data System (ADS)
Chen, Peng; Yang, Jingsong
2016-08-01
In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.
Design and realization of an active SAR calibrator for TerraSAR-X
NASA Astrophysics Data System (ADS)
Dummer, Georg; Lenz, Rainer; Lutz, Benjamin; Kühl, Markus; Müller-Glaser, Klaus D.; Wiesbeck, Werner
2005-10-01
TerraSAR-X is a new earth observing satellite which will be launched in spring 2006. It carries a high resolution X-band SAR sensor. For high image data quality, accurate ground calibration targets are necessary. This paper describes a novel system concept for an active and highly integrated, digitally controlled SAR system calibrator. A total of 16 active transponder and receiver systems and 17 receiver only systems will be fabricated for a calibration campaign. The calibration units serve for absolute radiometric calibration of the SAR image data. Additionally, they are equipped with an extra receiver path for two dimensional satellite antenna pattern recognition. The calibrator is controlled by a dedicated digital Electronic Control Unit (ECU). The different voltages needed by the calibrator and the ECU are provided by the third main unit called Power Management Unit (PMU).
NASA Technical Reports Server (NTRS)
Jeffries, Martin; Morris, Kim; Liston, Glen
1996-01-01
Images taken by the ERS-1 synthetic aperture radar (SAR) were used to identify and to differentiate between the lakes that freeze completely to the bottom and those that do not, on the North Slope, in northwestern Alaska. The ice thickness at the time each lake froze completely is determined with numerical ice growth model that gives a maximum simulated thickness of 2.2 m. A method combining the ERS-1 SAR images and numerical ice growth model was used to determine the ice growth and the water availability in these regions.
Retrieval of the thickness of undeformed sea ice from C-band compact polarimetric SAR images
NASA Astrophysics Data System (ADS)
Zhang, X.; Dierking, W.; Zhang, J.; Meng, J. M.; Lang, H. T.
2015-10-01
In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. The parameter is denoted as "CP-Ratio". In model simulations we investigated the sensitivity of CP-Ratio to the dielectric constant, thickness, surface roughness, and incidence angle. From the results of the simulations we deduced optimal conditions for the thickness retrieval. On the basis of C-band CTLR SAR data, which were generated from Radarsat-2 quad-polarization images acquired jointly with helicopter-borne sea ice thickness measurements in the region of the Sea of Labrador, we tested empirical equations for thickness retrieval. An exponential fit between CP-Ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.92 for the retrieval procedure when applying it on level ice of 0.9 m mean thickness.
Interferon-β 1a and SARS Coronavirus Replication
Hensley, Lisa E.; Fritz, Elizabeth A.; Karp, Christopher; Huggins, John W.; Geisbert, Thomas W.
2004-01-01
A global outbreak of severe acute respiratory syndrome (SARS) caused by a novel coronavirus began in March 2003. The rapid emergence of SARS and the substantial illness and death it caused have made it a critical public health issue. Because no effective treatments are available, an intensive effort is under way to identify and test promising antiviral drugs. Here, we report that recombinant human interferon (IFN)-β 1a potently inhibits SARS coronavirus replication in vitro. PMID:15030704
NASA Astrophysics Data System (ADS)
Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun
2018-03-01
Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.
NASA Astrophysics Data System (ADS)
Pepe, S.; Di Martino, G.; Iodice, A.; Manzo, M.; Pepe, A.; Riccio, D.; Ruello, G.; Sansosti, E.; Tizzani, P.; Zinno, I.
2012-04-01
In the last two decades several aspects relevant to volcanic activity have been analyzed in terms of fractal parameters that effectively describe natural objects geometry. More specifically, these researches have been aimed at the identification of (1) the power laws that governed the magma fragmentation processes, (2) the energy of explosive eruptions, and (3) the distribution of the associated earthquakes. In this paper, the study of volcano morphology via satellite images is dealt with; in particular, we use the complete forward model developed by some of the authors (Di Martino et al., 2012) that links the stochastic characterization of amplitude Synthetic Aperture Radar (SAR) images to the fractal dimension of the imaged surfaces, modelled via fractional Brownian motion (fBm) processes. Based on the inversion of such a model, a SAR image post-processing has been implemented (Di Martino et al., 2010), that allows retrieving the fractal dimension of the observed surfaces, dictating the distribution of the roughness over different spatial scales. The fractal dimension of volcanic structures has been related to the specific nature of materials and to the effects of active geodynamic processes. Hence, the possibility to estimate the fractal dimension from a single amplitude-only SAR image is of fundamental importance for the characterization of volcano structures and, moreover, can be very helpful for monitoring and crisis management activities in case of eruptions and other similar natural hazards. The implemented SAR image processing performs the extraction of the point-by-point fractal dimension of the scene observed by the sensor, providing - as an output product - the map of the fractal dimension of the area of interest. In this work, such an analysis is performed on Cosmo-SkyMed, ERS-1/2 and ENVISAT images relevant to active stratovolcanoes in different geodynamic contexts, such as Mt. Somma-Vesuvio, Mt. Etna, Vulcano and Stromboli in Southern Italy, Shinmoe
NASA Technical Reports Server (NTRS)
Sekhon, R.
1981-01-01
Digital SEASAT-1 synthetic aperture radar (SAR) data were used to enhance linear features to extract geologically significant lineaments in the Appalachian region. Comparison of Lineaments thus mapped with an existing lineament map based on LANDSAT MSS images shows that appropriately processed SEASAT-1 SAR data can significantly improve the detection of lineaments. Merge MSS and SAR data sets were more useful fo lineament detection and landcover classification than LANDSAT or SEASAT data alone. About 20 percent of the lineaments plotted from the SEASAT SAR image did not appear on the LANDSAT image. About 6 percent of minor lineaments or parts of lineaments present in the LANDSAT map were missing from the SEASAT map. Improvement in the landcover classification (acreage and spatial estimation accuracy) was attained by using MSS-SAR merged data. The aerial estimation of residential/built-up and forest categories was improved. Accuracy in estimating the agricultural and water categories was slightly reduced.
Satellite on-board real-time SAR processor prototype
NASA Astrophysics Data System (ADS)
Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François
2017-11-01
A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and
Ionospheric Specifications for SAR Interferometry (ISSI)
NASA Technical Reports Server (NTRS)
Pi, Xiaoqing; Chapman, Bruce D; Freeman, Anthony; Szeliga, Walter; Buckley, Sean M.; Rosen, Paul A.; Lavalle, Marco
2013-01-01
The ISSI software package is designed to image the ionosphere from space by calibrating and processing polarimetric synthetic aperture radar (PolSAR) data collected from low Earth orbit satellites. Signals transmitted and received by a PolSAR are subject to the Faraday rotation effect as they traverse the magnetized ionosphere. The ISSI algorithms combine the horizontally and vertically polarized (with respect to the radar system) SAR signals to estimate Faraday rotation and ionospheric total electron content (TEC) with spatial resolutions of sub-kilometers to kilometers, and to derive radar system calibration parameters. The ISSI software package has been designed and developed to integrate the algorithms, process PolSAR data, and image as well as visualize the ionospheric measurements. A number of tests have been conducted using ISSI with PolSAR data collected from various latitude regions using the phase array-type L-band synthetic aperture radar (PALSAR) onboard Japan Aerospace Exploration Agency's Advanced Land Observing Satellite mission, and also with Global Positioning System data. These tests have demonstrated and validated SAR-derived ionospheric images and data correction algorithms.
Two-step single slope/SAR ADC with error correction for CMOS image sensor.
Tang, Fang; Bermak, Amine; Amira, Abbes; Amor Benammar, Mohieddine; He, Debiao; Zhao, Xiaojin
2014-01-01
Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μ m CMOS technology. The chip area of the proposed ADC is 7 μ m × 500 μ m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μ m(2) · cycles/sample.
MIMO-OFDM signal optimization for SAR imaging radar
NASA Astrophysics Data System (ADS)
Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.
2016-12-01
This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.
NASA Astrophysics Data System (ADS)
Krawczyk, Artur; Grzybek, Radosław
2018-01-01
The Satellite Radar Interferometry is one of the common methods that allow to measure the land subsidence caused by the underground black coal excavation. The interferometry images processed from the repeat-pass Synthetic Aperture Radar (SAR) systems give the spatial image of the terrain subjected to the surface subsidence over mining areas. Until now, the InSAR methods using data from the SAR Systems like ERS-1/ERS-2 and Envisat-1 were limited to a repeat-pass cycle of 35-day only. Recently, the ESA launched Sentinel-1A and 1B, and together they can provide the InSAR coverage in a 6-day repeat cycle. The studied area was the Upper Silesian Coal Basin in Poland, where the underground coal mining causes continuous subsidence of terrain surface and mining tremors (mine-induced seismicity). The main problem was with overlapping the subsidence caused by the mining exploitation with the epicentre tremors. Based on the Sentinel SAR images, research was done in regard to the correlation between the short term ground subsidence range border and the mine-induced seismicity epicentres localisation.
Urban Modelling Performance of Next Generation SAR Missions
NASA Astrophysics Data System (ADS)
Sefercik, U. G.; Yastikli, N.; Atalay, C.
2017-09-01
In synthetic aperture radar (SAR) technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX) and Cosmo-SkyMed (CSK) since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM) acquisition for urban areas utilizing interferometric SAR (InSAR) technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS) InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS) DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8-10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.
NASA Astrophysics Data System (ADS)
Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.
2017-12-01
The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano
Visual analytics for semantic queries of TerraSAR-X image content
NASA Astrophysics Data System (ADS)
Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai
2015-10-01
With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain
DUSTER: demonstration of an integrated LWIR-VNIR-SAR imaging system
NASA Astrophysics Data System (ADS)
Wilson, Michael L.; Linne von Berg, Dale; Kruer, Melvin; Holt, Niel; Anderson, Scott A.; Long, David G.; Margulis, Yuly
2008-04-01
The Naval Research Laboratory (NRL) and Space Dynamics Laboratory (SDL) are executing a joint effort, DUSTER (Deployable Unmanned System for Targeting, Exploitation, and Reconnaissance), to develop and test a new tactical sensor system specifically designed for Tier II UAVs. The system is composed of two coupled near-real-time sensors: EyePod (VNIR/LWIR ball gimbal) and NuSAR (L-band synthetic aperture radar). EyePod consists of a jitter-stabilized LWIR sensor coupled with a dual focal-length optical system and a bore-sighted high-resolution VNIR sensor. The dual focal-length design coupled with precision pointing an step-stare capabilities enable EyePod to conduct wide-area survey and high resolution inspection missions from a single flight pass. NuSAR is being developed with partners Brigham Young University (BYU) and Artemis, Inc and consists of a wideband L-band SAR capable of large area survey and embedded real-time image formation. Both sensors employ standard Ethernet interfaces and provide geo-registered NITFS output imagery. In the fall of 2007, field tests were conducted with both sensors, results of which will be presented.
A SAR Observation and Numerical Study on Ocean Surface Imprints of Atmospheric Vortex Streets.
Li, Xiaofeng; Zheng, Weizhong; Zou, Cheng-Zhi; Pichel, William G
2008-05-21
The sea surface imprints of Atmospheric Vortex Street (AVS) off Aleutian Volcanic Islands, Alaska were observed in two RADARSAT-1 Synthetic Aperture Radar (SAR) images separated by about 11 hours. In both images, three pairs of distinctive vortices shedding in the lee side of two volcanic mountains can be clearly seen. The length and width of the vortex street are about 60-70 km and 20 km, respectively. Although the AVS's in the two SAR images have similar shapes, the structure of vortices within the AVS is highly asymmetrical. The sea surface wind speed is estimated from the SAR images with wind direction input from Navy NOGAPS model. In this paper we present a complete MM5 model simulation of the observed AVS. The surface wind simulated from the MM5 model is in good agreement with SAR-derived wind. The vortex shedding rate calculated from the model run is about 1 hour and 50 minutes. Other basic characteristics of the AVS including propagation speed of the vortex, Strouhal and Reynolds numbers favorable for AVS generation are also derived. The wind associated with AVS modifies the cloud structure in the marine atmospheric boundary layer. The AVS cloud pattern is also observed on a MODIS visible band image taken between the two RADARSAT SAR images. An ENVISAT advance SAR image taken 4 hours after the second RADARSAT SAR image shows that the AVS has almost vanished.
A neural network detection model of spilled oil based on the texture analysis of SAR image
NASA Astrophysics Data System (ADS)
An, Jubai; Zhu, Lisong
2006-01-01
A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.
Comparison and Analysis of Geometric Correction Models of Spaceborne SAR
Jiang, Weihao; Yu, Anxi; Dong, Zhen; Wang, Qingsong
2016-01-01
Following the development of synthetic aperture radar (SAR), SAR images have become increasingly common. Many researchers have conducted large studies on geolocation models, but little work has been conducted on the available models for the geometric correction of SAR images of different terrain. To address the terrain issue, four different models were compared and are described in this paper: a rigorous range-doppler (RD) model, a rational polynomial coefficients (RPC) model, a revised polynomial (PM) model and an elevation derivation (EDM) model. The results of comparisons of the geolocation capabilities of the models show that a proper model for a SAR image of a specific terrain can be determined. A solution table was obtained to recommend a suitable model for users. Three TerraSAR-X images, two ALOS-PALSAR images and one Envisat-ASAR image were used for the experiment, including flat terrain and mountain terrain SAR images as well as two large area images. Geolocation accuracies of the models for different terrain SAR images were computed and analyzed. The comparisons of the models show that the RD model was accurate but was the least efficient; therefore, it is not the ideal model for real-time implementations. The RPC model is sufficiently accurate and efficient for the geometric correction of SAR images of flat terrain, whose precision is below 0.001 pixels. The EDM model is suitable for the geolocation of SAR images of mountainous terrain, and its precision can reach 0.007 pixels. Although the PM model does not produce results as precise as the other models, its efficiency is excellent and its potential should not be underestimated. With respect to the geometric correction of SAR images over large areas, the EDM model has higher accuracy under one pixel, whereas the RPC model consumes one third of the time of the EDM model. PMID:27347973
NASA Astrophysics Data System (ADS)
Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas
2018-05-01
Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.
Sparse 4D TomoSAR imaging in the presence of non-linear deformation
NASA Astrophysics Data System (ADS)
Khwaja, Ahmed Shaharyar; ćetin, Müjdat
2018-04-01
In this paper, we present a sparse four-dimensional tomographic synthetic aperture radar (4D TomoSAR) imaging scheme that can estimate elevation and linear as well as non-linear seasonal deformation rates of scatterers using the interferometric phase. Unlike existing sparse processing techniques that use fixed dictionaries based on a linear deformation model, we use a variable dictionary for the non-linear deformation in the form of seasonal sinusoidal deformation, in addition to the fixed dictionary for the linear deformation. We estimate the amplitude of the sinusoidal deformation using an optimization method and create the variable dictionary using the estimated amplitude. We show preliminary results using simulated data that demonstrate the soundness of our proposed technique for sparse 4D TomoSAR imaging in the presence of non-linear deformation.
NASA Astrophysics Data System (ADS)
Agram, P. S.; Gurrola, E. M.; Lavalle, M.; Sacco, G. F.; Rosen, P. A.
2016-12-01
The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.
Segmentation Of Polarimetric SAR Data
NASA Technical Reports Server (NTRS)
Rignot, Eric J. M.; Chellappa, Rama
1994-01-01
Report presents one in continuing series of studies of segmentation of polarimetric synthetic-aperture-radar, SAR, image data into regions. Studies directed toward refinement of method of automated analysis of SAR data.
NASA Astrophysics Data System (ADS)
Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.
2017-04-01
Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.
You, Hongjian
2018-01-01
Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach. PMID:29364194
An, Quanzhi; Pan, Zongxu; You, Hongjian
2018-01-24
Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.
Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images
NASA Technical Reports Server (NTRS)
Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.
1991-01-01
The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.
Road detection in SAR images using a tensor voting algorithm
NASA Astrophysics Data System (ADS)
Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian
2007-11-01
In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.
Calibration and Validation of Airborne InSAR Geometric Model
NASA Astrophysics Data System (ADS)
Chunming, Han; huadong, Guo; Xijuan, Yue; Changyong, Dou; Mingming, Song; Yanbing, Zhang
2014-03-01
The image registration or geo-coding is a very important step for many applications of airborne interferometric Synthetic Aperture Radar (InSAR), especially for those involving Digital Surface Model (DSM) generation, which requires an accurate knowledge of the geometry of the InSAR system. While the trajectory and attitude instabilities of the aircraft introduce severe distortions in three dimensional (3-D) geometric model. The 3-D geometrical model of an airborne SAR image depends on the SAR processor itself. Working at squinted model, i.e., with an offset angle (squint angle) of the radar beam from broadside direction, the aircraft motion instabilities may produce distortions in airborne InSAR geometric relationship, which, if not properly being compensated for during SAR imaging, may damage the image registration. The determination of locations of the SAR image depends on the irradiated topography and the exact knowledge of all signal delays: range delay and chirp delay (being adjusted by the radar operator) and internal delays which are unknown a priori. Hence, in order to obtain reliable results, these parameters must be properly calibrated. An Airborne InSAR mapping system has been developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS) to acquire three-dimensional geo-spatial data with high resolution and accuracy. To test the performance of the InSAR system, the Validation/Calibration (Val/Cal) campaign has carried out in Sichun province, south-west China, whose results will be reported in this paper.
Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN
NASA Astrophysics Data System (ADS)
Hughes, Lloyd H.; Schmitt, Michael; Mou, Lichao; Wang, Yuanyuan; Zhu, Xiao Xiang
2018-05-01
In this letter, we propose a pseudo-siamese convolutional neural network (CNN) architecture that enables to solve the task of identifying corresponding patches in very-high-resolution (VHR) optical and synthetic aperture radar (SAR) remote sensing imagery. Using eight convolutional layers each in two parallel network streams, a fully connected layer for the fusion of the features learned in each stream, and a loss function based on binary cross-entropy, we achieve a one-hot indication if two patches correspond or not. The network is trained and tested on an automatically generated dataset that is based on a deterministic alignment of SAR and optical imagery via previously reconstructed and subsequently co-registered 3D point clouds. The satellite images, from which the patches comprising our dataset are extracted, show a complex urban scene containing many elevated objects (i.e. buildings), thus providing one of the most difficult experimental environments. The achieved results show that the network is able to predict corresponding patches with high accuracy, thus indicating great potential for further development towards a generalized multi-sensor key-point matching procedure. Index Terms-synthetic aperture radar (SAR), optical imagery, data fusion, deep learning, convolutional neural networks (CNN), image matching, deep matching
Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region
NASA Astrophysics Data System (ADS)
Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.
2015-10-01
The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple
Hybrid space-airborne bistatic SAR geometric resolutions
NASA Astrophysics Data System (ADS)
Moccia, Antonio; Renga, Alfredo
2009-09-01
Performance analysis of Bistatic Synthetic Aperture Radar (SAR) characterized by arbitrary geometric configurations is usually complex and time-consuming since system impulse response has to be evaluated by bistatic SAR processing. This approach does not allow derivation of general equations regulating the behaviour of image resolutions with varying the observation geometry. It is well known that for an arbitrary configuration of bistatic SAR there are not perpendicular range and azimuth directions, but the capability to produce an image is not prevented as it depends only on the possibility to generate image pixels from time delay and Doppler measurements. However, even if separately range and Doppler resolutions are good, bistatic SAR geometries can exist in which imaging capabilities are very poor when range and Doppler directions become locally parallel. The present paper aims to derive analytical tools for calculating the geometric resolutions of arbitrary configuration of bistatic SAR. The method has been applied to a hybrid bistatic Synthetic Aperture Radar formed by a spaceborne illuminator and a receiving-only airborne forward-looking Synthetic Aperture Radar (F-SAR). It can take advantage of the spaceborne illuminator to dodge the limitations of monostatic FSAR. Basic modeling and best illumination conditions have been detailed in the paper.
32. SAR1, VIEW FROM STABLE LOFT. SCE negative no. 10319, ...
32. SAR-1, VIEW FROM STABLE LOFT. SCE negative no. 10319, November 1, 1923. Photograph by G. Haven Bishop. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
The Theoretical Problem of Partial Coherence and Partial Polarization in PolSAR and PolInSAR
NASA Astrophysics Data System (ADS)
Alvarez-Perez, J. L.
2013-08-01
Coherence is a key concept in all aspects related to SAR, and it is also an essential ingredient not only of its signal processing and image formation but also of the data postprocessing stages of SAR data. Coherence is however a non-trivial concept that has been the subject of much debate in the last sixty years, even if its definition in the context of PolInSAR has been almost univocal. Nevertheless, the mutual relationships between coherence, polarization and statistical independence in PolSAR has recently been the subject of discussion in [1]. Some of these questions affect the eigenanalysis-based approach to PolInSAR, as developed by Cloude and Papathanassiou's foundational work. Coherence involves the behaviour of electromagnetic waves in at least a pair of points and in this sense it plays an important role in interferometry that is not present in non-interferometric radar polarimetry. PolInSAR inherits some of the difficulties found in [1], which stem from the controversial confusion between coherence and polarization as present in PolSAR, as well as the ability of separating different physical contributors to the scattering phenomenon through the use of eigenvalues and eigenvectors. Although these are also issues present in eigenanalysis-based PolInSAR, it is still possible to analyze a scene in terms of coherence and this very concept of coherence is the subject of this paper. A new analysis of the concept of coherence for interferometry is proposed, including multiple observation point configurations that bring about statistical moments whose order is higher than two.
Hu, Jun; Li, Zhi-Wei; Ding, Xiao-Li; Zhu, Jian-Jun
2008-10-21
The M w =7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the
The Membrane Dynamics of Pexophagy Are Influenced by Sar1p in Pichia pastoris
Schroder, Laura A.; Ortiz, Michael V.
2008-01-01
Several Sec proteins including a guanosine diphosphate/guanosine triphosphate exchange factor for Sar1p have been implicated in autophagy. In this study, we investigated the role of Sar1p in pexophagy by expressing dominant-negative mutant forms of Sar1p in Pichia pastoris. When expressing sar1pT34N or sar1pH79G, starvation-induced autophagy, glucose-induced micropexophagy, and ethanol-induced macropexophagy are dramatically suppressed. These Sar1p mutants did not affect the initiation or expansion of the sequestering membranes nor the trafficking of Atg11p and Atg9p to these membranes during micropexophagy. However, the lipidation of Atg8p and assembly of the micropexophagic membrane apparatus, which are essential to complete the incorporation of the peroxisomes into the degradative vacuole, were inhibited when either Sar1p mutant protein was expressed. During macropexophagy, the expression of sar1pT34N inhibited the formation of the pexophagosome, whereas sar1pH79G suppressed the delivery of the peroxisome from the pexophagosome to the vacuole. The pexophagosome contained Atg8p in wild-type cells, but in cells expressing sar1pH79G these organelles contain both Atg8p and endoplasmic reticulum components as visualized by DsRFP-HDEL. Our results demonstrate key roles for Sar1p in both micro- and macropexophagy. PMID:18768759
Methods of evaluating the effects of coding on SAR data
NASA Technical Reports Server (NTRS)
Dutkiewicz, Melanie; Cumming, Ian
1993-01-01
It is recognized that mean square error (MSE) is not a sufficient criterion for determining the acceptability of an image reconstructed from data that has been compressed and decompressed using an encoding algorithm. In the case of Synthetic Aperture Radar (SAR) data, it is also deemed to be insufficient to display the reconstructed image (and perhaps error image) alongside the original and make a (subjective) judgment as to the quality of the reconstructed data. In this paper we suggest a number of additional evaluation criteria which we feel should be included as evaluation metrics in SAR data encoding experiments. These criteria have been specifically chosen to provide a means of ensuring that the important information in the SAR data is preserved. The paper also presents the results of an investigation into the effects of coding on SAR data fidelity when the coding is applied in (1) the signal data domain, and (2) the image domain. An analysis of the results highlights the shortcomings of the MSE criterion, and shows which of the suggested additional criterion have been found to be most important.
Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.
Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen
2015-09-11
This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.
Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map
Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen
2015-01-01
This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543
Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing
2017-01-01
This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm. PMID:28555057
NASA Astrophysics Data System (ADS)
Aulenbacher, Uwe; Rech, Klaus; Sedlmeier, Johannes; Pratisto, Hans; Wellig, Peter
2014-10-01
Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.
Playback system designed for X-Band SAR
NASA Astrophysics Data System (ADS)
Yuquan, Liu; Changyong, Dou
2014-03-01
SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.
NASA Astrophysics Data System (ADS)
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
Mapping and monitoring renewable resources with space SAR
NASA Technical Reports Server (NTRS)
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.
Spatio-Temporal Mining of PolSAR Satellite Image Time Series
NASA Astrophysics Data System (ADS)
Julea, A.; Meger, N.; Trouve, E.; Bolon, Ph.; Rigotti, C.; Fallourd, R.; Nicolas, J.-M.; Vasile, G.; Gay, M.; Harant, O.; Ferro-Famil, L.
2010-12-01
This paper presents an original data mining approach for describing Satellite Image Time Series (SITS) spatially and temporally. It relies on pixel-based evolution and sub-evolution extraction. These evolutions, namely the frequent grouped sequential patterns, are required to cover a minimum surface and to affect pixels that are sufficiently connected. These spatial constraints are actively used to face large data volumes and to select evolutions making sense for end-users. In this paper, a specific application to fully polarimetric SAR image time series is presented. Preliminary experiments performed on a RADARSAT-2 SITS covering the Chamonix Mont-Blanc test-site are used to illustrate the proposed approach.
Neural network-based feature point descriptors for registration of optical and SAR images
NASA Astrophysics Data System (ADS)
Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry
2018-04-01
Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.
Ship heading and velocity analysis by wake detection in SAR images
NASA Astrophysics Data System (ADS)
Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo
2016-11-01
With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.
Global Rapid Flood Mapping System with Spaceborne SAR Data
NASA Astrophysics Data System (ADS)
Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.
2017-12-01
As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from
Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong
2015-01-01
This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB. PMID:26712765
Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong
2015-12-26
This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.
