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.

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

NASA Astrophysics Data System (ADS)

Liang, J.; Liu, D.

2017-12-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

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.

Interferometric synthetic aperture radar imagery of the Gulf Stream

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

NASA Astrophysics Data System (ADS)

Hammann, Mark Gregory

The fusion of electro-optical (EO) multi-spectral satellite imagery with Synthetic Aperture Radar (SAR) data was explored with the working hypothesis that the addition of multi-band SAR will increase the land-cover (LC) classification accuracy compared to EO alone. Three satellite sources for SAR imagery were used: X-band from TerraSAR-X, C-band from RADARSAT-2, and L-band from PALSAR. Images from the RapidEye satellites were the source of the EO imagery. Imagery from the GeoEye-1 and WorldView-2 satellites aided the selection of ground truth. Three study areas were chosen: Wad Medani, Sudan; Campinas, Brazil; and Fresno- Kings Counties, USA. EO imagery were radiometrically calibrated, atmospherically compensated, orthorectifed, co-registered, and clipped to a common area of interest (AOI). SAR imagery were radiometrically calibrated, and geometrically corrected for terrain and incidence angle by converting to ground range and Sigma Naught (?0). The original SAR HH data were included in the fused image stack after despeckling with a 3x3 Enhanced Lee filter. The variance and Gray-Level-Co-occurrence Matrix (GLCM) texture measures of contrast, entropy, and correlation were derived from the non-despeckled SAR HH bands. Data fusion was done with layer stacking and all data were resampled to a common spatial resolution. The Support Vector Machine (SVM) decision rule was used for the supervised classifications. Similar LC classes were identified and tested for each study area. For Wad Medani, nine classes were tested: low and medium intensity urban, sparse forest, water, barren ground, and four agriculture classes (fallow, bare agricultural ground, green crops, and orchards). For Campinas, Brazil, five generic classes were tested: urban, agriculture, forest, water, and barren ground. For the Fresno-Kings Counties location 11 classes were studied: three generic classes (urban, water, barren land), and eight specific crops. In all cases the addition of SAR to EO resulted in higher overall classification accuracies. In many cases using more than a single SAR band also improved the classification accuracy. There was no single best SAR band for all cases; for specific study areas or LC classes, different SAR bands were better. For Wad Medani, the overall accuracy increased nearly 25% over EO by using all three SAR bands and GLCM texture. For Campinas, the improvement over EO was 4.3%; the large areas of vegetation were classified by EO with good accuracy. At Fresno-Kings Counties, EO+SAR fusion improved the overall classification accuracy by 7%. For times or regions where EO is not available due to extended cloud cover, classification with SAR is often the only option; note that SAR alone typically results in lower classification accuracies than when using EO or EO-SAR fusion. Fusion of EO and SAR was especially important to improve the separability of orchards from other crops, and separating urban areas with buildings from bare soil; those classes are difficult to accurately separate with EO. The outcome of this dissertation contributes to the understanding of the benefits of combining data from EO imagery with different SAR bands and SAR derived texture data to identify different LC classes. In times of increased public and private budget constraints and industry consolidation, this dissertation provides insight as to which band packages could be most useful for increased accuracy in LC classification.

Bistatic synthetic aperture radar

NASA Astrophysics Data System (ADS)

Yates, Gillian

Synthetic aperture radar (SAR) allows all-weather, day and night, surface surveillance and has the ability to detect, classify and geolocate objects at long stand-off ranges. Bistatic SAR, where the transmitter and the receiver are on separate platforms, is seen as a potential means of countering the vulnerability of conventional monostatic SAR to electronic countermeasures, particularly directional jamming, and avoiding physical attack of the imaging platform. As the receiving platform can be totally passive, it does not advertise its position by RF emissions. The transmitter is not susceptible to jamming and can, for example, operate at long stand-off ranges to reduce its vulnerability to physical attack. This thesis examines some of the complications involved in producing high-resolution bistatic SAR imagery. The effect of bistatic operation on resolution is examined from a theoretical viewpoint and analytical expressions for resolution are developed. These expressions are verified by simulation work using a simple 'point by point' processor. This work is extended to look at using modern practical processing engines for bistatic geometries. Adaptations of the polar format algorithm and range migration algorithm are considered. The principal achievement of this work is a fully airborne demonstration of bistatic SAR. The route taken in reaching this is given, along with some results. The bistatic SAR imagery is analysed and compared to the monostatic imagery collected at the same time. Demonstrating high-resolution bistatic SAR imagery using two airborne platforms represents what I believe to be a European first and is likely to be the first time that this has been achieved outside the US (the UK has very little insight into US work on this topic). Bistatic target characteristics are examined through the use of simulations. This also compares bistatic imagery with monostatic and gives further insight into the utility of bistatic SAR.

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

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.

Detection of macroalgae blooms by complex SAR imagery.

PubMed

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

2014-01-15

Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

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.

Extraction of linear features on SAR imagery

NASA Astrophysics Data System (ADS)

Liu, Junyi; Li, Deren; Mei, Xin

2006-10-01

Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

Statistics of multi-look AIRSAR imagery: A comparison of theory with measurements

NASA Technical Reports Server (NTRS)

Lee, J. S.; Hoppel, K. W.; Mango, S. A.

1993-01-01

The intensity and amplitude statistics of SAR images, such as L-Band HH for SEASAT and SIR-B, and C-Band VV for ERS-1 have been extensively investigated for various terrain, ground cover and ocean surfaces. Less well-known are the statistics between multiple channels of polarimetric of interferometric SAR's, especially for the multi-look processed data. In this paper, we investigate the probability density functions (PDF's) of phase differences, the magnitude of complex products and the amplitude ratios, between polarization channels (i.e. HH, HV, and VV) using 1-look and 4-look AIRSAR polarimetric data. Measured histograms are compared with theoretical PDF's which were recently derived based on a complex Gaussian model.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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.

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.

Evaluation of aircraft microwave data for locating zones for well stimulation and enhanced gas recovery. [Arkansas Arkoma Basin

NASA Technical Reports Server (NTRS)

Macdonald, H.; Waite, W.; Elachi, C.; Babcock, R.; Konig, R.; Gattis, J.; Borengasser, M.; Tolman, D.

1980-01-01

Imaging radar was evaluated as an adjunct to conventional petroleum exploration techniques, especially linear mapping. Linear features were mapped from several remote sensor data sources including stereo photography, enhanced LANDSAT imagery, SLAR radar imagery, enhanced SAR radar imagery, and SAR radar/LANDSAT combinations. Linear feature maps were compared with surface joint data, subsurface and geophysical data, and gas production in the Arkansas part of the Arkoma basin. The best LANDSAT enhanced product for linear detection was found to be a winter scene, band 7, uniform distribution stretch. Of the individual SAR data products, the VH (cross polarized) SAR radar mosaic provides for detection of most linears; however, none of the SAR enhancements is significantly better than the others. Radar/LANDSAT merges may provide better linear detection than a single sensor mapping mode, but because of operator variability, the results are inconclusive. Radar/LANDSAT combinations appear promising as an optimum linear mapping technique, if the advantages and disadvantages of each remote sensor are considered.

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

NASA Astrophysics Data System (ADS)

Schack, L.; Soergel, U.

2013-05-01

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

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Archived 1976-1985 JPL Aircraft SAR Data

NASA Technical Reports Server (NTRS)

Thompson, Thomas W.; Blom, Ronald G.

2016-01-01

This report describes archived data from the Jet Propulsion Laboratory (JPL) aircraft radar expeditions in the mid-1970s through the mid-1980s collected by Ron Blom, JPL Radar Geologist. The dataset was collected during Ron's career at JPL from the 1970s through 2015. Synthetic Aperture Radar (SAR) data in the 1970s and 1980s were recorded optically on long strips of film. SAR imagery was produced via an optical, holographic technique that resulted in long strips of film imagery.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed

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

2018-04-01

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

A comparison of airborne GEMS/SAR with satellite-borne Seasat/SAR radar imagery - The value of archived multiple data sets

NASA Technical Reports Server (NTRS)

Hanson, Bradford C.; Dellwig, Louis F.

1988-01-01

In a study concerning the value of using radar imagery from systems with diverse parameters, X-band images of the Northern Louisiana Salt dome area generated by the airborne Goodyear electronic mapping system (GEMS) are analyzed in conjunction with imagery generated by the satelliteborne Seasat/SAR. The GEMS operated with an incidence angle of 75 to 85 deg and a resolution of 12 m, whereas the Seasat/SAR operated with an incidence angle of 23 deg and a resolution of 25 m. It is found that otherwise unattainable data on land management activities, improved delineation of the drainage net, better definition of surface roughness in cleared areas, and swamp identification, became accessible when adjustments for the time lapse between the two missions were made and supporting ground data concerning the physical and vegetative characteristics of the terrain were acquired.

Rapid Landslide Mapping by Means of Post-Event Polarimetric SAR Imagery

NASA Astrophysics Data System (ADS)

Plank, Simon; Martinis, Sandro; Twele, Andre

2016-08-01

Rapid mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response. Reviewing the literature shows that most synthetic aperture radar (SAR) data-based landslide mapping procedures use change detection techniques. However, the required very high resolution (VHR) pre-event SAR imagery, acquired shortly before the landslide event, is commonly not available. Due to limitations in onboard disk space and downlink transmission rates modern VHR SAR missions do not systematically cover the entire world. We present a fast and robust procedure for mapping of landslides, based on change detection between freely available and systematically acquired pre-event optical and post-event polarimetric SAR data.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2009-11-01

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

An atlas of November 1978 synthetic aperture radar digitized imagery for oil spill studies

NASA Technical Reports Server (NTRS)

Maurer, H. E.; Oderman, W.; Crosswell, W. F.

1982-01-01

A data set is described which consists of digitized synthetic aperture radar (SAR) imagery plus correlative data and some preliminary analysis results. This data set should be of value to experimenters who are interested in the SAR instrument and its application to the detection and monitoring of oil on water and other distributed targets.

Synthetic Aperture Radar (SAR)-based paddy rice monitoring system: Development and application in key rice producing areas in Tropical Asia

NASA Astrophysics Data System (ADS)

Setiyono, T. D.; Holecz, F.; Khan, N. I.; Barbieri, M.; Quicho, E.; Collivignarelli, F.; Maunahan, A.; Gatti, L.; Romuga, G. C.

2017-01-01

Reliable and regular rice information is essential part of many countries’ national accounting process but the existing system may not be sufficient to meet the information demand in the context of food security and policy. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland paddy rice, especially in tropical region where pervasive cloud cover in the rainy seasons limits the use of optical imagery. This study uses multi-temporal X-band and C-band SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations across Tropical Asia and assimilate the information into ORYZA Crop Growth Simulation model (CGSM) to generate high resolution yield maps. The resulting cultivated rice area maps had classification accuracies above 85% and yield estimates were within 81-93% agreement against district level reported yields. The study sites capture much of the diversity in water management, crop establishment and rice maturity durations and the study demonstrates the feasibility of rice detection, yield monitoring, and damage assessment in case of climate disaster at national and supra-national scales using multi-temporal SAR imagery combined with CGSM and automated methods.

Fall Freeze-up of Sea Ice in the Beaufort-Chukchi Seas Using ERS-1 SAR and Buoy Data

NASA Technical Reports Server (NTRS)

Holt, B.; Winebrenner, B.; D., Nelson E.

1993-01-01

The lowering of air temperatures below freezing in the fall indicates the end of summer melt and the onset of steady sea ice growth. The thickness and condition of ice that remains at the end of summer has ramifications for the thickness that that ice will attain at the end of the following winter. This period also designates a shifting of key fluxes from upper ocean freshening from ice melt to increased salinity from brine extraction during ice growth. This transitional period has been examined in the Beaufort and Chukchi Seas using ERS-1 SAR imagery and air temperatures from drifting buoys during 1991 and 1992. The SAR imagery is used to examine the condition and types of ice present in this period. Much of the surface melt water has drained off at this time. Air temperatures from drifting buoys coincident in time and within 100 km radius of the SAR imagery have been obtained...

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Vesecky, John F.; Stewart, Robert H.

1982-04-01

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

Studies of ice sheet hydrology using SAR

NASA Technical Reports Server (NTRS)

Bindschadler, R. A.; Vornberger, P. L.

1989-01-01

Analysis of SAR data of the Greenland ice sheet in summer and winter suggest the use of SAR to monitor the temporal hydrology of ice sheets. Comparisons of each SAR data set with summer Landsat TM imagery show an areal-positive correlation with summer SAR data and a negative correlation with winter SAR data. It is proposed that the summer SAR data are most sensitive to the variable concentrations of free water in the surface snow and that the winter SAR data indicate variations in snow grain size.

Transition from lab to flight demo for model-based FLIR ATR and SAR-FLIR fusion

NASA Astrophysics Data System (ADS)

Childs, Martin B.; Carlson, Karen M.; Pujara, Neeraj

2000-08-01

Model-based automatic target recognition (ATR) using forward- looking infrared (FLIR) imagery, and using FLIR imagery combined with cues from a synthetic aperture radar (SAR) system, has been successfully demonstrated in the laboratory. For the laboratory demonstration, FLIR images, platform location, sensor data, and SAR cues were read in from files stored on computer disk. This ATR system, however, was intended to ultimately be flown in a fighter aircraft. We discuss the transition from laboratory demonstration to flight demonstration for this system. The obvious changes required were in the interfaces: the flight system must get live FLIR imagery from a sensor; it must get platform location, sensor data, and controls from the avionics computer in the aircraft via 1553 bus; and it must get SAR cues from the on-board SAR system, also via 1553 bus. Other changes included the transition to rugged hardware that would withstand the fighter aircraft environment, and the need for the system to be compact and self-contained. Unexpected as well as expected challenges were encountered. We discuss some of these challenges, how they were met, and the performance of the flight-demonstration system.

LiDAR data and SAR imagery acquired by an unmanned helicopter for rapid landslide investigation

NASA Astrophysics Data System (ADS)

Kasai, M.; Tanaka, Y.; Yamazaki, T.

2012-12-01

When earthquakes or heavy rainfall hits a landslide prone area, initial actions require estimation of the size of damage to people and infrastructure. This includes identifying the number and size of newly collapsed or expanded landslides, and appraising subsequent risks from remobilization of landslides and debris materials. In inapproachable areas, the UAV (Unmanned Aerial Vehicles) is likely to be of greatest use. In addition, repeat monitoring of sites after the event is a way of utilizing UAVs, particularly in terms of cost and convenience. In this study, LiDAR (SkEyesBox MP-1) data and SAR (Nano SAR) imagery, acquired over 0.5 km2 landslide prone area, are presented to assess the practicability of using unmanned helicopters (in this case a 10 year old YAMAHA RMAX G1) in these situations. LiDAR data was taken in July 2012, when tree foliage covered the ground surface. However, imagery was of sufficient quality to identify and measure landslide features. Nevertheless, LiDAR data obtained by a manned helicopter in the same area in August 2008 was more detailed, reflecting the function of the LiDAR scanner. On the other hand, 2 m resolution Nano SAR imagery produced reasonable results to elucidate hillslope condition. A quick method for data processing without loss of image quality was also investigated. In conclusion, the LiDAR scanner and UAV employed here could be used to plan immediate remedial activity of the area, before LiDAR measurement with a manned helicopter can be organized. SAR imagery from UAV is also available for this initial activity, and can be further applied to long term monitoring.

SAR observations in the Gulf of Mexico

NASA Technical Reports Server (NTRS)

Sheres, David

1992-01-01

The Gulf of Mexico (GOM) exhibits a wealth of energetic ocean features; they include the Loop Current with velocities of about 2 m/s and strong shear fronts, mesoscale eddies, double vortices, internal waves, and the outflow of the 'Mighty Mississippi' river. These energetic features can have a strong impact on the economies of the states surrounding the Gulf. Large fisheries, oil and gas production as well as pollution transport are relevant issues. These circulation features in the Gulf are invisible to conventional IR and visible satellite imagery during the Summer months due to cloud cover and uniform surface temperatures. Synthetic Aperture Radar (SAR) imagery of the Gulf does penetrate the cloud cover and shows a rich assembly of features there year-round. Below are preliminary results from GOM SAR imagery taken by SEASAT in 1978 and by the AIRSAR program in 1991.

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

NASA Astrophysics Data System (ADS)

Pinel, V.; Poland, M. P.; Hooper, A.

2014-12-01

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work - for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Radar systems for the water resources mission, volume 2

NASA Technical Reports Server (NTRS)

Moore, R. K.; Claassen, J. P.; Erickson, R. L.; Fong, R. K. T.; Hanson, B. C.; Komen, M. J.; Mcmillan, S. B.; Parashar, S. K.

1976-01-01

The application of synthetic aperture radar (SAR) in monitoring and managing earth resources was examined. The function of spaceborne radar is to provide maps and map imagery to be used for earth resource and oceanographic applications. Spaceborne radar has the capability of mapping the entire United States regardless of inclement weather; however, the imagery must have a high degree of resolution to be meaningful. Attaining this resolution is possible with the SAR system. Imagery of the required quality must first meet mission parameters in the following areas: antenna patterns, azimuth and range ambiguities, coverage, and angle of incidence.

An Improved Method for Deriving Mountain Glacier Motion by Integrating Information of Intensity and Phase Based on SAR Images

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 average accuracy of 0.2 m covering the entire glacier surface, which shows a maximum ice movement of 4.9 m over 46 days. Therefore, the integrated approach could present us with a novel way to comprehensively and accurately understand glacier dynamics by overcoming the incoherence phenomenon, and has great potential for glaciology study.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Ships and Maritime Targets Observation Campaigns Using Available C- and X-Band SAR Satellite

NASA Astrophysics Data System (ADS)

Velotto, Domenico; Bentes, Carlos; Lehner, Susanne

2015-04-01

Obviously, radar resolution and swath width are two very important factors when it comes to synthetic aperture radar (SAR) maritime targets detections. The dilemma of using single polarization SAR imagery with higher resolution and coverage or quad- (or dual- polarimetric) imagery with its richness of information, is still unsolved when it comes to this application.In the framework of ESA project MARISS and EU project DOLPHIN, in situ campaigns aimed at solving this dilemma have been carried out. Single and multi- polarimetric SAR data acquired by TerraSAR-X, RADARSAT-2 and COSMO-SkyMed have been acquired with close time gaps and partial coverage overlap. In this way several moving and non-moving maritime targets have been imaged with different polarization, geometry and working frequency. Available ground truth reports provided by Automatic Identification System (AIS) data, nautical chart and wind farm location are used to validate the different types of maritime targets.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

High-Performance Anti-Retransmission Deception Jamming Utilizing Range Direction Multiple Input and Multiple Output (MIMO) Synthetic Aperture Radar (SAR).

PubMed

Wang, Ruijia; Chen, Jie; Wang, Xing; Sun, Bing

2017-01-09

Retransmission deception jamming seriously degrades the Synthetic Aperture Radar (SAR) detection efficiency and can mislead SAR image interpretation by forming false targets. In order to suppress retransmission deception jamming, this paper proposes a novel multiple input and multiple output (MIMO) SAR structure range direction MIMO SAR, whose multiple channel antennas are vertical to the azimuth. First, based on the multiple channels of range direction MIMO SAR, the orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) signal was adopted as the transmission signal of each channel, which is defined as a sub-band signal. This sub-band signal corresponds to the transmission channel. Then, all of the sub-band signals are modulated with random initial phases and concurrently transmitted. The signal form is more complex and difficult to intercept. Next, the echoes of the sub-band signal are utilized to synthesize a wide band signal after preprocessing. The proposed method will increase the signal to interference ratio and peak amplitude ratio of the signal to resist retransmission deception jamming. Finally, well-focused SAR imagery is obtained using a conventional imaging method where the retransmission deception jamming strength is degraded and defocused. Simulations demonstrated the effectiveness of the proposed method.

High-Performance Anti-Retransmission Deception Jamming Utilizing Range Direction Multiple Input and Multiple Output (MIMO) Synthetic Aperture Radar (SAR)

PubMed Central

Wang, Ruijia; Chen, Jie; Wang, Xing; Sun, Bing

2017-01-01

Retransmission deception jamming seriously degrades the Synthetic Aperture Radar (SAR) detection efficiency and can mislead SAR image interpretation by forming false targets. In order to suppress retransmission deception jamming, this paper proposes a novel multiple input and multiple output (MIMO) SAR structure range direction MIMO SAR, whose multiple channel antennas are vertical to the azimuth. First, based on the multiple channels of range direction MIMO SAR, the orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) signal was adopted as the transmission signal of each channel, which is defined as a sub-band signal. This sub-band signal corresponds to the transmission channel. Then, all of the sub-band signals are modulated with random initial phases and concurrently transmitted. The signal form is more complex and difficult to intercept. Next, the echoes of the sub-band signal are utilized to synthesize a wide band signal after preprocessing. The proposed method will increase the signal to interference ratio and peak amplitude ratio of the signal to resist retransmission deception jamming. Finally, well-focused SAR imagery is obtained using a conventional imaging method where the retransmission deception jamming strength is degraded and defocused. Simulations demonstrated the effectiveness of the proposed method. PMID:28075367

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

NASA Technical Reports Server (NTRS)

Henderson, F. M. (Principal Investigator)

1980-01-01

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

Evaluation of single-band snow-patch mapping using high-resolution microwave remote sensing: an application in the maritime Antarctic

NASA Astrophysics Data System (ADS)

Mora, Carla; Jiménez, Juan Javier; Pina, Pedro; Catalão, João; Vieira, Gonçalo

2017-01-01

The mountainous and ice-free terrains of the maritime Antarctic generate complex mosaics of snow patches, ranging from tens to hundreds of metres. These can only be accurately mapped using high-resolution remote sensing. In this paper we evaluate the application of radar scenes from TerraSAR-X in High Resolution SpotLight mode for mapping snow patches at a test area on Fildes Peninsula (King George Island, South Shetlands). Snow-patch mapping and characterization of snow stratigraphy were conducted at the time of image acquisition on 12 and 13 January 2012. Snow was wet in all studied snow patches, with coarse-grain and rounded crystals showing advanced melting and with frequent ice layers in the snow pack. Two TerraSAR-X scenes in HH and VV polarization modes were analysed, with the former showing the best results when discriminating between wet snow, lake water and bare soil. However, significant overlap in the backscattering signal was found. Average wet-snow backscattering was -18.0 dB in HH mode, with water showing -21.1 dB and bare soil showing -11.9 dB. Single-band pixel-based and object-oriented image classification methods were used to assess the classification potential of TerraSAR-X SpotLight imagery. The best results were obtained with an object-oriented approach using a watershed segmentation with a support vector machine (SVM) classifier, with an overall accuracy of 92 % and Kappa of 0.88. The main limitation was the west to north-west facing snow patches, which showed significant error, an issue related to artefacts from the geometry of satellite imagery acquisition. The results show that TerraSAR-X in SpotLight mode provides high-quality imagery for mapping wet snow and snowmelt in the maritime Antarctic. The classification procedure that we propose is a simple method and a first step to an implementation in operational mode if a good digital elevation model is available.

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

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.