Using Sentinel-1 SAR satellites to map wind speed variation across offshore wind farm clusters
NASA Astrophysics Data System (ADS)
James, S. F.
2017-11-01
Offshore wind speed maps at 500m resolution are derived from freely available satellite Synthetic Aperture Radar (SAR) data. The method for processing many SAR images to derive wind speed maps is described in full. The results are tested against coincident offshore mast data. Example wind speed maps for the UK Thames Estuary offshore wind farm cluster are presented.
NASA Astrophysics Data System (ADS)
Xue, D.; Yu, X.; Jia, S.; Chen, F.; Li, X.
2018-04-01
In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.
NASA Astrophysics Data System (ADS)
Ferro-Famil, L.; El Hajj Chehade, B.; Ho Tong Minh, D.; Tebaldini, S.; LE Toan, T.
2016-12-01
Developing and improving methods to monitor forest biomass in space and time is a timely challenge, especially for tropical forests, for which SAR imaging at larger wavelength presents an interesting potential. Nevertheless, directly estimating tropical forest biomass from classical 2-D SAR images may reveal a very complex and ill-conditioned problem, since a SAR echo is composed of numerous contributions, whose features and importance depend on many geophysical parameters, such has ground humidity, roughness, topography… that are not related to biomass. Recent studies showed that SAR modes of diversity, i.e. polarimetric intensity ratios or interferometric phase centers, do not fully resolve this under-determined problem, whereas Pol-InSAR tree height estimates may be related to biomass through allometric relationships, with, in general over tropical forests, significant levels of uncertainty and lack of robustness. In this context, 3-D imaging using SAR tomography represents an appealing solution at larger wavelengths, for which wave penetration properties ensures a high quality mapping of a tropical forest reflectivity in the vertical direction. This paper presents a series of studies led, in the frame of the preparation of the next ESA mission BIOMASS, on the estimation of biomass over a tropical forest in French Guiana, using Polarimetric SAR Tomographic (Pol-TomSAR) data acquired at P band by ONERA. It is then shown that Pol-TomoSAR significantly improves the retrieval of forest above ground biomass (AGB) in a high biomass forest (200 up to 500 t/ha), with an error of only 10% at 1.5-ha resolution using a reflectivity estimates sampled at a predetermined elevation. The robustness of this technique is tested by applying the same approach over another site, and results show a similar relationship between AGB and tomographic reflectivity over both sites. The excellent ability of Pol-TomSAR to retrieve both canopy top heights and ground topography with an error
Developing an interactive teleradiology system for SARS diagnosis
NASA Astrophysics Data System (ADS)
Sun, Jianyong; Zhang, Jianguo; Zhuang, Jun; Chen, Xiaomeng; Yong, Yuanyuan; Tan, Yongqiang; Chen, Liu; Lian, Ping; Meng, Lili; Huang, H. K.
2004-04-01
Severe acute respiratory syndrome (SARS) is a respiratory illness that had been reported in Asia, North America, and Europe in last spring. Most of the China cases of SARS have occurred by infection in hospitals or among travelers. To protect the physicians, experts and nurses from the SARS during the diagnosis and treatment procedures, the infection control mechanisms were built in SARS hospitals. We built a Web-based interactive teleradiology system to assist the radiologists and physicians both in side and out side control area to make image diagnosis. The system consists of three major components: DICOM gateway (GW), Web-based image repository server (Server), and Web-based DICOM viewer (Viewer). This system was installed and integrated with CR, CT and the hospital information system (HIS) in Shanghai Xinhua hospital to provide image-based ePR functions for SARS consultation between the radiologists, physicians and experts inside and out side control area. The both users inside and out side the control area can use the system to process and manipulate the DICOM images interactively, and the system provide the remote control mechanism to synchronize their operations on images and display.
7. SOUTHEAST PENSTOCK ENTERING RECEIVER ON NORTHEAST SIDE OF SAR1, ...
7. SOUTHEAST PENSTOCK ENTERING RECEIVER ON NORTHEAST SIDE OF SAR-1, ALSO SHOWING TURBINE SHUT OFF VALVES AND ISOLATION VALVE. VIEW TO WEST. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
36. SAR1 UNDER CONSTRUCTION, WITH WORKERS ATOP CRANE. EEC print ...
36. SAR-1 UNDER CONSTRUCTION, WITH WORKERS ATOP CRANE. EEC print no. N-C-01-00031, no date. Photograph by Benjamin F. Pearson. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
33. SAR1, LOOKING DOWN CANYON OVER TAILRACE CONSTRUCTION. EEC print ...
33. SAR-1, LOOKING DOWN CANYON OVER TAILRACE CONSTRUCTION. EEC print no. G-C-01-00269, no date. Photograph by Benjamin F. Pearson. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
35. SAR1 UNDER CONSTRUCTION, SHOWING TAILRACE AREA AND SCAFFOLDING. EEC ...
35. SAR-1 UNDER CONSTRUCTION, SHOWING TAILRACE AREA AND SCAFFOLDING. EEC print no. N-C-01-00028, no date. Photograph by Benjamin F. Pearson. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture
NASA Technical Reports Server (NTRS)
Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.
1991-01-01
The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.
Using SAR Interferograms and Coherence Images for Object-Based Delineation of Unstable Slopes
NASA Astrophysics Data System (ADS)
Friedl, Barbara; Holbling, Daniel
2015-05-01
This study uses synthetic aperture radar (SAR) interferometric products for the semi-automated identification and delineation of unstable slopes and active landslides. Single-pair interferograms and coherence images are therefore segmented and classified in an object-based image analysis (OBIA) framework. The rule-based classification approach has been applied to landslide-prone areas located in Taiwan and Southern Germany. The semi-automatically obtained results were validated against landslide polygons derived from manual interpretation.
NASA Astrophysics Data System (ADS)
Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.
2016-05-01
The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.
NASA Astrophysics Data System (ADS)
Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias
2018-04-01
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.
Characterizing and estimating noise in InSAR and InSAR time series with MODIS
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.
NASA Astrophysics Data System (ADS)
Aiello, Martina; Gianinetto, Marco
2017-10-01
Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.
Rapid Flood Map Generation from Spaceborne SAR Observations
NASA Astrophysics Data System (ADS)
Yun, S. H.; Liang, C.; Manipon, G.; Jung, J.; Gurrola, E. M.; Owen, S. E.; Hua, H.; Agram, P. S.; Webb, F.; Sacco, G. F.; Rosen, P. A.; Simons, M.
2016-12-01
The Advanced Rapid Imaging and Analysis (ARIA) team has responded to the January 2016 US Midwest Floods along the Mississippi River. Daily teleconferences with FEMA, NOAA, NGA, and USGS, provided information on precipitation and flood crest migration, based on which we coordinated with the Japanese Aerospace Exploration Agency (JAXA) through NASA headquarters for JAXA's ALOS-2 timely tasking over two paths. We produced flood extent maps using ALOS-2 SM3 mode Level 1.5 data that were provided through the International Charter and stored at the US Geological Survey's Hazards Data Distribution System (HDDS) archive. On January 6, the first four frames (70 km x 240 km) were acquired, which included the City of Memphis. We registered post-event SAR images to pre-event images, applied radiometric calibration, took a logarithm of the ratio of the two images. Two thresholds were applied to represent flooded areas that became open water (colored in blue) and flooded areas with tall vegetation (colored in red). The second path was acquired on January 11 further down along the Mississippi River. Seven frames (70 km x 420 km) were acquired and flood maps were created in the similar fashion. The maps were delivered to the FEMA as well as posted on ARIA's public website. The FEMA stated that SAR provides inspection priority for optical imagery and ground response. The ALOS-2 data and the products have been a very important source of information during this response as the flood crest has moved down stream. The SAR data continue to be an important resource during times when optical observations are often not useful. In close collaboration with FEMA and USGS, we also work on other flood events including June 2016 China Floods using European Space Agency's (ESA's) Sentienl-1 data, to produce flood extent maps and identify algorithmic needs and ARIA system's requirements to automate and rapidly produce and deliver flood maps for future events. With the addition of Sentinel-1B
Evaluation of C-band SAR data from SAREX 1992: Tapajos study site
NASA Technical Reports Server (NTRS)
Shimabukuro, Yosio Edemir; Filho, Pedro Hernandez; Lee, David Chung Liang; Ahern, F. J.; Paivadossantosfilho, Celio; Rolodealmeida, Rionaldo
1993-01-01
As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.
Interferometric synthetic aperture radar (InSAR)—its past, present and future
Lu, Zhong; Kwoun, Oh-Ig; Rykhus, R.P.
2007-01-01
Very simply, interferometric synthetic aperture radar (InSAR) involves the use of two or more synthetic aperture radar (SAR) images of the same area to extract landscape topography and its deformation patterns. A SAR system transmits electromagnetic waves at a wavelength that can range from a few millimeters to tens of centimeters and therefore can operate during day and night under all-weather conditions. Using SAR processing technique (Curlander and McDonough, 1991), both the intensity and phase of the reflected (or backscattered) radar signal of each ground resolution element (a few meters to tens of meters) can be calculated in the form of a complex-valued SAR image that represents the reflectivity of the ground surface. The amplitude or intensity of the SAR image is determined primarily by terrain slope, surface roughness, and dielectric constants, whereas the phase of the SAR image is determined primarily by the distance between the satellite antenna and the ground targets. InSAR imaging utilizes the interaction of electromagnetic waves, referred to as interference, to measure precise distances between the satellite antenna and ground resolution elements to derive landscape topography and its subtle change in elevation.
Polarimetric SAR Interferometry to Monitor Land Subsidence in Tehran
NASA Astrophysics Data System (ADS)
Sadeghi, Zahra; Valadan Zoej, Mohammad Javad; Muller, Jan-Peter
2016-08-01
This letter uses a combination of ADInSAR with a coherence optimization method. Polarimetric DInSAR is able to enhance pixel phase quality and thus coherent pixel density. The coherence optimization method is a search-based approach to find the optimized scattering mechanism introduced by Navarro-Sanchez [1]. The case study is southwest of Tehran basin located in the North of Iran. It suffers from a high-rate of land subsidence and is covered by agricultural fields. Usually such an area would significantly decorrelate but applying polarimetric ADInSAR it is possible to obtain a more coherent pixel coverage. A set of dual-pol TerraSAR-X images was ordered for polarimetric ADInSAR procedure. The coherence optimization method is shown to have increased the density and phase quality of coherent pixels significantly.
SAR Speckle Noise Reduction Using Wiener Filter
NASA Technical Reports Server (NTRS)
Joo, T. H.; Held, D. N.
1983-01-01
Synthetic aperture radar (SAR) images are degraded by speckle. A multiplicative speckle noise model for SAR images is presented. Using this model, a Wiener filter is derived by minimizing the mean-squared error using the known speckle statistics. Implementation of the Wiener filter is discussed and experimental results are presented. Finally, possible improvements to this method are explored.
Digital SAR processing using a fast polynomial transform
NASA Technical Reports Server (NTRS)
Butman, S.; Lipes, R.; Rubin, A.; Truong, T. K.
1981-01-01
A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network.
Flood extent and water level estimation from SAR using data-model integration
NASA Astrophysics Data System (ADS)
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.
Shallow magma system of Kilauea volcano investigated using L-band synthetic aperture radar data
NASA Astrophysics Data System (ADS)
Fukushima, Y.; Sinnett, D. K.; Segall, P.
2009-12-01
L-band synthetic aperture radar (SAR) images on Kilauea volcano have been archived by Japanese JERS-1 (1992-1998) and ALOS (2006-) satellites. L-band interferometric SAR (InSAR) can measure displacements in a broader region compared to C-band, thanks to higher phase coherence on vegetated areas. We made InSAR analyses on Kilauea using the following L-band data sets: J1) two JERS-1 images, acquired on 20 Oct. 1992 and 1 Mar. 1993 from a descending orbit (RSP path 589) with off-nadir angle of 34.3 degrees, J2) three JERS-1 images, acquired between 8 Oct. 1993 and 3 Jul. 1997 from a descending orbit (RSP path 590) with off-nadir angle of 34.3 degrees, A1) 13 ALOS images, acquired between 24 Jun. 2006 and 14 Feb. 2009 from an ascending orbit with off-nadir angle 9.9 degrees, and A2) 11 ALOS images, acquired between 21 May 2006 and 26 Feb. 2009 from a descending orbit with off-nadir angle 9.9 degrees. One-second SRTM digital elevation data were used to remove the topographic phase. The interferogram of the data set J1 contains signals of 1) a maximum of about 30 cm of range decrease resulting from a dike intrusion in the Makaopuhi crater area, 2) about 10 cm of maximum range increase in the Pu`u `O`o crater area, and 3) a few cm of range increase along the East Rift Zone (ERZ) between the summit and Pu`u `O`o craters. An interferogram (8 Oct. 1993 - 3 Jul. 1997) of the data set J2 indicates 1) range increase (maximum 7 cm/yr) in both the summit and Pu`u `O`o areas, 2) range increase (maximum 5 cm/yr) along the ERZ between the summit and Makaopuhi crater, and 3) range decrease (maximum 6cm/yr) on the southern flank near the coast that is consistent with a seaward movement of the southern flank. A small baseline subset InSAR time-series analysis was performed using all the images of the data sets A1 and A2, assuming that the data acquisitions had been made in pure vertical direction. The analysis period includes the 2007 Father's day dike intrusion. A preliminary result
Integration of SAR and AIS for ship detection and identification
NASA Astrophysics Data System (ADS)
Yang, Chan-Su; Kim, Tae-Ho
2012-06-01
This abstract describes the preliminary design concept for an integration system of SAR and AIS data. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Once both data reports are obtained, one need to match the timings of AIS data acquisition over the SAR image acquisition time with consideration of local time & boundary to extract the closest time signal from AIS report in order to know the AIS based ship positions, but still one cannot be able to distinguish which ships have the AIS transponder after projection of AIS based position onto the SAR image acquisition boundary. As far as integration is concerned, the ship dead-reckoning concept is most important forecasted position which provides the AIS based ship position at the time of SAR image acquisition and also provides the hints for azimuth shift which occurred in SAR image for the case of moving ships which moves in the direction perpendicular to the direction of flight path. Unknown ship's DR estimation is to be carried out based on the initial positions, speed and course over ground, which has already been shorted out from AIS reports, during the step of time matching. This DR based ship's position will be the candidate element for searching the SAR based ship targets for the purpose of identification & matching within the certain boundary around DR. The searching method is performed by means of estimation of minimum distance from ship's DR to SAR based ship position, and once it determines, so the candidate element will look for matching like ship size match of DR based ship's dimension wrt SAR based ship's edge, there may be some error during the matching with SAR based ship edges with actual ship's hull design as per the longitudinal and transverse axis size information obtained from the AIS reports due to
34. SAR2, WATERDRIVEN EXCITERS. SCE negative no. 10329, November 1, ...
34. SAR-2, WATER-DRIVEN EXCITERS. SCE negative no. 10329, November 1, 1923. Photograph by G. Haven Bishop. - Santa Ana River Hydroelectric System, SAR-2 Powerhouse, Redlands, San Bernardino County, CA
NASA Astrophysics Data System (ADS)
Owen, S. E.; Hua, H.; Rosen, P. A.; Agram, P. S.; Webb, F.; Simons, M.; Yun, S. H.; Sacco, G. F.; Liu, Z.; Fielding, E. J.; Lundgren, P.; Moore, A. W.
2017-12-01
A new era of geodetic imaging arrived with the launch of the ESA Sentinel-1A/B satellites in 2014 and 2016, and with the 2016 confirmation of the NISAR mission, planned for launch in 2021. These missions assure high quality, freely and openly distributed regularly sampled SAR data into the indefinite future. These unprecedented data sets are a watershed for solid earth sciences as we progress towards the goal of ubiquitous InSAR measurements. We now face the challenge of how to best address the massive volumes of data and intensive processing requirements. Should scientists individually process the same data independently themselves? Should a centralized service provider create standard products that all can use? Are there other approaches to accelerate science that are cost effective and efficient? The Advanced Rapid Imaging and Analysis (ARIA) project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. However, there are challenges in defining the optimal InSAR data products for the solid earth science community. In this presentation, we will present our experience with InSAR users, our lessons learned the advantages of on demand and standard products, and our proposal for the most effective path forward.
Lu, Z.; Wicks, C.; Kwoun, O.; Power, J.A.; Dzurisin, D.
2005-01-01
In March 1996, an intense earthquake swarm beneath Akutan Island, Alaska, was accompanied by extensive ground cracking but no eruption of Akutan volcano. Radar interferograms produced from L-band JERS-1 and C-band ERS-1/2 images show uplift associated with the swarm by as much as 60 cm on the western part of the island. The JERS-1 interferogram has greater coherence, especially in areas with loose surface material or thick vegetation. It also shows subsidence of similar magnitude on the eastern part of the island and displacements along faults reactivated during the swarm. The axis of uplift and subsidence strikes about N70??W, which is roughly parallel to a zone of fresh cracks on the northwest flank of the volcano, to normal faults that cut the island and to the inferred maximum compressive stress direction. A common feature of models that fit the deformation is the emplacement of a shallow dike along this trend beneath the northwest flank of the volcano. Both before and after the swarm, the northwest flank was uplifted 5-20 mm/year relative to the southwest flank, probably by magma intrusion. The zone of fresh cracks subsided about 20 mm during 1996-1997 and at lesser rates thereafter, possibly because of cooling and degassing of the intrusion. ?? 2005 CASI.
NASA Astrophysics Data System (ADS)
Teutsch, Michael; Saur, Günter
2011-11-01
Spaceborne SAR imagery offers high capability for wide-ranging maritime surveillance especially in situations, where AIS (Automatic Identification System) data is not available. Therefore, maritime objects have to be detected and optional information such as size, orientation, or object/ship class is desired. In recent research work, we proposed a SAR processing chain consisting of pre-processing, detection, segmentation, and classification for single-polarimetric (HH) TerraSAR-X StripMap images to finally assign detection hypotheses to class "clutter", "non-ship", "unstructured ship", or "ship structure 1" (bulk carrier appearance) respectively "ship structure 2" (oil tanker appearance). In this work, we extend the existing processing chain and are now able to handle full-polarimetric (HH, HV, VH, VV) TerraSAR-X data. With the possibility of better noise suppression using the different polarizations, we slightly improve both the segmentation and the classification process. In several experiments we demonstrate the potential benefit for segmentation and classification. Precision of size and orientation estimation as well as correct classification rates are calculated individually for single- and quad-polarization and compared to each other.
Research on a dem Coregistration Method Based on the SAR Imaging Geometry
NASA Astrophysics Data System (ADS)
Niu, Y.; Zhao, C.; Zhang, J.; Wang, L.; Li, B.; Fan, L.
2018-04-01
Due to the systematic error, especially the horizontal deviation that exists in the multi-source, multi-temporal DEMs (Digital Elevation Models), a method for high precision coregistration is needed. This paper presents a new fast DEM coregistration method based on a given SAR (Synthetic Aperture Radar) imaging geometry to overcome the divergence and time-consuming problem of the conventional DEM coregistration method. First, intensity images are simulated for two DEMs under the given SAR imaging geometry. 2D (Two-dimensional) offsets are estimated in the frequency domain using the intensity cross-correlation operation in the FFT (Fast Fourier Transform) tool, which can greatly accelerate the calculation process. Next, the transformation function between two DEMs is achieved via the robust least-square fitting of 2D polynomial operation. Accordingly, two DEMs can be precisely coregistered. Last, two DEMs, i.e., one high-resolution LiDAR (Light Detection and Ranging) DEM and one low-resolution SRTM (Shutter Radar Topography Mission) DEM, covering the Yangjiao landslide region of Chongqing are taken as an example to test the new method. The results indicate that, in most cases, this new method can achieve not only a result as much as 80 times faster than the minimum elevation difference (Least Z-difference, LZD) DEM registration method, but also more accurate and more reliable results.
52. SAR1, OPERATOR WORKING GOVERNOR. EEC print no. GC0100390, no ...
52. SAR-1, OPERATOR WORKING GOVERNOR. EEC print no. G-C-01-00390, no date. Photograph by Benjamin F. Pearson. - Santa Ana River Hydroelectric System, SAR-1 Powerhouse, Redlands, San Bernardino County, CA
1. RUINED PORTION OF SANTA ANA CANAL INTAKE ALONGSIDE SAR3 ...
1. RUINED PORTION OF SANTA ANA CANAL INTAKE ALONGSIDE SAR-3 SYSTEM TUNNEL, JUST TO SOUTH OF SAR-2. VIEW TO SOUTHEAST. - Santa Ana River Hydroelectric System, Abandoned Tunnel, Redlands, San Bernardino County, CA
NASA Technical Reports Server (NTRS)
Aftabi, Pedarm; Talbot, hristopher; Fielding, Eric
2005-01-01
As part of a long-term attempt to learn how the climatic and tectonic signal interact to shape a steady state mountain monitored displacement of a markers in SE termination and also near the summit of a small viscous salt fountain extruding onto the Central plateau of Iran. The marker displacements relate to the first InSAR interferograms of salt extrusion (980913 to 990620) calculated Earth tides, winds, air pressures and temperatures. In the first documented staking exercise, hammered wooden stakes vertically through the surgical marl (c. 1 Ocm deep) onto the top of crystalline salt. These stakes installed in an irregular array elongate E-W along the c.50 m high cliff marking the effective SE terminus of the glacier at Qum Kuh(Centra1 Iran) ,just to the E of a NE trending river cliff about 40 m high. We merely measured the distances between pairs of stakes with known azimuth about 2 m apart to calculate sub horizontal strain in a small part of Qum Kuh. Stakes moved and micro strains for up to 46 pairs of stakes (p strain= ((lengthl-length2)/1engthl) x 10-1) was calculated for each seven stake epochs and plotted against their azimuth on simplified array maps. The data fit well the sine curves cxpected of the maximum and minimum strain ellipses. The first documented stakes located on the SE where the InSAR image show -1 1 to 0 mm pink to purple, 0 to lOmm purple to blue, and show high activity of salt in low activity area of the InSAR image (980913 to 990620).Short term micro strains of stake tie lines record anisotropic expansions due to heating and contraction due to cooling. All epochs changed between 7 to 1 17 days (990928 to000 1 16), showed 200 to 400 micro strain lengthening and shortening. The contraction and extension existed in each epoch, but the final strain was extension in E-W in Epoch land 6, contraction in E-W direction during epochs 2-3-4-5 and 7. The second pair of stakes hammered about 20 cm deep into the deep soils(more than 1 m) , near summit
A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.
Zeng, Hong-Cheng; Wang, Peng-Bo; Chen, Jie; Liu, Wei; Ge, LinLin; Yang, Wei
2016-02-26
Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method.
A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR
Zeng, Hong-Cheng; Wang, Peng-Bo; Chen, Jie; Liu, Wei; Ge, LinLin; Yang, Wei
2016-01-01
Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method. PMID:26927117
Earth Studies Using L-band Synthetic Aperture Radar
NASA Technical Reports Server (NTRS)
Rosen, Paul A.
1999-01-01
L-band SAR has played an important role in studies of the Earth by revealing the nature of the larger-scale (decimeter) surface features. JERS-1, by supplying multi-seasonal coverage of the much of the earth, has demonstrated the importance of L-band SARs. Future L-band SARs such as ALOS and LightSAR will pave the way for science missions that use SAR instruments. As technology develops to enable lower cost SAR instruments, missions will evolve to each have a unique science focus. International coordination of multi-parameter constellations and campaigns will maximize science return.
Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming
2017-12-22
The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.
Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case
Ao, Dongyang; Hu, Cheng; Tian, Weiming
2017-01-01
The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917
2004-03-03
JPL Researcher Bruce Chapman at an AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign. AirSAR 2004 is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.
Research on vehicle detection based on background feature analysis in SAR images
NASA Astrophysics Data System (ADS)
Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping
2017-10-01
Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.
Oil Spill detection off the eastern coast of India using Sentinel-1 dual polarimeteric SAR imagery
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
Ruan, Z.; Yan, S.; Liu, G.; Guo, H.; LV, M.
2016-12-01
Glacier dynamic parameters, such as velocity fields and motion patterns, play a crucial role in the estimation of ice mass balance variations and in the monitoring of glacier-related hazards. Characterized by being independent of cloud cover and solar illumination, synthetic aperture radar (SAR) at long wavelength has provided an invaluable way to measure mountain glacier motion. Compared with optical imagery and in-situ surveys, it has been successfully exploited to detect glacier motion in many previous studies, usually with pixel-tracking (PT), differential interferometric SAR (D-InSAR) and multi-aperture interferometry (MAI) methods. However, the reliability of the extracted glacier velocities heavily depends on complex terrain topography and diverse glacial motion types. D-InSAR and MAI techniques are prone to fail in the case of mountain glaciers because of the steep terrain and their narrow sizes. PT method is considered to be the alternative way, although it is subject to a low accuracy.We propose an integrated strategy based on comprehensive utilization of the phase information (D-InSAR and MAI) and intensity information (PT) of SAR images, which is used to yield an accurate and detailed ice motion pattern for the typical glaciers in the West Kunlun Mountains, China, by fully exploiting the SAR imagery. In order to avoid the error introduced by the motion decomposition operation, the derived ice motion is presented in the SAR imaging dimension composed of the along-track and slant-range directions. The Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM) at 3 arc-sec resolution is employed to remove and compensate for the topography-related signal in the D-InSAR, MAI, and PT methods. Compared with the traditional SAR-based methods, the proposed approach can determine the ice motion over a widely varying range of ice velocities with a relatively high accuracy. Its capability is proved by the detailed ice displacement pattern with the
Digital SAR processing using a fast polynomial transform
NASA Technical Reports Server (NTRS)
Truong, T. K.; Lipes, R. G.; Butman, S. A.; Reed, I. S.; Rubin, A. L.
1984-01-01
A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network. Previously announced in STAR as N82-11295
Zhang, Yue; Zou, Huanxin; Luo, Tiancheng; Qin, Xianxiang; Zhou, Shilin; Ji, Kefeng
2016-01-01
The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER) works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR) images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR) and Airborne Synthetic Aperture Radar (AirSAR) data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods. PMID:27754385
InSAR observation of the September 3rd nuclear test in North Korea
NASA Astrophysics Data System (ADS)
Wei, M.
2017-12-01
InSAR data from ALOS-2 and Sentinel-1B satellites show significant loss of coherence in phase images covering the September 3rd event at Mt Mantap, which provide strong evidence that the nuclear test occurred there. The area with low coherence is consistent with several seismic-determined locations. The loss of coherence is much more significant than that of the January 6, 2016 event, which also has good InSAR data coverage and show surface displacement. For regions that stay coherent at peripheral area of Mt Mantap, the data show line-of-sight displacement up to 10 cm. In comparison, TerraSAR-X InSAR data (generated by Dr. Teng Wang) show subsidence up to 2 m and horizontal displacement up to 4 m in the area that ALOS2 and Sentinel-1B lost coherence. The large displacement is calculated from the shift of pixels in amplitude images, which does not work for ALOS and Sentinel-1B data. Nevertheless, all InSAR data suggest that the event occurred at Mt Mantap. We conclude that InSAR provides a powerful, independent tool for monitoring and characterizing nuclear tests, whether announced or not, to complement the seismic method.
Software For Tie-Point Registration Of SAR Data
NASA Technical Reports Server (NTRS)
Rignot, Eric; Dubois, Pascale; Okonek, Sharon; Van Zyl, Jacob; Burnette, Fred; Borgeaud, Maurice
1995-01-01
SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.
1. OVERVIEW OF FIFTH FLUME ABOVE SAR1 FOREBAY, SHOWING OLD ...
1. OVERVIEW OF FIFTH FLUME ABOVE SAR-1 FOREBAY, SHOWING OLD AND NEWER CEMENT FOOTINGS. VIEW TO NORTHEAST. - Santa Ana River Hydroelectric System, Flumes & Tunnels below Sandbox, Redlands, San Bernardino County, CA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wahl, D.E.; Jakowatz, C.V. Jr.; Ghiglia, D.C.
1991-01-01
Autofocus methods in SAR and self-survey techniques in SONAR have a common mathematical basis in that they both involve estimation and correction of phase errors introduced by sensor position uncertainties. Time delay estimation and correlation methods have been shown to be effective in solving the self-survey problem for towed SONAR arrays. Since it can be shown that platform motion errors introduce similar time-delay estimation problems in SAR imaging, the question arises as to whether such techniques could be effectively employed for autofocus of SAR imagery. With a simple mathematical model for motion errors in SAR, we will show why suchmore » correlation/time-delay techniques are not nearly as effective as established SAR autofocus algorithms such as phase gradient autofocus or sub-aperture based methods. This analysis forms an important bridge between signal processing methodologies for SAR and SONAR. 5 refs., 4 figs.« less
NASA Astrophysics Data System (ADS)
Zhang, B.; Koirala, R.; Oliver-Cabrera, T.; Wdowinski, S.; Osmanoglu, B.
2017-12-01
Hurricanes can cause winds, rainfall and storm surge, all of which could result in flooding. Between August and September 2017, Hurricanes Harvey, Irma and Maria made landfall over Texas, Florida and Puerto Rico causing destruction and damages. Flood mapping is important for water management and to estimate risks and property damage. Though water gauges are able to monitor water levels, they are normally distributed sparsely. To map flooding products of these extreme events, we use Synthetic Aperture Radar (SAR) observations acquired by the European satellite constellation Sentinel-1. We obtained two acquisitions from before each flooding event, a single acquisition during the hurricane, and two after each event, a total of five acquisitions. We use both amplitude and phase observations to map extent and magnitude of flooding respectively. To map flooding extents, we use amplitude images from before, after and if possible during the hurricane pass. A calibration is used to convert the image raw data to backscatter coefficient, termed sigma nought. We generate a composite of the two image layers using red and green bands to show the change of sigma nought between acquisitions, which directly reflects the extent of flooding. Because inundation can result with either an increase or decrease of sigma nought values depending on the surface scattering characteristics, we map flooded areas in location where sigma nought changes were above a detection threshold. To study magnitude of flooding we study Interferometric Synthetic Aperture Radar (InSAR) phase changes. Changes in the water level can be detected by the radar when the signal is reflected away from water surface and bounces again by another object (e.g. trees and/or buildings) known as double bounce phase. To generate meaningful interferograms, we compare phase information with the nearest water gauge records to verify our results. Preliminary results show that the three hurricanes caused flooding condition over
Polarimetric SAR calibration experiment using active radar calibrators
NASA Astrophysics Data System (ADS)
Freeman, Anthony; Shen, Yuhsyen; Werner, Charles L.
1990-03-01
Active radar calibrators are used to derive both the amplitude and phase characteristics of a multichannel polarimetric SAR from the complex image data. Results are presented from an experiment carried out using the NASA/JPL DC-8 aircraft SAR over a calibration site at Goldstone, California. As part of the experiment, polarimetric active radar calibrators (PARCs) with adjustable polarization signatures were deployed. Experimental results demonstrate that the PARCs can be used to calibrate polarimetric SAR images successfully. Restrictions on the application of the PARC calibration procedure are discussed.
Polarimetric SAR calibration experiment using active radar calibrators
NASA Technical Reports Server (NTRS)
Freeman, Anthony; Shen, Yuhsyen; Werner, Charles L.
1990-01-01
Active radar calibrators are used to derive both the amplitude and phase characteristics of a multichannel polarimetric SAR from the complex image data. Results are presented from an experiment carried out using the NASA/JPL DC-8 aircraft SAR over a calibration site at Goldstone, California. As part of the experiment, polarimetric active radar calibrators (PARCs) with adjustable polarization signatures were deployed. Experimental results demonstrate that the PARCs can be used to calibrate polarimetric SAR images successfully. Restrictions on the application of the PARC calibration procedure are discussed.
Emergency product generation for disaster management using RISAT and DMSAR quick look SAR processors
NASA Astrophysics Data System (ADS)
Desai, Nilesh; Sharma, Ritesh; Kumar, Saravana; Misra, Tapan; Gujraty, Virendra; Rana, SurinderSingh
2006-12-01
generate full-swath (6 to 75 Kms) DMSAR images in 1m / 3m / 5m / 10m / 30m resolution SAR operating modes. For RISAT mission, this generic Quick Look SAR Processor will be mainly used for browse product generation at NRSA-Shadnagar (SAN) ground receive station. RISAT QLP/NRTP is also proposed to provide an alternative emergency SAR product generation chain. For this, the S/C aux data appended in Onboard SAR Frame Format (x, y, z, x', y', z', roll, pitch, yaw) and predicted orbit from previous days Orbit Determination data will be used. The QLP / NRTP will produce ground range images in real / near real time. For emergency data product generation, additional Off-line tasks like geo-tagging, masking, QC etc needs to be performed on the processed image. The QLP / NRTP would generate geo-tagged images from the annotation data available from the SAR P/L data itself. Since the orbit & attitude information are taken as it is, the location accuracy will be poorer compared to the product generated using ADIF, where smoothened attitude and orbit are made available. Additional tasks like masking, output formatting and Quality checking of the data product will be carried out at Balanagar, NRSA after the image annotated data from QLP / NRTP is sent to Balanagar. The necessary interfaces to the QLP/NRTP for Emergency product generation are also being worked out. As is widely acknowledged, QLP/NRTP for RISAT and DMSAR is an ambitious effort and the technology of future. It is expected that by the middle of next decade, the next generation SAR missions worldwide will have onboard SAR Processors of varying capabilities and generate SAR Data products and Information products onboard instead of SAR raw data. Thus, it is also envisaged that these activities related to QLP/NRTP implementation for RISAT ground segment and DMSAR will be a significant step which will directly feed into the development of onboard real time processing systems for ISRO's future space borne SAR missions. This paper
2004-03-03
JPL Researcher Tim Miller at the primary AirSAR station aboard NASA's DC-8 flying laboratory during the AirSAR 2004 campaign. AirSAR 2004 is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.
Using SAR satellite data time series for regional glacier mapping
NASA Astrophysics Data System (ADS)
Winsvold, Solveig H.; Kääb, Andreas; Nuth, Christopher; Andreassen, Liss M.; van Pelt, Ward J. J.; Schellenberger, Thomas
2018-03-01
With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.
NASA Technical Reports Server (NTRS)
Boerner, W. M.; Mott, H.; Verdi, J.; Darizhapov, D.; Dorjiev, B.; Tsybjito, T.; Korsunov, V.; Tatchkov, G.; Bashkuyev, Y.; Cloude, S.;
1998-01-01
During the past decade, Radar Polarimetry has established itself as a mature science and advanced technology in high resolution POL-SAR imaging, image target characterization and selective image feature extraction.
NASA Astrophysics Data System (ADS)
Wang, Haipeng; Xu, Feng; Jin, Ya-Qiu; Ouchi, Kazuo
An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.
Chirp Scaling Algorithms for SAR Processing
NASA Technical Reports Server (NTRS)
Jin, M.; Cheng, T.; Chen, M.
1993-01-01
The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.
Pre-processing SAR image stream to facilitate compression for transport on bandwidth-limited-link
Rush, Bobby G.; Riley, Robert
2015-09-29
Pre-processing is applied to a raw VideoSAR (or similar near-video rate) product to transform the image frame sequence into a product that resembles more closely the type of product for which conventional video codecs are designed, while sufficiently maintaining utility and visual quality of the product delivered by the codec.
NASA Astrophysics Data System (ADS)
Liu, Wei; Wei, Tingcun; Li, Bo; Yang, Lifeng; Xue, Feifei; Hu, Yongcai
2016-05-01
This paper presents a 12-bit 1 MS/s successive approximation register-analog to digital converter (SAR-ADC) for the 32-channel front-end electronics of CZT-based PET imaging system. To reduce the capacitance mismatch, instead of the fractional capacitor, the unit capacitor is used as the bridge capacitor in the split-capacitor digital to analog converter (DAC) circuit. In addition, in order to eliminate the periodical DNL errors of -1 LSB which often exists in the SAR-ADC using the charge-redistributed DAC, a calibration algorithm is proposed and verified by the experiments. The proposed 12-bit 1 MS/s SAR-ADC is designed and implemented using a 0.35 μm CMOS technology, it occupies only an active area of 986×956 μm2. The measurement results show that, at the power supply of 3.3/5.0 V and the sampling rate of 1 MS/s, the ADC with calibration has a signal-to-noise-and-distortion ratio (SINAD) of 67.98 dB, the power dissipation of 5 mW, and a figure of merit (FOM) of 2.44 pJ/conv.-step. This ADC is with the features of high accuracy, low power and small layout area, it is especially suitable to the one-chip integration of the front-end readout electronics.
Airborne Multi-Band SAR in the Arctic
NASA Astrophysics Data System (ADS)
Gardner, J. M.; Brozena, J. M.; Liang, R.; Ball, D.; Holt, B.; Thomson, J.
2016-12-01
As one component of the Office of Naval Research supported Sea State Departmental Research Initiative during October of 2015 the Naval Research Laboratory flew an ultrawide-band, low-frequency, polarimetric SAR over the southward advancing sea ice in Beaufort Sea. The flights were coordinated with the research team aboard the R/V Sikuliaq working near and in the advancing pack ice. The majority of the SAR data were collected with the L-Band sensor (1000-1500 MHz) from an altitude of 10,000', providing a useful swath 6 km wide with 75o and 25 o angles of incidence at the inner and outer edge of the swath respectively. Some data were also collected with the P-Band SAR (215-915 MHz). The extremely large bandwidths allowed for formation of image pixels as small as 30 cm, however, we selected 60 cm pixel size to reduce image speckle. The separate polarimetric images are calibrated to one pixel to allow for calculations such as polarimetric decompositions that require the images to be well aligned. Both frequencies are useful particularly for the detection of ridges and areas of deformed ice. There are advantages and disadvantages to airborne SAR imagery compared to satellites. The chief advantages being the enormous allowable bandwidth leading to very fine range resolution, and the ability to fly arbitrary trajectories on demand. The latter permits specific areas to be imaged at a given time with a specified illumination direction. An area can even be illuminated from all directions by flying a circular trajectory around the target area. This captures ice features that are sensitive to illumination direction such as cracks, sastrugi orientation, and ridges. The disadvantages include variation of intensity across the swath with range and incidence angle. In addition to the SAR data, we collected photogrammetric imagery from a DSS-439, scanning lidar from a Riegl Q560 and surface brightness temperatures from a KT-19. However, since all of these sensors are nadir pointing
(abstract) Monitoring the Freeze/Thaw Transitions in Taiga Forests Using ERS-1 SAR
NASA Technical Reports Server (NTRS)
Rignot, E.; Williams, C.; Donald, K. Mc; Way, J. B.; Zimmerman, R.; Viereck, L.
1994-01-01
Automated recording stations have been installed at the Bonanza Creek Experimental Forest, a Long Term Ecological Research (LTER) site located near Fairbanks, Alaska, in a forest stand of the Tanana River floodplain underlain by discontinuous permafrost. These stations provide a continuous record of dielectric constant and temperature of tree trunks, and soil moisture and temperature profiles down to the root zone. Along with the weather stations deployed at the same location, these measurements provide a continuous record of the environmental and phenologic conditions of the forest during a complete seasonal cycle. At the same time, ERS-1 SAR imaged the study site repeatedly from space to provide radar backscatter measurements of the forest approximately three times a month. Here, we examine the temporal dynamic of ERS-1 SAR measurements in relation with the changing environmental and phenologic state of the forest canopy and of the forest ground layers during the winter/spring and fall/winter transitions of 1992 and 1993. During these transitions, we examine whether changes in radar backscatter observed by ERS-1 may be related to freezing or thawing of the soil and vegetation in order to determine the start and end of the growing season for the forest. The results of this analysis are used in turn to determine whether similar changes are observed over larger regions. Mosaics of SAR data generated along three different North-South Alaskan ERS-1 transects that intercept with our study site are used in combination with hourly air temperature and daily precipitation rates gathered at airport weather stations by the National Weather Service. Results obtained using ERS-1 data collected from January 1992 to mid-1993 will be discussed.
Brain MR imaging at ultra-low radiofrequency power.
Sarkar, Subhendra N; Alsop, David C; Madhuranthakam, Ananth J; Busse, Reed F; Robson, Philip M; Rofsky, Neil M; Hackney, David B
2011-05-01
To explore the lower limits for radiofrequency (RF) power-induced specific absorption rate (SAR) achievable at 1.5 T for brain magnetic resonance (MR) imaging without loss of tissue signal or contrast present in high-SAR clinical imaging in order to create a potentially viable MR method at ultra-low RF power to image tissues containing implanted devices. An institutional review board-approved HIPAA-compliant prospective MR study design was used, with written informed consent from all subjects prior to MR sessions. Seven healthy subjects were imaged prospectively at 1.5 T with ultra-low-SAR optimized three-dimensional (3D) fast spin-echo (FSE) and fluid-attenuated inversion-recovery (FLAIR) T2-weighted sequences and an ultra-low-SAR 3D spoiled gradient-recalled acquisition in the steady state T1-weighted sequence. Corresponding high-SAR two-dimensional (2D) clinical sequences were also performed. In addition to qualitative comparisons, absolute signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) for multicoil, parallel imaging acquisitions were generated by using a Monte Carlo method for quantitative comparison between ultra-low-SAR and high-SAR results. There were minor to moderate differences in the absolute tissue SNR and CNR values and in qualitative appearance of brain images obtained by using ultra-low-SAR and high-SAR techniques. High-SAR 2D T2-weighted imaging produced slightly higher SNR, while ultra-low-SAR 3D technique not only produced higher SNR for T1-weighted and FLAIR images but also higher CNRs for all three sequences for most of the brain tissues. The 3D techniques adopted here led to a decrease in the absorbed RF power by two orders of magnitude at 1.5 T, and still the image quality was preserved within clinically acceptable imaging times. RSNA, 2011
NASA Astrophysics Data System (ADS)
Vickers, H.; Eckerstorfer, M.; Malnes, E.; Larsen, Y.; Hindberg, H.
2016-11-01
Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.
Hardware Development and Error Characterization for the AFIT RAIL SAR System
This research is focused on updating the Air Force Institute of Technology (AFIT) Radar Instrumentation Lab (RAIL)Synthetic Aperture Radar ( SAR ...collections from a receiver in motion. Secondly, orthogonal frequency-division multiplexing (OFDM) signals are used to form ( SAR ) images in multiple...experimental and simulation configurations. This research analyses, characterizes and attempts compensation of relevant SAR image error sources, such as Doppler
Detecting and monitoring UCG subsidence with InSAR
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mellors, R J; Foxall, W; Yang, X
2012-03-23
The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidencemore » related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness.« less
The flight test of Pi-SAR(L) for the repeat-pass interferometric SAR
NASA Astrophysics Data System (ADS)
Nohmi, Hitoshi; Shimada, Masanobu; Miyawaki, Masanori
2006-09-01
This paper describes the experiment of the repeat pass interferometric SAR using Pi-SAR(L). The air-borne repeat-pass interferometric SAR is expected as an effective method to detect landslide or predict a volcano eruption. To obtain a high-quality interferometric image, it is necessary to make two flights on the same flight pass. In addition, since the antenna of the Pi-SAR(L) is secured to the aircraft, it is necessary to fly at the same drift angle to keep the observation direction same. We built a flight control system using an auto pilot which has been installed in the airplane. This navigation system measures position and altitude precisely with using a differential GPS, and the PC Navigator outputs a difference from the desired course to the auto pilot. Since the air density is thinner and the speed is higher than the landing situation, the gain of the control system is required to be adjusted during the repeat pass flight. The observation direction could be controlled to some extent by adjusting a drift angle with using a flight speed control. The repeat-pass flight was conducted in Japan for three days in late November. The flight was stable and the deviation was within a few meters for both horizontal and vertical direction even in the gusty condition. The SAR data were processed in time domain based on range Doppler algorism to make the complete motion compensation. Thus, the interferometric image processed after precise phase compensation is shown.
Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR.
Frey, Othmar; Morsdorf, Felix; Meier, Erich
2008-09-24
In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR).
A computerized scheme of SARS detection in early stage based on chest image of digital radiograph
NASA Astrophysics Data System (ADS)
Zheng, Zhong; Lan, Rihui; Lv, Guozheng
2004-05-01
A computerized scheme for early severe acute respiratory syndrome(SARS) lesion detection in digital chest radiographs is presented in this paper. The total scheme consists of two main parts: the first part is to determine suspect lesions by the theory of locally orderless images(LOI) and their spatial features; the second part is to select real lesions among these suspect ones by their frequent features. The method we used in the second part is firstly developed by Katsuragawa et al with necessary modification. Preliminary results indicate that these features are good criterions to tell early SARS lesions apart from other normal lung structures.
Deep learning model-based algorithm for SAR ATR
NASA Astrophysics Data System (ADS)
Friedlander, Robert D.; Levy, Michael; Sudkamp, Elizabeth; Zelnio, Edmund
2018-05-01
Many computer-vision-related problems have successfully applied deep learning to improve the error rates with respect to classifying images. As opposed to optically based images, we have applied deep learning via a Siamese Neural Network (SNN) to classify synthetic aperture radar (SAR) images. This application of Automatic Target Recognition (ATR) utilizes an SNN made up of twin AlexNet-based Convolutional Neural Networks (CNNs). Using the processing power of GPUs, we trained the SNN with combinations of synthetic images on one twin and Moving and Stationary Target Automatic Recognition (MSTAR) measured images on a second twin. We trained the SNN with three target types (T-72, BMP2, and BTR-70) and have used a representative, synthetic model from each target to classify new SAR images. Even with a relatively small quantity of data (with respect to machine learning), we found that the SNN performed comparably to a CNN and had faster convergence. The results of processing showed the T-72s to be the easiest to identify, whereas the network sometimes mixed up the BMP2s and the BTR-70s. In addition we also incorporated two additional targets (M1 and M35) into the validation set. Without as much training (for example, one additional epoch) the SNN did not produce the same results as if all five targets had been trained over all the epochs. Nevertheless, an SNN represents a novel and beneficial approach to SAR ATR.
Empirical wind retrieval model based on SAR spectrum measurements
NASA Astrophysics Data System (ADS)
Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad
ambiguity from polarimetric SAR. A criterion based on the complex correlation coefficient between the VV and VH signals sign is applied to select the wind direction. An additional quality control on the wind speed value retrieved with the spectral method is applied. Here, we use the direction obtained with the spectral method and the backscattered signal for CMOD wind speed estimate. The algorithm described above may be refined by the use of numerous SAR data and wind measurements. In the present preliminary work the first results of SAR images combined with in situ data processing are presented. Our results are compared to the results obtained using previously developed models CMOD, C-2PO for VH polarization and statistical wind retrieval approaches [1]. Acknowledgments. This work is supported by the Russian Foundation of Basic Research (grants 13-05-00852-a). [1] M. Portabella, A. Stoffelen, J. A. Johannessen, Toward an optimal inversion method for synthetic aperture radar wind retrieval, Journal of geophysical research, V. 107, N C8, 2002
NASA Astrophysics Data System (ADS)
Liu, Yuanyuan; Zhao, Chaoying; Zhang, Qin; Yang, Chengsheng
2018-02-01
Qingxu-Jiaocheng, China has been suffering severe land subsidence along with the development of ground fissure, which are controlled by local fault and triggered by groundwater withdrawal. With multi-sensor SAR images, we study the spatiotemporal evolution of ground deformation over Qingxu-Jiaocheng with an IPTA InSAR technique and assess the role of groundwater withdrawal to the observed deformation. Discrete GPS measurements are applied to verify the InSAR results. The RMSE of the differences between InSAR and GPS, i.e. ALOS and GPS and Envisat and GPS, are 5.7 mm and 6.3 mm in the LOS direction, respectively. The east-west and vertical components of the observed deformation from 2007 to 2010 are decomposed by using descending-track Envisat and ascending-track ALOS interferograms, indicating that the east-west component cannot be neglected when the deformation is large or the ground fissure is active. Four phases of land subsidence in the study region are successfully retrieved, and its spatiotemporal evolution is quantitatively analyzed. Lastly, a flat lying sill model with distributed contractions is implemented to model the InSAR deformation over Qingxu-Jiaocheng, which manifests that the ground deformation is mainly caused by groundwater withdrawal. This research provides new insights into the land subsidence monitoring and its mechanism inversion over Qingxu-Jiaocheng region.
Monitoring Building Deformation with InSAR: Experiments and Validation.
Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng
2016-12-20
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.
Monitoring Building Deformation with InSAR: Experiments and Validation
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
NASA Astrophysics Data System (ADS)
Sridhar, J.
2015-12-01
The focus of this work is to examine polarimetric decomposition techniques primarily focussed on Pauli decomposition and Sphere Di-Plane Helix (SDH) decomposition for forest resource assessment. The data processing methods adopted are Pre-processing (Geometric correction and Radiometric calibration), Speckle Reduction, Image Decomposition and Image Classification. Initially to classify forest regions, unsupervised classification was applied to determine different unknown classes. It was observed K-means clustering method gave better results in comparison with ISO Data method.Using the algorithm developed for Radar Tools, the code for decomposition and classification techniques were applied in Interactive Data Language (IDL) and was applied to RISAT-1 image of Mysore-Mandya region of Karnataka, India. This region is chosen for studying forest vegetation and consists of agricultural lands, water and hilly regions. Polarimetric SAR data possess a high potential for classification of earth surface.After applying the decomposition techniques, classification was done by selecting region of interests andpost-classification the over-all accuracy was observed to be higher in the SDH decomposed image, as it operates on individual pixels on a coherent basis and utilises the complete intrinsic coherent nature of polarimetric SAR data. Thereby, making SDH decomposition particularly suited for analysis of high-resolution SAR data. The Pauli Decomposition represents all the polarimetric information in a single SAR image however interpretation of the resulting image is difficult. The SDH decomposition technique seems to produce better results and interpretation as compared to Pauli Decomposition however more quantification and further analysis are being done in this area of research. The comparison of Polarimetric decomposition techniques and evolutionary classification techniques will be the scope of this work.
Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart
2011-01-01
We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.
Analysis of Wind and Sea State in SAR data of Hurricanes
NASA Astrophysics Data System (ADS)
Hoja, D.; Schulz-Stellenfleth, J.; Lehner, S.; Horstmann, J.
2003-04-01
Spaceborne synthetic aperture radar (SAR) is still the only instrument providing directional ocean wave and in addition surface wind information on a global and continuous basis. Operating in ASAR wave mode ENVISAT, launched in 2002, provides 10 km x 5 km SAR images every 100 km along the orbit. These SAR data continue and expand the SAR era of the European Remote Sensing satellites ERS-1 and ERS-2, which have acquired similar SAR data since 1991 on a global basis. To not only use the official ERS SAR wave mode product, which consists only of the SAR image power spectrum, but also the full SAR image information a subset of 27 days globally distributed ERS-2 SAR raw data were processed to single look complex SAR imagettes using the BSAR processor developed at the German Aerospace Center. These data have the same format as the official ESA product for ENVISAT ASAR wave mode data. This subset of 34,000 ERS-2 SAR imagettes was used to develop and validate algorithms for wind and wave retrieval, which are also applicable to ENVISAT ASAR wave mode data. The time frame of the dataset covers several tropical cyclones in the Atlantic Ocean of which hurricane Fran has been investigated in detail together with additional data available from scatterometers, buoys and weather centers. Hurricane Fran was active from August 23 to September 8, 1996. During this time, hurricane Fran developed near the African coast and progressed over the North Atlantic Ocean. Landfall occurred on September 5, 1996 at the coast of North Carolina, USA. Fran was part of a whole series of tropical cyclones travelling about the same course in a short time. The wind is extracted from SAR imagery and compared to results of the numerical model output provided by the European Center for Medium-Range Weather Forecast (ECMWF) and co-located ERS-2 scatterometer measurements. The Swell and wind sea systems generated by the tropical cyclones are measured using SAR cross spectra and a newly developed
Interferon-Beta 1a and SARS Coronavirus Replication
2004-02-01
A global outbreak of severe acute respiratory syn- drome ( SARS ) caused by a novel coronavirus began in March 2003. The rapid emergence of SARS and...emerging infectious disease. The etiologic agent was identified as a coronavirus ( SARS -CoV) that is not closely related to any of the previously...some coronaviruses , including avian infectious bronchitis virus, murine hepati- tis virus, and human coronavirus 229E, are susceptible to type I
NASA Astrophysics Data System (ADS)
de Oliveira, Cleber Gonzales; Paradella, Waldir Renato; da Silva, Arnaldo de Queiroz
The Brazilian Amazon is a vast territory with an enormous need for mapping and monitoring of renewable and non-renewable resources. Due to the adverse environmental condition (rain, cloud, dense vegetation) and difficult access, topographic information is still poor, and when available needs to be updated or re-mapped. In this paper, the feasibility of using Digital Surface Models (DSMs) extracted from TerraSAR-X Stripmap stereo-pair images for detailed topographic mapping was investigated for a mountainous area in the Carajás Mineral Province, located on the easternmost border of the Brazilian Amazon. The quality of the radargrammetric DSMs was evaluated regarding field altimetric measurements. Precise topographic field information acquired from a Global Positioning System (GPS) was used as Ground Control Points (GCPs) for the modeling of the stereoscopic DSMs and as Independent Check Points (ICPs) for the calculation of elevation accuracies. The analysis was performed following two ways: (1) the use of Root Mean Square Error (RMSE) and (2) calculations of systematic error (bias) and precision. The test for significant systematic error was based on the Student's-t distribution and the test of precision was based on the Chi-squared distribution. The investigation has shown that the accuracy of the TerraSAR-X Stripmap DSMs met the requirements for 1:50,000 map (Class A) as requested by the Brazilian Standard for Cartographic Accuracy. Thus, the use of TerraSAR-X Stripmap images can be considered a promising alternative for detailed topographic mapping in similar environments of the Amazon region, where available topographic information is rare or presents low quality.