Calibration of Two-dimensional Floodplain Modeling in the Atchafalaya River Basin Using SAR Interferometry

NASA Technical Reports Server (NTRS)

Jung, Hahn Chul; Jasinski, Michael; Kim, Jin-Woo; Shum, C. K.; Bates, Paul; Lee, Hgongki; Neal, Jeffrey; Alsdorf, Doug

2012-01-01

Two-dimensional (2D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the 2D spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD-ACC hydrodynamic model is applied to the central Atchafalaya River Basin, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in coupled 1D/2D model calibration. Two calibration schemes focusing on Manning s roughness are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62 day simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. The best-fit models show that the mean absolute errors are 3.8 cm for a single in situ gage calibration and 5.7 cm/46 days for InSAR water level calibration. The optimum values of Manning's roughness coefficients are 0.024/0.10 for the channel/floodplain, respectively, using a single in situ gage, and 0.028/0.10 for channel/floodplain the using SAR. Based on the calibrated water elevation changes, daily storage changes within the size of approx 230 sq km of the model area are also calculated to be of the order of 107 cubic m/day during high water of the modeled period. This study demonstrates the feasibility of SAR interferometry to support 2D hydrodynamic model calibration and as a tool for improved understanding of complex floodplain hydrodynamics

Routine Ocean Monitoring With Synthetic Aperture Radar Imagery Obtained From the Alaska Satellite Facility

NASA Astrophysics Data System (ADS)

Pichel, W. G.; Clemente-Colon, P.; Li, X.; Friedman, K.; Monaldo, F.; Thompson, D.; Wackerman, C.; Scott, C.; Jackson, C.; Beal, R.; McGuire, J.; Nicoll, J.

2006-12-01

The Alaska Satellite Facility (ASF) has been processing synthetic aperture radar (SAR) data for research and for near-real-time applications demonstrations since shortly after the launch of the European Space Agency's ERS-1 satellite in 1991. The long coastline of Alaska, the vast extent of ocean adjacent to Alaska, a scarcity of in-situ observations, and the persistence of cloud cover all contribute to the need for all-weather ocean observations in the Alaska region. Extensive experience with SAR product processing algorithms and SAR data analysis techniques, and a growing sophistication on the part of SAR data and product users have amply demonstrated the value of SAR instruments in providing this all-weather ocean observation capability. The National Oceanic and Atmospheric Administration (NOAA) has been conducting a near-real-time applications demonstration of SAR ocean and hydrologic products in Alaska since September 1999. This Alaska SAR Demonstration (AKDEMO) has shown the value of SAR-derived, high-resolution (sub kilometer) ocean surface winds to coastal weather forecasting and the understanding of coastal wind phenomena such as gap winds, barrier jets, vortex streets, and lee waves. Vessel positions and ice information derived from SAR imagery have been used for management of fisheries, protection of the fishing fleet, enforcement of fisheries regulations, and protection of endangered marine mammals. Other ocean measurements, with potentially valuable applications, include measurement of wave state (significant wave height, dominant wave direction and wavelength, and wave spectra), mapping of oil spills, and detection of shallow-water bathymetric features. In addition to the AKDEMO, ASF-processed SAR imagery is being used: (1) in the Gulf of Mexico for hurricane wind studies, and post-hurricane oil-spill and oil-platform analyses (the latter employing ship-detection algorithms for detection of changes in oil-platform locations); (2) in the North Pacific to help locate convergence zones for marine debris detection (i.e., the GhostNet project); (3) in marine sanctuaries for internal wave climatology in support of marine ecosystem studies, and vessel detection for sanctuary protection; and (4) in coastal areas for ocean feature mapping (eddies, river plumes, upwelling, fronts). These applications demonstrations have added to our understanding of ocean and atmospheric processes and their interaction, particularly in the coastal environment. A much improved knowledge of the highly variable nature of coastal winds such as gap winds and barrier jets is a good example of the contribution that SAR imagery and derived products have made to our understanding of coastal processes.

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.

Making SAR Data Accessible - ASF's ALOS PALSAR Radiometric Terrain Correction Project

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Arko, S. A.; Gens, R.

2015-12-01

While SAR data have proven valuable for a wide range of geophysical research questions, so far, largely only the SAR-educated science communities have been able to fully exploit the information content of internationally available SAR archives. The main issues that have been preventing a more widespread utilization of SAR are related to (1) the diversity and complexity of SAR data formats, (2) the complexity of the processing flows needed to extract geophysical information from SAR, (3) the lack of standardization and automation of these processing flows, and (4) the often ignored geocoding procedures, leaving the data in image coordinate space. In order to improve upon this situation, ASF's radiometric terrain-correction (RTC) project is generating uniformly formatted and easily accessible value-added products from the ASF Distributed Active Archive Center's (DAAC) five-year archive of JAXA's ALOS PALSAR sensor. Specifically, the project applies geometric and radiometric corrections to SAR data to allow for an easy and direct combination of obliquely acquired SAR data with remote sensing imagery acquired in nadir observation geometries. Finally, the value-added data is provided to the user in the broadly accepted Geotiff format, in order to support the easy integration of SAR data into GIS environments. The goal of ASF's RTC project is to make SAR data more accessible and more attractive to the broader SAR applications community, especially to those users that currently have limited SAR expertise. Production of RTC products commenced October 2014 and will conclude late in 2015. As of July 2015, processing of 71% of ASF's ALOS PALSAR archive was completed. Adding to the utility of this dataset are recent changes to the data access policy that allow the full-resolution RTC products to be provided to the public, without restriction. In this paper we will introduce the processing flow that was developed for the RTC project and summarize the calibration and validation procedures that were implemented to determine and monitor system performance. The paper will also show the current progress of RTC processing, provide examples of generated data sets, and demonstrate the benefit of the RTC archives for applications such as land-use classification and change detection.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

USGS Publications Warehouse

Pinel, Virginie; Poland, Michael P.; Hooper, Andy

2014-01-01

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work – for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

Reduction and coding of synthetic aperture radar data with Fourier transforms

NASA Technical Reports Server (NTRS)

Tilley, David G.

1995-01-01

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

Flood Extent Mapping Using Dual-Polarimetric SENTINEL-1 Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Jo, M.-J.; Osmanoglu, B.; Zhang, B.; Wdowinski, S.

2018-04-01

Rapid generation of synthetic aperture radar (SAR) based flood extent maps provide valuable data in disaster response efforts thanks to the cloud penetrating ability of microwaves. We present a method using dual-polarimetric SAR imagery acquired on Sentinel-1a/b satellites. A false-colour map is generated using pre- and post- disaster imagery, allowing operators to distinguish between existing standing water pre-flooding, and recently flooded areas. The method works best in areas of standing water and provides mixed results in urban areas. A flood depth map is also estimated by using an external DEM. We will present the methodology, it's estimated accuracy as well as investigations into improving the response in urban areas.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Sea Ice Concentration Estimation Using Active and Passive Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, F.; Zhang, S.; Zhu, T.

2017-12-01

In this abstract, a decision-level fusion method by utilizing SAR and passive microwave remote sensing data for sea ice concentration estimation is investigated. Sea ice concentration product from passive microwave concentration retrieval methods has large uncertainty within thin ice zone. Passive microwave data including SSM/I, AMSR-E, and AMSR-2 provide daily and long time series observations covering whole polar sea ice scene, and SAR images provide rich sea ice details with high spatial resolution including deformation and polarimetric features. In the proposed method, the merits from passive microwave data and SAR data are considered. Sea ice concentration products from ASI and sea ice category label derived from CRF framework in SAR imagery are calibrated under least distance protocol. For SAR imagery, incident angle and azimuth angle were used to correct backscattering values from slant range to ground range in order to improve geocoding accuracy. The posterior probability distribution between category label from SAR imagery and passive microwave sea ice concentration product is modeled and integrated under Bayesian network, where Gaussian statistical distribution from ASI sea ice concentration products serves as the prior term, which represented as an uncertainty of sea ice concentration. Empirical model based likelihood term is constructed under Bernoulli theory, which meets the non-negative and monotonically increasing conditions. In the posterior probability estimation procedure, final sea ice concentration is obtained using MAP criterion, which equals to minimize the cost function and it can be calculated with nonlinear iteration method. The proposed algorithm is tested on multiple satellite SAR data sets including GF-3, Sentinel-1A, RADARSAT-2 and Envisat ASAR. Results show that the proposed algorithm can improve the accuracy of ASI sea ice concentration products and reduce the uncertainty along the ice edge.

Interlobate comparison of glacial-depositional style as evidenced by small-relief glacial landscape features in Illinois, Indiana, and Ohio, utilizing SIR-B

NASA Technical Reports Server (NTRS)

Johnson, W. H.; Bleuer, N. K.; Fraser, G. S.; Totten, S. M.

1984-01-01

The objectives and expected results of an investigation of the use of the Shuttle Imaging Radar-B (SIR-B) as a basic tool in the recognition and mapping of glacial landforms are discussed. The main goals are: (1) to evaluate the ability of SIR-B to delineate varying sizes, shapes, and relief of surface forms; (2) to compare and contrast SIR-B imagery with selected Seasat SAR imagery; (3) to utilize SIR-B imagery synergistically with available SEASAT SAR, LANDSAT RBV, and other imagery sources to identify and map suites of glacial landforms; and (4) eventually to interpret the suites in terms of ice dynamics and conditions of deglaciation, to relate them to the stratigraphic record, and to evaluate interactions of the major lobes and sublobes.

Working group organizational meeting

NASA Technical Reports Server (NTRS)

1982-01-01

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

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

NASA Astrophysics Data System (ADS)

Hack, Dan E.; Saville, Michael A.

2010-04-01

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

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.

Applying a particle filtering technique for canola crop growth stage estimation in Canada

NASA Astrophysics Data System (ADS)

Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi

2017-10-01

Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.

Dome growth at Mount Cleveland, Aleutian Arc, quantified by time-series TerraSAR-X imagery

USGS Publications Warehouse

Wang, Teng; Poland, Michael; Lu, Zhong

2016-01-01

Synthetic aperture radar imagery is widely used to study surface deformation induced by volcanic activity; however, it is rarely applied to quantify the evolution of lava domes, which is important for understanding hazards and magmatic system characteristics. We studied dome formation associated with eruptive activity at Mount Cleveland, Aleutian Volcanic Arc, in 2011–2012 using TerraSAR-X imagery. Interferometry and offset tracking show no consistent deformation and only motion of the crater rim, suggesting that ascending magma may pass through a preexisting conduit system without causing appreciable surface deformation. Amplitude imagery has proven useful for quantifying rates of vertical and areal growth of the lava dome within the crater from formation to removal by explosive activity to rebirth. We expect that this approach can be applied at other volcanoes that host growing lava domes and where hazards are highly dependent on dome geometry and growth rates.

Initial observations on using SAR to monitor wildfire scars in boreal forests

NASA Technical Reports Server (NTRS)

Kasischke, E. S.; Bourgeau-Chavez, L. L.; French, N. H. F.; Harrell, P.; Christensen, N. L., Jr.

1992-01-01

Initial observations on the effects of wildfires in black spruce forests on radar backscatter are presented. Airborne and spaceborne SAR imagery are utilized to illustrate two distinct fire signatures. A theory is presented to explain these differences.

An unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data - A case study in complex temperate forest stands

NASA Astrophysics Data System (ADS)

Abdullahi, Sahra; Schardt, Mathias; Pretzsch, Hans

2017-05-01

Forest structure at stand level plays a key role for sustainable forest management, since the biodiversity, productivity, growth and stability of the forest can be positively influenced by managing its structural diversity. In contrast to field-based measurements, remote sensing techniques offer a cost-efficient opportunity to collect area-wide information about forest stand structure with high spatial and temporal resolution. Especially Interferometric Synthetic Aperture Radar (InSAR), which facilitates worldwide acquisition of 3d information independent from weather conditions and illumination, is convenient to capture forest stand structure. This study purposes an unsupervised two-stage clustering approach for forest structure classification based on height information derived from interferometric X-band SAR data which was performed in complex temperate forest stands of Traunstein forest (South Germany). In particular, a four dimensional input data set composed of first-order height statistics was non-linearly projected on a two-dimensional Self-Organizing Map, spatially ordered according to similarity (based on the Euclidean distance) in the first stage and classified using the k-means algorithm in the second stage. The study demonstrated that X-band InSAR data exhibits considerable capabilities for forest structure classification. Moreover, the unsupervised classification approach achieved meaningful and reasonable results by means of comparison to aerial imagery and LiDAR data.

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.

Signal processing techniques for the U.S. Army Research Laboratory stepped frequency ultra-wideband radar

NASA Astrophysics Data System (ADS)

Nguyen, Lam

2017-05-01

The U.S. Army Research Laboratory (ARL) recently designed and tested a new prototype radar, the Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) radar system, based on a stepped-frequency architecture to address issues associated with our previous impulse-based radars. This is a low-frequency ultra-wideband (UWB) radar with frequencies spanning from 300 to 2000 MHz. Mounted on a vehicle, the radar can be configured in either sidelooking or forward-looking synthetic aperture radar (SAR) mode. We recently conducted our first experiment at Yuma Proving Grounds (YPG). This paper summarizes the radar configurations, parameters, and SAR geometry. The radar data and other noise sources, to include the self-interference signals and radio-frequency interference (RFI) noise sources, are presented and characterized in both the raw (pre-focus) and SAR imagery domains. This paper also describes our signal processing techniques for extracting noise from radar data, as well as the SAR imaging algorithms for forming SAR imagery in both forward- and side-looking modes. Finally, this paper demonstrates our spectral recovery technique and results for a radar operating in a spectrally restricted environment.

Monitoring and characterizing natural hazards with satellite InSAR imagery

USGS Publications Warehouse

Lu, Zhong; Zhang, Jixian; Zhang, Yonghong; Dzurisin, Daniel

2010-01-01

Interferometric synthetic aperture radar (InSAR) provides an all-weather imaging capability for measuring ground-surface deformation and inferring changes in land surface characteristics. InSAR enables scientists to monitor and characterize hazards posed by volcanic, seismic, and hydrogeologic processes, by landslides and wildfires, and by human activities such as mining and fluid extraction or injection. Measuring how a volcano’s surface deforms before, during, and after eruptions provides essential information about magma dynamics and a basis for mitigating volcanic hazards. Measuring spatial and temporal patterns of surface deformation in seismically active regions is extraordinarily useful for understanding rupture dynamics and estimating seismic risks. Measuring how landslides develop and activate is a prerequisite to minimizing associated hazards. Mapping surface subsidence or uplift related to extraction or injection of fluids during exploitation of groundwater aquifers or petroleum reservoirs provides fundamental data on aquifer or reservoir properties and improves our ability to mitigate undesired consequences. Monitoring dynamic water-level changes in wetlands improves hydrological modeling predictions and the assessment of future flood impacts. In addition, InSAR imagery can provide near-real-time estimates of fire scar extents and fire severity for wildfire management and control. All-weather satellite radar imagery is critical for studying various natural processes and is playing an increasingly important role in understanding and forecasting natural hazards.

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.

Detecting seasonal landslide movement within the Cascade landslide complex (Washington) using time-series SAR imagery

USGS Publications Warehouse

Hu, Xie; Wang, Teng; Pierson, Thomas C.; Lu, Zhong; Kim, Jin-Woo; Cecere, Thomas H.

2016-01-01

Detection of slow or limited landslide movement within broad areas of forested terrain has long been problematic, particularly for the Cascade landslide complex (Washington) located along the Columbia River Gorge. Although parts of the landslide complex have been found reactivated in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here we apply novel time-series strategies to study the spatial distribution and temporal behavior of the landslide movement between 2007 and 2011 using InSAR images from two overlapping L-band ALOS PALSAR-1 satellite tracks. Our results show that the reactivated part has moved approximately 700 mm downslope during the 4-year observation period, while other parts of the landslide complex have generally remained stable. However, we also detect about 300 mm of seasonal downslope creep in a terrain block upslope of the Cascade landslide complex—terrain previously thought to be stable. The temporal oscillation of the seasonal movement can be correlated with precipitation, implying that seasonal movement here is hydrology-driven. The seasonal movement also has a frequency similar to GPS-derived regional ground oscillations due to mass loading by stored rainfall and subsequent rebound but with much smaller magnitude, suggesting different hydrological loading effects. From the time-series amplitude information on terrain upslope of the headscarp, we also re-evaluate the incipient motion related to the 2008 Greenleaf Basin rock avalanche, not previously recognized by traditional SAR/InSAR methods. The approach used in this study can be used to identify active landslides in forested terrain, to track the seasonal movement of landslides, and to identify previously unknown landslide hazards.

Large Scale Crop Mapping in Ukraine Using Google Earth Engine

NASA Astrophysics Data System (ADS)

Shelestov, A.; Lavreniuk, M. S.; Kussul, N.

2016-12-01

There are no globally available high resolution satellite-derived crop specific maps at present. Only coarse-resolution imagery (> 250 m spatial resolution) has been utilized to derive global cropland extent. In 2016 we are going to carry out a country level demonstration of Sentinel-2 use for crop classification in Ukraine within the ESA Sen2-Agri project. But optical imagery can be contaminated by cloud cover that makes it difficult to acquire imagery in an optimal time range to discriminate certain crops. Due to the Copernicus program since 2015, a lot of Sentinel-1 SAR data at high spatial resolution is available for free for Ukraine. It allows us to use the time series of SAR data for crop classification. Our experiment for one administrative region in 2015 showed much higher crop classification accuracy with SAR data than with optical only time series [1, 2]. Therefore, in 2016 within the Google Earth Engine Research Award we use SAR data together with optical ones for large area crop mapping (entire territory of Ukraine) using cloud computing capabilities available at Google Earth Engine (GEE). This study compares different classification methods for crop mapping for the whole territory of Ukraine using data and algorithms from GEE. Classification performance assessed using overall classification accuracy, Kappa coefficients, and user's and producer's accuracies. Also, crop areas from derived classification maps compared to the official statistics [3]. S. Skakun et al., "Efficiency assessment of multitemporal C-band Radarsat-2 intensity and Landsat-8 surface reflectance satellite imagery for crop classification in Ukraine," IEEE Journal of Selected Topics in Applied Earth Observ. and Rem. Sens., 2015, DOI: 10.1109/JSTARS.2015.2454297. N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "The use of satellite SAR imagery to crop classification in Ukraine within JECAM project," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.1497-1500, 13-18 July 2014, Quebec City, Canada. F.J. Gallego, N. Kussul, S. Skakun, O. Kravchenko, A. Shelestov, O. Kussul, "Efficiency assessment of using satellite data for crop area estimation in Ukraine," International Journal of Applied Earth Observation and Geoinformation vol. 29, pp. 22-30, 2014.

Applications of Radarsat-1 synthetic aperture radar imagery to assess hurricane-related flooding of coastal Louisiana

USGS Publications Warehouse

Kiage, L.M.; Walker, N.D.; Balasubramanian, S.; Babin, A.; Barras, J.

2005-01-01

The Louisiana coast is subjected to hurricane impacts including flooding of human settlements, river channels and coastal marshes, and salt water intrusion. Information on the extent of flooding is often required quickly for emergency relief, repairs of infrastructure, and production of flood risk maps. This study investigates the feasibility of using Radarsat-1 SAR imagery to detect flooded areas in coastal Louisiana after Hurricane Lili, October 2002. Arithmetic differencing and multi-temporal enhancement techniques were employed to detect flooding and to investigate relationships between backscatter and water level changes. Strong positive correlations (R2=0.7-0.94) were observed between water level and SAR backscatter within marsh areas proximate to Atchafalaya Bay. Although variations in elevation and vegetation type did influence and complicate the radar signature at individual sites, multi-date differences in backscatter largely reflected the patterns of flooding within large marsh areas. Preliminary analyses show that SAR imagery was not useful in mapping urban flooding in New Orleans after Hurricane Katrina's landfall on 29 August 2005. ?? 2005 Taylor & Francis.

On the merging of optical and SAR satellite imagery for surface water mapping applications

NASA Astrophysics Data System (ADS)

Markert, Kel N.; Chishtie, Farrukh; Anderson, Eric R.; Saah, David; Griffin, Robert E.

2018-06-01

Optical and Synthetic Aperture Radar (SAR) imagery from satellite platforms provide a means to discretely map surface water; however, the application of the two data sources in tandem has been inhibited by inconsistent data availability, the distinct physical properties that optical and SAR instruments sense, and dissimilar data delivery platforms. In this paper, we describe a preliminary methodology for merging optical and SAR data into a common data space. We apply our approach over a portion of the Mekong Basin, a region with highly variable surface water cover and persistent cloud cover, for surface water applications requiring dense time series analysis. The methods include the derivation of a representative index from both sensors that transforms data from disparate physical units (reflectance and backscatter) to a comparable dimensionless space applying a consistent water extraction approach to both datasets. The merging of optical and SAR data allows for increased observations in cloud prone regions that can be used to gain additional insight into surface water dynamics or flood mapping applications. This preliminary methodology shows promise for a common optical-SAR water extraction; however, data ranges and thresholding values can vary depending on data source, yielding classification errors in the resulting surface water maps. We discuss some potential future approaches to address these inconsistencies.

Sampling Of SAR Imagery For Wind Resource Assesment

NASA Astrophysics Data System (ADS)

Badger, Merete; Badger, Jake; Hasager, Charlotte; Nielsen, Morten

2010-04-01

Wind resources over the sea can be assessed from a series of wind fields retrieved from Envisat ASAR imagery, or other SAR data. Previous wind resource maps have been produced through random sampling of 70 or more satellite scenes over a given area of interest followed by fitting of a Weibull function to the data. Here we introduce a more advanced sampling strategy based on wind class methodology that is normally applied in Risø DTU’s numerical modeling of wind resources. The aim is to obtain a more representative data set using fewer satellite SAR scenes. The new sampling strategy has been applied within a wind and solar resource assessment study for the United Arab Emirates (UAE) and also for wind resource mapping over a domain in the North Sea, as part of the EU- NORSEWInD project (2008-2012).

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

PubMed

Eftekhari, Akram; Saadatseresht, Mohammad; Motagh, Mahdi

2013-09-09

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

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

PubMed Central

Eftekhari, Akram; Saadatseresht, Mohammad; Motagh, Mahdi

2013-01-01

The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10−3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction. PMID:24021971

Synergistic use of optical and InSAR data for urban impervious surface mapping: A case study in Hong Kong

USGS Publications Warehouse

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

2009-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning and watershed resource management, require accurate and up‐to‐date geospatial data of urban impervious surfaces. In this study, the potential of the synergistic use of optical and InSAR data in urban impervious surface mapping at the sub‐pixel level was investigated. A case study in Hong Kong was conducted for this purpose by applying a classification and regression tree (CART) algorithm to SPOT 5 multispectral imagery and ERS‐2 SAR data. Validated by reference data derived from high‐resolution colour‐infrared (CIR) aerial photographs, our results show that the addition of InSAR feature information can improve the estimation of impervious surface percentage (ISP) in comparison with using SPOT imagery alone. The improvement is especially notable in separating urban impervious surface from the vacant land/bare ground, which has been a difficult task in ISP modelling with optical remote sensing data. In addition, the results demonstrate the potential to map urban impervious surface by using InSAR data alone. This allows frequent monitoring of world's cities located in cloud‐prone and rainy areas.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

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

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.

Airborne Multi-Band SAR in the Arctic

NASA Astrophysics Data System (ADS)

Gardner, J. M.; Brozena, J. M.; Liang, R.; Ball, D.; Holt, B.; Thomson, J.