Schatten Matrix Norm Based Polarimetric SAR Data Regularization Application over Chamonix Mont-Blanc
NASA Astrophysics Data System (ADS)
Le, Thu Trang; Atto, Abdourrahmane M.; Trouve, Emmanuel
2013-08-01
The paper addresses the filtering of Polarimetry Synthetic Aperture Radar (PolSAR) images. The filtering strategy is based on a regularizing cost function associated with matrix norms called the Schatten p-norms. These norms apply on matrix singular values. The proposed approach is illustrated upon scattering and coherency matrices on RADARSAT-2 PolSAR images over the Chamonix Mont-Blanc site. Several p values of Schatten p-norms are surveyed and their capabilities on filtering PolSAR images is provided in comparison with conventional strategies for filtering PolSAR data.
Process for combining multiple passes of interferometric SAR data
Bickel, Douglas L.; Yocky, David A.; Hensley, Jr., William H.
2000-11-21
Interferometric synthetic aperture radar (IFSAR) is a promising technology for a wide variety of military and civilian elevation modeling requirements. IFSAR extends traditional two dimensional SAR processing to three dimensions by utilizing the phase difference between two SAR images taken from different elevation positions to determine an angle of arrival for each pixel in the scene. This angle, together with the two-dimensional location information in the traditional SAR image, can be transformed into geographic coordinates if the position and motion parameters of the antennas are known accurately.
GTPase Sar1 regulates the trafficking and secretion of the virulence factor gp63 in Leishmania.
Parashar, Smriti; Mukhopadhyay, Amitabha
2017-07-21
Metalloprotease gp63 ( Leishmania donovani gp63 (Ldgp63)) is a critical virulence factor secreted by Leishmania However, how newly synthesized Ldgp63 exits the endoplasmic reticulum (ER) and is secreted by this parasite is unknown. Here, we cloned, expressed, and characterized the GTPase LdSar1 and other COPII components like LdSec23, LdSec24, LdSec13, and LdSec31 from Leishmania to understand their role in ER exit of Ldgp63. Using dominant-positive (LdSar1:H74L) and dominant-negative (LdSar1:T34N) mutants of LdSar1, we found that GTP-bound LdSar1 specifically binds to LdSec23, which binds, in turn, with LdSec24(1-702) to form a prebudding complex. Moreover, LdSec13 specifically interacted with His 6 -LdSec31(1-603), and LdSec31 bound the prebudding complex via LdSec23. Interestingly, dileucine 594/595 and valine 597 residues present in the Ldgp63 C-terminal domain were critical for binding with LdSec24(703-966), and GFP-Ldgp63 L594A/L595A or GFP-Ldgp63 V597S mutants failed to exit from the ER. Moreover, Ldgp63-containing COPII vesicle budding from the ER was inhibited by LdSar1:T34N in an in vitro budding assay, indicating that GTP-bound LdSar1 is required for budding of Ldgp63-containing COPII vesicles. To directly demonstrate the function of LdSar1 in Ldgp63 trafficking, we coexpressed RFP-Ldgp63 along with LdSar1:WT-GFP or LdSar1:T34N-GFP and found that LdSar1:T34N overexpression blocks Ldgp63 trafficking and secretion in Leishmania Finally, we noted significantly compromised survival of LdSar1:T34N-GFP-overexpressing transgenic parasites in macrophages. Taken together, these results indicated that Ldgp63 interacts with the COPII complex via LdSec24 for Ldgp63 ER exit and subsequent secretion. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
NASA Astrophysics Data System (ADS)
Sato, H. P.
2017-12-01
Maoxien area in Sichuan Province, China has many landslide. For example, landslide (rock avalanche) occurred on the slope in Xinmocun Village in Maoxeien on 24 June 2017. I produced and interpreetd InSAR image using ALOS/PALSAR data observed on 19 Jul 2007-3 Sep 2007 and on 27 Jan 2011-14 Mar 2011, and ALOS-2/PALSAR-2 data observed on 26 Jul 2015-13 Dec 2015 and on 13 Dec 2015-11 Dec 2016. These images give good coherence and it was easy to identify local landslide surface deformation. As a result, e.g., two slopes were estimated to have local landslide surface deformation; one is at 103.936587 deg E and 32.04462 deg N, another is at 103.674754 deg E and 31.852838 N. However, the slope in Xinmocun Village was not identified as landslide precursory deformation. In the poster I will present more InSAR image observed after 11 Dec 2016 and discuss the possibility of local landslide surface deformaton using InSAR image. ALOS/PALSAR and ALOS-2/PALSAR-2 data were provided by JAXA through Landslide Working Group in JAXA and through Special Research 2015-B-02 of Earthquake Research Institute/Tokyo University. This study was supported by KAKENHI (17H02973).
NASA Astrophysics Data System (ADS)
Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang
2018-05-01
Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.
Satellite SAR interferometric techniques applied to emergency mapping
NASA Astrophysics Data System (ADS)
Stefanova Vassileva, Magdalena; Riccardi, Paolo; Lecci, Daniele; Giulio Tonolo, Fabio; Boccardo Boccardo, Piero; Chiesa, Giuliana; Angeluccetti, Irene
2017-04-01
monitoring maps for risk prevention and mitigation purposes. Nevertheless, multi-temporal techniques require large SAR temporal datasets, i.e. 20 and more images. Being the Sentinel-1 missions operational only since April 2014, multi-mission SAR datasets should be therefore exploited to carry out historical analysis.
An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images
NASA Astrophysics Data System (ADS)
Ruan, Z.; Yan, S.; Liu, G.; LV, M.
2017-12-01
Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS
Compact time- and space-integrating SAR processor: performance analysis
NASA Astrophysics Data System (ADS)
Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.; Christensen, Marc P.
1995-06-01
Progress made during the previous 12 months toward the fabrication and test of a flight demonstration prototype of the acousto-optic time- and space-integrating real-time SAR image formation processor is reported. Compact, rugged, and low-power analog optical signal processing techniques are used for the most computationally taxing portions of the SAR imaging problem to overcome the size and power consumption limitations of electronic approaches. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results reported for this year include tests of a laboratory version of the RAPID SAR concept on phase history data generated from real SAR high-resolution imagery; a description of the new compact 2D acousto-optic scanner that has a 2D space bandwidth product approaching 106 sports, specified and procured for NEOS Technologies during the last year; and a design and layout of the optical module portion of the flight-worthy prototype.
Space Radar Image of Kilauea, Hawaii - interferometry 1
NASA Technical Reports Server (NTRS)
1994-01-01
This X-band image of the volcano Kilauea was taken on October 4, 1994, by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar. The area shown is about 9 kilometers by 13 kilometers (5.5 miles by 8 miles) and is centered at about 19.58 degrees north latitude and 155.55 degrees west longitude. This image and a similar image taken during the first flight of the radar instrument on April 13, 1994 were combined to produce the topographic information by means of an interferometric process. This is a process by which radar data acquired on different passes of the space shuttle is overlaid to obtain elevation information. Three additional images are provided showing an overlay of radar data with interferometric fringes; a three-dimensional image based on altitude lines; and, finally, a topographic view of the region. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR. The Instituto Ricerca Elettromagnetismo
Azimuthal resolution degradation due to ocean surface motion in focused arrays and SARS
NASA Astrophysics Data System (ADS)
1990-06-01
During the meeting at WHOI (5-18-90), a discussion arose of the ability of the focused array to simulate the R/v ratios typical of airborne and/or spaceborne SARs. In particular, the ability was questioned of the focused array to yield the same azimuthal resolution, rho, as the SAR. Although the focused array can be sampled to yield the same azimuthal resolution as the SAR, it is likely that the images generated by the focused array will not be identical to those produced by a SAR with the same azimuth resolution. For a true SAR, biases in the Doppler history of azimuthally traveling waves due to their along-track motion will cause shifts in their apparent position. This will cause waves which are physically at one location to shift over several pixel widths in the image. The limited swath width of the focused array will prevent if from observing scattered power from waves falling outside the swath, thus such waves will not affect the image formed within the swath, as would happen in the SAR. Thus, it is likely that the focused array will not yield the same image as a SAR having the same resolution.
C- and L-band space-borne SAR incidence angle normalization for efficient Arctic sea ice monitoring
NASA Astrophysics Data System (ADS)
Mahmud, M. S.; Geldsetzer, T.; Howell, S.; Yackel, J.; Nandan, V.
2017-12-01
C-band Synthetic Aperture Radar (SAR) has been widely used effectively for operational sea ice monitoring, owing to its greater seperability between snow-covered first-year (FYI) and multi-year (MYI) ice types, during winter. However, during the melt season, C-band SAR backscatter contrast reduces between FYI and MYI. To overcome the limitations of C-band, several studies have recommended utlizing L-band SAR, as it has the potential to significantly improve sea ice classification. Given its longer wavelength, L-band can efficiently separate FYI and MYI types, especially during melt season. Therefore, the combination of C- and L-band SAR is an optimal solution for efficient seasonal sea ice monitoring. As SAR acquires images over a range of incidence angles from near-range to far-range, SAR backscatter varies substantially. To compensate this variation in SAR backscatter, incidence angle dependency of C- and L-band SAR backscatter for different FYI and MYI types is crucial to quantify, which is the objective of this study. Time-series SAR imagery from C-band RADARSAT-2 and L-band ALOS PALSAR during winter months of 2010 across 60 sites over the Canadian Arctic was acquired. Utilizing 15 images for each sites during February-March for both C- and L-band SAR, incidence angle dependency was calculated. Our study reveals that L- and C-band backscatter from FYI and MYI decreases with increasing incidence angle. The mean incidence angle dependency for FYI and MYI were estimated to be -0.21 dB/1° and -0.30 dB/1° respectively from L-band SAR, and -0.22 dB/1° and -0.16 dB/1° from C-band SAR, respectively. While the incidence angle dependency for FYI was found to be similar in both frequencies, it doubled in case of MYI from L-band, compared to C-band. After applying the incidence angle normalization method to both C- and L-band SAR images, preliminary results indicate improved sea ice type seperability between FYI and MYI types, with substantially lower number of mixed
An Accurate Co-registration Method for Airborne Repeat-pass InSAR
NASA Astrophysics Data System (ADS)
Dong, X. T.; Zhao, Y. H.; Yue, X. J.; Han, C. M.
2017-10-01
Interferometric Synthetic Aperture Radar (InSAR) technology plays a significant role in topographic mapping and surface deformation detection. Comparing with spaceborne repeat-pass InSAR, airborne repeat-pass InSAR solves the problems of long revisit time and low-resolution images. Due to the advantages of flexible, accurate, and fast obtaining abundant information, airborne repeat-pass InSAR is significant in deformation monitoring of shallow ground. In order to getting precise ground elevation information and interferometric coherence of deformation monitoring from master and slave images, accurate co-registration must be promised. Because of side looking, repeat observing path and long baseline, there are very different initial slant ranges and flight heights between repeat flight paths. The differences of initial slant ranges and flight height lead to the pixels, located identical coordinates on master and slave images, correspond to different size of ground resolution cells. The mismatching phenomenon performs very obvious on the long slant range parts of master image and slave image. In order to resolving the different sizes of pixels and getting accurate co-registration results, a new method is proposed based on Range-Doppler (RD) imaging model. VV-Polarization C-band airborne repeat-pass InSAR images were used in experiment. The experiment result shows that the proposed method leads to superior co-registration accuracy.
NASA Astrophysics Data System (ADS)
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.
Estimating Elevation Angles From SAR Crosstalk
NASA Technical Reports Server (NTRS)
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.
Postseismic Deformation following the 1995 Kobe, Japan, Earthquake Detected by Space Geodesy
NASA Astrophysics Data System (ADS)
Hashimoto, Manabu; Ozawa, Taku; Nishimura, Takuya; Munekane, Hiroshi; Tobita, Mikio
2017-04-01
A Mw 6.8 earthquake hit the city of Kobe, southwest Japan, and its surrounding area on January 17, 1995, and claimed more than 6,400 fatalities. The source faults, trending in the NE-SW direction, are estimated beneath the foothill of the Rokko Mountains, which are located north of the city and the highest peak is 931 m high, but it has a dominant right lateral strike slip components. The Rokko Mountains may have been built by the motion of active faults, but the uplift during the 1995 earthquake may not be enough. Therefore there is a possibility that postseismic deformation contributes to the building of the Rokko Mountains. In order to study the postseismic deformation following the Kobe earthquake, we collected all available space geodetic data during about 20 years, including ERS-1/2, Envisat, JERS-1, ALOS/PALSAR and ALOS-2/PALSAR-2 images and continuous GPS data, and reanalyzed them. Especially, temporal continuous GPS observation made by the Geographical Survey Institute (present the Geospatial Information Authority), Japan in and around the Kobe area is important. We recalculated coordinates of these continuous GPS stations with recent PPP procedure using reanalyzed orbits and clocks of satellites. We made DInSAR and PSInSAR analyses of SAR images using ASTER-GDEM ver.2 or GSI DEM. Time series analysis of JERS-1 images revealed line-of-sight (LOS) decrease of the Rokko Mountains. PS-InSAR results of ALOS/PALSAR also revealed slight uplift north of the Rokko Mountains that uplifted by 20 cm coseismically. These observations suggest that the Rokko Mountains might have uplifted during the postseismic period. LOS increase in a wedge shaped region between two active faults east of the Rokko Mountains in the vicinity of the NE terminus of the source fault of the Kobe earthquake. The LOS increase is also confirmed by ERS-1/2, Envisat and ALOS/PALSAR images. These facts indicate that the subsidence between these two faults continued up to 2010. Continuous GPS
NASA Astrophysics Data System (ADS)
Fabbrini, L.; Messina, M.; Greco, M.; Pinelli, G.
2011-10-01
In the context of augmented integrity Inertial Navigation System (INS), recent technological developments have been focusing on landmark extraction from high-resolution synthetic aperture radar (SAR) images in order to retrieve aircraft position and attitude. The article puts forward a processing chain that can automatically detect linear landmarks on highresolution synthetic aperture radar (SAR) images and can be successfully exploited also in the context of augmented integrity INS. The processing chain uses constant false alarm rate (CFAR) edge detectors as the first step of the whole processing procedure. Our studies confirm that the ratio of averages (RoA) edge detector detects object boundaries more effectively than Student T-test and Wilcoxon-Mann-Whitney (WMW) test. Nevertheless, all these statistical edge detectors are sensitive to violation of the assumptions which underlie their theory. In addition to presenting a solution to the previous problem, we put forward a new post-processing algorithm useful to remove the main false alarms, to select the most probable edge position, to reconstruct broken edges and finally to vectorize them. SAR images from the "MSTAR clutter" dataset were used to prove the effectiveness of the proposed algorithms.
An ice-motion tracking system at the Alaska SAR facility
NASA Technical Reports Server (NTRS)
Kwok, Ronald; Curlander, John C.; Pang, Shirley S.; Mcconnell, Ross
1990-01-01
An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.
Using dynamic interferometric synthetic aperature radar (InSAR) to image fast-moving surface waves
Vincent, Paul
2005-06-28
A new differential technique and system for imaging dynamic (fast moving) surface waves using Dynamic Interferometric Synthetic Aperture Radar (InSAR) is introduced. This differential technique and system can sample the fast-moving surface displacement waves from a plurality of moving platform positions in either a repeat-pass single-antenna or a single-pass mode having a single-antenna dual-phase receiver or having dual physically separate antennas, and reconstruct a plurality of phase differentials from a plurality of platform positions to produce a series of desired interferometric images of the fast moving waves.
Alternative synthetic aperture radar (SAR) modalities using a 1D dynamic metasurface antenna
NASA Astrophysics Data System (ADS)
Boyarsky, Michael; Sleasman, Timothy; Pulido-Mancera, Laura; Imani, Mohammadreza F.; Reynolds, Matthew S.; Smith, David R.
2017-05-01
Synthetic aperture radar (SAR) systems conventionally rely on mechanically-actuated reflector dishes or large phased arrays for generating steerable directive beams. While these systems have yielded high-resolution images, the hardware suffers from considerable weight, high cost, substantial power consumption, and moving parts. Since these disadvantages are particularly relevant in airborne and spaceborne systems, a flat, lightweight, and low-cost solution is a sought-after goal. Dynamic metasurface antennas have emerged as a recent technology for generating waveforms with desired characteristics. Metasurface antennas consist of an electrically-large waveguide loaded with numerous subwavelength radiators which selectively leak energy from a guided wave into free space to form various radiation patterns. By tuning each radiating element, we can modulate the aperture's overall radiation pattern to generate steered directive beams, without moving parts or phase shifters. Furthermore, by using established manufacturing methods, these apertures can be made to be lightweight, low-cost, and planar, while maintaining high performance. In addition to their hardware benefits, dynamic metasurfaces can leverage their dexterity and high switching speeds to enable alternative SAR modalities for improved performance. In this work, we briefly discuss how dynamic metasurfaces can conduct existing SAR modalities with similar performance as conventional systems from a significantly simpler hardware platform. We will also describe two additional modalities which may achieve improved performance as compared to traditional modalities. These modalities, enhanced resolution stripmap and diverse pattern stripmap, offer the ability to circumvent the trade-off between resolution and region-of-interest size that exists within stripmap and spotlight. Imaging results with a simulated dynamic metasurface verify the benefits of these modalities and a discussion of implementation considerations
Geodetic integration of Sentinel-1A IW data using PSInSAR in Hungary
NASA Astrophysics Data System (ADS)
Farkas, Péter; Hevér, Renáta; Grenerczy, Gyula
2015-04-01
ESA's latest Synthetic Aperture Radar (SAR) mission Sentinel-1 is a huge step forward in SAR interferometry. With its default acquisition mode called the Interferometric Wide Swath Mode (IW) areas through all scales can be mapped with an excellent return time of 12 days (while only the Sentinel-1A is in orbit). Its operational data policy is also a novelty, it allows scientific users free and unlimited access to data. It implements a new type of ScanSAR mode called Terrain Observation with Progressive Scan (TOPS) SAR. It has the same resolution as ScanSAR but with better signal-to-noise ratio distribution. The bigger coverage is achieved by rotation of the antenna in the azimuth direction, therefore it requires very precise co-registration because even errors under a pixel accuracy can introduce azimuth phase variations caused by differences in Doppler-centroids. In our work we will summarize the benefits and the drawbacks of the IW mode. We would like to implement the processing chain of GAMMA Remote Sensing of such data for mapping surface motion with special attention to the co-registration step. Not only traditional InSAR but the advanced method of Persistent Scatterer InSAR (PSInSAR) will be performed and presented as well. PS coverage, along with coherence, is expected to be good due to the small perpendicular and temporal baselines. We would also like to integrate these measurements into national geodetic networks using common reference points. We have installed trihedral corner reflectors at some selected sites to aid precise collocation. Thus, we aim to demonstrate that Sentinel-1 can be effectively used for surface movement detection and monitoring and it can also provide valuable information for the improvement of our networks.
Skipping the real world: Classification of PolSAR images without explicit feature extraction
NASA Astrophysics Data System (ADS)
Hänsch, Ronny; Hellwich, Olaf
2018-06-01
The typical processing chain for pixel-wise classification from PolSAR images starts with an optional preprocessing step (e.g. speckle reduction), continues with extracting features projecting the complex-valued data into the real domain (e.g. by polarimetric decompositions) which are then used as input for a machine-learning based classifier, and ends in an optional postprocessing (e.g. label smoothing). The extracted features are usually hand-crafted as well as preselected and represent (a somewhat arbitrary) projection from the complex to the real domain in order to fit the requirements of standard machine-learning approaches such as Support Vector Machines or Artificial Neural Networks. This paper proposes to adapt the internal node tests of Random Forests to work directly on the complex-valued PolSAR data, which makes any explicit feature extraction obsolete. This approach leads to a classification framework with a significantly decreased computation time and memory footprint since no image features have to be computed and stored beforehand. The experimental results on one fully-polarimetric and one dual-polarimetric dataset show that, despite the simpler approach, accuracy can be maintained (decreased by only less than 2 % for the fully-polarimetric dataset) or even improved (increased by roughly 9 % for the dual-polarimetric dataset).
InSAR time series analysis of ALOS-2 ScanSAR data and its implications for NISAR
NASA Astrophysics Data System (ADS)
Liang, C.; Liu, Z.; Fielding, E. J.; Huang, M. H.; Burgmann, R.
2017-12-01
The JAXA's ALOS-2 mission was launched on May 24, 2014. It operates at L-band and can acquire data in multiple modes. ScanSAR is the main operational mode and has a 350 km swath, somewhat larger than the 250 km swath of the SweepSAR mode planned for the NASA-ISRO SAR (NISAR) mission. ALOS-2 has been acquiring a wealth of L-band InSAR data. These data are of particular value in areas of dense vegetation and high relief. The InSAR technical development for ALOS-2 also enables the preparation for the upcoming NISAR mission. We have been developing advanced InSAR processing techniques for ALOS-2 over the past two years. Here, we report the important issues for doing InSAR time series analysis using ALOS-2 ScanSAR data. First, we present ionospheric correction techniques for both regular ScanSAR InSAR and MAI (multiple aperture InSAR) ScanSAR InSAR. We demonstrate the large-scale ionospheric signals in the ScanSAR interferograms. They can be well mitigated by the correction techniques. Second, based on our technical development of burst-by-burst InSAR processing for ALOS-2 ScanSAR data, we find that the azimuth Frequency Modulation (FM) rate error is an important issue not only for MAI, but also for regular InSAR time series analysis. We identify phase errors caused by azimuth FM rate errors during the focusing process of ALOS-2 product. The consequence is mostly a range ramp in the InSAR time series result. This error exists in all of the time series results we have processed. We present the correction techniques for this error following a theoretical analysis. After corrections, we present high quality ALOS-2 ScanSAR InSAR time series results in a number of areas. The development for ALOS-2 can provide important implications for NISAR mission. For example, we find that in most cases the relative azimuth shift caused by ionosphere can be as large as 4 m in a large area imaged by ScanSAR. This azimuth shift is half of the 8 m azimuth resolution of the SweepSAR mode
Processing techniques for software based SAR processors
NASA Technical Reports Server (NTRS)
Leung, K.; Wu, C.
1983-01-01
Software SAR processing techniques defined to treat Shuttle Imaging Radar-B (SIR-B) data are reviewed. The algorithms are devised for the data processing procedure selection, SAR correlation function implementation, multiple array processors utilization, cornerturning, variable reference length azimuth processing, and range migration handling. The Interim Digital Processor (IDP) originally implemented for handling Seasat SAR data has been adapted for the SIR-B, and offers a resolution of 100 km using a processing procedure based on the Fast Fourier Transformation fast correlation approach. Peculiarities of the Seasat SAR data processing requirements are reviewed, along with modifications introduced for the SIR-B. An Advanced Digital SAR Processor (ADSP) is under development for use with the SIR-B in the 1986 time frame as an upgrade for the IDP, which will be in service in 1984-5.
The InSAR Scientific Computing Environment
NASA Technical Reports Server (NTRS)
Rosen, Paul A.; Gurrola, Eric; Sacco, Gian Franco; Zebker, Howard
2012-01-01
We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms
NASA Astrophysics Data System (ADS)
Owen, S. E.; Simons, M.; Hua, H.; Yun, S. H.; Agram, P. S.; Milillo, P.; Sacco, G. F.; Webb, F.; Rosen, P. A.; Lundgren, P.; Milillo, G.; Manipon, G. J. M.; Moore, A. W.; Liu, Z.; Polet, J.; Cruz, J.
2014-12-01
ARIA is a joint JPL/Caltech project to automate synthetic aperture radar (SAR) and GPS imaging capabilities for scientific understanding, hazard response, and societal benefit. We have built a prototype SAR and GPS data system that forms the foundation for hazard monitoring and response capability, as well as providing imaging capabilities important for science studies. Together, InSAR and GPS have the ability to capture surface deformation in high spatial and temporal resolution. For earthquakes, this deformation provides information that is complementary to seismic data on location, geometry and magnitude of earthquakes. Accurate location information is critical for understanding the regions affected by damaging shaking. Regular surface deformation measurements from SAR and GPS are useful for monitoring changes related to many processes that are important for hazard and resource management such as volcanic deformation, groundwater withdrawal, and landsliding. Observations of SAR coherence change have a demonstrated use for damage assessment for hazards such as earthquakes, tsunamis, hurricanes, and volcanic eruptions. These damage assessment maps can be made from imagery taken day or night and are not affected by clouds, making them valuable complements to optical imagery. The coherence change caused by the damage from hazards (building collapse, flooding, ash fall) is also detectable with intelligent algorithms, allowing for rapid generation of damage assessment maps over large areas at fine resolution, down to the spatial scale of single family homes. We will present the progress and results we have made on automating the analysis of SAR data for hazard monitoring and response using data from the Italian Space Agency's (ASI) COSMO-SkyMed constellation of X-band SAR satellites. Since the beginning of our project with ASI, our team has imaged deformation and coherence change caused by many natural hazard events around the world. We will present progress on our
Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart
2011-01-01
We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859
NASA Astrophysics Data System (ADS)
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.
Improved spatial mapping of rainfall events with spaceborne SAR imagery
NASA Technical Reports Server (NTRS)
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.
Glacier Frontal Line Extraction from SENTINEL-1 SAR Imagery in Prydz Area
NASA Astrophysics Data System (ADS)
Li, F.; Wang, Z.; Zhang, S.; Zhang, Y.
2018-04-01
Synthetic Aperture Radar (SAR) can provide all-day and all-night observation of the earth in all-weather conditions with high resolution, and it is widely used in polar research including sea ice, sea shelf, as well as the glaciers. For glaciers monitoring, the frontal position of a calving glacier at different moments of time is of great importance, which indicates the estimation of the calving rate and flux of the glaciers. In this abstract, an automatic algorithm for glacier frontal extraction using time series Sentinel-1 SAR imagery is proposed. The technique transforms the amplitude imagery of Sentinel-1 SAR into a binary map using SO-CFAR method, and then frontal points are extracted using profile method which reduces the 2D binary map to 1D binary profiles, the final frontal position of a calving glacier is the optimal profile selected from the different average segmented profiles. The experiment proves that the detection algorithm for SAR data can automatically extract the frontal position of glacier with high efficiency.
Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico
NASA Technical Reports Server (NTRS)
Rebillard, PH.; Dixon, T.
1984-01-01
A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area
NASA Astrophysics Data System (ADS)
Reppucci, Antonio; Moreno, Laura
2010-12-01
Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.
Galloway, D.L.; Hoffmann, J.
2007-01-01
The application of satellite differential synthetic aperture radar (SAR) interferometry, principally coherent (InSAR) and to a lesser extent, persistent-scatterer (PSI) techniques to hydrogeologic studies has improved capabilities to map, monitor, analyze, and simulate groundwater flow, aquifer-system compaction and land subsidence. A number of investigations over the previous decade show how the spatially detailed images of ground displacements measured with InSAR have advanced hydrogeologic understanding, especially when a time series of images is used in conjunction with histories of changes in water levels and management practices. Important advances include: (1) identifying structural or lithostratigraphic boundaries (e.g. faults or transitional facies) of groundwater flow and deformation; (2) defining the material and hydraulic heterogeneity of deforming aquifer-systems; (3) estimating system properties (e.g. storage coefficients and hydraulic conductivities); and (4) constraining numerical models of groundwater flow, aquifer-system compaction, and land subsidence. As a component of an integrated approach to hydrogeologic monitoring and characterization of unconsolidated alluvial groundwater basins differential SAR interferometry contributes unique information that can facilitate improved management of groundwater resources. Future satellite SAR missions specifically designed for differential interferometry will enhance these contributions. ?? Springer-Verlag 2006.
Foldbelt exploration with synthetic aperture radar (SAR) in Papua New Guinea
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ellis, J.M.; Pruett, F.D.
1987-05-01
Synthetic aperture radar (SAR) is being successfully used within the southern fold and thrust belt of Papua New Guinea to map surface structure and stratigraphy and to help plan a hydrocarbon exploration program. The airborne SAR imagery, along with other surface data, is used as a primary exploration tool because acquisition of acceptable seismic data is extremely costly due to extensive outcrops of Tertiary Darai Limestone which develops rugged karst topography. Most anticlines in the licenses are capped with this deeply karstified limestone. The region is ideally suited to geologic analysis using remote sensing technology. The area is seldom cloudmore » free and is covered with tropical rain forest, and geologic field studies are limited. The widespread karst terrain is exceedingly dangerous, if not impossible, to traverse on the ground. SAR is used to guide ongoing field work, modeling of subsurface structure, and selection of well locations. SAR provides their explorationists with an excellent data base because (1) structure is enhanced with low illumination, (2) resolution is 6 x 12 m, (3) digital reprocessing is possible, (4) clouds are penetrated by the SAR, and (5) the survey was designed for stereoscopic photogeology. Landsat images and vertical aerial photographs complement SAR but provide subdued structural information because of minimal shadowing (due to high sun angles) and the jungle cover. SAR imagery reveals large-scale mass wasting that has led to a reevaluation of previously acquired field data. Lithologies can be recognized by textural and tonal changes on the SAR images despite near-continuous canopy of jungle. Reprocessing and contrast stretching of the digital radar imagery provide additional geologic information.« less
Vegetation canopy discrimination and biomass assessment using multipolarized airborne SAR
NASA Technical Reports Server (NTRS)
Ulaby, F. T.; Dobson, M. C.; Held, D. N.
1985-01-01
Multipolarized airborne Synthetic Aperture Radar (SAR) data were acquired over a largely agricultural test site near Macomb, Illinois, in conjunction with the Shuttle Imaging Radar (SIR-B) experiment in October 1984. The NASA/JPL L-band SAR operating at 1.225 GHz made a series of daily overflights with azimuth view angles both parallel and orthogonal to those of SIR-B. The SAR data was digitally recorded in the quadpolarization configuration. An extensive set of ground measurements were obtained throughout the test site and include biophysical and soil measurements of approximately 400 agricultural fields. Preliminary evaluation of some of the airborne SAR imagery indicates a great potential for crop discrimination and assessment of canopy condition. False color composites constructed from the combination of three linear polarizations (HH, VV, and HV) were found to be clearly superior to any single polarization for purposes of crop classification. In addition, an image constructed using the HH return to modulate intensity and the phase difference between HH and VV returns to modulate chroma indicates a clear capability for assessment of canopy height and/or biomass. In particular, corn fields heavily damaged by infestations of corn borer are readily distinguished from noninfested fields.
Geocoding of AIRSAR/TOPSAR SAR Data
NASA Technical Reports Server (NTRS)
Holecz, Francesco; Lou, Yun-Ling; vanZyl, Jakob
1996-01-01
It has been demonstrated and recognized that radar interferometry is a promising method for the determination of digital elevation information and terrain slope from Synthetic Aperture Radar (SAR) data. An important application of Interferometric SAR (InSAR) data in areas with topographic variations is that the derived elevation and slope can be directly used for the absolute radiometric calibration of the amplitude SAR data as well as for scattering mechanisms analysis. On the other hand polarimetric SAR data has long been recognized as permitting a more complete inference of natural surfaces than a single channel radar system. In fact, imaging polarimetry provides the measurement of the amplitude and relative phase of all transmit and receive polarizations. On board the NASA DC-8 aircraft, NASA/JPL operates the multifrequency (P, L and C bands) multipolarimetric radar AIRSAR. The TOPSAR, a special mode of the AIRSAR system, is able to collect single-pass interferometric C- and/or L-band VV polarized data. A possible configuration of the AIRSAR/TOPSAR system is to acquire single-pass interferometric data at C-band VV polarization and polarimetric radar data at the two other lower frequencies. The advantage of this system configuration is to get digital topography information at the same time the radar data is collected. The digital elevation information can therefore be used to correctly calibrate the SAR data. This step is directly included in the new AIRSAR Integrated Processor. This processor uses a modification of the full motion compensation algorithm described by Madsen et al. (1993). However, the Digital Elevation Model (DEM) with the additional products such as local incidence angle map, and the SAR data are in a geometry which is not convenient, since especially DEMs must be referred to a specific cartographic reference system. Furthermore, geocoding of SAR data is important for multisensor and/or multitemporal purposes. In this paper, a procedure to
The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm
NASA Astrophysics Data System (ADS)
Tan, Linglong; Li, Changkai; Wang, Yueqin
2018-04-01
SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.
Classification Comparisons Between Compact Polarimetric and Quad-Pol SAR Imagery
NASA Astrophysics Data System (ADS)
Souissi, Boularbah; Doulgeris, Anthony P.; Eltoft, Torbjørn
2015-04-01
Recent interest in dual-pol SAR systems has lead to a novel approach, the so-called compact polarimetric imaging mode (CP) which attempts to reconstruct fully polarimetric information based on a few simple assumptions. In this work, the CP image is simulated from the full quad-pol (QP) image. We present here the initial comparison of polarimetric information content between QP and CP imaging modes. The analysis of multi-look polarimetric covariance matrix data uses an automated statistical clustering method based upon the expectation maximization (EM) algorithm for finite mixture modeling, using the complex Wishart probability density function. Our results showed that there are some different characteristics between the QP and CP modes. The classification is demonstrated using a E-SAR and Radarsat2 polarimetric SAR images acquired over DLR Oberpfaffenhofen in Germany and Algiers in Algeria respectively.
Mera, David; Cotos, José M; Varela-Pet, José; Garcia-Pineda, Oscar
2012-10-01
Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean's surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time. Copyright © 2012 Elsevier Ltd. All rights reserved.
Spotlight SAR interferometry for terrain elevation mapping and interferometric change detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eichel, P.H.; Ghiglia, D.C.; Jakowatz, C.V. Jr.
1996-02-01
In this report, we employ an approach quite different from any previous work; we show that a new methodology leads to a simpler and clearer understanding of the fundamental principles of SAR interferometry. This methodology also allows implementation of an important collection mode that has not been demonstrated to date. Specifically, we introduce the following six new concepts for the processing of interferometric SAR (INSAR) data: (1) processing using spotlight mode SAR imaging (allowing ultra-high resolution), as opposed to conventional strip-mapping techniques; (2) derivation of the collection geometry constraints required to avoid decorrelation effects in two-pass INSAR; (3) derivation ofmore » maximum likelihood estimators for phase difference and the change parameter employed in interferometric change detection (ICD); (4) processing for the two-pass case wherein the platform ground tracks make a large crossing angle; (5) a robust least-squares method for two-dimensional phase unwrapping formulated as a solution to Poisson`s equation, instead of using traditional path-following techniques; and (6) the existence of a simple linear scale factor that relates phase differences between two SAR images to terrain height. We show both theoretical analysis, as well as numerous examples that employ real SAR collections to demonstrate the innovations listed above.« less
What is missing? An operational inundation mapping framework by SAR data
NASA Astrophysics Data System (ADS)
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
Mume, Eskender; Asad, Ali; Di Bartolo, Nadine M; Kong, Linggen; Smith, Christopher; Sargeson, Alan M; Price, Roger; Smith, Suzanne V
2013-10-28
A novel hexa aza cage, N(1)-(4-isothiocyanatobenzyl)-3,6,10,13,16,19-hexaazabicyclo[6.6.6]icosane-1,8-diamine (SarAr-NCS) was synthesized in good yield and characterized by (1)H NMR and electrospray mass spectrometry. A new method for the synthesis of the related N(1)-(4-carboxybenzyl)-3,6,10,13,16,19-hexaazabicyclo[6.6.6]icosane-1,8-diamine (AmBaSar) using the p-carboxybenzaldehyde is reported. The complexation of Cu(2+), Co(2+) and Zn(2+) by the two ligands over a range of pHs was found to be similar to the parent derivative SarAr. SarAr-NCS was conjugated to both silica particles (≈90 nm diam.) and the model B72.3 murine antibody. The SarAr-NCSN-silica particles were radiolabeled with Cu(2+) doped (64)Cu and the number of ligands conjugated was calculated to be an average of 7020 ligands per particle. Conjugation of SarAr-NCS to the B72.3 antibody was optimized over a range of conditions. The SarAr-NCSN-B72.3 conjugate was stored in buffer and as a lyophilized powder at 4 °C over 38 days. Its radiolabeling efficiency, stability and immunoreactivity were maintained. The development of a high yielding synthesis of SarAr-NCS should provide an entry point for a wide range of Cu and Zn radiometal PET imaging agents and potentially radiotherapeutic agents with (67)Cu.
Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping
NASA Astrophysics Data System (ADS)
Bahr, Thomas
2014-05-01
The use of SAR data has become increasingly popular in recent years and in a wide array of industries. Having access to SAR can be highly important and critical especially for public safety. Updating a GIS with contemporary information from SAR data allows to deliver a reliable set of geospatial information to advance civilian operations, e.g. search and rescue missions. SAR imaging offers the great advantage, over its optical counterparts, of not being affected by darkness, meteorological conditions such as clouds, fog, etc., or smoke and dust, frequently associated with disaster zones. In this paper we present the operational processing of SAR data within a GIS environment for rapid disaster mapping. For this technique we integrated the SARscape modules for ENVI with ArcGIS®, eliminating the need to switch between software packages. Thereby the premier algorithms for SAR image analysis can be directly accessed from ArcGIS desktop and server environments. They allow processing and analyzing SAR data in almost real time and with minimum user interaction. This is exemplified by the November 2010 flash flood in the Veneto region, Italy. The Bacchiglione River burst its banks on Nov. 2nd after two days of heavy rainfall throughout the northern Italian region. The community of Bovolenta, 22 km SSE of Padova, was covered by several meters of water. People were requested to stay in their homes; several roads, highways sections and railroads had to be closed. The extent of this flooding is documented by a series of Cosmo-SkyMed acquisitions with a GSD of 2.5 m (StripMap mode). Cosmo-SkyMed is a constellation of four Earth observation satellites, allowing a very frequent coverage, which enables monitoring using a very high temporal resolution. This data is processed in ArcGIS using a single-sensor, multi-mode, multi-temporal approach consisting of 3 steps: (1) The single images are filtered with a Gamma DE-MAP filter. (2) The filtered images are geocoded using a reference
Rapid Mapping Of Floods Using SAR Data: Opportunities And Critical Aspects
NASA Astrophysics Data System (ADS)
Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco
2013-04-01
The potentiality of spaceborne Synthetic Aperture Radar (SAR) for flood mapping was demonstrated by several past investigations. The synoptic view, the capability to operate in almost all-weather conditions and during both day time and night time and the sensitivity of the microwave band to water are the key features that make SAR data useful for monitoring inundation events. In addition, their high spatial resolution, which can reach 1m with the new generation of X-band instruments such as TerraSAR-X and COSMO-SkyMed (CSK), allows emergency managers to use flood maps at very high spatial resolution. CSK gives also the possibility of performing frequent observations of regions hit by floods, thanks to the four-satellite constellation. Current research on flood mapping using SAR is focused on the development of automatic algorithms to be used in near real time applications. The approaches are generally based on the low radar return from smooth open water bodies that behave as specular reflectors and appear dark in SAR images. The major advantage of automatic algorithms is the computational efficiency that makes them suitable for rapid mapping purposes. The choice of the threshold value that, in this kind of algorithms, separates flooded from non-flooded areas is a critical aspect because it depends on the characteristics of the observed scenario and on system parameters. To deal with this aspect an algorithm for automatic detection of the regions of low backscatter has been developed. It basically accomplishes three steps: 1) division of the SAR image in a set of non-overlapping sub-images or splits; 2) selection of inhomogeneous sub-images that contain (at least) two populations of pixels, one of which is formed by dark pixels; 3) the application in sequence of an automatic thresholding algorithm and a region growing algorithm in order to produce a homogeneous map of flooded areas. Besides the aforementioned choice of the threshold, rapid mapping of floods may
Comparison of Filters Dedicated to Speckle Suppression in SAR Images
NASA Astrophysics Data System (ADS)
Kupidura, P.
2016-06-01
This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images - a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling "salt and pepper" noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction). The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.
Acousto-optic time- and space-integrating spotlight-mode SAR processor
NASA Astrophysics Data System (ADS)
Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.
1993-09-01
The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.
Assessment of documentation requirements under DOE 5481. 1, Safety Analysis and Review System (SARS)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Browne, E.T.
1981-03-01
This report assesses the requirements of DOE Order 5481.1, Safety Analysis and Review System for DOE Operations (SARS) in regard to maintaining SARS documentation. Under SARS, all pertinent details of the entire safety analysis and review process for each DOE operation are to be traceable from the initial identification of a hazard. This report is intended to provide assistance in identifying the points in the SARS cycle at which documentation is required, what type of documentation is most appropriate, and where it ultimately should be maintained.
Computerized ionospheric tomography based on geosynchronous SAR
NASA Astrophysics Data System (ADS)
Hu, Cheng; Tian, Ye; Dong, Xichao; Wang, Rui; Long, Teng
2017-02-01
Computerized ionospheric tomography (CIT) based on spaceborne synthetic aperture radar (SAR) is an emerging technique to construct the three-dimensional (3-D) image of ionosphere. The current studies are all based on the Low Earth Orbit synthetic aperture radar (LEO SAR) which is limited by long repeat period and small coverage. In this paper, a novel ionospheric 3-D CIT technique based on geosynchronous SAR (GEO SAR) is put forward. First, several influences of complex atmospheric environment on GEO SAR focusing are detailedly analyzed, including background ionosphere and multiple scattering effects (induced by turbulent ionosphere), tropospheric effects, and random noises. Then the corresponding GEO SAR signal model is constructed with consideration of the temporal-variant background ionosphere within the GEO SAR long integration time (typically 100 s to 1000 s level). Concurrently, an accurate total electron content (TEC) retrieval method based on GEO SAR data is put forward through subband division in range and subaperture division in azimuth, obtaining variant TEC value with respect to the azimuth time. The processing steps of GEO SAR CIT are given and discussed. Owing to the short repeat period and large coverage area, GEO SAR CIT has potentials of covering the specific space continuously and completely and resultantly has excellent real-time performance. Finally, the TEC retrieval and GEO SAR CIT construction are performed by employing a numerical study based on the meteorological data. The feasibility and correctness of the proposed methods are verified.
Brady Geothermal Field InSAR Raw Data
Ali, Tabrez
2015-03-31
List of TerraSAR-X/TanDEM-X images acquired between 2015-01-01 and 2015-03-31, and archived at https://winsar.unavco.org. See file "BHS InSAR Data with URLs.csv" for individual links. NOTE: The user must create an account in order to access the data (See "Instructions for Creating an Account" below).
What InSAR time-series methods are best suited for the Ecuadorian volcanoes
NASA Astrophysics Data System (ADS)
Mirzaee, S.; Amelung, F.
2017-12-01
Ground displacement measurements from stacks of SAR images obtained using interferometric time-series approaches play an increasingly important role for volcanic hazard assessment. The inflation of the ground surface can indicate that magma ascends to shallower levels and that a volcano gets ready for an eruption. Commonly used InSAR time-series approaches include Small Baseline (SB), Persistent Scatter InSAR (PSI) and SqueeSAR methods but it remains unclear which approach is best suited for volcanic environments. On this poster we present InSAR deformation measurements for the active volcanoes of Ecuador (Cotopaxi, Tungurahua and Pichincha) using a variety of INSAR time-series methods. We discuss the pros and cons of each method given the available data stacks (TerraSAR-X, Cosmo-Skymed and Sentinel-1) in an effort to design a comprehensive observation strategy for the Ecuadorian volcanoes. SAR data are provided in the framework of the Group on Earth Observation's Ecuadorian Volcano Geohazard Supersite.
Local SAR in parallel transmission pulse design.
Lee, Joonsung; Gebhardt, Matthias; Wald, Lawrence L; Adalsteinsson, Elfar
2012-06-01
The management of local and global power deposition in human subjects (specific absorption rate, SAR) is a fundamental constraint to the application of parallel transmission (pTx) systems. Even though the pTx and single channel have to meet the same SAR requirements, the complex behavior of the spatial distribution of local SAR for transmission arrays poses problems that are not encountered in conventional single-channel systems and places additional requirements on pTx radio frequency pulse design. We propose a pTx pulse design method which builds on recent work to capture the spatial distribution of local SAR in numerical tissue models in a compressed parameterization in order to incorporate local SAR constraints within computation times that accommodate pTx pulse design during an in vivo magnetic resonance imaging scan. Additionally, the algorithm yields a protocol-specific ultimate peak in local SAR, which is shown to bound the achievable peak local SAR for a given excitation profile fidelity. The performance of the approach was demonstrated using a numerical human head model and a 7 Tesla eight-channel transmit array. The method reduced peak local 10 g SAR by 14-66% for slice-selective pTx excitations and 2D selective pTx excitations compared to a pTx pulse design constrained only by global SAR. The primary tradeoff incurred for reducing peak local SAR was an increase in global SAR, up to 34% for the evaluated examples, which is favorable in cases where local SAR constraints dominate the pulse applications. Copyright © 2011 Wiley Periodicals, Inc.
Integration of SAR and DEM data: Geometrical considerations
NASA Technical Reports Server (NTRS)
Kropatsch, Walter G.
1991-01-01
General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.
Ma-Lauer, Yue; Carbajo-Lozoya, Javier; Hein, Marco Y; Müller, Marcel A; Deng, Wen; Lei, Jian; Meyer, Benjamin; Kusov, Yuri; von Brunn, Brigitte; Bairad, Dev Raj; Hünten, Sabine; Drosten, Christian; Hermeking, Heiko; Leonhardt, Heinrich; Mann, Matthias; Hilgenfeld, Rolf; von Brunn, Albrecht
2016-08-30
Highly pathogenic severe acute respiratory syndrome coronavirus (SARS-CoV) has developed strategies to inhibit host immune recognition. We identify cellular E3 ubiquitin ligase ring-finger and CHY zinc-finger domain-containing 1 (RCHY1) as an interacting partner of the viral SARS-unique domain (SUD) and papain-like protease (PL(pro)), and, as a consequence, the involvement of cellular p53 as antagonist of coronaviral replication. Residues 95-144 of RCHY1 and 389-652 of SUD (SUD-NM) subdomains are crucial for interaction. Association with SUD increases the stability of RCHY1 and augments RCHY1-mediated ubiquitination as well as degradation of p53. The calcium/calmodulin-dependent protein kinase II delta (CAMK2D), which normally influences RCHY1 stability by phosphorylation, also binds to SUD. In vivo phosphorylation shows that SUD does not regulate phosphorylation of RCHY1 via CAMK2D. Similarly to SUD, the PL(pro)s from SARS-CoV, MERS-CoV, and HCoV-NL63 physically interact with and stabilize RCHY1, and thus trigger degradation of endogenous p53. The SARS-CoV papain-like protease is encoded next to SUD within nonstructural protein 3. A SUD-PL(pro) fusion interacts with RCHY1 more intensively and causes stronger p53 degradation than SARS-CoV PL(pro) alone. We show that p53 inhibits replication of infectious SARS-CoV as well as of replicons and human coronavirus NL63. Hence, human coronaviruses antagonize the viral inhibitor p53 via stabilizing RCHY1 and promoting RCHY1-mediated p53 degradation. SUD functions as an enhancer to strengthen interaction between RCHY1 and nonstructural protein 3, leading to a further increase in in p53 degradation. The significance of these findings is that down-regulation of p53 as a major player in antiviral innate immunity provides a long-sought explanation for delayed activities of respective genes.
Ma-Lauer, Yue; Carbajo-Lozoya, Javier; Müller, Marcel A.; Deng, Wen; Lei, Jian; Meyer, Benjamin; Kusov, Yuri; von Brunn, Brigitte; Bairad, Dev Raj; Hünten, Sabine; Drosten, Christian; Hermeking, Heiko; Leonhardt, Heinrich; Mann, Matthias; Hilgenfeld, Rolf; von Brunn, Albrecht
2016-01-01
Highly pathogenic severe acute respiratory syndrome coronavirus (SARS-CoV) has developed strategies to inhibit host immune recognition. We identify cellular E3 ubiquitin ligase ring-finger and CHY zinc-finger domain-containing 1 (RCHY1) as an interacting partner of the viral SARS-unique domain (SUD) and papain-like protease (PLpro), and, as a consequence, the involvement of cellular p53 as antagonist of coronaviral replication. Residues 95–144 of RCHY1 and 389–652 of SUD (SUD-NM) subdomains are crucial for interaction. Association with SUD increases the stability of RCHY1 and augments RCHY1-mediated ubiquitination as well as degradation of p53. The calcium/calmodulin-dependent protein kinase II delta (CAMK2D), which normally influences RCHY1 stability by phosphorylation, also binds to SUD. In vivo phosphorylation shows that SUD does not regulate phosphorylation of RCHY1 via CAMK2D. Similarly to SUD, the PLpros from SARS-CoV, MERS-CoV, and HCoV-NL63 physically interact with and stabilize RCHY1, and thus trigger degradation of endogenous p53. The SARS-CoV papain-like protease is encoded next to SUD within nonstructural protein 3. A SUD–PLpro fusion interacts with RCHY1 more intensively and causes stronger p53 degradation than SARS-CoV PLpro alone. We show that p53 inhibits replication of infectious SARS-CoV as well as of replicons and human coronavirus NL63. Hence, human coronaviruses antagonize the viral inhibitor p53 via stabilizing RCHY1 and promoting RCHY1-mediated p53 degradation. SUD functions as an enhancer to strengthen interaction between RCHY1 and nonstructural protein 3, leading to a further increase in in p53 degradation. The significance of these findings is that down-regulation of p53 as a major player in antiviral innate immunity provides a long-sought explanation for delayed activities of respective genes. PMID:27519799
Use of Sentinel-1 SAR data to monitor Mosul dam vulnerability
NASA Astrophysics Data System (ADS)
Riccardi, Paolo; Tessari, Giulia; Lecci, Daniele; Floris, Mario; Pasquali, Paolo
2017-04-01
. It was completed in 1984 and started generating power on 1986. Since then, frequent consolidation works have been carried out pumping cement mixtures into the soil foundation to keep it stable and prevent it from sinking and then breaking apart. To overcome the impossibility of directly monitoring the structure, analysis of recent deformation affecting the Mosul dam is achieved considering C-band Sentinel-1 SAR data, acquired from the end of 2014 to the present. These 20-m ground resolution data can provide a millimetric precision on displacements. Furthermore, ESA archive available SAR data (ERS and Envisat) are considered to reconstruct the temporal evolution of the deformations. In this work, different stacks of data are processed applying SBAS and PS A-DInSAR techniques; deformation fields obtained from SAR data are evaluated to assess the temporal evolution of the strains affecting the structure. Obtained results represent the preliminary stage of a multidisciplinary project, finalised to assess possible damages affecting a dam through remote sensing and civil engineering surveys.