2016-12-01

As one component of the Office of Naval Research supported Sea State Departmental Research Initiative during October of 2015 the Naval Research Laboratory flew an ultrawide-band, low-frequency, polarimetric SAR over the southward advancing sea ice in Beaufort Sea. The flights were coordinated with the research team aboard the R/V Sikuliaq working near and in the advancing pack ice. The majority of the SAR data were collected with the L-Band sensor (1000-1500 MHz) from an altitude of 10,000', providing a useful swath 6 km wide with 75o and 25 o angles of incidence at the inner and outer edge of the swath respectively. Some data were also collected with the P-Band SAR (215-915 MHz). The extremely large bandwidths allowed for formation of image pixels as small as 30 cm, however, we selected 60 cm pixel size to reduce image speckle. The separate polarimetric images are calibrated to one pixel to allow for calculations such as polarimetric decompositions that require the images to be well aligned. Both frequencies are useful particularly for the detection of ridges and areas of deformed ice. There are advantages and disadvantages to airborne SAR imagery compared to satellites. The chief advantages being the enormous allowable bandwidth leading to very fine range resolution, and the ability to fly arbitrary trajectories on demand. The latter permits specific areas to be imaged at a given time with a specified illumination direction. An area can even be illuminated from all directions by flying a circular trajectory around the target area. This captures ice features that are sensitive to illumination direction such as cracks, sastrugi orientation, and ridges. The disadvantages include variation of intensity across the swath with range and incidence angle. In addition to the SAR data, we collected photogrammetric imagery from a DSS-439, scanning lidar from a Riegl Q560 and surface brightness temperatures from a KT-19. However, since all of these sensors are nadir pointing, and some restricted to relatively low-altitude, it was difficult to obtain data co-registered with the SAR. At this meeting we will present some initial results from the SAR imagery, including differentiation of young, thin, and older ice features, and comparisons with satellite SAR with L-band and C-band frequencies.

Further SEASAT SAR coastal ocean wave analysis

NASA Technical Reports Server (NTRS)

Kasischke, E. S.; Shuchman, R. A.; Meadows, G. A.; Jackson, P. L.; Tseng, Y.

1981-01-01

Analysis techniques used to exploit SEASAT synthetic aperture radar (SAR) data of gravity waves are discussed and the SEASAT SAR's ability to monitor large scale variations in gravity wave fields in both deep and shallow water is evaluated. The SAR analysis techniques investigated included motion compensation adjustments and the semicausal model for spectral analysis of SAR wave data. It was determined that spectra generated from fast Fourier transform analysis (FFT) of SAR wave data were not significantly altered when either range telerotation adjustments or azimuth focus shifts were used during processing of the SAR signal histories, indicating that SEASAT imagery of gravity waves is not significantly improved or degraded by motion compensation adjustments. Evaluation of the semicausal (SC) model using SEASAT SAR data from Rev. 974 indicates that the SC spectral estimates were not significantly better than the FFT results.

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

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

Separated Component-Based Restoration of Speckled SAR Images

DTIC Science & Technology

2013-01-01

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

A comparison between remote sensing approaches to water extent monitoring

NASA Astrophysics Data System (ADS)

elmi, omid; javad tourian, mohammad; sneeuw, nico

2013-04-01

Monitoring the variation of water storage in a long period is a primary issue for understanding the impact of climate change and human activities on earth water resources. In order to obtain the change in water volume in a lake and reservoir, in addition to water level, water extent must be repeatedly determined in an appropriate time interval. Optical satellite imagery as a passive system is the main source of determination of coast line change as it is easy to interpret. Optical sensors acquire the reflected energy from the sunlight in various bands from visible to near infrared. Also, panchromatic mode provides more geometric details. Establishing a ratio between visible bands is the most common way of extract coastlines because with this ratio, water and land can be separated directly. Also, since the reflectance value of water is distinctly less than soil in infrared bands, applying a histogram threshold on this band is a effective way of coastline extraction. However, optical imagery is highly vulnerable to occurrence of dense clouds and fog. Moreover, the coastline is hard to detect where it is covered by dense vegetation. Synthetic aperture radar (SAR) as an active system provides an alternative source for monitoring the spatial change in coastlines. Two methods for monitoring the shoreline with SAR data have been published. First, the backscatter difference is calculated between two images acquired at different times. Second, the change in coastline is detected by computing the coherence of two SAR images acquired at different times. A SAR system can operate in all weather, so clouds and fog don't impact its efficiency. Also, it can penetrate into the plant canopy. However, in comparison with optical imagery, interpretation of SAR image in this case is relatively hard because of limitation in the number of band and polarization modes, also due to effects caused by speckle noises, slant-range imaging and shadows. The primary aim of this study is a comparison between the performance and result of different methods of the water area monitoring over a long period by applying optic and SAR images. The secondary goal is investigation a method to integrate SAR and optical imagery for water extent monitoring to improve the performance. The case study of this paper is Urmia lake located in the northwest of Iran. Its area has impressively decreased since 1995, so water extent monitoring is vital in this case.

Use of SAR imagery and other remotely-sensed data in deriving ice information during a severe ice event on the Grand Banks (Newfoundland)

NASA Technical Reports Server (NTRS)

Carsey, F. D.; Argus, S. D.

1988-01-01

Image data from synthetic aperture radar (SAR) are used to observe an ice compaction event off the East Coast of Newfoundland in spring, 1987. The information developed from sequential SAR observations is shown to do a remarkably effective job of describing the ice conditions; the difficult variable is the ice thickness which is found to be surprisingly large (2 to 4 times the thickness predictable from thermodynamic growth alone). It may be possible to model the ice thickness using SAR-derived ice motion.

Perceptual compression of magnitude-detected synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Werness, Susan A.

1994-01-01

A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.

Graph Matching for the Registration of Persistent Scatterers to Optical Oblique Imagery

NASA Astrophysics Data System (ADS)

Schack, L.; Soergel, U.; Heipke, C.

2016-06-01

Matching Persistent Scatterers (PS) to airborne optical imagery is one possibility to augment applications and deepen the understanding of SAR processing and products. While recently this data registration task was done with PS and optical nadir images the alternatively available optical oblique imagery is mostly neglected. Yet, the sensing geometry of oblique images is very similar in terms of viewing direction with respect to SAR.We exploit the additional information coming with these optical sensors to assign individual PS to single parts of buildings. The key idea is to incorporate topology information which is derived by grouping regularly aligned PS at facades and use it together with a geometry based measure in order to establish a consistent and meaningful matching result. We formulate this task as an optimization problem and derive a graph matching based algorithm with guaranteed convergence in order to solve it. Two exemplary case studies show the plausibility of the presented approach.

Multisensor comparison of ice concentration estimates in the marginal ice zone

NASA Technical Reports Server (NTRS)

Burns, B. A.; Cavalieri, D. J.; Gloersen, P.; Keller, M. R.; Campbell, W. J.

1987-01-01

Aircraft remote sensing data collected during the 1984 summer Marginal Ice Zone Experiment in the Fram Strait are used to compare ice concentration estimates derived from synthetic aperture radar (SAR) imagery, passive microwave imagery at several frequencies, aerial photography, and spectral photometer data. The comparison is carried out not only to evaluate SAR performance against more established techniques but also to investigate how ice surface conditions, imaging geometry, and choice of algorithm parameters affect estimates made by each sensor.Active and passive microwave sensor estimates of ice concentration derived using similar algorithms show an rms difference of 13 percent. Agreement between each microwave sensor and near-simultaneous aerial photography is approximately the same (14 percent). The availability of high-resolution microwave imagery makes it possible to ascribe the discrepancies in the concentration estimates to variations in ice surface signatures in the scene.

Modeling of SAR signatures of shallow water ocean topography

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Kozma, A.; Kasischke, E. S.; Lyzenga, D. R.

1984-01-01

A hydrodynamic/electromagnetic model was developed to explain and quantify the relationship between the SEASAT synthetic aperture radar (SAR) observed signatures and the bottom topography of the ocean in the English Channel region of the North Sea. The model uses environmental data and radar system parameters as inputs and predicts SAR-observed backscatter changes over topographic changes in the ocean floor. The model results compare favorably with the actual SEASAT SAR observed backscatter values. The developed model is valid for only relatively shallow water areas (i.e., less than 50 meters in depth) and suggests that for bottom features to be visible on SAR imagery, a moderate to high velocity current and a moderate wind must be present.

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.

Advanced Unsupervised Classification Methods to Detect Anomalies on Earthen Levees Using Polarimetric SAR Imagery

PubMed Central

Marapareddy, Ramakalavathi; Aanstoos, James V.; Younan, Nicolas H.

2016-01-01

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We used L-band Synthetic Aperture Radar (SAR) to screen levees for anomalies. SAR technology, due to its high spatial resolution and soil penetration capability, is a good choice for identifying problematic areas on earthen levees. Using the parameters entropy (H), anisotropy (A), alpha (α), and eigenvalues (λ, λ1, λ2, and λ3), we implemented several unsupervised classification algorithms for the identification of anomalies on the levee. The classification techniques applied are H/α, H/A, A/α, Wishart H/α, Wishart H/A/α, and H/α/λ classification algorithms. In this work, the effectiveness of the algorithms was demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the Southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers. PMID:27322270

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

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

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

1991-01-01

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

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.

The 1997 eruption of Okmok Volcano, Alaska: A synthesis of remotely sensed imagery

USGS Publications Warehouse

Patrick, M.R.; Dehn, J.; Papp, K.R.; Lu, Z.; Dean, K.; Moxey, L.; Izbekov, P.; Guritz, R.

2003-01-01

Okmok Volcano, in the eastern Aleutian Islands, erupted in February and March of 1997 producing a 6-km-long lava flow and low-level ash plumes. This caldera is one of the most active in the Aleutian Arc, and is now the focus of international multidisciplinary studies. A synthesis of remotely sensed data (AirSAR, derived DEMs, Landsat MSS and ETM+ data, AVHRR, ERS, JERS, Radarsat) has given a sequence of events for the virtually unobserved 1997 eruption. Elevation data from the AirSAR sensor acquired in October 2000 over Okmok were used to create a 5-m resolution DEM mosaic of Okmok Volcano. AVHRR nighttime imagery has been analyzed between February 13 and April 11, 1997. Landsat imagery and SAR data recorded prior to and after the eruption allowed us to accurately determine the extent of the new flow. The flow was first observed on February 13 without precursory thermal anomalies. At this time, the flow was a large single lobe flowing north. According to AVHRR Band 3 and 4 radiance data and ground observations, the first lobe continued growing until mid to late March, while a second, smaller lobe began to form sometime between March 11 and 12. This is based on a jump in the thermal and volumetric flux determined from the imagery, and the physical size of the thermal anomalies. Total radiance values waned after March 26, indicating lava effusion had ended and a cooling crust was growing. The total area (8.9 km2), thickness (up to 50 m) and volume (1.54×108 m3) of the new lava flow were determined by combining observations from SAR, Landsat ETM+, and AirSAR DEM data. While the first lobe of the flow ponded in a pre-eruption depression, our data suggest the second lobe was volume-limited. Remote sensing has become an integral part of the Alaska Volcano Observatory’s monitoring and hazard mitigation efforts. Studies like this allow access to remote volcanoes, and provide methods to monitor potentially dangerous ones.

Data Analytics for SAR

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

Murphy, David Patrick; Calef, Matthew Thomas

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Refraction of coastal ocean waves

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Kasischke, E. S.

1981-01-01

Refraction of gravity waves in the coastal area off Cape Hatteras, NC as documented by synthetic aperture radar (SAR) imagery from Seasat orbit 974 (collected on September 3, 1978) is discussed. An analysis of optical Fourier transforms (OFTs) from more than 70 geographical positions yields estimates of wavelength and wave direction for each position. In addition, independent estimates of the same two quantities are calculated using two simple theoretical wave-refraction models. The OFT results are then compared with the theoretical results. A statistical analysis shows a significant degree of linear correlation between the data sets. This is considered to indicate that the Seasat SAR produces imagery whose clarity is sufficient to show the refraction of gravity waves in shallow water.

Determining Titan surface topography from Cassini SAR data

USGS Publications Warehouse

Stiles, Bryan W.; Hensley, Scott; Gim, Yonggyu; Bates, David M.; Kirk, Randolph L.; Hayes, Alex; Radebaugh, Jani; Lorenz, Ralph D.; Mitchell, Karl L.; Callahan, Philip S.; Zebker, Howard; Johnson, William T.K.; Wall, Stephen D.; Lunine, Jonathan I.; Wood, Charles A.; Janssen, Michael; Pelletier, Frederic; West, Richard D.; Veeramacheneni, Chandini

2009-01-01

A technique, referred to as SARTopo, has been developed for obtaining surface height estimates with 10 km horizontal resolution and 75 m vertical resolution of the surface of Titan along each Cassini Synthetic Aperture Radar (SAR) swath. We describe the technique and present maps of the co-located data sets. A global map and regional maps of Xanadu and the northern hemisphere hydrocarbon lakes district are included in the results. A strength of the technique is that it provides topographic information co-located with SAR imagery. Having a topographic context vastly improves the interpretability of the SAR imagery and is essential for understanding Titan. SARTopo is capable of estimating surface heights for most of the SAR-imaged surface of Titan. Currently nearly 30% of the surface is within 100 km of a SARTopo height profile. Other competing techniques provide orders of magnitude less coverage. We validate the SARTopo technique through comparison with known geomorphological features such as mountain ranges and craters, and by comparison with co-located nadir altimetry, including a 3000 km strip that had been observed by SAR a month earlier. In this area, the SARTopo and nadir altimetry data sets are co-located tightly (within 5-10 km for one 500 km section), have similar resolution, and as expected agree closely in surface height. Furthermore the region contains prominent high spatial resolution topography, so it provides an excellent test of the resolution and precision of both techniques.

Opium Field Detection in South Oxfordshire Using SAR Polarimetry

NASA Astrophysics Data System (ADS)

Walker, Nick; Marino, Armando

2011-03-01

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

Comparative analysis of recent satellite missions for multi-temporal SAR interferometry

NASA Astrophysics Data System (ADS)

Bovenga, Fabio; Refice, Alberto; Belmonte, Antonella; Pasquariello, Guido

2016-10-01

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, the atmospheric artifacts, the visibility problems related to the ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new interesting opportunity is provided by Sentinel-1 mission, which has a spatial resolution comparable to previous ESA C-band missions, and revisit times reduced to up to 6 days. It is envisioned that, by offering regular, global-scale coverage, improved temporal resolution and freely available imagery, Sentinel-1 will guarantee an increasing use of MTI for ground displacement investigations. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications to ground instability monitoring. Issues related to coherent target detection and mean velocity precision will be addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of multi-sensor ground instability investigation over the site of Marina di Lesina, Southern Italy, a village lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift pattern affecting the entire village area, and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been used, coming from both legacy ERS and ENVISAT missions, and last-generation Radarsat-2, COSMO-SkyMed, and Sentinel-1A sensors.

Fusion of radar and optical data for mapping and monitoring of water bodies

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyn

2017-10-01

Remote sensing techniques owe their great popularity to the possibility to obtain of rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. The main areas of interest for remote sensing research had always been concerned with environmental studies, especially water bodies monitoring. Many methods that are using visible and near- an infrared band of the electromagnetic spectrum had been already developed to detect surface water reservoirs. Moreover, the usage of an image obtained in visible and infrared spectrum allows quality monitoring of water bodies. Nevertheless, retrieval of water boundaries and mapping surface water reservoirs with optical sensors is still quite demanding. Therefore, the microwave data could be the perfect complement to data obtained with passive optical sensors to detect and monitor aquatic environment especially surface water bodies. This research presents the methodology to detect water bodies with open- source satellite imagery acquired with both optical and microwave sensors. The SAR Sentinel- 1 and multispectral Sentinel- 2 imagery were used to detect and monitor chosen reservoirs in Poland. In the research Level, 1 Sentinel- 2 data and Level 1 SAR images were used. SAR data were mainly used for mapping water bodies. Next, the results of water boundaries extraction with Sentinel-1 data were compared to results obtained after application of modified spectral indices for Sentinel- 2 data. The multispectral optical data can be used in the future for the evaluation of the quality of the reservoirs. Preliminary results obtained in the research had shown, that the fusion of data obtained with optical and microwave sensors allow for the complex detection of water bodies and could be used in the future quality monitoring of water reservoirs.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Observations of internal waves in the Gulf of California by SEASAT SAR

NASA Technical Reports Server (NTRS)

Fu, L. L.; Holt, B.

1983-01-01

Internal waves which are among the most commonly observed oceanic phenomena in the SEASAT SAR imagery are discussed. These waves are associated with the vertical displacements of constant water density surfaces in the ocean. Their amplitudes are maximum at depths where the water density changes most rapidly usually at depths from 50 to 100 m, whereas the horizontal currents associated with these waves are maximum at the sea surface where the resulting oscillatory currents modulate the sea surface roughness and produce the signatures detected by SAR.

Observations of internal waves in the Gulf of California by SEASAT SAR

NASA Astrophysics Data System (ADS)

Fu, L. L.; Holt, B.

1983-07-01

Internal waves which are among the most commonly observed oceanic phenomena in the SEASAT SAR imagery are discussed. These waves are associated with the vertical displacements of constant water density surfaces in the ocean. Their amplitudes are maximum at depths where the water density changes most rapidly usually at depths from 50 to 100 m, whereas the horizontal currents associated with these waves are maximum at the sea surface where the resulting oscillatory currents modulate the sea surface roughness and produce the signatures detected by SAR.

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

NASA Astrophysics Data System (ADS)

Tanguy, Marion; Bernier, Monique; Chokmani, Karem

2015-04-01

When a flood hits an inhabited area, managers and services responsible for public safety need precise, reliable and up to date maps of the areas affected by the flood, in order to quickly roll out and to coordinate the adequate intervention and assistance plans required to limit the human and material damages caused by the disaster. Synthetic aperture radar (SAR) sensors are now considered as one of the most adapted tool for flood detection and mapping in a context of crisis management. Indeed, due to their capacity to acquire data night and day, in almost all meteorological conditions, SAR sensors allow the acquisition of synoptic but detailed views of the areas affected by the flood, even during the active phases of the event. Moreover, new generation sensors such as RADARSAT-2, TerraSAR-X, COSMO-SkyMed, are providing very high resolution images of the disaster (down to 1m ground resolution). Further, critical improvements have been made on the temporal repetitivity of acquisitions and on data availability, through the development of satellite constellations (i.e the four COSMO-Skymed or the Sentinel-1A and 1B satellites) and thanks to the implementation of the International Charter "Space and Major Disasters", which guarantees high priority images acquisition and delivery with 4 to 12 hours. If detection of open water flooded areas is relatively straightforward with SAR imagery, flood detection in built-up areas is often associated with important issues. Indeed, because of the side looking geometry of the SAR sensors, structures such as tall vegetation and structures parallel to the satellite direction of travel may produce shadow and layover effects, leading to important over and under-detections of flooded pixels. Besides, the numerous permanent water-surfaces like radar response areas present in built-up environments, such as parking lots, roads etc., may be mixed up with flooded areas, resulting in substantial inaccuracies in the final flood map. In spite of the many efforts recently done toward the improvements of the accuracy of the processing algorithms for flood detection in urban areas with high resolution SAR imagery, these algorithms still encounter difficulties to detect urban flooded pixels with precision. The difficulties do not seem to be only ascribable to the choice of SAR image processing methods, but can also be imputed to the limitations of the SAR imaging technique itself in urban areas. We propose a fully automatic and effective approach for near-real time delineation of urban and rural flooded areas, which combines the capacity of SAR imagery to detect open water areas, and explicit hydrodynamic characteristics of the region affected by the flood, expressed through flood recurrence interval data. This innovative approach has been tested with RADARSAT-2 Fine and Ultrafine Mode images acquired during the 2011 Richelieu River flooding, in Canada. It proved successful in accurately delineating flooding in urban and rural areas, with a RMSE inferior to 2 pixels.

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.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

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

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 pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

Agricultural crop harvest progress monitoring by fully polarimetric synthetic aperture radar imagery

NASA Astrophysics Data System (ADS)

Yang, Hao; Zhao, Chunjiang; Yang, Guijun; Li, Zengyuan; Chen, Erxue; Yuan, Lin; Yang, Xiaodong; Xu, Xingang

2015-01-01

Dynamic mapping and monitoring of crop harvest on a large spatial scale will provide critical information for the formulation of optimal harvesting strategies. This study evaluates the feasibility of C-band polarimetric synthetic aperture radar (PolSAR) for monitoring the harvesting progress of oilseed rape (Brassica napus L.) fields. Five multitemporal, quad-pol Radarsat-2 images and one optical ZY-1 02C image were acquired over a farmland area in China during the 2013 growing season. Typical polarimetric signatures were obtained relying on polarimetric decomposition methods. Temporal evolutions of these signatures of harvested fields were compared with the ones of unharvested fields in the context of the entire growing cycle. Significant sensitivity was observed between the specific polarimetric parameters and the harvest status of oilseed rape fields. Based on this sensitivity, a new method that integrates two polarimetric features was devised to detect the harvest status of oilseed rape fields using a single image. The validation results are encouraging even for the harvested fields covered with high residues. This research demonstrates the capability of PolSAR remote sensing in crop harvest monitoring, which is a step toward more complex applications of PolSAR data in precision agriculture.

Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders.

PubMed

Gallego, Antonio-Javier; Gil, Pablo; Pertusa, Antonio; Fisher, Robert B

2018-03-06

In this work, we use deep neural autoencoders to segment oil spills from Side-Looking Airborne Radar (SLAR) imagery. Synthetic Aperture Radar (SAR) has been much exploited for ocean surface monitoring, especially for oil pollution detection, but few approaches in the literature use SLAR. Our sensor consists of two SAR antennas mounted on an aircraft, enabling a quicker response than satellite sensors for emergency services when an oil spill occurs. Experiments on TERMA radar were carried out to detect oil spills on Spanish coasts using deep selectional autoencoders and RED-nets (very deep Residual Encoder-Decoder Networks). Different configurations of these networks were evaluated and the best topology significantly outperformed previous approaches, correctly detecting 100% of the spills and obtaining an F 1 score of 93.01% at the pixel level. The proposed autoencoders perform accurately in SLAR imagery that has artifacts and noise caused by the aircraft maneuvers, in different weather conditions and with the presence of look-alikes due to natural phenomena such as shoals of fish and seaweed.

The Use of Satellite and Aircraft SAR to Detect and Chart Hazards to Navigation.

DTIC Science & Technology

1983-08-01

CLASSIFICATION OF THIS PAGE (W~ho D~Fiamwdj REPOT DCUMNTATON AGEREAD INSTRUCTIONSREPOT DCUMNTATON AGEBEFORE COMPLETING FORM I REPORT NUMBER 1 OVT ACCESSION AO. 3...Science Data Center is thanked for providing copies of selected SIR-A imagery. av L i _ _ _ .* . -_i [RIM RADAR DIVISION TABLE OF CONTENTS 1 ...INTRODUCTION ..................................................... 1 2. EXECUTIVE SUMMARY ................................................ 5 3. SURVEY OF SAR

Computationally Efficient Resampling of Nonuniform Oversampled SAR Data

DTIC Science & Technology

2010-05-01

noncoherently . The resample data is calculated using both a simple average and a weighted average of the demodulated data. The average nonuniform...trials with randomly varying accelerations. The results are shown in Fig. 5 for the noncoherent power difference and Fig. 6 for and coherent power...simple average. Figure 5. Noncoherent difference between SAR imagery generated with uniform sampling and nonuniform sampling that was resampled

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.

Classifying coastal resources by integrating optical and radar imagery and color infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, Gene A.; Sapkota, Sijan

1998-01-01

A progressive classification of a marsh and forest system using Landsat Thematic Mapper (TM), color infrared (CIR) photograph, and ERS-1 synthetic aperture radar (SAR) data improved classification accuracy when compared to classification using solely TM reflective band data. The classification resulted in a detailed identification of differences within a nearly monotypic black needlerush marsh. Accuracy percentages of these classes were surprisingly high given the complexities of classification. The detailed classification resulted in a more accurate portrayal of the marsh transgressive sequence than was obtainable with TM data alone. Individual sensor contribution to the improved classification was compared to that using only the six reflective TM bands. Individually, the green reflective CIR and SAR data identified broad categories of water, marsh, and forest. In combination with TM, SAR and the green CIR band each improved overall accuracy by about 3% and 15% respectively. The SAR data improved the TM classification accuracy mostly in the marsh classes. The green CIR data also improved the marsh classification accuracy and accuracies in some water classes. The final combination of all sensor data improved almost all class accuracies from 2% to 70% with an overall improvement of about 20% over TM data alone. Not only was the identification of vegetation types improved, but the spatial detail of the classification approached 10 m in some areas.