NASA Astrophysics Data System (ADS)
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.
Layover and shadow detection based on distributed spaceborne single-baseline InSAR
NASA Astrophysics Data System (ADS)
Huanxin, Zou; Bin, Cai; Changzhou, Fan; Yun, Ren
2014-03-01
Distributed spaceborne single-baseline InSAR is an effective technique to get high quality Digital Elevation Model. Layover and Shadow are ubiquitous phenomenon in SAR images because of geometric relation of SAR imaging. In the signal processing of single-baseline InSAR, the phase singularity of Layover and Shadow leads to the phase difficult to filtering and unwrapping. This paper analyzed the geometric and signal model of the Layover and Shadow fields. Based on the interferometric signal autocorrelation matrix, the paper proposed the signal number estimation method based on information theoretic criteria, to distinguish Layover and Shadow from normal InSAR fields. The effectiveness and practicability of the method proposed in the paper are validated in the simulation experiments and theoretical analysis.
Ground settlement monitoring from temporarily persistent scatterers between two SAR acquisitions
Lei, Z.; Xiaoli, D.; Guangcai, F.; Zhong, L.
2009-01-01
We present an improved differential interferometric synthetic aperture radar (DInSAR) analysis method that measures motions of scatterers whose phases are stable between two SAR acquisitions. Such scatterers are referred to as temporarily persistent scatterers (TPS) for simplicity. Unlike the persistent scatterer InSAR (PS-InSAR) method that relies on a time-series of interferograms, the new algorithm needs only one interferogram. TPS are identified based on pixel offsets between two SAR images, and are specially coregistered based on their estimated offsets instead of a global polynomial for the whole image. Phase unwrapping is carried out based on an algorithm for sparse data points. The method is successfully applied to measure the settlement in the Hong Kong Airport area. The buildings surrounded by vegetation were successfully selected as TPS and the tiny deformation signal over the area was detected. ??2009 IEEE.
Research on Multi-Temporal PolInSAR Modeling and Applications
NASA Astrophysics Data System (ADS)
Hong, Wen; Pottier, Eric; Chen, Erxue
2014-11-01
In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman-Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal Land P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.
Research on Multi-Temporal PolInSAR Modeling and Applications
NASA Astrophysics Data System (ADS)
Hong, Wen; Pottier, Eric; Chen, Erxue
2014-11-01
In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman- Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal L- and P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.
InSAR data for monitoring land subsidence: time to think big
NASA Astrophysics Data System (ADS)
Ferretti, A.; Colombo, D.; Fumagalli, A.; Novali, F.; Rucci, A.
2015-11-01
Satellite interferometric synthetic aperture radar (InSAR) data have proven effective and valuable in the analysis of urban subsidence phenomena based on multi-temporal radar images. Results obtained by processing data acquired by different radar sensors, have shown the potential of InSAR and highlighted the key points for an operational use of this technology, namely: (1) regular acquisition over large areas of interferometric data stacks; (2) use of advanced processing algorithms, capable of estimating and removing atmospheric disturbances; (3) access to significant processing power for a regular update of the information over large areas. In this paper, we show how the operational potential of InSAR has been realized thanks to the recent advances in InSAR processing algorithms, the advent of cloud computing and the launch of new satellite platforms, specifically designed for InSAR analyses (e.g. Sentinel-1a operated by the ESA and ALOS2 operated by JAXA). The processing of thousands of SAR scenes to cover an entire nation has been performed successfully in Italy in a project financed by the Italian Ministry of the Environment. The challenge for the future is to pass from the historical analysis of SAR scenes already acquired in digital archives to a near real-time monitoring program where up to date deformation data are routinely provided to final users and decision makers.
Detection and imaging of moving objects with SAR by a joint space-time-frequency processing
NASA Astrophysics Data System (ADS)
Barbarossa, Sergio; Farina, Alfonso
This paper proposes a joint spacetime-frequency processing scheme for the detection and imaging of moving targets by Synthetic Aperture Radars (SAR). The method is based on the availability of an array antenna. The signals received by the array elements are combined, in a spacetime processor, to cancel the clutter. Then, they are analyzed in the time-frequency domain, by computing their Wigner-Ville Distribution (WVD), in order to estimate the instantaneous frequency, to be used for the successive phase compensation, necessary to produce a high resolution image.
Basic to Advanced InSAR Processing: GMTSAR
NASA Astrophysics Data System (ADS)
Sandwell, D. T.; Xu, X.; Baker, S.; Hogrelius, A.; Mellors, R. J.; Tong, X.; Wei, M.; Wessel, P.
2017-12-01
Monitoring crustal deformation using InSAR is becoming a standard technique for the science and application communities. Optimal use of the new data streams from Sentinel-1 and NISAR will require open software tools as well as education on the strengths and limitations of the InSAR methods. Over the past decade we have developed freely available, open-source software for processing InSAR data. The software relies on the Generic Mapping Tools (GMT) for the back-end data analysis and display and is thus called GMTSAR. With startup funding from NSF, we accelerated the development of GMTSAR to include more satellite data sources and provide better integration and distribution with GMT. In addition, with support from UNAVCO we have offered 6 GMTSAR short courses to educate mostly novice InSAR users. Currently, the software is used by hundreds of scientists and engineers around the world to study deformation at more than 4300 different sites. The most challenging aspect of the recent software development was the transition from image alignment using the cross-correlation method to a completely new alignment algorithm that uses only the precise orbital information to geometrically align images to an accuracy of better than 7 cm. This development was needed to process a new data type that is being acquired by the Sentinel-1A/B satellites. This combination of software and open data is transforming radar interferometry from a research tool into a fully operational time series analysis tool. Over the next 5 years we are planning to continue to broaden the user base through: improved software delivery methods; code hardening; better integration with data archives; support for high level products being developed for NISAR; and continued education and outreach.
Simulation-Based Evaluation of Light Posts and Street Signs as 3-D Geolocation Targets in SAR Images
NASA Astrophysics Data System (ADS)
Auer, S.; Balss, U.
2017-05-01
The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.
MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?
Deledalle, Charles-Alban; Denis, Loic; Tabti, Sonia; Tupin, Florence
2017-09-01
Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.
NASA Technical Reports Server (NTRS)
Lee, Seung-Kuk; Fatoyinbo, Temilola; Lagomasino, David; Osmanoglu, Batuhan; Feliciano, Emanuelle
2016-01-01
The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.
NASA Astrophysics Data System (ADS)
Mangla, Rohit; Kumar, Shashi; Nandy, Subrata
2016-05-01
SAR and LiDAR remote sensing have already shown the potential of active sensors for forest parameter retrieval. SAR sensor in its fully polarimetric mode has an advantage to retrieve scattering property of different component of forest structure and LiDAR has the capability to measure structural information with very high accuracy. This study was focused on retrieval of forest aboveground biomass (AGB) using Terrestrial Laser Scanner (TLS) based point clouds and scattering property of forest vegetation obtained from decomposition modelling of RISAT-1 fully polarimetric SAR data. TLS data was acquired for 14 plots of Timli forest range, Uttarakhand, India. The forest area is dominated by Sal trees and random sampling with plot size of 0.1 ha (31.62m*31.62m) was adopted for TLS and field data collection. RISAT-1 data was processed to retrieve SAR data based variables and TLS point clouds based 3D imaging was done to retrieve LiDAR based variables. Surface scattering, double-bounce scattering, volume scattering, helix and wire scattering were the SAR based variables retrieved from polarimetric decomposition. Tree heights and stem diameters were used as LiDAR based variables retrieved from single tree vertical height and least square circle fit methods respectively. All the variables obtained for forest plots were used as an input in a machine learning based Random Forest Regression Model, which was developed in this study for forest AGB estimation. Modelled output for forest AGB showed reliable accuracy (RMSE = 27.68 t/ha) and a good coefficient of determination (0.63) was obtained through the linear regression between modelled AGB and field-estimated AGB. The sensitivity analysis showed that the model was more sensitive for the major contributed variables (stem diameter and volume scattering) and these variables were measured from two different remote sensing techniques. This study strongly recommends the integration of SAR and LiDAR data for forest AGB estimation.
Brady's Geothermal Field - Metadata for InSAR Holdings
Ali, Tabrez
2016-07-29
List of synthetic aperture radar (SAR) images acquired by TerraSAR-X and TanDEM-X satellite missions and archived at UNAVCO's WINSAR facility. See file "Bradys TSX Holdings.csv" for individual links. NOTE: The user must create an account in order to access the data (See "Instructions for Creating an Account" below).
Analysis of Benefits and Pitfalls of Satellite SAR for Coastal Area Monitoring
NASA Astrophysics Data System (ADS)
Nunziata, F.; Buono, A.; Mgliaccio, M.; Li, X.; Wei, Y.
2016-08-01
This study aims at describing the outcomes of the Dragon-3 project no. 10689. The undertaken activities deal with coastal area monitoring and they include sea pollution and coastline extraction. The key remote sensing tool is the Synthetic Aperture Radar (SAR) that provides fine resolution images of the microwave reflectivity of the observed scene. However, the interpretation of SAR images is not at all straightforward and all the above-mentioned coastal area applications cannot be easily addressed using single-polarization SAR. Hence, the main outcome of this project is investigating the capability of multi-polarization SAR measurements to generate added-vale product in the frame of coastal area management.
2004-03-03
Personnel viewing AirSAR hardware while touring the outside of NASA's DC-8 during a stop-off on the AirSAR 2004 Mesoamerica campaign, L-R: Fernando Gutierrez, Costa Rican Minister of Science and Technology(MICIT); NASA Administrator Sean O'Keefe; Dr. Gahssem Asrar, NASA Associate Administrator for Earth Science Enterprises; JPL scientist Bruce Chapman; and Craig Dobson, NASA Program Manager for AirSAR. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that will use an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR), in a mission ranging from the tropical rain forests of Central America to frigid Antarctica.
Land subsidence in the Yangtze River Delta, China revealed from multi-frequency SAR Interferometry
NASA Astrophysics Data System (ADS)
Li, Zhenhong; Motagh, Mahdi; Yu, Jun; Gong, Xulong; Wu, Jianqiang; Zhu, Yefei; Chen, Huogen; Zhang, Dengming; Xu, Yulin
2014-05-01
Land subsidence is a major worldwide hazard, and its principal causes are subsurface fluid withdrawal, drainage of organic soils, sinkholes, underground mining, hydrocompaction, thawing permafrost, and natural consolidation. Land subsidence causes many problems including: damage to public facilities such as bridges, roads, railroads, electric power lines, underground pipes; damage to private and public buildings; and in some cases of low-lying land, can increase the risk of coastal flooding from storm surges and rising sea-levels. In China, approximately 48600 km2 of land, an area roughly 30 times of the size of the Greater London, has subsided (nearly 50 cities across 16 provinces), and the annual direct economic loss is estimated to be more than RMB 100 million (~12 million). It is believed that the Suzhou-Wuxi-Changzhou region within the Yangtze River Delta is the most severely affected area for subsidence hazards in China. With its global coverage and all-weather imaging capability, Interferometric SAR (InSAR) is revolutionizing our ability to image the Earth's surface and the evolution of its shape over time. In this paper, an advanced InSAR time series technique, InSAR TS + AEM, has been employed to analysed ERS (C-band), Envisat (C-band) and TerraSAR-X (X-band) data collected over the Suzhou-Wuxi-Changzhou region during the period from 1992 to 2013. Validation with precise levelling and GPS data suggest: (1) the accuracy of the InSAR-derived mean velocity measurements is 1-3 mm/yr; (2) InSAR-derived displacements agreed with precise levelling with root mean square errors around 5 mm. It is evident that InSAR TS + AEM can be used to image the evolution of deformation patterns in the Suzhou-Wuxi-Changzhou region over time: the maximum mean velocity decreased from ~12 cm/yr during the period of 1992-1993 to ~2 cm/yr in 2003-2013. This is believed to be a result of the prohibition of groundwater use carried out by Jiangsu provincial government. The combination
InSAR Monitoring of Landslides using RADARSAT and Alos
NASA Astrophysics Data System (ADS)
Singhroy, V.; Pierre-Jean, A.; Pavlic, G.
2009-05-01
We present the results of InSAR monitoring of several landslides using RADARDAT, and ALOS satellites. InSAR techniques are increasingly being used in slope stability assessment. Our research has shown that differential InSAR and coherent target monitoring techniques using field corner reflectors are useful to monitor landslide activity along strategic transportation and energy corridors. The Mackenzie Valley in northern Canada is experiencing one of the highest rates on mean annual air temperature for any region in Canada, thereby triggering melting in the permafrost, which results in active layer detachment slides. There are approximately 2000 landslides along the proposed Mackenzie Valley pipeline route. In addition, the Trans Canada Highway in the Canadian Rockies are affected by several rock avalanches and slow retrogressive slides. The ALOS PALSAR InSAR results show that we can observe deformation on both vegetated and exposed rock areas on the Little Smokey slide and the Frank Slide. RADARSAT-1 InSAR images indicate the different level of activity of the slopes (large and small) during different periods of the year. RADARSAT-2 is providing the high resolution rapid revisit capabilities needed to continuously monitor these active slopes along Canadian strategic energy and transportation corridors. The information produced by our InSAR activity maps on various landslides are used to realign the pipeline route in sensitive permafrost areas, and to install slope stability measures along the Trans-Canada and Provincial Highways. Using these different satellites we are able to develop guidelines for more reliable uses of these SAR missions Keywords: InSAR, landslides, RADARSAT, ALOS .
A novel multi-band SAR data technique for fully automatic oil spill detection in the ocean
NASA Astrophysics Data System (ADS)
Del Frate, Fabio; Latini, Daniele; Taravat, Alireza; Jones, Cathleen E.
2013-10-01
With the launch of the Italian constellation of small satellites for the Mediterranean basin observation COSMO-SkyMed and the German TerraSAR-X missions, the delivery of very high-resolution SAR data to observe the Earth day or night has remarkably increased. In particular, also taking into account other ongoing missions such as Radarsat or those no longer working such as ALOS PALSAR, ERS-SAR and ENVISAT the amount of information, at different bands, available for users interested in oil spill analysis has become highly massive. Moreover, future SAR missions such as Sentinel-1 are scheduled for launch in the very next years while additional support can be provided by Uninhabited Aerial Vehicle (UAV) SAR systems. Considering the opportunity represented by all these missions, the challenge is to find suitable and adequate image processing multi-band procedures able to fully exploit the huge amount of data available. In this paper we present a new fast, robust and effective automated approach for oil-spill monitoring starting from data collected at different bands, polarizations and spatial resolutions. A combination of Weibull Multiplicative Model (WMM), Pulse Coupled Neural Network (PCNN) and Multi-Layer Perceptron (MLP) techniques is proposed for achieving the aforementioned goals. One of the most innovative ideas is to separate the dark spot detection process into two main steps, WMM enhancement and PCNN segmentation. The complete processing chain has been applied to a data set containing C-band (ERS-SAR, ENVISAT ASAR), X-band images (Cosmo-SkyMed and TerraSAR-X) and L-band images (UAVSAR) for an overall number of more than 200 images considered.
Global Tropospheric Noise Maps for InSAR Observations
NASA Astrophysics Data System (ADS)
Yun, S. H.; Hensley, S.; Agram, P. S.; Chaubell, M.; Fielding, E. J.; Pan, L.
2014-12-01
Radio wave's differential phase delay variation through the troposphere is the largest error sources in Interferometric Synthetic Aperture Radar (InSAR) measurements, and water vapor variability in the troposphere is known to be the dominant factor. We use the precipitable water vapor (PWV) products from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors mounted on Terra and Aqua satellites to produce tropospheric noise maps of InSAR. We estimate the slope and y-intercept of power spectral density curve of MODIS PWV and calculate the structure function to estimate the expected tropospheric noise level as a function of distance. The results serve two purposes: 1) to provide guidance on the expected covariance matrix for geophysical modeling, 2) to provide quantitative basis for the science Level-1 requirements of the planned NASA-ISRO L-band SAR mission (NISAR mission). We populate lookup tables of such power spectrum parameters derived from each 1-by-1 degree tile of global coverage. The MODIS data were retrieved from OSCAR (Online Services for Correcting Atmosphere in Radar) server. Users will be able to use the lookup tables and calculate expected tropospheric noise level of any date of MODIS data at any distance scale. Such calculation results can be used for constructing covariance matrix for geophysical modeling, or building statistics to support InSAR missions' requirements. For example, about 74% of the world had InSAR tropospheric noise level (along a radar line-of-sight for an incidence angle of 40 degrees) of 2 cm or less at 50 km distance scale during the time period of 2010/01/01 - 2010/01/09.
Internal Wave Study in the South China Sea Using SAR
NASA Technical Reports Server (NTRS)
Liu, Antony K.; Hsu, Ming-Kuang; Zukor, Dorothy (Technical Monitor)
2000-01-01
Recently, the internal wave distribution maps in the China Seas have been compiled from hundreds of ERS-1/2, RADARSAT, and Space Shuttle SAR (Synthetic Aperture Radar) images from 1993 to 1999. Based on internal wave distribution map, most of internal waves in the northeast part of South China Sea were propagating westward. The wave crest can be as long as 200 km with amplitude of 100 m due to strong current from the Kuroshio branching out into the South China Sea. Based on the observations from drilling rigs near DongSha Island by Amoco Production Co., the solitons may be generated in a 4 km wide channel between Batan and Sabtang islands in Luzon Strait. The proposed generation mechanism is similar to the lee wave formation from a shallow topography. Both depression and elevation internal waves have been observed in the same RADARSAT ScanSAR image on May 4, 1998 near DongSha Island. Furthermore, depression and elevation internal waves have also been observed by SAR at the same location on the shelf in April and June, 1993 (in different seasons) respectively. Numerical models have been used to interpret their generation mechanism and evolution processes. Based on the SAR images, near DongSha Island, the westward propagating huge internal solitons are often encountered and diffracted/broken by the coral reefs on the shelf. After passing the island, the diffracted waves will re-merge or interact with each other. It has been observed that after the nonlinear wave-wave interaction, the phase of wave packet is shifted and wavelength is also changed. Examples of mesoscale features observed in SAR images, such as fronts, raincells, bathymetry, ship wakes, and oil spills will be presented. Recent mooring measurements in April 1999 near Dongsha Island, future field test ASIAEX (Asian Seas International Acoustics Experiment) planned for April 2001, and some pretest survey data will be discussed in this paper.
NASA Astrophysics Data System (ADS)
Penna, Pedro A. A.; Mascarenhas, Nelson D. A.
2018-02-01
The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.
InSAR Scientific Computing Environment - The Home Stretch
NASA Astrophysics Data System (ADS)
Rosen, P. A.; Gurrola, E. M.; Sacco, G.; Zebker, H. A.
2011-12-01
The Interferometric Synthetic Aperture Radar (InSAR) Scientific Computing Environment (ISCE) is a software development effort in its third and final year within the NASA Advanced Information Systems and Technology program. The ISCE is a new computing environment for geodetic image processing for InSAR sensors enabling scientists to reduce measurements directly from radar satellites to new geophysical products with relative ease. The environment can serve as the core of a centralized processing center to bring Level-0 raw radar data up to Level-3 data products, but is adaptable to alternative processing approaches for science users interested in new and different ways to exploit mission data. Upcoming international SAR missions will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystem. The InSAR Scientific Computing Environment has the functionality to become a key element in processing data from NASA's proposed DESDynI mission into higher level data products, supporting a new class of analyses that take advantage of the long time and large spatial scales of these new data. At the core of ISCE is a new set of efficient and accurate InSAR algorithms. These algorithms are placed into an object-oriented, flexible, extensible software package that is informed by modern programming methods, including rigorous componentization of processing codes, abstraction and generalization of data models. The environment is designed to easily allow user contributions, enabling an open source community to extend the framework into the indefinite future. ISCE supports data from nearly all of the available satellite platforms, including ERS, EnviSAT, Radarsat-1, Radarsat-2, ALOS, TerraSAR-X, and Cosmo-SkyMed. The code applies a number of parallelization techniques and sensible approximations for speed. It is configured to work on modern linux-based computers with gcc compilers and python
Liu, Ye V.; Massare, Michael J.; Barnard, Dale L.; Kort, Thomas; Nathan, Margret; Wang, Lei; Smith, Gale
2011-01-01
SARS-CoV was the cause of the global pandemic in 2003 that infected over 8000 people in 8 months. Vaccines against SARS are still not available. We developed a novel method to produce high levels of a recombinant SARS virus-like particles (VLPs) vaccine containing the SARS spike (S) protein and the influenza M1 protein using the baculovirus insect cell expression system. These chimeric SARS VLPs have a similar size and morphology to the wild type SARS-CoV. We tested the immunogenicity and protective efficacy of purified chimeric SARS VLPs and full length SARS S protein vaccines in a mouse lethal challenge model. The SARS VLP vaccine, containing 0.8 μg of SARS S protein, completely protected mice from death when administered intramuscular (IM) or intranasal (IN) routes in the absence of an adjuvant. Likewise, the SARS VLP vaccine, containing 4 μg of S protein without adjuvant, reduced lung virus titer to below detectable level, protected mice from weight loss, and elicited a high level of neutralizing antibodies against SARS-CoV. Sf9 cell-produced full length purified SARS S protein was also an effective vaccine against SARS-CoV but only when co-administered IM with aluminum hydroxide. SARS-CoV VLPs are highly immunogenic and induce neutralizing antibodies and provide protection against lethal challenge. Sf9 cell-based VLP vaccines are a potential tool to provide protection against novel pandemic agents. PMID:21762752
DEM generation in cloudy-rainy mountainous area with multi-baseline SAR interferometry
NASA Astrophysics Data System (ADS)
Wu, Hong'an; Zhang, Yonghong; Jiang, Decai; Kang, Yonghui
2018-03-01
Conventional singe baseline InSAR is easily affected by atmospheric artifacts, making it difficult to generate highprecision DEM. To solve this problem, in this paper, a multi-baseline interferometric phase accumulation method with weights fixed by coherence is proposed to generate higher accuracy DEM. The mountainous area in Kunming, Yunnan Province, China is selected as study area, which is characterized by cloudy weather, rugged terrain and dense vegetation. The multi-baseline InSAR experiments are carried out by use of four ALOS-2 PALSAR-2 images. The generated DEM is evaluated by Chinese Digital Products of Fundamental Geographic Information 1:50000 DEM. The results demonstrate that: 1) the proposed method can reduce atmospheric artifacts significantly; 2) the accuracy of InSAR DEM generated by six interferograms satisfies the standard of 1:50000 DEM Level Three and American DTED-1.
Terrain Measurement with SAR/InSAR
NASA Astrophysics Data System (ADS)
Li, Deren; Liao, Mingsheng; Balz, Timo; Zhang, Lu; Yang, Tianliang
2016-08-01
Terrain measurement and surface motion estimation are the most important applications for commercial and scientific SAR missions. In Dragon-3, we worked on these applications, especially regarding DEM generation, surface motion estimation with SAR time- series for urban subsidence monitoring and landslide motion estimation, as well as developing tomographic SAR processing methods in urban areas.
NASA Astrophysics Data System (ADS)
Taravat, A.; Del Frate, F.
2013-09-01
As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.
Sea ice motion measurements from Seasat SAR images
NASA Technical Reports Server (NTRS)
Leberl, F.; Raggam, J.; Elachi, C.; Campbell, W. J.
1983-01-01
Data from the Seasat synthetic aperture radar (SAR) experiment are analyzed in order to determine the accuracy of this information for mapping the distribution of sea ice and its motion. Data from observations of sea ice in the Beaufort Sea from seven sequential orbits of the satellite were selected to study the capabilities and limitations of spaceborne radar application to sea-ice mapping. Results show that there is no difficulty in identifying homologue ice features on sequential radar images and the accuracy is entirely controlled by the accuracy of the orbit data and the geometric calibration of the sensor. Conventional radargrammetric methods are found to serve well for satellite radar ice mapping, while ground control points can be used to calibrate the ice location and motion measurements in the cases where orbit data and sensor calibration are lacking. The ice motion was determined to be approximately 6.4 + or - 0.5 km/day. In addition, the accuracy of pixel location was found over land areas. The use of one control point in 10,000 sq km produced an accuracy of about + or 150 m, while with a higher density of control points (7 in 1000 sq km) the location accuracy improves to the image resolution of + or - 25 m. This is found to be applicable for both optical and digital data.
Wiebe, M G; Robson, G D; Shuster, J R; Trinci, A P
1999-08-05
Fusarium venenatum (formerly Fusarium graminearum) JeRS 325 produces heterologous glucoamylase (GAM) under the regulation of a Fusarium oxysporum alkaline (trypsin-like) protease promoter. The glucoamylase gene was used as a reporter gene to study the effects of ammonium and pH on GAM production under the control of the alkaline protease promoter. Between pH 4.0 and 5.8, GAM production in glucose-limited chemostat cultures of JeRS 325 grown at a dilution rate of 0.10 h-1 (doubling time, 6.9 h) on (NH4)2SO4 medium increased in a linear manner with increase in pH. However, at pH 4.0 and below GAM production was almost completely repressed in glucose-limited chemostat cultures grown on (NH4)2SO4 or NaNO3 medium. Thus GAM production in JeRS 325 is regulated by culture pH, not by the nature of the nitrogen source in the medium. The difficulty of using unbuffered medium when investigating putative ammonium repression is also shown. The study demonstrates the potential for use of the alkaline protease promoter in F. graminearum for the production of recombinant proteins in a pH dependent man ner. Copyright 1999 John Wiley & Sons, Inc.
Relationship between post-SARS osteonecrosis and PAI-1 4G/5G gene polymorphisms.
Sun, Wei; Li, Zirong; Shi, Zhengcai; Wang, Bailiang; Gao, Fuqiang; Yang, Yurun; Guo, Wanshou
2014-05-01
To explore the correlation between post-severe acute respiratory symptom (SARS) patients with osteonecrosis, investigate the etiology of post-SARS osteonecrosis and select the sensitive molecular symbols for early diagnosis and distinguish the high-risk population. The studied subjects were divided into two groups. Sixty-two post-SARS patients with osteonecrosis were one group, and 52 age- and sex-matched healthy people were as normal controlled group. Empty stomach blood samples from cubital veins were collected from both groups. Plasminogen activator inhibitor (PAI) by means of enzyme-linked immunosorbent assay and PAI-1 4G/5G polymorphism was detected by polymerase chain reaction and solid phase oligonucleotide assay. The blood agents of post-SARS patients changed obviously with 15.64 ± 13.85 U/ml while the control group 7.96 ± 4.27 U/ml; 4G/4G genotype for the PAI-1 polymorphism detected in post-SARS group was more than that of the control group, but had no statistical significance. The plasma PAI activity was related to homozygote 4G/4G genotype. This reveals that homozygote 4G/4G genotype may be a susceptible gene mark to Chinese osteonecrosis patients. Plasminogen activator inhibitor-1 is sensitive blood symbol for screening high-risk susceptible population; 4G/4G PAI-1 genotype may be an etiological factor in osteonecrosis.
InSAR datum connection using GNSS-augmented radar transponders
NASA Astrophysics Data System (ADS)
Mahapatra, Pooja; der Marel, Hans van; van Leijen, Freek; Samiei-Esfahany, Sami; Klees, Roland; Hanssen, Ramon
2018-01-01
Deformation estimates from Interferometric Synthetic Aperture Radar (InSAR) are relative: they form a `free' network referred to an arbitrary datum, e.g. by assuming a reference point in the image to be stable. However, some applications require `absolute' InSAR estimates, i.e. expressed in a well-defined terrestrial reference frame, e.g. to compare InSAR results with those of other techniques. We propose a methodology based on collocated InSAR and Global Navigation Satellite System (GNSS) measurements, achieved by rigidly attaching phase-stable millimetre-precision compact active radar transponders to GNSS antennas. We demonstrate this concept through a simulated example and practical case studies in the Netherlands.
A new clustering algorithm applicable to multispectral and polarimetric SAR images
NASA Technical Reports Server (NTRS)
Wong, Yiu-Fai; Posner, Edward C.
1993-01-01
We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.
Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu
2017-01-23
Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.
2004-03-10
School children from Punta Arenas, Chile, talk with Dr. David Imel, an AirSAR scientist from NASA JPL, during AirSAR 2004. AirSAR 2004 is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central and South America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. In South America and Antarctica, AirSAR collected imagery and data to help determine the contribution of Southern Hemisphere glaciers to sea level rise due to climate change. In Patagonia, researchers found this contribution had more than doubled from 1995 to 2000, compared to the previous 25 years. AirSAR data will make it possible to determine whether that trend is continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.
Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le
2018-02-12
The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.
Space-based detection of wetlands' surface water level changes from L-band SAR interferometry
Wdowinski, S.; Kim, S.-W.; Amelung, F.; Dixon, T.H.; Miralles-Wilhelm, F.; Sonenshein, R.
2008-01-01
Interferometric processing of JERS-1 L-band Synthetic Aperture Radar (SAR) data acquired over south Florida during 1993-1996 reveals detectable surface changes in the Everglades wetlands. Although our study is limited to south Florida it has implication for other large-scale wetlands, because south Florida wetlands have diverse vegetation types and both managed and natural flow environments. Our analysis reveals that interferometric coherence level is sensitive to wetland vegetation type and to the interferogram time span. Interferograms with time spans less than six months maintain phase observations for all wetland types, allowing characterization of water level changes in different wetland environments. The most noticeable changes occur between the managed and the natural flow wetlands. In the managed wetlands, fringes are organized, follow patterns related to some of the managed water control structures and have high fringe-rate. In the natural flow areas, fringes are irregular and have a low fringe-rate. The high fringe rate in managed areas reflects dynamic water topography caused by high flow rate due to gate operation. Although this organized fringe pattern is not characteristic of most large-scale wetlands, the high level of water level change enables accurate estimation of the wetland InSAR technique, which lies in the range of 5-10??cm. The irregular and low rate fringe pattern in the natural flow area reflects uninterrupted flow that diffuses water efficiently and evenly. Most of the interferograms in the natural flow area show an elongated fringe located along the transitional zone between salt- and fresh-water wetlands, reflecting water level changes due to ocean tides. ?? 2007 Elsevier Inc. All rights reserved.
Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection
Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun
2016-01-01
Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated
Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.
Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun
2016-07-19
Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated
NASA Astrophysics Data System (ADS)
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
Design of integrated ship monitoring system using SAR, RADAR, and AIS
NASA Astrophysics Data System (ADS)
Yang, Chan-Su; Kim, Tae-Ho; Hong, Danbee; Ahn, Hyung-Wook
2013-06-01
When we talk about for the ship detection, identification and its classification, we need to go for the wide area of monitoring and it may be possible only through satellite based monitoring approach which monitors and covers coastal as well as the oceanic zone. Synthetic aperture radar (SAR) has been widely used to detect targets of interest with the advantage of the operating capability in all weather and luminance free condition (Margarit and Tabasco, 2011). In EU waters, EMSA(European Maritime Safety Agency) is operating the SafeSeaNet and CleanSeaNet systems which provide the current positions of all ships and oil spill monitoring information in and around EU waters in a single picture to Member States using AIS, LRIT and SAR images. In many countries, a similar system has been developed and the key of the matter is to integrate all available data. This abstract describes the preliminary design concept for an integration system of RADAR, AIS and SAR data for vessel traffic monitoring. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should be also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Land-based RADAR can provide ships positions detected and tracked in near real time. In general, SAR are used to acquire image data over large coverage area, AIS reports are obtained from ship based transmitter, and RADAR can monitor continuously ships for a limited area. In this study, we developed individual ship monitoring algorithms using RADAR(FMCW and Pulse X-band), AIS and SAR(RADARSAT-2 Full-pol Mode). We conducted field experiments two times for displaying the RADAR, AIS and SAR integration over the Pyeongtaek Port, South Korea.
Chen, Zhenwei; Zhang, Lei; Zhang, Guo
2016-01-01
Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level. PMID:27649207
Chen, Zhenwei; Zhang, Lei; Zhang, Guo
2016-09-17
Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.
NASA Technical Reports Server (NTRS)
Carsey, Frank D.
1989-01-01
Science objectives, opportunities and requirements are discussed for the utilization of data from the Synthetic Aperture Radar (SAR) on the European First Remote Sensing Satellite, to be flown by the European Space Agency in the early 1990s. The principal applications of the imaging data are in studies of geophysical processes taking place within the direct-reception area of the Alaska SAR Facility in Fairbanks, Alaska, essentially the area within 2000 km of the receiver. The primary research that will be supported by these data include studies of the oceanography and sea ice phenomena of Alaskan and adjacent polar waters and the geology, glaciology, hydrology, and ecology of the region. These studies focus on the area within the reception mask of ASF, and numerous connections are made to global processes and thus to the observation and understanding of global change. Processes within the station reception area both affect and are affected by global phenomena, in some cases quite critically. Requirements for data processing and archiving systems, prelaunch research, and image processing for geophysical product generation are discussed.
Multi-dimensional SAR tomography for monitoring the deformation of newly built concrete buildings
NASA Astrophysics Data System (ADS)
Ma, Peifeng; Lin, Hui; Lan, Hengxing; Chen, Fulong
2015-08-01
Deformation often occurs in buildings at early ages, and the constant inspection of deformation is of significant importance to discover possible cracking and avoid wall failure. This paper exploits the multi-dimensional SAR tomography technique to monitor the deformation performances of two newly built buildings (B1 and B2) with a special focus on the effects of concrete creep and shrinkage. To separate the nonlinear thermal expansion from total deformations, the extended 4-D SAR technique is exploited. The thermal map estimated from 44 TerraSAR-X images demonstrates that the derived thermal amplitude is highly related to the building height due to the upward accumulative effect of thermal expansion. The linear deformation velocity map reveals that B1 is subject to settlement during the construction period, in addition, the creep and shrinkage of B1 lead to wall shortening that is a height-dependent movement in the downward direction, and the asymmetrical creep of B2 triggers wall deflection that is a height-dependent movement in the deflection direction. It is also validated that the extended 4-D SAR can rectify the bias of estimated wall shortening and wall deflection by 4-D SAR.
Generation of Classical DInSAR and PSI Ground Motion Maps on a Cloud Thematic Platform
NASA Astrophysics Data System (ADS)
Mora, Oscar; Ordoqui, Patrick; Romero, Laia
2016-08-01
This paper presents the experience of ALTAMIRA INFORMATION uploading InSAR (Synthetic Aperture Radar Interferometry) services in the Geohazard Exploitation Platform (GEP), supported by ESA. Two different processing chains are presented jointly with ground motion maps obtained from the cloud computing, one being DIAPASON for classical DInSAR and SPN (Stable Point Network) for PSI (Persistent Scatterer Interferometry) processing. The product obtained from DIAPASON is the interferometric phase related to ground motion (phase fringes from a SAR pair). SPN provides motion data (mean velocity and time series) on high-quality pixels from a stack of SAR images. DIAPASON is already implemented, and SPN is under development to be exploited with historical data coming from ERS-1/2 and ENVISAT satellites, and current acquisitions of SENTINEL-1 in SLC and TOPSAR modes.
SAR Ambiguity Study for the Cassini Radar
NASA Technical Reports Server (NTRS)
Hensley, Scott; Im, Eastwood; Johnson, William T. K.
1993-01-01
The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.
Monitoring of "urban villages" in Shenzhen, China from high-resolution GF-1 and TerraSAR-X data
NASA Astrophysics Data System (ADS)
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.
Exploitation of Digital Surface Models Generated from WORLDVIEW-2 Data for SAR Simulation Techniques
NASA Astrophysics Data System (ADS)
Ilehag, R.; Auer, S.; d'Angelo, P.
2017-05-01
GeoRaySAR, an automated SAR simulator developed at DLR, identifies buildings in high resolution SAR data by utilizing geometric knowledge extracted from digital surface models (DSMs). Hitherto, the simulator has utilized DSMs generated from LiDAR data from airborne sensors with pre-filtered vegetation. Discarding the need for pre-optimized model input, DSMs generated from high resolution optical data (acquired with WorldView-2) are used for the extraction of building-related SAR image parts in this work. An automatic preprocessing of the DSMs has been developed for separating buildings from elevated vegetation (trees, bushes) and reducing the noise level. Based on that, automated simulations are triggered considering the properties of real SAR images. Locations in three cities, Munich, London and Istanbul, were chosen as study areas to determine advantages and limitations related to WorldView-2 DSMs as input for GeoRaySAR. Beyond, the impact of the quality of the DSM in terms of building extraction is evaluated as well as evaluation of building DSM, a DSM only containing buildings. The results indicate that building extents can be detected with DSMs from optical satellite data with various success, dependent on the quality of the DSM as well as on the SAR imaging perspective.
NASA Astrophysics Data System (ADS)
Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.
2018-02-01
This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.
Xiong, P; Zeng, X; Song, M S; Jia, S W; Zhong, M H; Xiao, L L; Lan, W; Cai, C; Wu, X W; Gong, F L; Wang, W
2008-02-01
Severe acute respiratory syndrome (SARS), caused by infection with a novel coronavirus (SARS-CoV), was the first major novel infectious disease at the beginning of the 21st century, with China especially affected. SARS was characterized by high infectivity, morbidity and mortality, and the confined pattern of the disease spreading among the countries of South-East and East Asia suggested the existence of susceptible factor(s) in these populations. Studies in the populations of Hong Kong and Taiwan showed an association of human leucocyte antigen (HLA) polymorphisms with the development and/or severity of SARS, respectively. The aim of the present study was to define the genotypic patterns of HLA-A, -B and -DRB1 loci in SARS patients and a co-resident population of Guangdong province, southern China, where the first SARS case was reported. The samples comprised 95 cases of recovered SARS patients and 403 unrelated healthy controls. HLA -A, -B and -DRB1 alleles were genotyped using polymerase chain reaction with sequence-specific primers. The severity of the disease was assessed according to the history of lung infiltration, usage of assisted ventilation and occurrence of lymphocytopenia. Although the allelic frequencies of A23, A34, B60, DRB1*12 in the SARS group were slightly higher, and A33, -B58 and -B61 were lower than in the controls, no statistical significance was found when the Pc value was considered. Similarly, no association of HLA alleles with the severity of the disease was detected. Thus, variations in the major histocompatibility complex are unlikely to have contributed significantly to either the susceptibility or the severity of SARS in the population of Guangdong.
NASA Technical Reports Server (NTRS)
Fielding, Eric J.; Wright, Tim J.; Muller, Jordan; Parsons, Barry E.; Walker, Richard
2004-01-01
At depth, many fold-and-thrust belts are composed of a gently dipping, basal thrust fault and steeply dipping, shallower splay faults that terminate beneath folds at the surface. Movement on these buried faults is difficult to observe, but synthetic aperture radar (SAR) interferometry has imaged slip on at least 600 square kilometers of the Shahdad basal-thrust and splay-fault network in southeast Iran.
23. OVERVIEW OF SAR3 AREA, SHOWING CORNER OF SAR3 WITH ...
23. OVERVIEW OF SAR-3 AREA, SHOWING CORNER OF SAR-3 WITH TAILRACE, ADMINISTRATIVE OFFICE, TOILET SHED, AND RETAINING WALLS AT FORMER EMPLOYEE HOUSING SITE. VIEW TO SOUTHEAST. PANORAMA 1/2. - Santa Ana River Hydroelectric System, Redlands, San Bernardino County, CA
Automatic SAR/optical cross-matching for GCP monograph generation
NASA Astrophysics Data System (ADS)
Nutricato, Raffaele; Morea, Alberto; Nitti, Davide Oscar; La Mantia, Claudio; Agrimano, Luigi; Samarelli, Sergio; Chiaradia, Maria Teresa
2016-10-01
Ground Control Points (GCP), automatically extracted from Synthetic Aperture Radar (SAR) images through 3D stereo analysis, can be effectively exploited for an automatic orthorectification of optical imagery if they can be robustly located in the basic optical images. The present study outlines a SAR/Optical cross-matching procedure that allows a robust alignment of radar and optical images, and consequently to derive automatically the corresponding sub-pixel position of the GCPs in the optical image in input, expressed as fractional pixel/line image coordinates. The cross-matching in performed in two subsequent steps, in order to gradually gather a better precision. The first step is based on the Mutual Information (MI) maximization between optical and SAR chips while the last one uses the Normalized Cross-Correlation as similarity metric. This work outlines the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight stereo images with different beams and passes are available. The experimental analysis involves different satellite images, in order to evaluate the performances of the algorithm w.r.t. the optical spatial resolution. An assessment of the performances of the algorithm has been carried out, and errors are computed by measuring the distance between the GCP pixel/line position in the optical image, automatically estimated by the tool, and the "true" position of the GCP, visually identified by an expert user in the optical images.
The Performance Analysis Based on SAR Sample Covariance Matrix
Erten, Esra
2012-01-01
Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given. PMID:22736976
1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model
NASA Astrophysics Data System (ADS)
Phan, X. V.; Ferro-Famil, L.; Gay, M.; Durand, Y.; Dumont, M.; Morin, S.; Allain, S.; D'Urso, G.; Girard, A.
2014-10-01
The structure and physical properties of a snowpack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential divergences and accumulated errors, to a limited spatial resolution, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and improve its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parameters, like its depth, snow grain size and density. SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re
UAVSAR and TerraSAR-X Based InSAR Detection of Localized Subsidence in the New Orleans Area
NASA Astrophysics Data System (ADS)
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
SU-F-I-27: Measurement of SAR and Temperature Elevation During MRI Scans
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seo, Y
Purpose: The poor reliability and repeatability of the manufacturer-reported SAR values on clinical MRI systems have been acknowledged. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation at 1.5 and 3T MRI systems. Methods: SAR measurement experiment was performed at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T1w inversion recovery, and T2w TSE) with imaging parameters were selected. A hydroxyl-ethylcelluose (HEC) gelled saline phantom mimicking human body tissue was made. Human torso phantom were constructed, based on Korean adult standard anthropometric reference data (Fig.1). FDTD method was utilized to calculatemore » the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located inside the phantom. 55 Fiber Bragg Grating (FBG) temperature sensors (27 sensors in upper and lower cover lids, and one sensor located in the center as a reference) were located inside the phantom to measure temperature change during MRI scan (Fig.2). Results: Simulation shows that SAR value is 0.4 W/kg in the periphery and 0.001 W/kg in the center (Fig.2). One 1.5T and one of two 3T MRI systems represent that the measured SAR values were lower than MRI scanner-reported SAR values. However, the other 3T MRI scanner shows that the averaged SAR values measured by probe 2, 3, and 4 are 6.83, 7.59, and 6.01 W/kg, compared to MRI scanner-reported whole body SAR value (<1.5 W/kg) for T2w TSE (Table 1). The temperature elevation measured by FBG sensors is 5.2°C in the lateral shoulder, 5.1°C in the underarm, 4.7°C in the anterior axilla, 4.8°C in the posterior axilla, and 4.8°C in the lateral waist for T2w TSE (Fig.3). Conclusion: It is essential to assess the safety of MRI system for patient by measuring accurate SAR deposited in the body during clinical MRI.« less
Modified Polar-Format Software for Processing SAR Data
NASA Technical Reports Server (NTRS)
Chen, Curtis
2003-01-01
HMPF is a computer program that implements a modified polar-format algorithm for processing data from spaceborne synthetic-aperture radar (SAR) systems. Unlike prior polar-format processing algorithms, this algorithm is based on the assumption that the radar signal wavefronts are spherical rather than planar. The algorithm provides for resampling of SAR pulse data from slant range to radial distance from the center of a reference sphere that is nominally the local Earth surface. Then, invoking the projection-slice theorem, the resampled pulse data are Fourier-transformed over radial distance, arranged in the wavenumber domain according to the acquisition geometry, resampled to a Cartesian grid, and inverse-Fourier-transformed. The result of this process is the focused SAR image. HMPF, and perhaps other programs that implement variants of the algorithm, may give better accuracy than do prior algorithms for processing strip-map SAR data from high altitudes and may give better phase preservation relative to prior polar-format algorithms for processing spotlight-mode SAR data.
Numerical Analysis of Orbital Perturbation Effects on Inclined Geosynchronous SAR
Dong, Xichao; Hu, Cheng; Long, Teng; Li, Yuanhao
2016-01-01
The geosynchronous synthetic aperture radar (GEO SAR) is susceptible to orbit perturbations, leading to orbit drifts and variations. The influences behave very differently from those in low Earth orbit (LEO) SAR. In this paper, the impacts of perturbations on GEO SAR orbital elements are modelled based on the perturbed dynamic equations, and then, the focusing is analyzed theoretically and numerically by using the Systems Tool Kit (STK) software. The accurate GEO SAR slant range histories can be calculated according to the perturbed orbit positions in STK. The perturbed slant range errors are mainly the first and second derivatives, leading to image drifts and defocusing. Simulations of the point target imaging are performed to validate the aforementioned analysis. In the GEO SAR with an inclination of 53° and an argument of perigee of 90°, the Doppler parameters and the integration time are different and dependent on the geometry configurations. Thus, the influences are varying at different orbit positions: at the equator, the first-order phase errors should be mainly considered; at the perigee and apogee, the second-order phase errors should be mainly considered; at other positions, first-order and second-order exist simultaneously. PMID:27598168
Research on Inversion Models for Forest Height Estimation Using Polarimetric SAR Interferometry
NASA Astrophysics Data System (ADS)
Zhang, L.; Duan, B.; Zou, B.
2017-09-01
The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can't estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.
Titan's surface from the Cassini RADAR radiometry data during SAR mode
Paganelli, F.; Janssen, M.A.; Lopes, R.M.; Stofan, E.; Wall, S.D.; Lorenz, R.D.; Lunine, J.I.; Kirk, R.L.; Roth, L.; Elachi, C.
2008-01-01
We present initial results on the calibration and interpretation of the high-resolution radiometry data acquired during the Synthetic Aperture Radar (SAR) mode (SAR-radiometry) of the Cassini Radar Mapper during its first five flybys of Saturn's moon Titan. We construct maps of the brightness temperature at the 2-cm wavelength coincident with SAR swath imaging. A preliminary radiometry calibration shows that brightness temperature in these maps varies from 64 to 89 K. Surface features and physical properties derived from the SAR-radiometry maps and SAR imaging are strongly correlated; in general, we find that surface features with high radar reflectivity are associated with radiometrically cold regions, while surface features with low radar reflectivity correlate with radiometrically warm regions. We examined scatterplots of the normalized radar cross-section ??0 versus brightness temperature, outlining signatures that characterize various terrains and surface features. The results indicate that volume scattering is important in many areas of Titan's surface, particularly Xanadu, while other areas exhibit complex brightness temperature variations consistent with variable slopes or surface material and compositional properties. ?? 2007.
Impulse Response Shaping for Ultra Wide Band SAR in a Circular Flight Path
NASA Technical Reports Server (NTRS)
Jin, Michael Y.
1996-01-01
An ultra wide band SAR (synthetic aperture radar) has potential applications on imaging underground objects. Flying this SAR in a circular flight path is an efficient way to acquire high resolution images from a localized area. This paper characterizes the impulse response of sucha system. The results indicate that to achieve an image with a more uniformed resolution over the entire imaged area, proper weighting coeficients should be applied to both the principle aperture and the complimentary aperture.
NASA Astrophysics Data System (ADS)
Zhang, Siqian; Kuang, Gangyao
2014-10-01
In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.
The use of the DInSAR method in the monitoring of road damage caused by mining activities
NASA Astrophysics Data System (ADS)
Murdzek, Radosław; Malik, Hubert; Leśniak, Andrzej
2018-04-01
This paper reviews existing remote sensing methods of road damage detection and demonstrates the possibility of using DInSAR (Differential Interferometry SAR) method to identify endangered road sections. In this study two radar images collected by Sentinel-1 satellite have been used. Images were acquired with 24 days interval in 2015. The analysis allowed to estimate the scale of the post-mining deformation that occurred in Upper Silesia and to indicate areas where road infrastructure is particularly vulnerable to damage.
Damage extraction of buildings in the 2015 Gorkha, Nepal earthquake from high-resolution SAR data
NASA Astrophysics Data System (ADS)
Yamazaki, Fumio; Bahri, Rendy; Liu, Wen; Sasagawa, Tadashi
2016-05-01
Satellite remote sensing is recognized as one of the effective tools for detecting and monitoring affected areas due to natural disasters. Since SAR sensors can capture images not only at daytime but also at nighttime and under cloud-cover conditions, they are especially useful at an emergency response period. In this study, multi-temporal high-resolution TerraSAR-X images were used for damage inspection of the Kathmandu area, which was severely affected by the April 25, 2015 Gorkha Earthquake. The SAR images obtained before and after the earthquake were utilized for calculating the difference and correlation coefficient of backscatter. The affected areas were identified by high values of the absolute difference and low values of the correlation coefficient. The post-event high-resolution optical satellite images were employed as ground truth data to verify our results. Although it was difficult to estimate the damage levels for individual buildings, the high resolution SAR images could illustrate their capability in detecting collapsed buildings at emergency response times.
A Cloud-Based System for Automatic Hazard Monitoring from Sentinel-1 SAR Data
NASA Astrophysics Data System (ADS)
Meyer, F. J.; Arko, S. A.; Hogenson, K.; McAlpin, D. B.; Whitley, M. A.
2017-12-01
Despite the all-weather capabilities of Synthetic Aperture Radar (SAR), and its high performance in change detection, the application of SAR for operational hazard monitoring was limited in the past. This has largely been due to high data costs, slow product delivery, and limited temporal sampling associated with legacy SAR systems. Only since the launch of ESA's Sentinel-1 sensors have routinely acquired and free-of-charge SAR data become available, allowing—for the first time—for a meaningful contribution of SAR to disaster monitoring. In this paper, we present recent technical advances of the Sentinel-1-based SAR processing system SARVIEWS, which was originally built to generate hazard products for volcano monitoring centers. We outline the main functionalities of SARVIEWS including its automatic database interface to Sentinel-1 holdings of the Alaska Satellite Facility (ASF), and its set of automatic processing techniques. Subsequently, we present recent system improvements that were added to SARVIEWS and allowed for a vast expansion of its hazard services; specifically: (1) In early 2017, the SARVIEWS system was migrated into the Amazon Cloud, providing access to cloud capabilities such as elastic scaling of compute resources and cloud-based storage; (2) we co-located SARVIEWS with ASF's cloud-based Sentinel-1 archive, enabling the efficient and cost effective processing of large data volumes; (3) we integrated SARVIEWS with ASF's HyP3 system (http://hyp3.asf.alaska.edu/), providing functionality such as subscription creation via API or map interface as well as automatic email notification; (4) we automated the production chains for seismic and volcanic hazards by integrating SARVIEWS with the USGS earthquake notification service (ENS) and the USGS eruption alert system. Email notifications from both services are parsed and subscriptions are automatically created when certain event criteria are met; (5) finally, SARVIEWS-generated hazard products are now
SAR-based sea traffic monitoring: a reliable approach for maritime surveillance
NASA Astrophysics Data System (ADS)
Renga, Alfredo; Graziano, Maria D.; D'Errico, M.; Moccia, A.; Cecchini, A.
2011-11-01
Maritime surveillance problems are drawing the attention of multiple institutional actors. National and international security agencies are interested in matters like maritime traffic security, maritime pollution control, monitoring migration flows and detection of illegal fishing activities. Satellite imaging is a good way to identify ships but, characterized by large swaths, it is likely that the imaged scenes contain a large number of ships, with the vast majority, hopefully, performing legal activities. Therefore, the imaging system needs a supporting system which identifies legal ships and limits the number of potential alarms to be further monitored by patrol boats or aircrafts. In this framework, spaceborne Synthetic Aperture Radar (SAR) sensors, terrestrial AIS and the ongoing satellite AIS systems can represent a great potential synergy for maritime security. Starting from this idea the paper develops different designs for an AIS constellation able to reduce the time lag between SAR image and AIS data acquisition. An analysis of SAR-based ship detection algorithms is also reported and candidate algorithms identified.