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

NASA Technical Reports Server (NTRS)

Monaldo, Frank M.; Lyzenga, David R.

1988-01-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

Sentinel-1 and ground-based sensors for a continuous monitoring of the Corvara landslide kinematic (South Tirol, Italy)

NASA Astrophysics Data System (ADS)

Schlögel, Romy; Darvishi, Mehdi; Cuozzo, Giovanni; Kofler, Christian; Rutzinger, Martin; Zieher, Thomas; Toschi, Isabella; Remondino, Fabio

2017-04-01

Sentinel-1 mission allows us to have Synthetic Aperture Radar (SAR) acquisitions over large areas every 6 days with spatial resolution of 20 m. This new open-source generation of satellites has enhanced the capabilities for continuously studying earth surface changes. Over the past two decades, several studies have demonstrated the potential of Differential Synthetic Aperture Radar Interferometry (DInSAR) for detecting and quantifying land surface deformation. DInSAR limitations and challenges are linked to the SAR properties and the field conditions (especially in Alpine environments) leading to spatial and temporal decorrelation of the SAR signal. High temporal decorrelation can be caused by changes in vegetation (particularly in non-urban areas), atmospheric conditions or high ground surface velocity. In this study, kinematics of the complex and vegetated Corvara landslide, situated in Val Badia (South Tirol, Italy), are monitored by a network of 3 permanent and 13 monthly Differential Global Positioning System (DGPS) stations. The slope displacement rates are found to be highly unsteady and reach several meters a year. This analysis focuses on evaluating the limitations of Sentinel-1 imagery processed with Small Baseline Subset (SBAS) technique in comparison to ground-based measurements for assessing the landslide kinematic linked to meteorological conditions. Selecting some particular acquisitions, coherence thresholds and unwrapping processes gives various results in terms of reliability and accuracy supporting the understanding of the landslide velocity field. The evolution of the coherence and phase signals are studied according to the changing field conditions and the monitored ground-based displacements. DInSAR deformation maps and residual topographic heights are finally compared with difference of high resolution Digital Elevation Models at local scale. This research is conducted within the project LEMONADE (http://lemonade.mountainresearch.at) funded by the Euregio Science Fund.

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

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.

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.

SAR imaging and hydrodynamic analysis of ocean bottom topographic waves

NASA Astrophysics Data System (ADS)

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

2006-09-01

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

Analysis of Wind and Sea State in SAR data of Hurricanes

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

The SIR-B science investigations plan

NASA Technical Reports Server (NTRS)

1984-01-01

Shuttle Imaging Radar-B (SIR-B) is the second synthetic aperture radar (SAR) to be flown on the National Aeronautics and Space Administration's Space Transportation System (Shuttle). It is the first spaceborne SAR to feature an antenna that allows acquisition of multiincidence angle imagery. An international team of scientists will use SIR-B to conduct investigations in a wide range of disciplines. The radar, the mission, and the investigations are described.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

USGS Publications Warehouse

Lu, Z.; Kwoun, Oh-Ig

2008-01-01

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

The physical basis for estimating wave energy spectra from SAR imagery

NASA Technical Reports Server (NTRS)

Lyzenga, David R.

1987-01-01

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

Spaceborne synthetic aperture radar signal processing using FPGAs

NASA Astrophysics Data System (ADS)

Sugimoto, Yohei; Ozawa, Satoru; Inaba, Noriyasu

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

Miles, Katie; Willis, Ian; Benedek, Corinne; Williamson, Andrew; Tedesco, Marco

2017-04-01

Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) are an important component of the ice sheet's mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) to investigate SGLs in West Greenland. SAR can image through cloud and in darkness, overcoming some of the limitations of commonly used optical sensors. A semi automated algorithm is developed to detect surface lakes from Sentinel images during the 2015 summer. It generally detects water in all locations where a Landsat-8 NDWI classification (with a relatively high threshold value) detects water. A combined set of images from Landsat-8 and Sentinel-1 is used to track lake behaviour at a comparable temporal resolution to that which is possible with MODIS, but at a higher spatial resolution. A fully automated lake drainage detection algorithm is used to investigate both rapid and slow drainages for both small and large lakes through the summer. Our combined Landsat-Sentinel dataset, with a temporal resolution of three days, could track smaller lakes (mean 0.089 km2) than are resolvable in MODIS (minimum 0.125 km2). Small lake drainage events (lakes smaller than can be detected using MODIS) were found to occur at lower elevations ( 200 m) and slightly earlier in the melt season than larger events, as were slow lake drainage events compared to rapid events. The Sentinel imagery allows the analysis to be extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August, 1270 m mean elevation). Finally, the Sentinel imagery allows subsurface lakes (which are invisible to optical sensors) to be detected, and, for the first time, their dates of appearance and freeze-through to be calculated (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface lakes detected in this study (1593 m mean elevation). Sentinel imagery therefore provides great potential for tracking melting, water movement and freezing within the firn zone of the GrIS.

School children from Punta Arenas, Chile, talk with Dr. David Imel, an AirSAR scientist from NASA JPL, during AirSAR 2004

NASA Image and Video Library

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.

SP mountain data analysis

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

A P-band SAR interference filter

NASA Technical Reports Server (NTRS)

Taylor, Victor B.

1992-01-01

The synthetic aperture radar (SAR) interference filter is an adaptive filter designed to reduce the effects of interference while minimizing the introduction of undesirable side effects. The author examines the adaptive spectral filter and the improvement in processed SAR imagery using this filter for Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) data. The quality of these improvements is determined through several data fidelity criteria, such as point-target impulse response, equivalent number of looks, SNR, and polarization signatures. These parameters are used to characterize two data sets, both before and after filtering. The first data set consists of data with the interference present in the original signal, and the second set consists of clean data which has been coherently injected with interference acquired from another scene.

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

Resolving Topographic Changes at Volcanoes Using Pleiades-1 Tri-stereo Imagery and Other Methods: the Example of Fogo Volcano.

NASA Astrophysics Data System (ADS)

Bagnardi, M.; González, P. J.; Hooper, A. J.; Richter, N.; Walter, T. R.

2016-12-01

Precise, quantitative analyses of topographic changes associated with the emplacement of volcanic products provide the means to infer key parameters for the assessment of hazards associated with volcanic processes. Different techniques can be applied to generate high-resolution digital elevation models (DEMs), using both ground-based and air/space-borne sensors. In this study, we first evaluate the use of very high resolution (VHR) tri-stereo optical imagery from the Pleiades-1 satellite constellation for volcanological applications. With this scope, we generate a 1 m resolution DEM of Fogo Volcano, Cape Verde, and use this DEM to quantify topographic changes associated with the 2014-2015 eruption. We observe that, when compared with the classic stereo approach, the use of tri-stereo imagery highly enhances the ability of photogrammetric techniques to estimate heights through increasing the point cloud density and by reducing the number of pixels with no measurements. From the Pleiades-1 post-eruption topography we subtract heights from a pre-eruptive DEM, obtained using spaceborne synthetic aperture radar (SAR) data from the TanDEM-X mission, and estimate the volume of the 2014-2015 lava flow ( 46 million m3) and the mean output rate throughout the eruption (5-7 m3/s). We subsequently use complementary datasets from a variety of sensors (Terrestrial Laser Scanning, UAV optical imagery, Structure from Motion from hand-held DSLR cameras) to fill gaps in Pleiades-1 data coverage and to generate a merged, high-resolution DEM of the volcano. To weight the contribution of each dataset, we carry out a comparative analysis of the accuracy of the different DEMs and identify advantages and disadvantages associated with the use of each technique. Finally, using SAR data acquired by the Sentinel-1a satellite, we apply SAR interferometry (InSAR) and measure the lava flow subsidence due to cooling and contraction in the months after its emplacement and compare this to the measured lava flow thickness. Maximum subsidence is recorded in those areas where lava flow thickness is also maximum, and where the substrate onto which the lava flow was emplaced is highly compactable.

The Utility of SAR to Monitor Ocean Processes.

DTIC Science & Technology

1981-11-01

echo received from ocean waves include the motion of the a horizontally polarized wave will have its E vector parallel to scattering surfaces, the so...radiation is defined by the direction of the electric field intensity, E, vector . For example, a horizontally polarized wave will have its E vector ...Oil Spill Off the East Coast of the United States ................ .... 55 19. L-band Parallel and Cross Polarized SAR Imagery of Ice in the Beaufort

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

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Glacier and snow hydrology investigation in the Upper Indus Basin using Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Jouvet, G.; Stastny, T.; Oettershagen, P.; Hugentobler, M.; Mantel, T.; Melzer, A.; Weidmann, Y.; Funk, M.; Siegwart, R.; Lund, J.; Forster, R. R.; Burgess, E. W.

2017-12-01

The flows of the Indus River are a vital resource for food security, ecosystem services, hydropower and economy for China, India and Pakistan. Glaciers of the Karakoram Mountains are the largest drivers of discharge in the Upper Indus Basin, and combined with snowmelt constitute the majority of runoff. While recently verified in near balance, the glaciers of the Karakoram exhibit substantial variation both spatially and temporally. Complex climatology, coupled with the challenges of field study in this rugged range, illicit notable uncertainties in observation and prediction of glacial status. Satellite-borne radar sensors acquire imagery regardless of cloud cover or time of day, and offer unique insights into physical processes due to their wavelength. Here we utilize Sentinel-1 synthetic aperture radar (SAR) imagery to track transient snow lines on glaciers of the Shigar watershed throughout multiple ablation seasons, and discuss the utility of this information in relation to snow and glacier mass balance. As the Sentinel-1 sensor ascending and descending passes capture morning and evening imagery in this region, diurnal radar variations will also be explored as indicators of melt-refreeze cycles and their correlation with peak runoff.

Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders

PubMed Central

2018-01-01

In this work, we use deep neural autoencoders to segment oil spills from Side-Looking Airborne Radar (SLAR) imagery. Synthetic Aperture Radar (SAR) has been much exploited for ocean surface monitoring, especially for oil pollution detection, but few approaches in the literature use SLAR. Our sensor consists of two SAR antennas mounted on an aircraft, enabling a quicker response than satellite sensors for emergency services when an oil spill occurs. Experiments on TERMA radar were carried out to detect oil spills on Spanish coasts using deep selectional autoencoders and RED-nets (very deep Residual Encoder-Decoder Networks). Different configurations of these networks were evaluated and the best topology significantly outperformed previous approaches, correctly detecting 100% of the spills and obtaining an F1 score of 93.01% at the pixel level. The proposed autoencoders perform accurately in SLAR imagery that has artifacts and noise caused by the aircraft maneuvers, in different weather conditions and with the presence of look-alikes due to natural phenomena such as shoals of fish and seaweed. PMID:29509720

Geological and Structural Patterns on Titan Enhanced Through Cassini's SAR PCA and High-Resolution Radiometry

NASA Astrophysics Data System (ADS)

Paganelli, F.; Schubert, G.; Lopes, R. M. C.; Malaska, M.; Le Gall, A. A.; Kirk, R. L.

2016-12-01

The current SAR data coverage on Titan encompasses several areas in which multiple radar passes are present and overlapping, providing additional information to aid the interpretation of geological and structural features. We exploit the different combinations of look direction and variable incidence angle to examine Cassini Synthetic Aperture RADAR (SAR) data using the Principal Component Analysis (PCA) technique and high-resolution radiometry, as a tool to aid in the interpretation of geological and structural features. Look direction and variable incidence angle is of particular importance in the analysis of variance in the images, which aid in the perception and identification of geological and structural features, as extensively demonstrated in Earth and planetary examples. The PCA enhancement technique uses projected non-ortho-rectified SAR imagery in order to maintain the inherent differences in scattering and geometric properties due to the different look directions, while enhancing the geometry of surface features. The PC2 component provides a stereo view of the areas in which complex surface features and structural patterns can be enhanced and outlined. We focus on several areas of interest, in older and recently acquired flybys, in which evidence of geological and structural features can be enhanced and outlined in the PC1 and PC2 components. Results of this technique provide enhanced geometry and insights into the interpretation of the observed geological and structural features, thus allowing a better understanding towards the geology and tectonics on Titan.

Observation of wave refraction at an ice edge by synthetic aperture radar

NASA Technical Reports Server (NTRS)

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

1991-01-01

In this note the refraction of waves at the ice edge is studied by using aircraft synthesis aperture radar (SAR). Penetration of a dominant swell from open ocean into the ice cover was observed by SAR during the Labrador Ice Margin Experiment (LIMEX), conducted on the marginal ice zone (MIZ) off the east coast of Newfoundland, Canada, in March 1987. At an ice edge with a large curvature, the dominant swell component disappeared locally in the SAR imagery. Six subscenes of waves in the MIZ from the SAR image have been processed, revealing total reflection, refraction, and energy reduction of the ocean waves by the ice cover. The observed variations of wave spectra from SAR near the ice edge are consistent with the model prediction of wave refraction at the ice edge due to the change of wave dispersion relation in ice developed by Liu and Mollo-Christensen (1988).

Target surface finding using 3D SAR data

NASA Astrophysics Data System (ADS)

Ruiter, Jason R.; Burns, Joseph W.; Subotic, Nikola S.

2005-05-01

Methods of generating more literal, easily interpretable imagery from 3-D SAR data are being studied to provide all weather, near-visual target identification and/or scene interpretation. One method of approaching this problem is to automatically generate shape-based geometric renderings from the SAR data. In this paper we describe the application of the Marching Tetrahedrons surface finding algorithm to 3-D SAR data. The Marching Tetrahedrons algorithm finds a surface through the 3-D data cube, which provides a recognizable representation of the target surface. This algorithm was applied to the public-release X-patch simulations of a backhoe, which provided densely sampled 3-D SAR data sets. The performance of the algorithm to noise and spatial resolution were explored. Surface renderings were readily recognizable over a range of spatial resolution, and maintained their fidelity even under relatively low Signal-to-Noise Ratio (SNR) conditions.

Utilization of remote sensing in Alaska permafrost studies

NASA Technical Reports Server (NTRS)

Hall, D. K.

1981-01-01

Permafrost related features such as: aufeis, tundra, thaw lakes and subsurface ice features were studied. LANDSAT imagery was used to measure the extent and distribution of aufeis in Arctic Slope rivers over a period of 7 years. Interannual extent of large aufeis fields was found to vary significantly. Digital LANDSAT data were used to study the short term effects of a tundra fire which burned a 48 sq km area in northwestern Alaska. Vegetation regrowth was inferred from Landsat spectral reflectance increases and compared to in-situ measurements. Aircraft SAR (Synethic Aperture Radar) imagery was used in conjunction with LANDSAT imagery used in conjunction with LANDSAT imagery to qualitatively determine depth categories for thaw lakes in northern Alaska.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Shadow Probability of Detection and False Alarm for Median-Filtered SAR Imagery

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

Raynal, Ann Marie; Doerry, Armin Walter; Miller, John A.

2014-06-01

Median filtering reduces speckle in synthetic aperture radar (SAR) imagery while preserving edges, at the expense of coarsening the resolution, by replacing the center pixel of a sliding window by the median value. For shadow detection, this approach helps distinguish shadows from clutter more easily, while preserving shadow shape delineations. However, the nonlinear operation alters the shadow and clutter distributions and statistics, which must be taken into consideration when computing probability of detection and false alarm metrics. Depending on system parameters, median filtering can improve probability of detection and false alarm by orders of magnitude. Herein, we examine shadow probabilitymore » of detection and false alarm in a homogeneous, ideal clutter background after median filter post-processing. Some comments on multi-look processing effects with and without median filtering are also made.« less

Joint synthetic aperture radar plus ground moving target indicator from single-channel radar using compressive sensing

DOEpatents

Thompson, Douglas; Hallquist, Aaron; Anderson, Hyrum

2017-10-17

The various embodiments presented herein relate to utilizing an operational single-channel radar to collect and process synthetic aperture radar (SAR) and ground moving target indicator (GMTI) imagery from a same set of radar returns. In an embodiment, data is collected by randomly staggering a slow-time pulse repetition interval (PRI) over a SAR aperture such that a number of transmitted pulses in the SAR aperture is preserved with respect to standard SAR, but many of the pulses are spaced very closely enabling movers (e.g., targets) to be resolved, wherein a relative velocity of the movers places them outside of the SAR ground patch. The various embodiments of image reconstruction can be based on compressed sensing inversion from undersampled data, which can be solved efficiently using such techniques as Bregman iteration. The various embodiments enable high-quality SAR reconstruction, and high-quality GMTI reconstruction from the same set of radar returns.

Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery

NASA Astrophysics Data System (ADS)

Fors, Ane S.; Divine, Dmitry V.; Doulgeris, Anthony P.; Renner, Angelika H. H.; Gerland, Sebastian

2017-03-01

In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Co-polarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6. 2 m s-1), with a Spearman's correlation coefficient of 0. 46. At low wind speeds (0. 6 m s-1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of -0. 53. To further investigate these relations, regression fits were made both for the intermediate (R2fit = 0. 21) and low (R2fit = 0. 26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51 × 51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above ˜ 40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future.

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

A data compression technique for synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Minden, G. J.

1986-01-01

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

Making Mosaics Of SAR Imagery

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.

Preliminary observations of Labrador Sea marginal ice zone rheology using C-band SAR

NASA Technical Reports Server (NTRS)

Drinkwater, Mark R.; Squire, Vernon A.

1989-01-01

SAR imagery collected in the Labrador Sea during Limex '87 are used to interpret modes of sea-ice deformation. The ice canopy exhibited two distinct rheologies separated by a clear line of shear; a quasi-brittle inner regime and a nonlinear viscous outer regime. A single constitutive relation capable of modeling both is unlikely within a plastic rate-independent formulation. Rate dependent effects are discussed as an explanation for brittle fracture in ductile materials.

Evaluating suitability of Pol-SAR (TerraSAR-X, Radarsat-2) for automated sea ice classification

NASA Astrophysics Data System (ADS)

Ressel, Rudolf; Singha, Suman; Lehner, Susanne

2016-05-01

Satellite borne SAR imagery has become an invaluable tool in the field of sea ice monitoring. Previously, single polarimetric imagery were employed in supervised and unsupervised classification schemes for sea ice investigation, which was preceded by image processing techniques such as segmentation and textural features. Recently, through the advent of polarimetric SAR sensors, investigation of polarimetric features in sea ice has attracted increased attention. While dual-polarimetric data has already been investigated in a number of works, full-polarimetric data has so far not been a major scientific focus. To explore the possibilities of full-polarimetric data and compare the differences in C- and X-bands, we endeavor to analyze in detail an array of datasets, simultaneously acquired, in C-band (RADARSAT-2) and X-band (TerraSAR-X) over ice infested areas. First, we propose an array of polarimetric features (Pauli and lexicographic based). Ancillary data from national ice services, SMOS data and expert judgement were utilized to identify the governing ice regimes. Based on these observations, we then extracted mentioned features. The subsequent supervised classification approach was based on an Artificial Neural Network (ANN). To gain quantitative insight into the quality of the features themselves (and reduce a possible impact of the Hughes phenomenon), we employed mutual information to unearth the relevance and redundancy of features. The results of this information theoretic analysis guided a pruning process regarding the optimal subset of features. In the last step we compared the classified results of all sensors and images, stated respective accuracies and discussed output discrepancies in the cases of simultaneous acquisitions.

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

PubMed

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

2018-05-12

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

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

NASA Astrophysics Data System (ADS)

Gambheer, Phani Raj

2012-07-01

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

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

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Nicoll, J.

2011-12-01

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

Further insights into glacier changes derived from declassified reconnaissance imagery (Corona and Hexagon)

NASA Astrophysics Data System (ADS)

Goerlich, Franz; Paul, Frank; Bolch, Tobias

2017-04-01

The variable and often complex dynamics of the glaciers in High Mountain Asia have recently been studied intensively from satellite imagery. Time-series of optical and SAR imagery revealed rapid changes and strong trends in glacier extent and surface flow velocities as well as elevation changes from differencing of DEMs and altimetry sensors over the 1990 to 2015 period. In contrast to nearly all other regions in the world, especially glaciers in the Karakoram had balanced budgets and often rapidly advanced during surge events and retreated thereafter. This complicates the interpretation of climate change impacts on the glaciers in the region and leaves high uncertainties for calculation of future glacier and run-off development. A key for an improved understanding of glacier dynamics in this region is an extension of the observation period. This can be achieved using Corona and Hexagon reconnaissance satellite imagery from the 1960s and 1970s providing a comparably high spatial resolution between 2.7 and 7.6 m. Thereby, the keyhole satellites allow both, determination of glacier extents and calculation of DTMs from stereo image pairs that can be used to determine geodetic volume/ mass changes. The latter has already been performed on a regional scale for glaciers in the Himalaya and Tien Shan using Hexagon and Corona imagery with high accuracies. However, due to a particular camera model and complex distortion effects, which is especially the case for Corona images, the analysis is a challenging task. Therefore, we have developed a workflow to generate DTMs and orthophotos from Corona that considers the complex camera model. This study will present the workflow with its limitations, challenges and the obtained accuracy over stable ground. With our generated DTMs and Orthophotos, we already calculated mass balances and length changes for the Ak-Shirak range in Tian Shan and currently adapting the workflow to the Karakoram and Pamir mountains. Furthermore, the DTMs help us to detect glaciers of surge-type behaviour and to reconstruct full surge cycles with the extent to the early and mid 1960s.

NASA Dryden Mission Manager Walter Klein poses with school children that visited the DC-8 during AirSAR 2004 in Punta Arenas, Chile

NASA Image and Video Library

2004-03-10

NASA Dryden Mission Manager Walter Klein poses with school children that visited the DC-8 during AirSAR 2004 in Punta Arenas, Chile. 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.

Static Rupture Model of the 2010 M7.2 El Mayor-Cucapah Earthquake from ALOS, ENVISAT, SPOT and GPS Data

NASA Astrophysics Data System (ADS)

Fialko, Y.; Gonzalez, A.; Gonzalez-Garcia, J. J.; Barbot, S.; Leprince, S.; Sandwell, D. T.; Agnew, D. C.

2010-12-01

The April 4, 2010 "Easter Sunday" earthquake on the US-Mexico border was the largest event to strike Southern California in the last 18 years. The earthquake occurred on a northwest trending fault close to, but not coincident with the identified 1892 Laguna Salada rupture. We investigate coseismic deformation due to the 2010 El Mayor-Cucapah earthquake using Synthetic Aperture Radar (SAR) imagery form ENVISAT and ALOS satellites, optical imagery from SPOT-5 satellite, and continuous and campaign GPS data. The earliest campaign postseismic GPS survey was conducted within days after the earthquake, and provided the near-field cosesmic offsets. Along-track SAR interferograms and amplitude cross-correlation of optical images reveal a relatively simple continuous fault trace with maximum offsets of the order of 3 meters. This is in contrast to the results of geological mapping that portrayed a complex broad zone of distributed faulting. Also, SAR data indicate that the rupture propagated bi-laterally from the epicenter near the town of Durango both to the North-West into the Cucapah mountains and to the South-East into the Mexically valley. The inferred South-East part of the rupture was subsequently field-checked and associated with several fresh scarps, although overall the earthquake fault does not have a conspicuous surface trace South-East of the hypocenter. It is worth noting that the 2010 earthquake propagated into stress shadows of prior events - the Laguna Salada earthquake that ruptured the North-West part of the fault in 1892, and several M6+ earthquakes that ruptured the South-East part of the fault over the last century. Analysis of the coseismic displacement field at the Earth's surface (in particular, the full 3-component displacement field retrieved from SAR and optical imagery) shows a pronounced asymmetry in horizontal displacements across both nodal planes. The maximum displacements are observed in the North-Eastern and South-Western quadrants. This pattern cannot be explained by oblique slip on a quasi-planar fault. Multi-parametric inversions of the space geodetic data suggest that the El Mayor-Cucapah earthquake occurred on a helix-shaped rupture, with Eastward dip in the Northern section and Westward dip in the Southern section. This interpretation is consistent with field observations of the surface rupture and aftershock data, and provides an explanation for a strong non-double-couple component suggested by the seismic moment tensor solution. The total geodetic moment of our best-fitting model is in a good agreement with the seismic moment. We will also discuss effects of the elastic structure on the inferred static rupture model, and observations of early postseismic deformation.

AIRSAR observations of the Gulf Stream with interpretation from sea truth and modeling

NASA Technical Reports Server (NTRS)

Valenzuela, G. R.; Chubb, S. R.; Marmorino, G. O.; Trump, C. L.; Lee, J. S.; Cooper, A. L.; Askari, F.; Keller, W. C.; Kaiser, J. A. C.; Mied, R. P.

1991-01-01

On 20 Jul., JPL/DC-8 synthetic aperture radar (SAR) participated in the 17-21 Jul. 1990 NRL Gulf Stream (GS) experiment in preparation for SIR-C missions in 1993, 1994, and 1996 for calibration purposes and to check modes and techniques for operation at our experimental site off the east coast of the US. During this experiment, coordinated and near simultaneous measurements were performed from ship (R/V Cape Henlopen) and other aircraft (NADC/P-3 and NRL/P-3) to address scientific questions relating to the origin of 'slick-like' features observed by Scully-Power, the refraction and modulation of waves by variable currents, the effect of current and thermal fronts on radar imagery signatures and the modification of Kelvin ship wakes by fronts. The JPL/DC-8 and NADC/P-3 SAR's are fully polarimetric systems. Their composite frequency range varies between P- and X-band. We describe in detail the Airborne SAR (AIRSAR) participation in the Jul. 1990 GS experiment and present preliminary results of the ongoing analysis and interpretation of the radar imagery in the context of ground truth, other remote measurements, and modeling efforts.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Sea ice type maps from Alaska synthetic aperture radar facility imagery: An assessment

NASA Technical Reports Server (NTRS)

Fetterer, Florence M.; Gineris, Denise; Kwok, Ronald

1994-01-01

Synthetic aperture radar (SAR) imagery received at the Alaskan SAR Facility is routinely and automatically classified on the Geophysical Processor System (GPS) to create ice type maps. We evaluated the wintertime performance of the GPS classification algorithm by comparing ice type percentages from supervised classification with percentages from the algorithm. The root mean square (RMS) difference for multiyear ice is about 6%, while the inconsistency in supervised classification is about 3%. The algorithm separates first-year from multiyear ice well, although it sometimes fails to correctly classify new ice and open water owing to the wide distribution of backscatter for these classes. Our results imply a high degree of accuracy and consistency in the growing archive of multiyear and first-year ice distribution maps. These results have implications for heat and mass balance studies which are furthered by the ability to accurately characterize ice type distributions over a large part of the Arctic.

L to R; Walter Klein (in tan flight suit), Tim Miller, and David Bushman briefing press in Santiago, Chile, for NASA's AirSAR 2004 mission

NASA Image and Video Library

2004-03-10

L to R; NASA Dryden Mission Manager Walter Klein (in tan flight suit), JPL AirSAR Scientist Tim Miller, and Mission Manager David Bushman briefing press in Santiago, Chile, for NASA's AirSAR 2004 mission. 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.

Summer snowmelt patterns in the South Shetlands using TerraSAR-X imagery

NASA Astrophysics Data System (ADS)

Mora, C.; Jimenez, J. J.; Catalao Fernades, J.; Ferreira, A.; David, A.; Ramos, M.; Vieira, G.

2014-12-01

Snow plays an important role in controlling ground thermal regime and thus influencing permafrost distribution in the lower areas of the South Shetlands archipelago, where late lying snowpatches protect the soil from summer warming. However, summer snow distribution is complex in the mountainous environments of the Maritime Antarctica and it is very difficult to obtain accurate mapping products of snow cover extent and also to monitor snowmelt. Field observations of snow cover in the region are currently based on: i) thickness data from a very scarce network of meteorological stations, ii) temperature poles allowing to estimate snow thickness, iii) and time-lapse cameras allowing for assessing snow distribution over relatively small areas. The high cloudiness of the Maritime Antarctic environment limits good mapping results from the analysis of optical remote sensing imagery such as Landsat, QuickBird or GeoEye. Therefore, microwave sensors provide the best imagery, since they are not influenced by cloudiness and are sensitive to wet-snow, typical of the melting season. We have acquired TerraSAR-X scenes for Deception and Livingston Islands for January-March 2014 in spotlight (HH, VV and HH/VV) and stripmap modes (HH) and analyse the radar backscattering for determining the differences between wet-snow, dry-snow and bare soil aiming at developing snow melt pattern maps. For ground truthing, snowpits were dug in order to characterize snow stratigraphy, grain size, grain type and snow density and to evaluate its effects on radar backscattering. Time-lapse cameras allow to identify snow patch boundaries in the field and ground surface temperatures obtained with minloggers, together with air temperatures, allow to identify the presence of snow cover in the ground. The current research is conducted in the framework of the project PERMANTAR-3 (Permafrost monitoring and modelling in Antarctic Peninsula - PTDC/AAG-GLO/3908/2012 of the FCT and PROPOLAR).

SEASAT synthetic-aperture radar data user's manual

NASA Technical Reports Server (NTRS)

Pravdo, S. H.; Huneycutt, B.; Holt, B. M.; Held, D. N.

1983-01-01

The SEASAT Synthetic-Aperture Radar (SAR) system, the data processors, the extent of the image data set, and the means by which a user obtains this data are described and the data quality is evaluated. The user is alerted to some potential problems with the existing volume of SEASAT SAR image data, and allows him to modify his use of that data accordingly. Secondly, the manual focuses on the ultimate focuses on the ultimate capabilities of the raw data set and evaluates the potential of this data for processing into accurately located, amplitude-calibrated imagery of high resolution. This allows the user to decide whether his needs require special-purpose data processing of the SAR raw data.

SAR investigations of glaciers in northwestern North America

NASA Technical Reports Server (NTRS)

Lingle, Craig S.; Harrison, William D.

1995-01-01

The objective of this project was to investigate the utility of satellite synthetic aperture radar (SAR) imagery for measurement of geophysical parameters on Alaskan glaciers relevant to their mass balance and dynamics, including: (1) the positions of firn lines (late-summer snow lines); (2) surface velocities on fast-flowing (surging) glaciers, and also on slower steady-flow glaciers; and (3) the positions and changes in the positions of glacier termini. Preliminary studies of topography and glacier surface velocity with SAR interferometry have also been carried out. This project was motivated by the relationships of multi-year to decadal changes in glacier geometry to changing climate, and the probable significant contribution of Alaskan glaciers to rising sea level.

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

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

NASA Technical Reports Server (NTRS)

Li, Shu-Sun; Romanovsky, V.; Lovick, Joe; Wang, Z.; Peterson, Rorik

2003-01-01

A method of mapping the active layer of Arctic permafrost using a combination of conventional synthetic aperture radar (SAR) backscatter and more sophisticated interferometric SAR (INSAR) techniques is proposed. The proposed research is based on the sensitivity of radar backscatter to the freeze and thaw status of the surface soil, and the sensitivity of INSAR techniques to centimeter- to sub-centimeter-level surface differential deformation. The former capability of SAR is investigated for deriving the timing and duration of the thaw period for surface soil of the active layer over permafrost. The latter is investigated for the feasibility of quantitative measurement of frost heaving and thaw settlement of the active layer during the freezing and thawing processes. The resulting knowledge contributes to remote sensing mapping of the active layer dynamics and Arctic land surface hydrology.

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.

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

NASA Astrophysics Data System (ADS)

Salas, W.; Torbick, N.

2017-12-01

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

Practical Considerations before Installing Ground-Based Geodetic Infrastructure for Integrated InSAR and cGNSS Monitoring of Vertical Land Motion.

PubMed

Parker, Amy L; Featherstone, Will E; Penna, Nigel T; Filmer, Mick S; Garthwaite, Matt C

2017-07-31

Continuously operating Global Navigation Satellite Systems (cGNSS) can be used to convert relative values of vertical land motion (VLM) derived from Interferometric Synthetic Aperture Radar (InSAR) to absolute values in a global or regional reference frame. Artificial trihedral corner reflectors (CRs) provide high-intensity and temporally stable reflections in SAR time series imagery, more so than naturally occurring permanent scatterers. Therefore, it is logical to co-locate CRs with cGNSS as ground-based geodetic infrastructure for the integrated monitoring of VLM. We describe the practical considerations for such co-locations using four case-study examples from Perth, Australia. After basic initial considerations such as land access, sky visibility and security, temporary test deployments of co-located CRs with cGNSS should be analysed together to determine site suitability. Signal to clutter ratios from SAR imagery are used to determine potential sites for placement of the CR. A significant concern is whether the co-location of a deliberately designed reflecting object generates unwanted multipath (reflected signals) in the cGNSS data. To mitigate against this, we located CRs >30 m from the cGNSS with no inter-visibility. Daily RMS values of the zero-difference ionosphere-free carrier-phase residuals, and ellipsoidal heights from static precise point positioning GNSS processing at each co-located site were then used to ascertain that the CR did not generate unwanted cGNSS multipath. These steps form a set of recommendations for the installation of such geodetic ground-infrastructure, which may be of use to others wishing to establish integrated InSAR-cGNSS monitoring of VLM elsewhere.

Comparing the Behavior of Polarimetric SAR Imagery (TerraSAR-X and Radarsat-2) for Automated Sea Ice Classification

NASA Astrophysics Data System (ADS)

Ressel, Rudolf; Singha, Suman; Lehner, Susanne

2016-08-01

Arctic Sea ice monitoring has attracted increasing attention over the last few decades. Besides the scientific interest in sea ice, the operational aspect of ice charting is becoming more important due to growing navigational possibilities in an increasingly ice free Arctic. For this purpose, satellite borne SAR imagery has become an invaluable tool. In past, mostly single polarimetric datasets were investigated with supervised or unsupervised classification schemes for sea ice investigation. Despite proven sea ice classification achievements on single polarimetric data, a fully automatic, general purpose classifier for single-pol data has not been established due to large variation of sea ice manifestations and incidence angle impact. Recently, through the advent of polarimetric SAR sensors, polarimetric features have moved into the focus of ice classification research. The higher information content four polarimetric channels promises to offer greater insight into sea ice scattering mechanism and overcome some of the shortcomings of single- polarimetric classifiers. Two spatially and temporally coincident pairs of fully polarimetric acquisitions from the TerraSAR-X/TanDEM-X and RADARSAT-2 satellites are investigated. Proposed supervised classification algorithm consists of two steps: The first step comprises a feature extraction, the results of which are ingested into a neural network classifier in the second step. Based on the common coherency and covariance matrix, we extract a number of features and analyze the relevance and redundancy by means of mutual information for the purpose of sea ice classification. Coherency matrix based features which require an eigendecomposition are found to be either of low relevance or redundant to other covariance matrix based features. Among the most useful features for classification are matrix invariant based features (Geometric Intensity, Scattering Diversity, Surface Scattering Fraction).

Practical Considerations before Installing Ground-Based Geodetic Infrastructure for Integrated InSAR and cGNSS Monitoring of Vertical Land Motion

PubMed Central

Featherstone, Will E.; Filmer, Mick S.

2017-01-01

Continuously operating Global Navigation Satellite Systems (cGNSS) can be used to convert relative values of vertical land motion (VLM) derived from Interferometric Synthetic Aperture Radar (InSAR) to absolute values in a global or regional reference frame. Artificial trihedral corner reflectors (CRs) provide high-intensity and temporally stable reflections in SAR time series imagery, more so than naturally occurring permanent scatterers. Therefore, it is logical to co-locate CRs with cGNSS as ground-based geodetic infrastructure for the integrated monitoring of VLM. We describe the practical considerations for such co-locations using four case-study examples from Perth, Australia. After basic initial considerations such as land access, sky visibility and security, temporary test deployments of co-located CRs with cGNSS should be analysed together to determine site suitability. Signal to clutter ratios from SAR imagery are used to determine potential sites for placement of the CR. A significant concern is whether the co-location of a deliberately designed reflecting object generates unwanted multipath (reflected signals) in the cGNSS data. To mitigate against this, we located CRs >30 m from the cGNSS with no inter-visibility. Daily RMS values of the zero-difference ionosphere-free carrier-phase residuals, and ellipsoidal heights from static precise point positioning GNSS processing at each co-located site were then used to ascertain that the CR did not generate unwanted cGNSS multipath. These steps form a set of recommendations for the installation of such geodetic ground-infrastructure, which may be of use to others wishing to establish integrated InSAR-cGNSS monitoring of VLM elsewhere. PMID:28758970

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

NASA Astrophysics Data System (ADS)

Gong, Lixia; Li, Qiang; Zhang, Jingfa

2016-08-01

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

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

A geological interpretation of Seasat-SAR imagery of Jamaica

NASA Technical Reports Server (NTRS)

Wadge, G.; Dixon, T. H.

1984-01-01

Spaceborne radar imagery obtained from Seasat allows an unobscured large-scale view of Jamaica that can be used for geological interpretation. Lineaments and textures visible in these images were mapped and compared with the known geology of the Tertiary karst limestones covering the central and western parts of the island. Some of these radar textures correlate with lithological units, while others follow tectonically-controlled zones or structural blocks. Mapping of radar lineaments has led to the recognition of three new aspects of Jamaican faults: (1) a major through-going NE-SW fault system, termed here the Vere-Annotto lineament; (2) a series of curving scissor faults in the central part of the island; and (3) the related observation that the dominant NNW-SSE tectonic fabric of the central part of the island takes the form of an elongate sigmoid in plan view. During most of the Neogene Jamaica has been part of an active zone of left-lateral transform motion between the Caribbean and North American plates and is a region of anomalous uplift. The radar imagery is a sensitive recorder of the deformation undergone by the karst limestones in this tectonic regime. Some of the observations are explained with models for a complex, evolving shear zone.

Multiband radar characterization of forest biomes

NASA Technical Reports Server (NTRS)

Dobson, M. Craig; Ulaby, Fawwaz T.

1990-01-01

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

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

NASA Astrophysics Data System (ADS)

Ajadi, Olaniyi A.

Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

Building detection in SAR imagery

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

Steinbach, Ryan Matthew

Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. I present two techniques that are effective and efficient at determining an approximate building location. This approximate location can be used to extract a portion of the SAR image to then perform a more robust detection. The proposed techniques assume that for the desired image, bright lines and shadows, SAR artifact effects, are approximately labeled. These labels are enhanced and utilized to locate buildings, only if the related bright lines and shadows can be grouped. In order tomore » find which of the bright lines and shadows are related, all of the bright lines are connected to all of the shadows. This allows the problem to be solved from a connected graph viewpoint, where the nodes are the bright lines and shadows and the arcs are the connections between bright lines and shadows. For the first technique, constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. The second technique calculates weights for the connections and then performs a series of increasingly relaxed hard and soft thresholds. This results in groups of various levels on their validity. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results demonstrate the outcome of the two techniques. The two techniques are compared and discussed.« less

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

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

2012-10-01

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

Multisensor satellite observations of meso- and submesoscale surface circulation in the Liguro-Provençal Basin

NASA Astrophysics Data System (ADS)

Karimova, Svetlana; Alvera-Azcarate, Aida

2017-04-01

Despite great efforts being paid to studying circulation of the Western Mediterranean Basin and the factors triggering bioproductivity of its marine ecosystem, the evidence provided by satellite imagery has not been fully analysed yet. In the present paper, we concentrate our attention on mesoscale and submesoscale circulation features of the Liguro-Provençal Basin captured by satellite radiometer, spectroradiometer, and radar images. Using such a dataset makes it possible to observe the circulation features from a wide spatial range, from the basin scale through mesoscale to the scales of a few kilometers. Mesoscale features in this study are being mostly observed with thermal infrared imagery retrieved by AVHRR and AATSR sensors. Special attention in the work was paid to an analysis of the data coming from a geostationary satellite, namely ones provided by SEVIRI. Due to their uniquely high temporal resolution, such imagery allows observing circulation features in their evolution. During the winter blooming events, surface circulation at meso- to submesoscales in the region of interest was additionally highlighted by images obtained in the visible range. Full spatial resolution images provided by Envisat MERIS, Sentinel-2 MSI, and Landsat TM/ETM+/OLI made the greatest contribution to this part. The smallest scales (namely submesoscale) are being observed with synthetic aperture radar (SAR) imagery provided by Envisat ASAR and Sentinel-1 SAR. During an analysis of SAR images, it was noted that there was strikingly great amount of biogenic surfactants on the water surface in the region of interest. Apparently, low biological productivity typical for the Western Mediterranean ecosystem is not a limiting factor for the formation of surfactant films seen in SAR imagery. This finding though requires further consideration in some other researches, and hereafter we just benefited from the presence of surfactants, because they behave as good tracers of surface currents. Even though the region of interest belongs to the areas with low mean eddy kinetic energy, analysis of the images listed above revealed that the Liguro-Provençal Basin was showing a surprisingly high eddy activity among submesoscale and mesoscale features. However, the typical size of eddies in this area was smaller than that in the southern part of the Western Mediterranean. The general impression retrieved from the observations performed is that the main contributors to generation of observed mesoscale vortical structures are (i) the instability of the main currents in the region of interest and especially frontal instability at the Liguro-Provençal front and (ii) instabilities caused by the coastline inhomogeneity, especially in the eastern part of the Basin. Submesoscale eddy activity seems to be developed to its full extent during the periods when the mesoscale activity in the region of interest is not so prominent. This study is supported by the University of Liege and the EU in the context of the FP7-PEOPLE-COFUND-BeIPD project. Satellite imagery is provided by the European Space Agency.

Multiscale morphological filtering for analysis of noisy and complex images

NASA Astrophysics Data System (ADS)

Kher, A.; Mitra, S.

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

NASA Technical Reports Server (NTRS)

Kher, A.; Mitra, S.

1993-01-01

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

NASA Technical Reports Server (NTRS)

Freedman, Adam; Hensley, Scott; Chapin, Elaine; Kroger, Peter; Hussain, Mushtaq; Allred, Bruce

1999-01-01

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

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.

C-band SAR observations of marginal ice zone rheology in the Labrador Sea

NASA Technical Reports Server (NTRS)

Drinkwater, Mark R.; Squire, Vernon A.

1989-01-01

Synthetic-aperture radar (SAR) imagery collected during the LIMEX'87 field program in the Labrador Sea is used to qualitatively interpret the deformational modes in play throughout the experiment. The ice cover exhibited two distinct rheologies separated by a clear line of shear: a nonlinear viscous outer regime, and a quasi-brittle inner regime. A single constitutive relation capable of effectively modeling both is unlikely within a plastic rate-independent formulation. Rate-dependent effects are discussed in relation to favoring brittle fraction in an otherwise ductile material.

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

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

NASA Astrophysics Data System (ADS)

Kanberoglu, Berkay; Frakes, David

2017-04-01

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

Sea ice motions in the Central Arctic pack ice as inferred from AVHRR imagery

NASA Technical Reports Server (NTRS)

Emery, William; Maslanik, James; Fowler, Charles

1995-01-01

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

PubMed Central

Taravat, Alireza; Oppelt, Natascha

2014-01-01

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

The interpretation of digital recordings of SIR-A, Seasat, and Landsat data of the Algerian salt deposits

NASA Technical Reports Server (NTRS)

Rebillard, P.; Ballais, J.-P.

1983-01-01

Seasat and SIR-A SAR and Landsat MSS imagery of the salt beds of western Algeria are compared. The Landsat image was made 5 yr before the Seasat image, which was taken nearly 9 yr before the Shuttle radar image. The latter was processed in the visible channel. Differences in the backscatter in the radar imagery are attributed to the viewing angle and the characteristics of each salt deposit. The imagery allowed a determination of the changes in the shapes and areal extent of the salt pools over time, as well as alterations in nearby vegetation cover and the evolution of aeolian formations.

A Pattern-Based Definition of Urban Context Using Remote Sensing and GIS

PubMed Central

Benza, Magdalena; Weeks, John R.; Stow, Douglas A.; López-Carr, David; Clarke, Keith C.

2016-01-01

In Sub-Saharan Africa rapid urban growth combined with rising poverty is creating diverse urban environments, the nature of which are not adequately captured by a simple urban-rural dichotomy. This paper proposes an alternative classification scheme for urban mapping based on a gradient approach for the southern portion of the West African country of Ghana. Landsat Enhanced Thematic Mapper Plus (ETM+) and European Remote Sensing Satellite-2 (ERS-2) synthetic aperture radar (SAR) imagery are used to generate a pattern based definition of the urban context. Spectral mixture analysis (SMA) is used to classify a Landsat scene into Built, Vegetation and Other land covers. Landscape metrics are estimated for Built and Vegetation land covers for a 450 meter uniform grid covering the study area. A measure of texture is extracted from the SAR imagery and classified as Built/Non-built. SMA based measures of Built and Vegetation fragmentation are combined with SAR texture based Built/Non-built maps through a decision tree classifier to generate a nine class urban context map capturing the transition from unsettled land at one end of the gradient to the compact urban core at the other end. Training and testing of the decision tree classifier was done using very high spatial resolution reference imagery from Google Earth. An overall classification agreement of 77% was determined for the nine-class urban context map, with user’s accuracy (commission errors) being lower than producer’s accuracy (omission errors). Nine urban contexts were classified and then compared with data from the 2000 Census of Ghana. Results suggest that the urban classes appropriately differentiate areas along the urban gradient. PMID:27867227

A Pattern-Based Definition of Urban Context Using Remote Sensing and GIS.

PubMed

Benza, Magdalena; Weeks, John R; Stow, Douglas A; López-Carr, David; Clarke, Keith C

2016-09-15

In Sub-Saharan Africa rapid urban growth combined with rising poverty is creating diverse urban environments, the nature of which are not adequately captured by a simple urban-rural dichotomy. This paper proposes an alternative classification scheme for urban mapping based on a gradient approach for the southern portion of the West African country of Ghana. Landsat Enhanced Thematic Mapper Plus (ETM+) and European Remote Sensing Satellite-2 (ERS-2) synthetic aperture radar (SAR) imagery are used to generate a pattern based definition of the urban context. Spectral mixture analysis (SMA) is used to classify a Landsat scene into Built, Vegetation and Other land covers. Landscape metrics are estimated for Built and Vegetation land covers for a 450 meter uniform grid covering the study area. A measure of texture is extracted from the SAR imagery and classified as Built/Non-built. SMA based measures of Built and Vegetation fragmentation are combined with SAR texture based Built/Non-built maps through a decision tree classifier to generate a nine class urban context map capturing the transition from unsettled land at one end of the gradient to the compact urban core at the other end. Training and testing of the decision tree classifier was done using very high spatial resolution reference imagery from Google Earth. An overall classification agreement of 77% was determined for the nine-class urban context map, with user's accuracy (commission errors) being lower than producer's accuracy (omission errors). Nine urban contexts were classified and then compared with data from the 2000 Census of Ghana. Results suggest that the urban classes appropriately differentiate areas along the urban gradient.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

Supraglacial lakes are an important component of the Greenland Ice Sheet’s mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) satellite to investigate supraglacial lakes in West Greenland. A semi-automated algorithm is developed to detect surface lakes from Sentinel-1 images during the 2015 summer. A combined Landsat-8 and Sentinel-1 dataset, which has a comparable temporal resolution to MODIS (3 days versus daily) but a higher spatial resolution (25-40 m versus 250-500 m), is then used together with a fully-automated lake drainage detection algorithm. Rapid (< 4 days) and slow (> 4 days) drainages are investigated for both small (< 0.125 km2, the minimum size detectable by MODIS) and large (≥ 0.125 km2) lakes through the summer. Drainage events of small lakes occur at lower elevations (mean 159 m), and slightly earlier (mean 4.5 days) in the melt season than those of large lakes. The analysis is extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August; 1270 m mean elevation). Finally, the Sentinel-1 imagery is used to detect subsurface lakes and, for the first time, their dates of appearance and freeze-through (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface lakes detected in this study (mean 1593 m and 1185 m, respectively). Sentinel-1 imagery therefore provides great potential for tracking melting, water movement and freezing within both the firn zone and ablation area of the Greenland Ice Sheet.

Phase History Decomposition for efficient Scatterer Classification in SAR Imagery

DTIC Science & Technology

2011-09-15

frequency. Professor Rick Martin provided key advice on frequency parameter estimation and the relationship between likelihood ratio testing and the least...132 6.1.1 Imaging Error Due to Interpolation . . . . . . . . . . . . . . . . . . . . . . . . 135 6.2 Subwindow Design and Weighting... test . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 MF matched filter

Complex faulting associated with the 22 December 2003 Mw 6.5 San Simeon California, earthquake, aftershocks and postseismic surface deformation

USGS Publications Warehouse

McLaren, Marcia K.; Hardebeck, Jeanne L.; Van Der Elst, Nicholas; Unruh, Jeffrey R.; Bawden, Gerald W.; Blair, James Luke

2008-01-01

We use data from two seismic networks and satellite interferometric synthetic aperture radar (InSAR) imagery to characterize the 22 December 2003 Mw 6.5 San Simeon earthquake sequence. Absolute locations for the mainshock and nearly 10,000 aftershocks were determined using a new three-dimensional (3D) seismic velocity model; relative locations were obtained using double difference. The mainshock location found using the 3D velocity model is 35.704° N, 121.096° W at a depth of 9.7±0.7 km. The aftershocks concentrate at the northwest and southeast parts of the aftershock zone, between the mapped traces of the Oceanic and Nacimiento fault zones. The northwest end of the mainshock rupture, as defined by the aftershocks, projects from the mainshock hypocenter to the surface a few kilometers west of the mapped trace of the Oceanic fault, near the Santa Lucia Range front and the >5 mm postseismic InSAR imagery contour. The Oceanic fault in this area, as mapped by Hall (1991), is therefore probably a second-order synthetic thrust or reverse fault that splays upward from the main seismogenic fault at depth. The southeast end of the rupture projects closer to the mapped Oceanic fault trace, suggesting much of the slip was along this fault, or at a minimum is accommodating much of the postseismic deformation. InSAR imagery shows ∼72 mm of postseismic uplift in the vicinity of maximum coseismic slip in the central section of the rupture, and ∼48 and ∼45 mm at the northwest and southeast end of the aftershock zone, respectively. From these observations, we model a ∼30-km-long northwest-trending northeast-dipping mainshock rupture surface—called the mainthrust—which is likely the Oceanic fault at depth, a ∼10-km-long southwest-dipping backthrust parallel to the mainthrust near the hypocenter, several smaller southwest-dipping structures in the southeast, and perhaps additional northeast-dipping or subvertical structures southeast of the mainshock plane. Discontinuous backthrust features opposite the mainthrust in the southeast part of the aftershock zone may offset the relic Nacimiento fault zone at depth. The InSAR data image surface deformation associated with both aseismic slip and aftershock production on the mainthrust and the backthrusts at the northwest and southeast ends of the aftershock zone. The well-defined mainthrust at the latitude of the epicenter and antithetic backthrust illuminated by the aftershock zone indicate uplift of the Santa Lucia Range as a popup block; aftershocks in the southeast part of the zone also indicate a popup block, but it is less well defined. The absence of backthrust features in the central part of the zone suggests range-front uplift by fault-propagation folding, or backthrusts in the central part were not activated during the mainshock.

Dr. Tom Mace talks with a student from Punta Arenas, Chile, during a tour of the DC-8 aircraft

NASA Image and Video Library

2004-03-10

Dr. Tom Mace, NASA DFRC Director of Airborne Sciences, talks with a student from Punta Arenas, Chile, during a tour of the DC-8 aircraft while it was in the country supporting the AirSAR 2004 campaign. 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.

Pilot Bill Brockett (left) and Chilean Air Force Captain Saez with school children in the cockpit of NASA Dryden's DC-8 flying laboratory

NASA Image and Video Library

2004-03-10

Pilot Bill Brockett (left) and Chilean Air Force Captain Saez with school children in the cockpit of NASA Dryden's DC-8 flying laboratory. Brockett explained NASA's AirSAR 2004 mission in Chile. 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.

NASA Dryden Mission Manager Walter Klein talks with school children from Punta Arenas, Chile, during a tour of the DC-8 aircraft

NASA Image and Video Library

2004-03-10

NASA Dryden Mission Manager Walter Klein talks with school children from Punta Arenas, Chile, during a tour of the DC-8 aircraft while it was in the country supporting the AirSAR 2004 campaign. 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.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

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

NASA Astrophysics Data System (ADS)

Boesswetter, C.

1986-07-01

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

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.

Precursory Slope Deformation around Landslide Area Detected by Insar Throughout Japan

NASA Astrophysics Data System (ADS)

Nakano, T.; Wada, K.; Yamanaka, M.; Kamiya, I.; Nakajima, H.

2016-06-01

Interferometric Synthetic Aperture Radar (InSAR) technique is able to detect a slope deformation around landslide (e.g., Singhroy et al., 2004; Une et al., 2008; Riedel and Walther, 2008; Sato et al., 2014). Geospatial Information Authority (GSI) of Japan has been performing the InSAR analysis regularly by using ALOS/PALSAR data and ALOS-2/PALSAR-2 data throughout Japan. There are a lot of small phase change sites except for crustal deformation with earthquake or volcano activity in the InSAR imagery. Most of the phase change sites are located in landslide area. We conducted field survey at the 10 sites of those phase change sites. As a result, we identified deformation of artificial structures or linear depressions caused by mass movement at the 9 sites. This result indicates that InSAR technique can detect on the continual deformation of landslide block for several years. GSI of Japan will continue to perform the InSAR analysis throughout Japan. Therefore, we will be able to observe and monitor precursory slope deformation around landslide areas throughout Japan.

Identification of ex-sand mining area using optical and SAR imagery

NASA Astrophysics Data System (ADS)

Indriasari, Novie; Kusratmoko, Eko; Indra, Tito Latif; Julzarika, Atriyon

2018-05-01

Open mining activities in Sumedang Regency has been operated since 1984 impacted to degradation of environment due to large area of ex-mining. Therefore, identification of ex-mining area which generally been used for sand mining is crucial and important to detect and monitor recent environmental degradation impacted from the ex-mining activities. In this research, identification ex-sand mining area using optical and SAR data in Sumedang Regency will be discussed. We use Landsat 5 TM acquisition date August 01, 2009 and Landsat 8 OLI acquired on June 24, 2016 to identify location of sand mining area, processed using Tasselled Cap Trasformation (TCT), while the landform deformation approached using ALOS PALSAR in 2009 and ALOS PALSAR 2 in 2016 processed using SAR interferometry (InSAR) method. The results show that TCT and InSAR method can can be used to identify the areas of ex-sand mining clearly. In 2016 the total area of ex-mining were 352.92 Ha. The land deformation show that during 7 years period since 2009 has impacted to the deformation at 7 meters.

20. OVERVIEW OF SAR3 COMPLEX, SHOWING FORMER RESIDENTIAL AREA, SAR3 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

20. OVERVIEW OF SAR-3 COMPLEX, SHOWING FORMER RESIDENTIAL AREA, SAR-3 SWITCH RACK, MAINTENANCE YARD, AND GREENSPOT BRIDGE. NOTE ALSO LARGE PIPE CONDUCTING TAILRACE WATER INTO IRRIGATION SYSTEM. VIEW TO SOUTHWEST. - Santa Ana River Hydroelectric System, Redlands, San Bernardino County, CA

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Neural Methods for Imagery, GMTI, and Information Fusion

DTIC Science & Technology

2006-03-15

Dynamic Range Contrast Enhanced Length & Power Normalized JV\\ 0.7 11 2500. No0 00 0.6 :a -30 - i 0.5 1 •4e ,3 ta I. a* 20 4B 60 Be° .0 120 140 160 s e...conditioned profile after length and power normalization. 2 Neural-Based Feature Extraction 2.2 Contrast enhancement and adaptive Rather than directly... power of the signal comprised of HRR range profiles synthesized from the is normalized. This ensures that very weak or very strong MSTAR SAR imagery

Integration of multispectral and SAR data for monitoring forest ecosystems recovery after fire

NASA Astrophysics Data System (ADS)

Stankova, Nataliya; Nedkov, Roumen; Ivanova, Iva; Avetisyan, Daniela

2017-09-01

The aim of this study is assessing the impacts and monitoring the condition and recovery processes of forest ecosystems after fire based on remote aerospace methods and data. To achieve this goal, satellite imagery in microwave and optical range of the spectrum were used. A hybrid model for assessing the instantaneous condition of forest ecosystems after fire that uses parallel data from optical and Synthetic Aperture Radar (SAR) was developed. Based on the three Tasseled Cap components (Brightness-BR, Greenness-GR and Wetness-W), a vector describing the current condition of the forest ecosystems was obtained and used as input data from the optical range. Results obtained by implementation of the proposed approach show that the integrated composite images of VIC and SAR represent the degree of recovery.

Active/passive microwave sensor comparison of MIZ-ice concentration estimates. [Marginal Ice Zone (MIZ)

NASA Technical Reports Server (NTRS)

Burns, B. A.; Cavalieri, D. J.; Keller, M. R.

1986-01-01

Active and passive microwave data collected during the 1984 summer Marginal Ice Zone Experiment in the Fram Strait (MIZEX 84) are used to compare ice concentration estimates derived from synthetic aperture radar (SAR) data to those obtained from passive microwave imagery at several frequencies. The comparison is carried out to evaluate SAR performance against the more established passive microwave technique, and to investigate discrepancies in terms of how ice surface conditions, imaging geometry, and choice of algorithm parameters affect each sensor. Active and passive estimates of ice concentration agree on average to within 12%. Estimates from the multichannel passive microwave data show best agreement with the SAR estimates because the multichannel algorithm effectively accounts for the range in ice floe brightness temperatures observed in the MIZ.

Single-Chip FPGA Azimuth Pre-Filter for SAR

NASA Technical Reports Server (NTRS)

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

2005-01-01

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals, the bandwidth of the AzPF is made 80 percent of fPR/M. The choice of four as the number of overlapping phases is justified by prior research in which it was shown that a filter of length 4M can effect an acceptable transfer function. The figure depicts prototype hardware comprising the AzPF and ancillary electronic circuits. The hardware was found to satisfy performance requirements in real-time tests at a sampling rate of 100 MHz.

Observing the polar oceans with spaceborne radar

NASA Technical Reports Server (NTRS)

Rothrock, Drew

1986-01-01

The application of spaceborne imaging radar data to polar oceanography and sea ice is explored. Several problems come to mind which are presently ripe with ideas and models, but are in need of new data, SAR data, for any progress to be made. These are the study of the ice mass balance, the ice momentum balance, and the circulation of the Arctic Ocean. These problems are described along with the data which is applicable to them and can be extracted from SAR imagery. Some uses are discussed of these data to explore mesoscale processes which affect the oceans and ice cover.

Landslide movement mapping by sub-pixel amplitude offset tracking - case study from Corvara landslide

NASA Astrophysics Data System (ADS)

Darvishi, Mehdi; Schlögel, Romy; Cuozzo, Giovanni; Callegari, Mattia; Thiebes, Benni; Bruzzone, Lorenzo; Mulas, Marco; Corsini, Alessandro; Mair, Volkmar

2016-04-01

Despite the advantages of Differential Synthetic Aperture Radar Interferometry (DInSAR) methods for quantifying landslide deformation over large areas, some limitations remain. These include for example geometric distortions, atmospheric artefacts, geometric and temporal decorrelations, data and scale constraints, and the restriction that only 1-dimentional line-of-sight (LOS) deformations can be measured. At local scale, the major limitations are dense vegetation, as well as large displacement rates which can lead to decorrelation between SAR acquisitions also for high resolution images and temporal baselines. Sub-pixel offset tracking was proposed to overcome some of these limitations. Two of the most important advantages of this technique are the mapping of 2-D displacements (azimuth and range directions), and the fact that there is no need for complex phase unwrapping algorithms which could give wrong results or fail in case of decorrelation or fast ground deformations. As sub-pixel offset tracking is highly sensitive to the spatial resolution of the data, latest generations of SAR sensors such as TerraSAR-X and COSMO-SkyMed providing high resolution data (up to 1m) have great potential to become established methods in the field of ground deformation monitoring. In this study, sub-pixel offset tracking was applied to COSMO SkyMed X-band imagery in order to quantify ground displacements and to evaluate the feasibility of offset tracking for landslide movement mapping and monitoring. The study area is the active Corvara landslide located in the Italian Alps, described as a slow-moving and deep-seated landslide with annual displacement rates of up to 20 m. Corner reflectors specifically designed for X-band were installed on the landslide and used as reference points for sub-pixel offset tracking. Satellite images covering the period from 2013 to 2015 were analyzed with an amplitude tracking tool for calculating the offsets and extracting 2-D displacements. Sub-pixel offset tracking outputs were integrated with DInSAR results and correlated to differential GPS measurements recorded at the same time as the SAR data acquisitions.

Xpatch prediction improvements to support multiple ATR applications

NASA Astrophysics Data System (ADS)

Andersh, Dennis J.; Lee, Shung W.; Moore, John T.; Sullivan, Douglas P.; Hughes, Jeff A.; Ling, Hao

1998-08-01

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.

XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays

NASA Astrophysics Data System (ADS)

Hazlett, Michael; Andersh, Dennis J.; Lee, Shung W.; Ling, Hao; Yu, C. L.

1995-06-01

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time domain signatures, and synthetic aperture radar (SAR) images of realistic 3-D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, curved surfaces, or solid geometries. The computer code, XPATCH, based on the shooting and bouncing ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. XPATCH computes the first-bounce physical optics plus the physical theory of diffraction contributions and the multi-bounce ray contributions for complex vehicles with materials. It has been found that the multi-bounce contributions are crucial for many aspect angles of all classes of vehicles. Without the multi-bounce calculations, the radar return is typically 10 to 15 dB too low. Examples of predicted range profiles, SAR imagery, and radar cross sections (RCS) for several different geometries are compared with measured data to demonstrate the quality of the predictions. The comparisons are from the UHF through the Ka frequency ranges. Recent enhancements to XPATCH for MMW applications and target Doppler predictions are also presented.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Rapid Damage Mapping for the 2015 M7.8 Gorkha Earthquake using Synthetic Aperture Radar Data from COSMO-SkyMed and ALOS-2 Satellites

NASA Astrophysics Data System (ADS)

Yun, S. H.; Hudnut, K. W.; Owen, S. E.; Webb, F.; Simons, M.; Macdonald, A.; Sacco, P.; Gurrola, E. M.; Manipon, G.; Liang, C.; Fielding, E. J.; Milillo, P.; Hua, H.; Coletta, A.

2015-12-01

The April 25, 2015 M7.8 Gorkha earthquake caused more than 8,000 fatalities and widespread building damage in central Nepal. Four days after the earthquake, the Italian Space Agency's (ASI's) COSMO-SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area. Nine days after the earthquake, the Japan Aerospace Exploration Agency's (JAXA's) ALOS-2 SAR satellite covered larger area. Using these radar observations, we rapidly produced damage proxy maps derived from temporal changes in Interferometric SAR (InSAR) coherence. These maps were qualitatively validated through comparison with independent damage analyses by National Geospatial-Intelligence Agency (NGA) and the UNITAR's (United Nations Institute for Training and Research's) Operational Satellite Applications Programme (UNOSAT), and based on our own visual inspection of DigitalGlobe's WorldView optical pre- vs. post-event imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

Waves and mesoscale features in the marginal ice zone

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chih Y.

1993-01-01

Ocean-ice interaction processes in the Marginal Ice Zone (MIZ) by waves and mesoscale features, such as upwelling and eddies, are studied using ERS-1 Synthetic Aperture Radar (SAR) imagery and wave-ice interaction models. Satellite observations of mesoscale features can play a crucial role in ocean-ice interaction study.

Oil detection in RADARSAT-2 quad-polarization imagery: implications for ScanSAR performance

NASA Astrophysics Data System (ADS)

Cheng, Angela; Arkett, Matt; Zagon, Tom; De Abreu, Roger; Mueller, Derek; Vachon, Paris; Wolfe, John

2011-11-01

Environment Canada's Integrated Satellite Tracking of Pollution (ISTOP) program uses RADARSAT-2 data to vector pollution surveillance assets to areas where oil discharges/spills are suspected in support of enforcement and/or cleanup efforts. RADARSAT-2's new imaging capabilities and ground system promises significant improvement's in ISTOP's ability to detect and report on oil pollution. Of specific interest is the potential of dual polarization ScanSAR data acquired with VV polarization to improve the detection of oil pollution compared to data acquired with HH polarization, and with VH polarization to concurrently detect ship targets. A series of 101 RADARSAT-2 fine quad images were acquired over Coal Oil Point, near Santa Barbara, California where a seep field naturally releases hydrocarbons. The oil and gas releases in this region are visible on the sea surface and have been well documented allowing for the remote sensing of a constant source of oil at a fixed location. Although the make-up of the oil seep field could be different from that of oil spills, it provides a representative target that can be routinely imaged under a variety of wind conditions. Results derived from the fine quad imagery with a lower noise floor were adjusted to mimic the noise floor limitations of ScanSAR. In this study it was found that VV performed better than HH for oil detection, especially at higher incidence angles.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

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

NASA Astrophysics Data System (ADS)

Harahsheh, H. A.

2016-06-01

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

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.

A fully automatic tool to perform accurate flood mapping by merging remote sensing imagery and ancillary data

NASA Astrophysics Data System (ADS)

D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco; Pasquariello, Guido

2016-04-01

Flooding is one of the most frequent and expansive natural hazard. High-resolution flood mapping is an essential step in the monitoring and prevention of inundation hazard, both to gain insight into the processes involved in the generation of flooding events, and from the practical point of view of the precise assessment of inundated areas. Remote sensing data are recognized to be useful in this respect, thanks to the high resolution and regular revisit schedules of state-of-the-art satellites, moreover offering a synoptic overview of the extent of flooding. In particular, Synthetic Aperture Radar (SAR) data present several favorable characteristics for flood mapping, such as their relative insensitivity to the meteorological conditions during acquisitions, as well as the possibility of acquiring independently of solar illumination, thanks to the active nature of the radar sensors [1]. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground: the presence of many land cover types, each one with a particular signature in presence of flood, requires modelling the behavior of different objects in the scene in order to associate them to flood or no flood conditions [2]. Generally, the fusion of multi-temporal, multi-sensor, multi-resolution and/or multi-platform Earth observation image data, together with other ancillary information, seems to have a key role in the pursuit of a consistent interpretation of complex scenes. In the case of flooding, distance from the river, terrain elevation, hydrologic information or some combination thereof can add useful information to remote sensing data. Suitable methods, able to manage and merge different kind of data, are so particularly needed. In this work, a fully automatic tool, based on Bayesian Networks (BNs) [3] and able to perform data fusion, is presented. It supplies flood maps describing the dynamics of each analysed event, combining time series of images, acquired by different sensors, with ancillary information. Some experiments have been performed by combining multi-temporal SAR intensity images, InSAR coherence and optical data, with geomorphic and other ground information. The tool has been tested on different flood events occurred in the Basilicata region (Italy) during the last years, showing good capabilities of identification of a large area interested by the flood phenomenon, partially overcoming the obstacle constituted by the presence of scattering/coherence classes corresponding to different land cover types, which respond differently to the presence of water and to inundation evolution [1] A. Refice et al, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 7, pp. 2711-2722, 2014. [2] L. Pulvirenti et al., IEEE Trans. Geosci. Rem. Sens., Vol. PP, pp. 1- 13, 2015. [3] A. D'Addabbo et al., "A Bayesian Network for Flood Detection combining SAR Imagery and Ancillary Data," IEEE Trans. Geosci. Rem. Sens., in press.

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

NASA DC-8 Ground Support Technicians Mark Corlew and Mike Lakowski perform routine maintenance on the aircraft in Punta Arenas, Chile

NASA Image and Video Library

2004-03-17

NASA DC-8 Ground Support Technicians Mark Corlew and Mike Lakowski perform routine maintenance on the aircraft at Carlos Ibanez del Campo International Airport in Punta Arenas, Chile. AirSAR 2004 is a three-week expedition by an international team of scientists that is using 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 will collect 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 decreasing, continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.

NASA DC-8 Ground Support Technician Joe Niquette performs routine maintenance on the DC-8 aircraft in Punta Arenas, Chile

NASA Image and Video Library

2004-03-17

NASA DC-8 Ground Support Technician Joe Niquette performs routine maintenance on the DC-8 aircraft at Carlos Ibanez del Campo International Airport in Punta Arenas, Chile. AirSAR 2004 is a three-week expedition by an international team of scientists that is using 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 will collect 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 decreasing, continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.

NASA DC-8 Pilots Craig Bomben and Bill Brockett explain the DC-8 cockpit to Chilean students onboard the DC-8 aircraft in Punta Arenas, Chile

NASA Image and Video Library

2004-03-17

NASA DC-8 Pilots Craig Bomben and Bill Brockett explain the DC-8 cockpit to Chilean students onboard the DC-8 aircraft at Carlos Ibanez del Campo International Airport in Punta Arenas, Chile. AirSAR 2004 is a three-week expedition by an international team of scientists that is using 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 will collect 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 decreasing, continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.

NASA DC-8 Mission Manager Walter Klein poses with a group of Chilean Students onboard the aircraft in Punta Arenas, Chile

NASA Image and Video Library

2004-03-17

NASA DC-8 Mission Manager Walter Klein poses with a group of Chilean Students onboard the aircraft at Carlos Ibanez del Campo International Airport in Punta Arenas, Chile. AirSAR 2004 is a three-week expedition by an international team of scientists that is using 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 will collect 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 decreasing, continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.

Chilean Air Force Captain Saez and Dr. Tom Mace discuss airborne science during a DC-8 ferry flight from Santiago to Punta Arenas, Chile

NASA Image and Video Library

2004-03-10

Chilean Air Force Captain Saez and Dr. Tom Mace, DFRC Director of Airborne Sciences, discuss airborne science during a DC-8 ferry flight from Santiago to Punta Arenas, Chile. 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.

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell

PubMed Central

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-García, Mateo; Dorta-Naranjo, Blas-Pablo

2008-01-01

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar. PMID:27879884

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell.

PubMed

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-Garcia, Mateo; Dorta-Naranjo, Blas-Pablo

2008-05-23

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar.

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.

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

USGS Publications Warehouse

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

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

SARS coronavirus papain-like protease inhibits the type I interferon signaling pathway through interaction with the STING-TRAF3-TBK1 complex.

PubMed

Chen, Xiaojuan; Yang, Xingxing; Zheng, Yang; Yang, Yudong; Xing, Yaling; Chen, Zhongbin

2014-05-01

SARS coronavirus (SARS-CoV) develops an antagonistic mechanism by which to evade the antiviral activities of interferon (IFN). Previous studies suggested that SARS-CoV papain-like protease (PLpro) inhibits activation of the IRF3 pathway, which would normally elicit a robust IFN response, but the mechanism(s) used by SARS PLpro to inhibit activation of the IRF3 pathway is not fully known. In this study, we uncovered a novel mechanism that may explain how SARS PLpro efficiently inhibits activation of the IRF3 pathway. We found that expression of the membrane-anchored PLpro domain (PLpro-TM) from SARS-CoV inhibits STING/TBK1/IKKε-mediated activation of type I IFNs and disrupts the phosphorylation and dimerization of IRF3, which are activated by STING and TBK1. Meanwhile, we showed that PLpro-TM physically interacts with TRAF3, TBK1, IKKε, STING, and IRF3, the key components that assemble the STING-TRAF3-TBK1 complex for activation of IFN expression. However, the interaction between the components in STING-TRAF3-TBK1 complex is disrupted by PLpro-TM. Furthermore, SARS PLpro-TM reduces the levels of ubiquitinated forms of RIG-I, STING, TRAF3, TBK1, and IRF3 in the STING-TRAF3-TBK1 complex. These results collectively point to a new mechanism used by SARS-CoV through which PLpro negatively regulates IRF3 activation by interaction with STING-TRAF3-TBK1 complex, yielding a SARS-CoV countermeasure against host innate immunity.

Sensor fusion and augmented reality with the SAFIRE system

NASA Astrophysics Data System (ADS)

Saponaro, Philip; Treible, Wayne; Phelan, Brian; Sherbondy, Kelly; Kambhamettu, Chandra

2018-04-01

The Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) mobile radar system was developed and exercised at an arid U.S. test site. The system can detect hidden target using radar, a global positioning system (GPS), dual stereo color cameras, and dual stereo thermal cameras. An Augmented Reality (AR) software interface allows the user to see a single fused video stream containing the SAR, color, and thermal imagery. The stereo sensors allow the AR system to display both fused 2D imagery and 3D metric reconstructions, where the user can "fly" around the 3D model and switch between the modalities.

Comparison of using single- or multi-polarimetric TerraSAR-X images for segmentation and classification of man-made maritime objects

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.

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.

InSAR constraints on soil moisture evolution after the March 2015 extreme precipitation event in Chile.

PubMed

Scott, C P; Lohman, R B; Jordan, T E

2017-07-07

Constraints on soil moisture can guide agricultural practices, act as input into weather, flooding and climate models and inform water resource policies. Space-based interferometric synthetic aperture radar (InSAR) observations provide near-global coverage, even in the presence of clouds, of proxies for soil moisture derived from the amplitude and phase content of radar imagery. We describe results from a 1.5 year-long InSAR time series spanning the March, 2015 extreme precipitation event in the hyperarid Atacama desert of Chile, constraining the immediate increase in soil moisture and drying out over the following months, as well as the response to a later, smaller precipitation event. The inferred temporal evolution of soil moisture is remarkably consistent between independent, overlapping SAR tracks covering a region ~100 km in extent. The unusually large rain event, combined with the extensive spatial and temporal coverage of the SAR dataset, present an unprecedented opportunity to image the time-evolution of soil characteristics over different surface types. Constraints on the timescale of shallow water storage after precipitation events are increasingly valuable as global water resources continue to be stretched to their limits and communities continue to develop in flood-prone areas.

Radar image processing for rock-type discrimination

NASA Technical Reports Server (NTRS)

Blom, R. G.; Daily, M.

1982-01-01

Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Monthly flooded area classification using low resolution SAR imagery in the Sudd wetland from 2007-2011

USDA-ARS?s Scientific Manuscript database

The annual flood cycle of the Sudd wetland in South Sudan plays an important role in the Nile River Basin water balance. The wetland, however, is extensive and sparsely instrumented, which has inhibited credible understanding of regional flooding across space and time. Here we explore the potential ...

Airborne SAR determination of relative ages of Walker Valley moraines, eastern Sierra Nevada

NASA Technical Reports Server (NTRS)

Fox, A.; Isacks, B.; Bloom, A.; Fielding, E.; Mcmurry, D.

1991-01-01

A regional study of the distribution and elevations of Pleistocene moraines in the Andes requires a method of determining relative age from space. One of our primary objectives is to establish the relative chronology of major climatic events responsible for glaciation in the Andes and other regions that are difficult to access on the ground and where suitable material for absolute age determination is lacking. The sensitivity of radar to surface roughness makes it possible to develop a remotely-based relative dating technique for landforms for which surface age and roughness can be correlated. We are developing such a technique with Airborne Synthetic Aperture Radar (AIRSAR) imagery of the eastern Sierra Nevada where independent evidence is available for the ages and physical characteristics of moraines. The Sierra Nevada moraines are similar in form and environmental setting to Andean moraines that we have targeted for study during the pending Shuttle Imaging Radar-C (SIR-C) mission. SAR imagery is used to differentiate the ages of five moraine sequences of Walker Valley in the eastern Sierra Nevada. Other aspects of this investigation are briefly discussed.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1981-01-01

Training and test data sets for CAM1S from NS-001 MSS data for two dates (geometrically adjusted to 30 meter resolution) were used to evaluate wavelength band. Two sets of tapes containing digitized HH and HV polarization data were obtained. Because the SAR data on the 9 track tapes contained no meaningful data, the 7 track tapes were copied onto 9 track tapes at LARS. The LARSYS programs were modified and a program was written to reformat the digitized SAR data into a LARSYS format. The radar imagery is being qualitatively interpreted. Results are to be used to identify possible cover types, to produce a classification map to aid in the numerical evaluation classification of radar data, and to develop an interpretation key for radar imagery. The four spatial resolution data sets were analyzed. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. A flowchart of steps taken to geometrically adjust a data set from the NS-001 scanner is presented.

Sea ice radar signatures from ERS-1 SAR during late Summer and Fall in the Beaufort and Chukchi Seas

NASA Technical Reports Server (NTRS)

Holt, Benjamin; Cunningham, Glenn; Kwok, Ron

1993-01-01

A study which examines ERS-1 C band SAR (Synthetic Aperture Radar) imagery of sea ice obtained in the Beaufort and Chukchi Seas from mid Summer through Fall freeze up and early Winter in 1991 is presented. Radar backscatter statistics of sea ice were obtained from the imagery, using common floes tracked through consecutive repeat images whenever possible. During the Summer months, strong fluctuations in ice signatures of several dB are observed over 2 to 3 day periods, which are found to be closely related to air temperature excursions above and below freezing that alters the phase of the ice surface. As air temperatures drop steadily below freezing in the Fall, the signatures of the pack ice increase in brightness and become more stable with time. Multiyear ice is distinguished from rough and smooth first year ice. There are also variations in the multiyear signatures with latitude. Large variations are seen in new ice and open water contained within leads which results in ambiguous classification.

The GF-3 SAR Data Processor

PubMed Central

Han, Bing; Ding, Chibiao; Zhong, Lihua; Liu, Jiayin; Qiu, Xiaolan; Hu, Yuxin; Lei, Bin

2018-01-01

The Gaofen-3 (GF-3) data processor was developed as a workstation-based GF-3 synthetic aperture radar (SAR) data processing system. The processor consists of two vital subsystems of the GF-3 ground segment, which are referred to as data ingesting subsystem (DIS) and product generation subsystem (PGS). The primary purpose of DIS is to record and catalogue GF-3 raw data with a transferring format, and PGS is to produce slant range or geocoded imagery from the signal data. This paper presents a brief introduction of the GF-3 data processor, including descriptions of the system architecture, the processing algorithms and its output format. PMID:29534464

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Target modelling for SAR image simulation

NASA Astrophysics Data System (ADS)

Willis, Chris J.

2014-10-01

This paper examines target models that might be used in simulations of Synthetic Aperture Radar imagery. We examine the basis for scattering phenomena in SAR, and briefly review the Swerling target model set, before considering extensions to this set discussed in the literature. Methods for simulating and extracting parameters for the extended Swerling models are presented. It is shown that in many cases the more elaborate extended Swerling models can be represented, to a high degree of fidelity, by simpler members of the model set. Further, it is shown that it is quite unlikely that these extended models would be selected when fitting models to typical data samples.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Guillen, Frank J.

1994-10-01

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

Synergy of VHR Optical and VHR SAR Data for High Resolution DSM Generation over Large Flat Areas: Pleiades and TerraSAR-X Exploitation over the Low Lying Banks of the Yangtze River (PR China)

NASA Astrophysics Data System (ADS)

Huber, C.; Studer, M.; Giraud, H.; Durand, A.; Fruteau, L.; Lai, X.; Maxant, J.; Li, F.; Cao, L.; Tinel, C.; Yesou, H.

2014-11-01

Water resource monitoring and preservation are some of the biggest issues at global scale, and space technologies are playing a key role in various applications related to water topics the recently launched Sentinel-1, the future Sentinel-2 and 2020 altimetric mission SWOT, will be powerful for an accurate mapping of continental water resources but would be even more powerful and useful in association with high quality Digital Surface Models (DSM). Within the Thematic User Commissioning phase intending to valorize Pleiades imagery, 6 tri-stereo sets of Pleiades-HR images were acquired over test sites located within the Yangtze low-intermediate watershed reaches. At the same time, TanDEM-X InSAR pairs were acquired over the same area in order to get a wider coverage.

Ice tracking techniques, implementation, performance, and applications

NASA Technical Reports Server (NTRS)

Rothrock, D. A.; Carsey, F. D.; Curlander, J. C.; Holt, B.; Kwok, R.; Weeks, W. F.

1992-01-01

Present techniques of ice tracking make use both of cross-correlation and of edge tracking, the former being more successful in heavy pack ice, the latter being critical for the broken ice of the pack margins. Algorithms must assume some constraints on the spatial variations of displacements to eliminate fliers, but must avoid introducing any errors into the spatial statistics of the measured displacement field. We draw our illustrations from the implementation of an automated tracking system for kinematic analyses of ERS-1 and JERS-1 SAR imagery at the University of Alaska - the Alaska SAR Facility's Geophysical Processor System. Analyses of the ice kinematic data that might have some general interest to analysts of cloud-derived wind fields are the spatial structure of the fields, and the evaluation and variability of average deformation and its invariants: divergence, vorticity and shear. Many problems in sea ice dynamics and mechanics can be addressed with the kinematic data from SAR.

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.

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.

Calibration of 2D Hydraulic Inundation Models with SAR Imagery in the Floodplain Region of the Lower Tagus River

NASA Astrophysics Data System (ADS)

Pestana, Rita; Matias, Magda; Canelas, Ricardo; Roque, Dora; Araujo, Amelia; Van Zeller, Emilia; Trigo-Teixeira, Antonio; Ferreira, Rui; Oliveira, Rodrigo; Heleno, Sandra; Falcão, Ana Paula; Gonçalves, Alexandre B.

2014-05-01

Floods account for 40% of all natural hazards worldwide and were responsible for the loss of about 100 thousand human lives and affected more than 1,4 million people in the last decade of the 20th century alone. Floods have been the deadliest natural hazard in Portugal in the last 100 years. In terms of inundated area, the largest floods in Portugal occur in the Lower Tagus (LT) River. On average, the river overflows every 2.5 years, at times blocking roads and causing important agricultural damages. The economical relevance of the area and the high frequency of the relevant flood events make the LT floodplain a good pilot region to conduct a data-driven, systematic calibration work of flood hydraulic models. This paper focus on the calibration of 2D-horizontal flood simulation models for the floods of 1997, 2001 and 2006 on a 70-km stretch of the LT River, between Tramagal and Omnias, using the software Tuflow. This computational engine provides 2D solutions based on the Stelling finite-difference, alternating direction implicit (ADI) scheme that solves the full 2D free surface shallow-water flow equations and allowed the introduction of structures that constrain water flow. The models were based on a digital terrain model (DTM) acquired in 2008 by radar techniques (5m of spatial resolution) and on in situ measurements of water elevation in Omnias (downstream boundary condition) and discharge in Tramagal and Zezere (upstream boundary conditions). Due to the relevancy of several dykes on this stretch of the LT River, non-existent on the available DTM, five of them were introduced in the models. All models have the same boundaries and were simulated using steady-state flow initial conditions. The resolution of the 2D grid mesh was 30m. Land cover data for the study area was retrieved from Corine Land Cover 2006 (CO-ordination of INformation on the Environment) with spatial resolution of 100m, and combined with estimated manning coefficients obtained in literature for the different land cover classes. Flood extent maps, derived from satellite-born Synthetic Aperture Radar (SAR), namely ERS SAR and ENVISAT ASAR imagery, provided the spatially distributed data needed for the calibration of the hydraulic models for the several floods. The flood extent maps obtained for each simulation were then compared with the flood extent maps derived from SAR imagery for each flood and the roughness coefficients changed accordingly. The models were also calibrated in terms of the stage at the gauging station Almourol, located 12km downriver from Tramagal. The combination of the calibration results for the several past floods provided 100 meters resolution Manning coefficient maps of the study area. An application of the obtained calibrated Manning coefficient maps was made for the largest flood of the 20th century (February 1979), for which no SAR imagery was available. In this case validation of the model was made in terms of the stage at the gauging station Almourol and at flood stage marks distributed throughout the floodplain.

SAR processing in the cloud for oil detection in the Arctic

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Investigation of Land Subsidence using ALOS PALSAR data: a case study in Mentougou (Beijing, China)

NASA Astrophysics Data System (ADS)

Chen, Jianping; Xiang, Jie; Xie, Shuai; Liu, Jing; Tarolli, Paolo

2017-04-01

Mining activities have been documented for centuries in Mentougou, and land subsidence resulting from mining operations has already been known over the past few decades. However, there has been ongoing concern that excessive groundwater extraction may lead to further subsidence. Therefore it is critical to map the land cover changes to understand the actual impact of these activities. So, the land cover changes from 2006 to 2011 were examined based on multi-source remote sensing imageries( including ALOS and landsat-7) by using object-oriented classifications combined with a decision tree and retrospective approaches. Also, land subsidence in Mentougou between 2006 and 2011 has been mapped using the interferometric synthetic aperture radar (InSAR) time-series analysis with the ALOS L-band SAR data. We processed 14 ascending SAR images during May 2006 to July 2011. Comparison of InSAR measurements with the land cover changes and pre-existing faults suggest that mining activities is the main cause of land subsidence. The land subsidence observed from InSAR data are approximately up to 15 mm/year in open-pit mining area and up to 24 mm/year in underground mining areas. The InSAR result are validated by the ground survey data in several areas, and the comparison between the InSAR result with the mining schedule showed there were some correlations between them. The result underline the potential use of InSAR measurements to provide better investigation for land subsidence, and also suggest that the most influential factors for land subsidence is underground coal mine.

A comparison of SAR ATR performance with information theoretic predictions

NASA Astrophysics Data System (ADS)

Blacknell, David

2003-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Multifrequency OFDM SAR in Presence of Deception Jamming

NASA Astrophysics Data System (ADS)

Schuerger, Jonathan; Garmatyuk, Dmitriy

2010-12-01

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

Preliminary results of SAR soil moisture experiment, November 1975

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Pathfinder radar development at Sandia National Laboratories

NASA Astrophysics Data System (ADS)

Castillo, Steven

2016-05-01

Since the invention of Synthetic Aperture Radar imaging in the 1950's, users or potential users have sought to exploit SAR imagery for a variety of applications including the earth sciences and defense. At Sandia Laboratories, SAR Research and Development and associated defense applications grew out of the nuclear weapons program in the 1980's and over the years has become a highly viable ISR sensor for a variety of tactical applications. Sandia SAR systems excel where real-­-time, high-­-resolution, all-­-weather, day or night surveillance is required for developing situational awareness. This presentation will discuss the various aspects of Sandia's airborne ISR capability with respect to issues related to current operational success as well as the future direction of the capability as Sandia seeks to improve the SAR capability it delivers into multiple mission scenarios. Issues discussed include fundamental radar capabilities, advanced exploitation techniques and human-­-computer interface (HMI) challenges that are part of the advances required to maintain Sandia's ability to continue to support ever changing and demanding mission challenges.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

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.

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.

29. OVERVIEW OF SAR3 COMPLEX, LOOKING NORTHEAST. FROM LEFT TO ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

29. OVERVIEW OF SAR-3 COMPLEX, LOOKING NORTHEAST. FROM LEFT TO RIGHT, THE STRUCTURES ARE THE SAR-3 POWERHOUSE, SWITCHRACK, OFFICE (IN BACKGROUND), WAREHOUSE, CARPENTER SHOP, MAINTENANCE YARD, STORAGE BUILDING, AND STORAGE GARAGE (IN BACKGROUND). - Santa Ana River Hydroelectric System, Redlands, San Bernardino County, CA

JPL scientist Dr. David Imel and U.S. Air Force Colonel Gwen Linde lead Chilean students on a tour of the DC-8 aircraft in Punta Arenas, Chile

NASA Image and Video Library

2004-03-17

JPL scientist Dr. David Imel and U.S. Air Force Colonel Gwen Linde, the Defense Department Attache Officer assigned to the Chilean Embassy, lead Chilean students on a tour of the DC-8 aircraft at Carlos Ibanez del Campo International Airport in Punta Arenas, Chile. AirSAR 2004 is a three-week expedition by an international team of scientists that is using 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 will collect 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 decreasing, continuing or accelerating. AirSAR will also provide reliable information on ice shelf thickness to measure the contribution of the glaciers to sea level.

Target Recognition in Ultra-Wideband SAR Imagery

DTIC Science & Technology

1994-08-01

Poles in a Transfer Function for Real Frequency Informa- tion," Lawrence Livermore Laboratory, UCRL -52050 (April 1974). 24. V. K Jain, T. K. Sarker, and...0.777 Gaussian 0.849 1 5,265 0.978 93 Distribution Adrnnstr ARPAJASTO Defris Techi Info Ctr Attn T DePersia Attn DTIC-DDA (2 copies) 3701 N Fairfax Dr

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

NASA Astrophysics Data System (ADS)

Notti, Davide; Calò, Fabiana; Cigna, Francesca; Manunta, Michele; Herrera, Gerardo; Berti, Matteo; Meisina, Claudia; Tapete, Deodato; Zucca, Francesco

2015-11-01

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes.

Techniques in processing multi-frequency multi-polarization spaceborne SAR data

NASA Technical Reports Server (NTRS)

Curlander, John C.; Chang, C. Y.

1991-01-01

This paper presents the algorithm design of the SIR-C ground data processor, with emphasis on the unique elements involved in the production of registered multifrequency polarimetric data products. A quick-look processing algorithm used for generation of low-resolution browse image products and estimation of echo signal parameters is also presented. Specifically the discussion covers: (1) azimuth reference function generation to produce registered polarimetric imagery; (2) geometric rectification to accommondate cross-track and along-track Doppler drifts; (3) multilook filtering designed to generate output imagery with a uniform resolution; and (4) efficient coding to compress the polarimetric image data for distribution.

Improved Absolute Radiometric Calibration of a UHF Airborne Radar

NASA Technical Reports Server (NTRS)

Chapin, Elaine; Hawkins, Brian P.; Harcke, Leif; Hensley, Scott; Lou, Yunling; Michel, Thierry R.; Moreira, Laila; Muellerschoen, Ronald J.; Shimada, Joanne G.; Tham, Kean W.;

An Efficient Image Recovery Algorithm for Diffraction Tomography Systems

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1993-01-01

A diffraction tomography system has potential application in ultrasonic medical imaging area. It is capable of achieving imagery with the ultimate resolution of one quarter the wavelength by collecting ultrasonic backscattering data from a circular array of sensors and reconstructing the object reflectivity using a digital image recovery algorithm performed by a computer. One advantage of such a system is that is allows a relatively lower frequency wave to penetrate more deeply into the object and still achieve imagery with a reasonable resolution. An efficient image recovery algorithm for the diffraction tomography system was originally developed for processing a wide beam spaceborne SAR data...

Advanced InSAR imaging for dune mapping

NASA Astrophysics Data System (ADS)

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

2015-04-01

Aeolian morphologies are formed in the presence of sufficient wind energy and available particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970's, remote sensing imagery both optical and radar, are used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of Aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two images or more. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This research aims to demonstrate how interferometric decorrelation, or, coherence change detection, can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the Nitzanim coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically and extensively in the field. High resolution TerraSAR-X (TSX) images, covering the entire research area were acquired for the period of October 2011 to July 2012 (15 images in total). All images were co-registreted, the first image was used as the master image. A coherence index was calculated for all the images. Analysis was performed in GIS software. The results display minor changes (coherence index in range of 0.4-0.65) on dune crests depending on the dune location relative to its distance from the sea and distance from the city. In addition, field results indicate erosion / deposition of sand in a cumulatively amount of approximately 30mm annually. The results of this study confirm that it is possible to monitor subtle changes in dunes and to identify dune stability or instability, only by the use of SAR images.

Ocean Wave Energy Estimation Using Active Satellite Imagery as a Solution of Energy Scarce in Indonesia Case Study: Poteran Island's Water, Madura

NASA Astrophysics Data System (ADS)

Nadzir, Z. A.; Karondia, L. A.; Jaelani, L. M.; Sulaiman, A.; Pamungkas, A.; Koenhardono, E. S.; Sulisetyono, A.

2015-10-01

Ocean wave energy is one of the ORE (Ocean Renewable Energies) sources, which potential, in which this energy has several advantages over fossil energy and being one of the most researched energy in developed countries nowadays. One of the efforts for mapping ORE potential is by computing energy potential generated from ocean wave, symbolized by Watt per area unit using various methods of observation. SAR (Synthetic Aperture Radar) is one of the hyped and most developed Remote Sensing method used to monitor and map the ocean wave energy potential effectively and fast. SAR imagery processing can be accomplished not only in remote sensing data applications, but using Matrices processing application as well such as MATLAB that utilizing Fast Fourier Transform and Band-Pass Filtering methods undergoing Pre-Processing stage. In this research, the processing and energy estimation from ALOSPALSAR satellite imagery acquired on the 5/12/2009 was accomplished using 2 methods (i.e Magnitude and Wavelength). This resulted in 9 potential locations of ocean wave energy between 0-228 W/m2, and 7 potential locations with ranged value between 182-1317 W/m2. After getting through buffering process with value of 2 km (to facilitate the construction of power plant installation), 9 sites of location were estimated to be the most potential location of ocean wave energy generation in the ocean with average depth of 8.058 m and annual wind speed of 6.553 knot.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Processing techniques development, volume 3

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Anuta, P. E.; Hixson, M. M.; Swain, P. H.

1978-01-01

The author has identified the following significant results. Analysis of the geometric characteristics of the aircraft synthetic aperture radar (SAR) relative to LANDSAT indicated that relatively low order polynominals would model the distortions to subpixel accuracy to bring SAR into registration for good quality imagery. Also the area analyzed was small, about 10 miles square, so this is an additional constraint. For the Air Force/ERIM data, none of the tested methods could achieve subpixel accuracy. Reasons for this is unknown; however, the noisy (high scintillation) nature of the data and attendent unrecognizability of features contribute to this error. It is concluded that the quadratic model would adequately provide distortion modeling for small areas, i.e., 10 to 20 miles square.

Top/bottom multisensor remote sensing of Arctic sea ice

NASA Technical Reports Server (NTRS)

Comiso, J. C.; Wadhams, P.; Krabill, W. B.; Swift, R. N.; Crawford, J. P.

1991-01-01

Results are presented on the Aircraft/Submarine Sea Ice Project experiment carried out in May 1987 to investigate concurrently the top and the bottom features of the Arctic sea-ice cover. Data were collected nearly simultaneously by instruments aboard two aircraft and a submarine, which included passive and active (SAR) microwave sensors, upward looking and sidescan sonars, a lidar profilometer, and an IR sensor. The results described fall into two classes of correlations: (1) quantitative correlations between profiles, such as ice draft (sonar), ice elevation (laser), SAR backscatter along the track line, and passive microwave brightness temperatures; and (2) qualitative and semiquantitative correlations between corresponding areas of imagery (i.e., passive microwave, AR, and sidescan sonar).

Wave propagation in the marginal ice zone - Model predictions and comparisons with buoy and synthetic aperture radar data

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Holt, Benjamin; Vachon, Paris W.

1991-01-01

Ocean wave dispersion relation and viscous attenuation by a sea ice cover are studied for waves propagating into the marginal ice zone (MIZ). The Labrador ice margin experiment (LIMEX), conducted on the MIZ off the east coast of Newfoundland, Canada in March 1987, provided aircraft SAR imagery, ice property and wave buoy data. Wave energy attenuation rates are estimated from SAR data and the ice motion package data that were deployed at the ice edge and into the ice pack, and compared with a model. It is shown that the model data comparisons are quite good for the ice conditions observed during LIMEX 1987.

A parametric study of rate of advance and area coverage rate performance of synthetic aperture radar.

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

Raynal, Ann Marie; William H. Hensley, Jr.; Burns, Bryan L.

2014-11-01

The linear ground distance per unit time and ground area covered per unit time of producing synthetic aperture radar (SAR) imagery, termed rate of advance (ROA) and area coverage rate (ACR), are important metrics for platform and radar performance in surveillance applications. These metrics depend on many parameters of a SAR system such as wavelength, aircraft velocity, resolution, antenna beamwidth, imaging mode, and geometry. Often the effects of these parameters on rate of advance and area coverage rate are non-linear. This report addresses the impact of different parameter spaces as they relate to rate of advance and area coverage ratemore » performance.« less

The SIR-B science plan

NASA Technical Reports Server (NTRS)

1982-01-01

The Shuttle Imaging Radar-B (SIR-B) will be the third in a series of spaceborne SAR experiments conducted by NASA which began with the 1978 launch of SEASAT and continued with the 1981 launch of SIR-A. Like SEASAT and SIR-A, SIR-B will operate at L-band and will be horizontally polarized. However, SIR-B will allow digitally processed imagery to be acquired at selectable incidence angles between 15 and 60 deg, thereby permitting, for the first time, parametric studies of the effect of illumination geometry on SAR image information extraction. This document presents a science plan for SIR-B and serves as a reference for the types of geoscientific, sensor, and processing experiments which are possible.

Utility of Characterizing and Monitoring Suspected Underground Nuclear Sites with VideoSAR

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

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

Satellite Remote Sensing For Aluminum And Nickel Laterites

NASA Astrophysics Data System (ADS)

Henderson, Frederick B.; Penfield, Glen T.; Grubbs, Donald K.

1984-08-01

The new LANDSAT-4,-5/Thematic Mapper (TM) land observational satellite remote sensing systems are providing dramatically new and important short wave infrared (SWIR) data, which combined with Landsat's Multi-Spectral Scanner (MSS) visible (VIS), very near infrared (VNIR), and thermal infrared (TI) data greatly improves regional geological mapping on a global scale. The TM will significantly improve clay, iron oxide, aluminum, and nickel laterite mapping capabilities over large areas of the world. It will also improve the ability to discriminate vegetation stress and species distribution associated with lateritic environments. Nickel laterites on Gag Island, Indonesia are defined by MSS imagery. Satellite imagery of the Cape Bougainville and the Darling Range, Australia bauxite deposits show the potential use of MSS data for exploration and mining applications. Examples of satellite syn-thetic aperture radar (SAR) for Jamaica document the use of this method for bauxite exploration. Thematic Mapper data will be combined with the French SPOT satellite's high spatial resolution and stereoscopic digital data, and U.S., Japanese, European, and Canadian Synthetic Aperture Radar (SAR) data to assist with logistics, mine development, and environ-mental concerns associated with aluminum and nickel lateritic deposits worldwide.

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Satellite on-board real-time SAR processor prototype

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Towards automated mapping of lake ice using RADARSAT-2 and simulated RCM compact polarimetric data

NASA Astrophysics Data System (ADS)

Duguay, Claude

2016-04-01

The Canadian Ice Service (CIS) produces a weekly ice fraction product (a text file with a single lake-wide ice fraction value, in tenth, estimated for about 140 large lakes across Canada and northern United States) created from the visual interpretation of RADARSAT-2 ScanSAR dual-polarization (HH and HV) imagery, complemented by optical satellite imagery (AVHRR, MODIS and VIIRS). The weekly ice product is generated in support of the Canadian Meteorological Centre (CMC) needs for lake ice coverage in their operational numerical weather prediction model. CIS is interested in moving from its current (manual) way of generating the ice fraction product to a largely automated process. With support from the Canadian Space Agency, a project was recently initiated to assess the potential of polarimetric SAR data for lake ice cover mapping in light of the upcoming RADARSAT Constellation Mission (to be launched in 2018). The main objectives of the project are to evaluate: 1) state-of-the-art image segmentation algorithms and 2) RADARSAT-2 polarimetric and simulated RADARSAT Constellation Mission (RCM) compact polarimetric SAR data for ice/open water discrimination. The goal is to identify the best segmentation algorithm and non-polarimetric/polarimetric parameters for automated lake ice monitoring at CIS. In this talk, we will present the background and context of the study as well as initial results from the analysis of RADARSAT-2 Standard Quad-Pol data acquired during the break-up and freeze-up periods of 2015 on Great Bear Lake, Northwest Territories.

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

USGS Publications Warehouse

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

2012-01-01

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

Radar systems for a polar mission, volume 1

NASA Technical Reports Server (NTRS)

Moore, R. K.; Claassen, J. P.; Erickson, R. L.; Fong, R. K. T.; Komen, M. J.; Mccauley, J.; Mcmillan, S. B.; Parashar, S. K.

1977-01-01

The application of synthetic aperture radar (SAR) in monitoring and managing earth resources is examined. Synthetic aperture radars form a class of side-looking airborne radar, often referred to as coherent SLAR, which permits fine-resolution radar imagery to be generated at long operating ranges by the use of signal processing techniques. By orienting the antenna beam orthogonal to the motion of the spacecraft carrying the radar, a one-dimensional imagery ray system is converted into a two-dimensional or terrain imaging system. The radar's ability to distinguish - or resolve - closely spaced transverse objects is determined by the length of the pulse. The transmitter components receivers, and the mixer are described in details.

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

NASA Astrophysics Data System (ADS)

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

1988-12-01

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

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

PubMed Central

Liu, Lei; Qiu, Xiaolan; Lei, Bin

2017-01-01

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

Extraction and height estimation of artificial vertical structures based on the wrapped interferometric phase difference within their layovers

NASA Astrophysics Data System (ADS)

Uemoto, Jyunpei; Nadai, Akitsugu; Kojima, Shoichiro; Kobayashi, Tatsuharu; Umehara, Toshihiko; Matsuoka, Takeshi; Uratsuka, Seiho; Satake, Makoto

2018-05-01

The geometric modulation of synthetic aperture radar (SAR) imagery such as radar shadow, foreshortening, and layover often complicates image interpretation while it contains useful information about targets. Recently, some methods for automatic building detection utilizing a peculiar pattern of phase differences (PDs) within building layovers on SAR interferograms have been proposed. One of the merits of these methods is the capability to detect buildings even taller than the height of ambiguity without incorporating any external data. In this paper, we propose a new method that has achieved the following improvements while maintaining the merit mentioned above. The first improvement is freedom from the dependence of target heights; without changing any parameters and thresholds, the proposed method can detect low-rise apartments to skyscrapers. The second one is the prevention of the false grouping of vertical structure constituents by considering relationships between their PDs. In addition, the method can measure the height of vertical structures without assuming their shape to be simple ones such as a parallelogram. These improvements have been verified by applying the method to real datasets acquired from an airborne X-band SAR. The quantitative assessment for apartment complexes has demonstrated the high performance of the method; the correctness and completeness are 94% and 83%, respectively. The mean error in the measured height is -0.2 m, while the standard deviation is 1.8 m. The verification using real datasets has revealed at the same time that the performance of the method can be degraded due to the crowdedness in dense urban areas including skyscrapers and owing to the poor discriminability between artificial vertical structures and trees. Overcoming these limitations is necessary in future studies.

Improving crop classification through attention to the timing of airborne radar acquisitions

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Protz, R.

1984-01-01

Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

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.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD.

PubMed

Solberg, Svein; Gizachew, Belachew; Næsset, Erik; Gobakken, Terje; Bollandsås, Ole Martin; Mauya, Ernest William; Olsson, Håkan; Malimbwi, Rogers; Zahabu, Eliakimu

2015-12-01

REDD+ implementation requires establishment of a system for measuring, reporting and verification (MRV) of forest carbon changes. A challenge for MRV is the lack of satellite based methods that can track not only deforestation, but also degradation and forest growth, as well as a lack of historical data that can serve as a basis for a reference emission level. Working in a miombo woodland in Tanzania, we here aim at demonstrating a novel 3D satellite approach based on interferometric processing of radar imagery (InSAR). Forest carbon changes are derived from changes in the forest canopy height obtained from InSAR, i.e. decreases represent carbon loss from logging and increases represent carbon sequestration through forest growth. We fitted a model of above-ground biomass (AGB) against InSAR height, and used this to convert height changes to biomass and carbon changes. The relationship between AGB and InSAR height was weak, as the individual plots were widely scattered around the model fit. However, we consider the approach to be unique and feasible for large-scale MRV efforts in REDD+ because the low accuracy was attributable partly to small plots and other limitations in the data set, and partly to a random pixel-to-pixel variation in trunk forms. Further processing of the InSAR data provides data on the categories of forest change. The combination of InSAR data from the Shuttle RADAR Topography Mission (SRTM) and the TanDEM-X satellite mission provided both historic baseline of change for the period 2000-2011, as well as annual change 2011-2012. A 3D data set from InSAR is a promising tool for MRV in REDD+. The temporal changes seen by InSAR data corresponded well with, but largely supplemented, the changes derived from Landsat data.

Massive Cloud Computing Processing of P-SBAS Time Series for Displacement Analyses at Large Spatial Scale

NASA Astrophysics Data System (ADS)

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

2016-12-01

A methodology for computing surface deformation time series and mean velocity maps of large areas is presented. Our approach relies on the availability of a multi-temporal set of Synthetic Aperture Radar (SAR) data collected from ascending and descending orbits over an area of interest, and also permits to estimate the vertical and horizontal (East-West) displacement components of the Earth's surface. The adopted methodology is based on an advanced Cloud Computing implementation of the Differential SAR Interferometry (DInSAR) Parallel Small Baseline Subset (P-SBAS) processing chain which allows the unsupervised processing of large SAR data volumes, from the raw data (level-0) imagery up to the generation of DInSAR time series and maps. The presented solution, which is highly scalable, has been tested on the ascending and descending ENVISAT SAR archives, which have been acquired over a large area of Southern California (US) that extends for about 90.000 km2. Such an input dataset has been processed in parallel by exploiting 280 computing nodes of the Amazon Web Services Cloud environment. Moreover, to produce the final mean deformation velocity maps of the vertical and East-West displacement components of the whole investigated area, we took also advantage of the information available from external GPS measurements that permit to account for possible regional trends not easily detectable by DInSAR and to refer the P-SBAS measurements to an external geodetic datum. The presented results clearly demonstrate the effectiveness of the proposed approach that paves the way to the extensive use of the available ERS and ENVISAT SAR data archives. Furthermore, the proposed methodology can be particularly suitable to deal with the very huge data flow provided by the Sentinel-1 constellation, thus permitting to extend the DInSAR analyses at a nearly global scale. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

Effects of TEL Confusers on Operator Target Acquisition Performance with SAR Imagery

DTIC Science & Technology

1998-12-01

processing known as the theory of signal detection (TSD) (Gescheider, 1985; Green & Swets, 1966; Macmillan & Creelman , 1991; Wilson, 1992). A TSD...localizations (Hacker & Ratcliff, 1979; Macmillan & Creelman , 1991). The index of bias in a target localization task provides a measure of the operator’s...of correct localizations substituted for hits (Macmillan & Creelman , 1991). Receiver Operating Characteristic Curves. In addition to the calculation

Naval Research Reviews. Volume 39, Number 3,

DTIC Science & Technology

1987-01-01

remote sensing, ice and waves, acoustics, and MIZEX East Research Area. biology . Operations benefitted greatly from SAR imagery, downlinked daily. in near...the carried out coordinated programs in oceanography . edd\\ Norwsegian Satellite Telemelr\\ Station under D).A. Horn. studies. biology and meteorology...processes are the principal generators of " ambient noise in the Arctic MIZ. 20 . % Biology Acknowledgements In MIZEX 87, growth rates and the standing

Holographic Location of Distant Points (PREPRINT)

DTIC Science & Technology

2010-06-01

respects and the nonimaging systems have significant advantages. This paper shows how to use holograms to construct a flat, solid, small, accurate, small... nonimaging point location system. 15. SUBJECT TERMS imagery, holographic 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT: SAR 18...respects and the nonimaging systems we have discussed earlier (1, 2) have significant advantages. This paper shows how to use holograms to construct a

SWIFT Obervations in the Sea State DRI

DTIC Science & Technology

2018-02-28

arctic-autumn , 98 (2017). [published, refereed] • Ardhuin et al, Measuring ocean waves in sea ice using SAR imagery: A quasi -deterministic approach...Graber, H. Shen, J. Gemmrich, S. Lehner, B. Holt, and T. Williams, Science and Experiment Plan: Sea State and Boundary Layer Physics of the...live along the Arctic coastline and experience climate change firsthand. Our results will be published in a special issue (http

Determination of The Water Catchment Area in Semarang City Using a Combination of Object Based Image Analysis (OBIA) Classification, InSAR and Geographic Information System (GIS) Methods Based On a High-Resolution SPOT 6 Image and Radar Imagery

NASA Astrophysics Data System (ADS)

Prasetyo, Yudo; Ardi Gunawan, Setyo; Maksum, Zia Ul

2016-11-01

Semarang is the biggest city in central Java-Indonesia which has a rapid and massive infrastructure development nowadays. In order to control water resources and flood, the local goverment has been built east and west flood canal in Kaligarang and West Semarang River. One of main problem in Semarang city is the lack of fresh water in dry season because ground water is not rechargeable well. Rechargeable groundwater ability depends on underground water recharge rate and catchment area condition. The objective of the study is to determine condition and classification of water catchment area in Semarang city. The catchment area conditions will be determine by five parameters as follows soil type, land use, slope, ground water potential and rainfall intensity. In this study, we use three methods approach to solve the problem which is segmentation classification to acquire land use classification from high resolution imagery using nearest neighborhood algorithm, Interferometric Synthetic Aperture Radar (SAR) to derive DTM from SAR Imagery and multi criteria weighting and spatial analysis using GIS method. There are three types optical image (ALOS PRISM, SPOT-6 and ALOS PALSAR) to calculate water catchment area condition in Semarang city. For final result, this research will divide the water catchment into six criteria as follows good, naturally normal, early critical, a little bit critical, critical and very critical condition. The result shows that water catchment area condition is in an early critical condition around 2607,523 Ha (33,17 %), naturally normal condition around 1507,674 Ha (19,18 %), a little bit critical condition around 1452,931 Ha (18,48 %), good with 1157,04 Ha (14,72 %), critical with 1058,639 Ha (13,47 %) and very critical with 75,0387 Ha (0,95 %). The distribution of water catchment area conditions in West and East Flood Canal have an irreguler pattern. In northern area of watershed consists of begin to critical, naturally normal and good condition. Meanwhile in southern area of watershed consists of a little bit critical, critical and very critical condition.

New Approaches To Off-Shore Wind Energy Management Exploiting Satellite EO Data

NASA Astrophysics Data System (ADS)

Morelli, Marco; Masini, Andrea; Venafra, Sara; Potenza, Marco Alberto Carlo

2013-12-01

Wind as an energy resource has been increasingly in focus over the past decades, starting with the global oil crisis in the 1970s. The possibility of expanding wind power production to off-shore locations is attractive, especially in sites where wind levels tend to be higher and more constant. Off-shore high-potential sites for wind energy plants are currently being looked up by means of wind atlases, which are essentially based on NWP (Numerical Weather Prediction) archive data and that supply information with low spatial resolution and very low accuracy. Moreover, real-time monitoring of active off- shore wind plants is being carried out using in-situ installed anemometers, that are not very reliable (especially on long time periods) and that should be periodically substituted when malfunctions or damages occur. These activities could be greatly supported exploiting archived and near real-time satellite imagery, that could provide accurate, global coverage and high spatial resolution information about both averaged and near real-time off-shore windiness. In this work we present new methodologies aimed to support both planning and near-real-time monitoring of off-shore wind energy plants using satellite SAR(Synthetic Aperture Radar) imagery. Such methodologies are currently being developed in the scope of SATENERG, a research project funded by ASI (Italian Space Agency). SAR wind data are derived from radar backscattering using empirical geophysical model functions, thus achieving greater accuracy and greater resolution with respect to other wind measurement methods. In detail, we calculate wind speed from X-band and C- band satellite SAR data, such as Cosmo-SkyMed (XMOD2) and ERS and ENVISAT (CMOD4) respectively. Then, using also detailed models of each part of the wind plant, we are able to calculate the AC power yield expected behavior, which can be used to support either the design of potential plants (using historical series of satellite images) or the monitoring and performance analysis of active plants (using near- real-time satellite imagery). We have applied these methods in several test cases and obtained successful results in comparison with standard methodologies.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically, and studied extensively in the field. High resolution TerraSAR-X (TSX) images covering the entire research area were acquired for the period of 2011 to 2012. Analysis was performed in imaging processing and GIS software. The coherence results display minor changes on the dune crest (0.42-0.49), compared to bigger changes in windward slope (0.31-0.37). The level of change depends on the dune location relative to its distance from the sea. Furthermore, the coherence results show decreasing over time. Field results indicate erosion/deposition of sand ranging from -99 to 137 mm/year. The results of this study confirm that it is possible to monitor subtle changes in sand dunes and to identify dune stability or instability, only by the use of SAR images, even in areas characterized by low coherence.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Investigation on Insar Time Series Deformation Model Considering Rheological Parameters for Soft Clay Subgrade Monitoring

NASA Astrophysics Data System (ADS)

Xing, X.; Yuan, Z.; Chen, L. F.; Yu, X. Y.; Xiao, L.

2018-04-01

The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.

Large-area landslide detection and monitoring with ALOS/PALSAR imagery data over Northern California and Southern Oregon, USA

USGS Publications Warehouse

Zhao, Chaoying; Lu, Zhong; Zhang, Qin; de la Fuente, Juan

2012-01-01

Multi-temporal ALOS/PALSAR images are used to automatically investigate landslide activity over an area of ~ 200 km by ~ 350 km in northern California and southern Oregon. Interferometric synthetic aperture radar (InSAR) deformation images, InSAR coherence maps, SAR backscattering intensity images, and a DEM gradient map are combined to detect active landslides by setting individual thresholds. More than 50 active landslides covering a total of about 40 km2 area are detected. Then the short baseline subsets (SBAS) InSAR method is applied to retrieve time-series deformation patterns of individual detected landslides. Down-slope landslide motions observed from adjacent satellite tracks with slightly different radar look angles are used to verify InSAR results and measurement accuracy. Comparison of the landslide motion with the precipitation record suggests that the landslide deformation correlates with the rainfall rate, with a lag time of around 1–2 months between the precipitation peak and the maximum landslide displacement. The results will provide new insights into landslide mechanisms in the Pacific Northwest, and facilitate development of early warning systems for landslides under abnormal rainfall conditions. Additionally, this method will allow identification of active landslides in broad areas of the Pacific Northwest in an efficient and systematic manner, including remote and heavily vegetated areas difficult to inventory by traditional methods.

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 while making landfall on Cuba and the Florida Keys, where IRMA still hit as a category 3 to 4 hurricane. Results are compared to the WW3 model, which could not be validated over an area under strong and variable wind conditions before. A new theory on hurricane intensification based on Kelvin-Helmholtz instability is discussed and a first comparison to the SAR data is given.

Integrating geologic and satellite radar data for mapping dome-and-basin patterns in the In Ouzzal Terrane, Western Hoggar, Algeria

NASA Astrophysics Data System (ADS)

Deroin, Jean-Paul; Djemai, Safouane; Bendaoud, Abderrahmane; Brahmi, Boualem; Ouzegane, Khadidja; Kienast, Jean-Robert

2014-11-01

The In Ouzzal Terrane (IOT) located in the north-western part of the Tuareg Shield forms an elongated N-S trending block, more than 400 km long and 80 km wide. It involves an Archaean crust remobilized during a very high-temperature metamorphic event related to the Palaeoproterozoic orogeny. The IOT largely crops out in the rocky and sandy desert of Western Hoggar. It corresponds mainly to a flat area with some reliefs composed of Late Panafrican granites, dyke networks or Cambrian volcanic rocks. These flat areas are generally covered by thin sand veneers. They are favorable for discriminating bedrock geological units using imaging radar, backscattering measurements, and field checking, because the stony desert is particularly sensitive to the radar parameters such as wavelength or polarization. The main radar data used are those obtained with the ALOS-PALSAR sensor (L-band), in ScanSAR mode (large swath) and Fine Beam modes. The PALSAR sensor has been also compared to ENVISAT-ASAR and to optical imagery. Detailed mapping of some key areas indicates extensive Archaean dome-and-basin patterns. In certain parts, the supracrustal synforms and orthogneiss domes exhibit linear or circular features corresponding to shear zones or rolling structures, respectively. The geological mapping of these dome-and-basin structures, and more generally of the Archaean and Proterozoic lithological units, is more accurate with the SAR imagery, particularly when using the L-band, than with the optical imagery. A quantitative approach is carried out in order to estimate the backscatter properties of the main rock types. Due to the large variety of configurations, radar satellite imagery such as ALOS PALSAR represents a key tool for geological mapping in arid region at different scales from the largest (e.g., 1:500,000) to the smallest (e.g., 1:50,000).

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed Central

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

2018-01-01

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

Modeling the Radar Return of Powerlines Using an Incremental Length Diffraction Coefficient Approach

NASA Astrophysics Data System (ADS)

Macdonald, Douglas

A method for modeling the signal from cables and powerlines in Synthetic Aperture Radar (SAR) imagery is presented. Powerline detection using radar is an active area of research. Accurately identifing the location of powerlines in a scene can be used to aid pilots of low flying aircraft in collision avoidance, or map the electrical infrastructure of an area. The focus of this research was on the forward modeling problem of generating the powerline SAR signal from first principles. Previous work on simulating SAR imagery involved methods that ranged from efficient but insufficiently accurate, depending on the application, to more exact but computationally complex. A brief survey of the numerous ways to model the scattering of electromagnetic radiation is provided. A popular tool that uses the geometric optics approximation for modeling imagery for remote sensing applications across a wide range of modalities is the Digitial Imaging and Remote Sensing Image Generation (DIRSIG) tool. This research shows the way in which DIRSIG generates the SAR phase history is unique compared to other methods used. In particular, DIRSIG uses the geometric optics approximation for the scattering of electromagnetic radiation and builds the phase history in the time domain on a pulse-by-pulse basis. This enables an efficient generation of the phase history of complex scenes. The drawback to this method is the inability to account for diffraction. Since the characteristic diameter of many communication cables and powerlines is on the order of the wavelength of the incident radiation, diffraction is the dominant mechanism by which the radiation gets