Transnational quarantine rhetorics: public mobilization in SARS and in H1N1 flu.
Ding, Huiling
2014-06-01
This essay examines how Chinese governments, local communities, and overseas Chinese in North America responded to the perceived health risks of Severe Acute Respiratory Syndrome (SARS) and H1N1 flu through the use of public and participatory rhetoric about risk and quarantines. Focusing on modes of security and quarantine practices, I examine how globalization and the social crises surrounding SARS and H1N1 flu operated to regulate differently certain bodies and areas. I identify three types of quarantines (mandatory, voluntary, and coerced) and conduct a transnational comparative analysis to investigate the relationships among quarantines, rhetoric, and public communication. I argue that health authorities must openly acknowledge the legitimacy of public input and actively seek public support regarding health crises. Only by collaborating with concerned communities and citizens and by providing careful guidance for public participation can health institutions ensure the efficacy of quarantine orders during emerging epidemics.
Information extraction and transmission techniques for spaceborne synthetic aperture radar images
NASA Technical Reports Server (NTRS)
Frost, V. S.; Yurovsky, L.; Watson, E.; Townsend, K.; Gardner, S.; Boberg, D.; Watson, J.; Minden, G. J.; Shanmugan, K. S.
1984-01-01
Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.
Schaber, G.G.
1999-01-01
Synthetic Aperture Radar (SAR) images acquired over part of the Yuma Desert in southwestern Arizona demonstrate the ability of C-band (5.7-cm wavelength), L-band (24.5 cm), and P-band (68 cm) AIRSAR signals to backscatter from increasingly greater depths reaching several meters in blow sand and sandy alluvium. AIRSAR images obtained within the Barry M. Goldwater Bombing and Gunnery Range near Yuma, Arizona, show a total reversal of C- and P-band backscatter contrast (image tone) for three distinct geologic units. This phenomenon results from an increasingly greater depth of radar imaging with increasing radar wavelength. In the case of sandy- and small pebble-alluvium surfaces mantled by up to several meters of blow sand, backscatter increases directly with SAR wavelength as a result of volume scattering from a calcic soil horizon at shallow depth and by volume scattering from the root mounds of healthy desert vegetation that locally stabilize blow sand. AIRSAR images obtained within the military range are also shown to be useful for detecting metallic military ordnance debris that is located either at the surface or covered by tens of centimeters to several meters of blow sand. The degree of detectability of this ordnance increases with SAR wavelength and is clearly maximized on P-band images that are processed in the cross-polarized mode (HV). This effect is attributed to maximum signal penetration at P-band and the enhanced PHV image contrast between the radar-bright ordnance debris and the radar-dark sandy desert. This article focuses on the interpretation of high resolution AIRSAR images but also Compares these airborne SAR images with those acquired from spacecraft sensors such as ERS-SAR and Space Radar Laboratory (SIR-C/X-SAR).Synthetic Aperture Radar (SAR) images acquired over part of the Yuma Desert in southwestern Arizona demonstrate the ability of C-band (5.7-cm wavelength), L-band (24.5 cm), and P-band (68 cm) AIRSAR signals to backscatter from
NASA Astrophysics Data System (ADS)
Mleczko, M.
2014-12-01
Polarimetric SAR data is not widely used in practice, because it is not yet available operationally from the satellites. Currently we can distinguish two approaches in POL - In - SAR technology: alternating polarization imaging (Alt - POL) and fully polarimetric (QuadPol). The first represents a subset of another and is more operational, while the second is experimental because classification of this data requires polarimetric decomposition of scattering matrix in the first stage. In the literature decomposition process is divided in two types: the coherent and incoherent decomposition. In this paper the decomposition methods have been tested using data from the high resolution airborne F - SAR system. Results of classification have been interpreted in the context of the land cover mapping capabilities
NASA Technical Reports Server (NTRS)
Curlander, John C.; Kwok, Ronald; Pang, Shirley S.; Pang, Amy A.
1990-01-01
Spaceborne synthetic-aperture-radar (SAR) images useful for mapping of planets and investigations in Earth sciences. Produces multiframe mosaic by combining images along ground track, in adjacent cross-track swaths, or in ascending and descending passes. Images registered with geocoded maps such as ones produced by MAPJTC (NPO-17718), required as input. Minimal intervention by operator required. MOSK implemented on DEC VAX 11/785 computer running VMS 4.5. Most subroutines in FORTRAN, but three in MAXL and one in APAL.
Lim, Byoung-Gyun; Woo, Jea-Choon; Lee, Hee-Young; Kim, Young-Soo
2008-01-01
Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is used to acquire the SAR images for synthetic wideband signals, errors occur due to approximations, so the images may not show the best possible result. This paper proposes a modified subpulse SAR processing algorithm for synthetic wideband signals which is based on RDA. An experiment with an automobile-based SAR system showed that the proposed algorithm is quite accurate with a considerable improvement in resolution and quality of the obtained SAR image. PMID:27873984
Ship Speed Retrieval From Single Channel TerraSAR-X Data
NASA Astrophysics Data System (ADS)
Soccorsi, Matteo; Lehner, Susanne
2010-04-01
A method to estimate the speed of a moving ship is presented. The technique, introduced in Kirscht (1998), is extended to marine application and validated on TerraSAR-X High-Resolution (HR) data. The generation of a sequence of single-look SAR images from a single- channel image corresponds to an image time series with reduced resolution. This allows applying change detection techniques on the time series to evaluate the velocity components in range and azimuth of the ship. The evaluation of the displacement vector of a moving target in consecutive images of the sequence allows the estimation of the azimuth velocity component. The range velocity component is estimated by evaluating the variation of the signal amplitude during the sequence. In order to apply the technique on TerraSAR-X Spot Light (SL) data a further processing step is needed. The phase has to be corrected as presented in Eineder et al. (2009) due to the SL acquisition mode; otherwise the image sequence cannot be generated. The analysis, when possible validated by the Automatic Identification System (AIS), was performed in the framework of the ESA project MARISS.
NASA Astrophysics Data System (ADS)
Liu, Z.; Lundgren, P.; Liang, C.; Farr, T. G.; Fielding, E. J.
2017-12-01
The improved spatiotemporal resolution of surface deformation from recent satellite and airborne InSAR measurements provides a great opportunity to improve our understanding of both tectonic and non-tectonic processes. In central California the primary plate boundary fault system (San Andreas fault) lies adjacent to the San Joaquin Valley (SJV), a vast structural trough that accounts for about one-sixth of the United Sates' irrigated land and one-fifth of its extracted groundwater. The central San Andreas fault (CSAF) displays a range of fault slip behavior with creeping in its central segment that decreases towards its northwest and southeast ends, where it transitions to being fully locked. Despite much progress, many questions regarding fault and anthropogenic processes in the region still remain. In this study, we combine satellite InSAR and NASA airborne UAVSAR data to image fault and anthropogenic deformation. The UAVSAR data cover fault perpendicular swaths imaged from opposing look directions and fault parallel swaths since 2009. The much finer spatial resolution and optimized viewing geometry provide important constraints on near fault deformation and fault slip at very shallow depth. We performed a synoptic InSAR time series analysis using Sentinel-1, ALOS, and UAVSAR interferograms. We estimate azimuth mis-registration between single look complex (SLC) images of Sentinel-1 in a stack sense to achieve accurate azimuth co-registration between SLC images for low coherence and/or long interval interferometric pairs. We show that it is important to correct large-scale ionosphere features in ALOS-2 ScanSAR data for accurate deformation measurements. Joint analysis of UAVSAR and ALOS interferometry measurements show clear variability in deformation along the fault strike, suggesting variable fault creep and locking at depth and along strike. In addition to fault creep, the L-band ALOS, and especially ALOS-2 ScanSAR interferometry, show large-scale ground
Li, Shih-Wein; Wang, Ching-Ying; Jou, Yu-Jen; Yang, Tsuey-Ching; Huang, Su-Hua; Wan, Lei; Lin, Ying-Ju; Lin, Cheng-Wen
2016-05-13
SARS coronavirus (SARS-CoV) papain-like protease (PLpro) has been identified in TGF-β1 up-regulation in human promonocytes (Proteomics 2012, 12: 3193-205). This study investigates the mechanisms of SARS-CoV PLpro-induced TGF-β1 promoter activation in human lung epithelial cells and mouse models. SARS-CoV PLpro dose- and time-dependently up-regulates TGF-β1 and vimentin in A549 cells. Dual luciferase reporter assays with TGF-β1 promoter plasmids indicated that TGF-β1 promoter region between -175 to -60, the Egr-1 binding site, was responsible for TGF-β1 promoter activation induced by SARS-CoV PLpro. Subcellular localization analysis of transcription factors showed PLpro triggering nuclear translocation of Egr-1, but not NF-κB and Sp-1. Meanwhile, Egr-1 silencing by siRNA significantly reduced PLpro-induced up-regulation of TGF-β1, TSP-1 and pro-fibrotic genes. Furthermore, the inhibitors for ROS (YCG063), p38 MAPK (SB203580), and STAT3 (Stattic) revealed ROS/p38 MAPK/STAT3 pathway involving in Egr-1 dependent activation of TGF-β1 promoter induced by PLpro. In a mouse model with a direct pulmonary injection, PLpro stimulated macrophage infiltration into lung, up-regulating Egr-1, TSP-1, TGF-β1 and vimentin expression in lung tissues. The results revealed that SARS-CoV PLpro significantly triggered Egr-1 dependent activation of TGF-β1 promoter via ROS/p38 MAPK/STAT3 pathway, correlating with up-regulation of pro-fibrotic responses in vitro and in vivo.
NASA Astrophysics Data System (ADS)
Logan, T. A.; Arko, S. A.; Rosen, P. A.
2013-12-01
To demonstrate the feasibility of orbital remote sensing for global ocean observations, NASA launched Seasat on June 27th, 1978. Being the first space borne SAR mission, Seasat produced the most detailed SAR images of Earth from space ever seen to that point in time. While much of the data collected in the USA was processed optically, a mere 150 scenes had been digitally processed by March 1980. In fact, only an estimated 3% of Seasat data was ever digitally processed. Thus, for over three decades, the majority of the SAR data from this historic mission has been dormant, virtually unavailable to scientists in the 21st century. Over the last year, researchers at the Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) have processed the Seasat SAR archives into imagery products. A telemetry decoding system was created and the data were filtered into readily processable signal files. Due to nearly 35 years of bit rot, the bit error rate (BER) for the ASF DAAC Seasat archives was on the order of 1 out of 100 to 1 out of 100,000. This extremely high BER initially seemed to make much of the data undecodable - because the minor frame numbers are just 7 bits and no range line numbers exist in the telemetry even the 'simple' tasks of tracking the minor frame number or locating the start of each range line proved difficult. Eventually, using 5 frame numbers in sequence and a handful of heuristics, the data were successfully decoded into full range lines. Concurrently, all metadata were stored into external files. Recovery of this metadata was also problematic, the BER making the information highly suspect and, initially at least, unusable in any sort of automated fashion. Because of the BER, all of the single bit metadata fields proved unreliable. Even fields that should be constant for a data take (e.g. receiving station, day of the year) showed high variability, each requiring a median filter to be usable. The most challenging, however, were the
Marine Targets Classification in PolInSAR Data
NASA Astrophysics Data System (ADS)
Chen, Peng; Yang, Jingsong; Ren, Lin
2014-11-01
In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.
Marine Targets Classification in PolInSAR Data
NASA Astrophysics Data System (ADS)
Chen, Peng; Yang, Jingsong; Ren, Lin
2014-11-01
In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then , A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.
Classification of the Gabon SAR Mosaic Using a Wavelet Based Rule Classifier
NASA Technical Reports Server (NTRS)
Simard, Marc; Saatchi, Sasan; DeGrandi, Gianfranco
2000-01-01
A method is developed for semi-automated classification of SAR images of the tropical forest. Information is extracted using the wavelet transform (WT). The transform allows for extraction of structural information in the image as a function of scale. In order to classify the SAR image, a Desicion Tree Classifier is used. The method of pruning is used to optimize classification rate versus tree size. The results give explicit insight on the type of information useful for a given class.
Tian, Lihong; Dai, Ling Ling; Yin, Zhi Jie; Fukuda, Masako; Kumamaru, Toshihiro; Dong, Xiang Bai; Xu, Xiu Ping; Qu, Le Qing
2013-07-01
Rice seed storage proteins glutelin and α-globulin are synthesized in the endoplasmic reticulum (ER) and deposited in protein storage vacuoles (PSVs). Sar1, a small GTPase, acts as a molecular switch to regulate the assembly of coat protein complex II, which exports secretory protein from the ER to the Golgi apparatus. To reveal the route by which glutelin and α-globulin exit the ER, four putative Sar1 genes (OsSar1a/b/c/d) were cloned from rice, and transgenic rice were generated with Sar1 overexpressed or suppressed by RNA interference (RNAi) specifically in the endosperm under the control of the rice glutelin promoter. Overexpression or suppression of any OsSar1 did not alter the phenotype. However, simultaneous knockdown of OsSar1a/b/c resulted in floury and shrunken seeds, with an increased level of glutelin precursor and decreased level of the mature α- and β-subunit. OsSar1abc RNAi endosperm generated numerous, spherical, novel protein bodies with highly electron-dense matrixes containing both glutelin and α-globulin. Notably, the novel protein bodies were surrounded by ribosomes, showing that they were derived from the ER. Some of the ER-derived dense protein bodies were attached to a blebbing structure containing prolamin. These results indicated that OsSar1a/b/c play a crucial role in storage proteins exiting from the ER, with functional redundancy in rice endosperm, and glutelin and α-globulin transported together from the ER to the Golgi apparatus by a pathway mediated by coat protein complex II.
Detection of moving humans in UHF wideband SAR
NASA Astrophysics Data System (ADS)
Sjögren, Thomas K.; Ulander, Lars M. H.; Frölind, Per-Olov; Gustavsson, Anders; Stenström, Gunnar; Jonsson, Tommy
2014-06-01
In this paper, experimental results for UHF wideband SAR imaging of humans on an open field and inside a forest is presented. The results show ability to detect the humans and suggest possible ways to improve the results. In the experiment, single channel wideband SAR mode of the UHF UWB system LORA developed by Swedish Defence Research Agency (FOI). The wideband SAR mode used in the experiment was from 220 to 450 MHz, thus with a fractional bandwidth of 0.68. Three humans walking and one stationary were available in the scene with one of the walking humans in the forest. The signature of the human in the forest appeared on the field, due to azimuth shift from the positive range speed component. One human on the field and the one in the forest had approximately the same speed and walking direction. The signatures in the SAR image were compared as a function of integration time based on focusing using the average relative speed of these given by GPS logs. A signal processing gain was obtained for the human in forest until approximately 15 s and 35 s for the human on the field. This difference is likely explained by uneven terrain and trees in the way, causing a non-straight walking path.
Analysis of wind and wave events at the MIZ based on TerraSAR-X satellite images
NASA Astrophysics Data System (ADS)
Gebhardt, Claus; Bidlot, Jean-Raymond; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey; Singha, Suman
2017-04-01
The seasonal opening-up of large expanses of open water in the Beaufort/Chukchi Sea is a phenomenon observed in recent years. The diameter of the open-water area is on the order of 1000 km around the sea ice minimum in summer. Thus, wind events in the area are accompanied by the build-up of sea waves. Significant wave heights of few to several meters may be reached. Under low to moderate winds, the morphology of the MIZ is governed by oceanic forcing. As a result, the MIZ resembles ocean circulation features such as eddies, meanders, etc.. In the case of strong wind events, however, the wind forcing may gain control. We analyse effects related to wind and wave events at the MIZ using TerraSAR-X satellite imagery. Methods such as the retrieval of sea state and wind data by empirical algorithms and automatic sea ice classification are applied. This is facilitated by a series of TerraSAR-X images acquired in support of a cruise of the research vessel R/V Sikuliaq in the Beaufort/Chukchi Sea in autumn 2015. For selected images, the results are presented and compared to numerical model forecasts which were as well part of the cruise support.
Statistical Approach To Extraction Of Texture In SAR
NASA Technical Reports Server (NTRS)
Rignot, Eric J.; Kwok, Ronald
1992-01-01
Improved statistical method of extraction of textural features in synthetic-aperture-radar (SAR) images takes account of effects of scheme used to sample raw SAR data, system noise, resolution of radar equipment, and speckle. Treatment of speckle incorporated into overall statistical treatment of speckle, system noise, and natural variations in texture. One computes speckle auto-correlation function from system transfer function that expresses effect of radar aperature and incorporates range and azimuth resolutions.
Satellite SAR data assessment for Silk Road archaeological prospection
NASA Astrophysics Data System (ADS)
Chen, Fulong; Lasaponara, Rosa; Masini, Nicola; Yang, Ruixia
2015-04-01
The development of Synthetic Aperture Radar (SAR) in terms of multi-band, multi-polarization and high-resolution data, favored the application of this technology also in archaeology [1]. Different approaches based on both single and multitemporal data analysis, exploiting the backscattering and the penetration of radar data, have been used for a number of archaeological sites and landscapes [2-5]. Nevertheless, the capability of this technology in archaeological applications has so far not been fully assessed. It lacks a contribution aimed at evaluating the potential of SAR technology for the same study area by using different bands, spatial resolutions and data processing solutions. In the framework of the Chinese-Italian bilateral project "Smart management of cultural heritage sites in Italy and China: Earth Observation and pilot projects", we addressed some pioneering investigations to assess multi-mode (multi-band, temporal, resolution) satellite SAR data (including X-band TerraSAR, C-band Envisat and L-band ALOS PALSAR) in archaeological prospection of the Silk road [6]. The Silk Road, a series of trade and cultural transmission routes connecting China to Europe, is the witness of civilization and friendship between the East and West dated back to 2000 years ago, that left us various relics (e.g. lost cities) to be uncovered and investigated.. In particular, the assessment has been performed in the Xinjiang and Gansu section pf the Silk Road focusing on : i) the subsurface penetration capability of SAR data in the arid and semi-arid region ii) and sensitivity of SAR imaging geometry for the detection of relics As regards the point i) , apart from the soil moisture, the penetration is seriously restricted by the soil porosity. For instance, negligible penetration signs were detected in Yumen Frontier Pass either using X- or L-band SAR data due to the occurrence of Yardang landscape. As regards the point ii), the flight path of SAR images in parallel with the
Li, Shih-Wein; Wang, Ching-Ying; Jou, Yu-Jen; Yang, Tsuey-Ching; Huang, Su-Hua; Wan, Lei; Lin, Ying-Ju; Lin, Cheng-Wen
2016-01-01
SARS coronavirus (SARS-CoV) papain-like protease (PLpro) has been identified in TGF-β1 up-regulation in human promonocytes (Proteomics 2012, 12: 3193-205). This study investigates the mechanisms of SARS-CoV PLpro-induced TGF-β1 promoter activation in human lung epithelial cells and mouse models. SARS-CoV PLpro dose- and time-dependently up-regulates TGF-β1 and vimentin in A549 cells. Dual luciferase reporter assays with TGF-β1 promoter plasmids indicated that TGF-β1 promoter region between −175 to −60, the Egr-1 binding site, was responsible for TGF-β1 promoter activation induced by SARS-CoV PLpro. Subcellular localization analysis of transcription factors showed PLpro triggering nuclear translocation of Egr-1, but not NF-κB and Sp-1. Meanwhile, Egr-1 silencing by siRNA significantly reduced PLpro-induced up-regulation of TGF-β1, TSP-1 and pro-fibrotic genes. Furthermore, the inhibitors for ROS (YCG063), p38 MAPK (SB203580), and STAT3 (Stattic) revealed ROS/p38 MAPK/STAT3 pathway involving in Egr-1 dependent activation of TGF-β1 promoter induced by PLpro. In a mouse model with a direct pulmonary injection, PLpro stimulated macrophage infiltration into lung, up-regulating Egr-1, TSP-1, TGF-β1 and vimentin expression in lung tissues. The results revealed that SARS-CoV PLpro significantly triggered Egr-1 dependent activation of TGF-β1 promoter via ROS/p38 MAPK/STAT3 pathway, correlating with up-regulation of pro-fibrotic responses in vitro and in vivo. PMID:27173006
NASA Astrophysics Data System (ADS)
Muckenhuber, Stefan; Sandven, Stein
2017-04-01
An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature-tracking and pattern-matching. A computational efficient feature-tracking algorithm produces an initial drift estimate and limits the search area for the pattern-matching, that provides small to medium scale drift adjustments and normalised cross correlation values as quality measure. The algorithm is designed to utilise the respective advantages of the two approaches and allows drift calculation at user defined locations. The pre-processing of the Sentinel-1 data has been optimised to retrieve a feature distribution that depends less on SAR backscatter peak values. A recommended parameter set for the algorithm has been found using a representative image pair over Fram Strait and 350 manually derived drift vectors as validation. Applying the algorithm with this parameter setting, sea ice drift retrieval with a vector spacing of 8 km on Sentinel-1 images covering 400 km x 400 km, takes less than 3.5 minutes on a standard 2.7 GHz processor with 8 GB memory. For validation, buoy GPS data, collected in 2015 between 15th January and 22nd April and covering an area from 81° N to 83.5° N and 12° E to 27° E, have been compared to calculated drift results from 261 corresponding Sentinel-1 image pairs. We found a logarithmic distribution of the error with a peak at 300 m. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.
Exploring cloud and big data components for SAR archiving and analysis
NASA Astrophysics Data System (ADS)
Baker, S.; Crosby, C. J.; Meertens, C.; Phillips, D.
2017-12-01
Under the Geodesy Advancing Geoscience and EarthScope (GAGE) NSF Cooperative Agreement, UNAVCO has seen the volume of the SAR Data Archive grow at a substantial rate, from 2 TB in Y1 and 5 TB in Y2 to 41 TB in Y3 primarily due to WInSAR PI proposal management of ALOS-2/JAXA (Japan Aerospace Exploration Agency) data and to a lesser extent Supersites and other data collections. JAXA provides a fixed number of scenes per year for each PI, and some data files are 50-60GB each, which accounts for the large volume of data. In total, over 100TB of SAR data are in the WInSAR/UNAVCO archive and a large portion of these are available unrestricted for WInSAR members. In addition to the existing data, newer data streams from the Sentinel-1 and NISAR missions will require efficient processing pipelines and easily scalable infrastructure to handle processed results. With these growing data sizes and space concerns, the SAR archive operations migrated to the Texas Advanced Computing Center (TACC) via an NSF XSEDE proposal in spring 2017. Data are stored on an HPC system while data operations are running on Jetstream virtual machines within the same datacenter. In addition to the production data operations, testing was done in early 2017 with container based InSAR processing analysis using JupyterHub and Docker images deployed on a VM cluster on Jetstream. The JupyterHub environment is well suited for short courses and other training opportunities for the community such as labs for university courses on InSAR. UNAVCO is also exploring new processing methodologies using DC/OS (the datacenter operating system) for batch and stream processing workflows and time series analysis with Big Data open source components like the Spark, Mesos, Akka, Cassandra, Kafka (SMACK) stack. The comparison of the different methodologies will provide insight into the pros and cons for each and help the SAR community with decisions about infrastructure and software requirements to meet their research
NASA Astrophysics Data System (ADS)
Li, C.; Zhou, X.; Tang, D.; Zhu, Z.
2018-04-01
Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.
Lucía Rodríguez, Romero; Pacheco, Leticia; Zavala Hurtado, José Alejandro
2008-06-01
Pteridophytes that indicate environmental alteration in the San Jer6nimo Amanalco temperate forest, Texcoco, Mexico. The patterns of distribution of 26 pteridophyte species were studied as possible indicators of environmental alteration in the temperate forest of San Jer6nimo Amanalco, Texcoco, State of Mexico. The presence and abundance of the pteridoflora was studied in relation to edaphic, topographic and vegetation variables in 100 sampling locations within an area of 494 hectares. The relationship between these variables was studied using Canonical Correspondence Analysis. Five landscapes were recognized in the study zone according to the degree of deterioration: severe erosion, erosion, mountain with moderate reversible deterioration, mountain with no evident deterioration, and canyon with no evident deterioration. Cheilanthes bonariensis and Pellaea ternifolia are indicators of environmental degradation. The taxa that only grow in landscapes without apparent alteration are Adiantum andicola, Adiantum poiretii, Argyrochosma incana, Asplenium blepharophorum, Dryopteris pseudo filix-mas, Equisetum hyemale and Pteris cretica.
Characterization and Mitigation of Radio Frequency Interference in PolSAR Data
NASA Astrophysics Data System (ADS)
Tao, Mingliang; Zhou, Feng; Zhang, Zijing
2017-11-01
Polarimetric synthetic aperture radar (PolSAR) is a very important instrument for active remote sensing. However, it is common to find that PolSAR echoes are often contaminated by incoherent electromagnetic interference, which is referred to as radio frequency interference (RFI). The analysis of RFI signatures and its influence on PolSAR data seems to be lacking in existing literatures, especially for PolSAR post products, such as the polarimetric decomposition parameters and clustering result. The goal of this paper is to reveal the link between RFI and polarization, as well as to analyze the impact of interference on PolSAR image and its post products. Qualitative and quantitative analyses of the adverse impact of RFI on the real measured NASA/Jet Propulsion Laboratory (JPL) Uninhabited Aerial Vehicle Synthetic Aperture Radar data set are illustrated from two perspectives, that is, evaluation of imaging quality and interpretation of scattering mechanisms. The point target response and effective number of looks are evaluated for assessing the distortion to focusing quality. Further, we discussed the characteristics of ultra wideband RFI and proposed a mitigation method using nonnegative matrix factorization along azimuth direction. The experimental results indicate the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura
2013-04-01
There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood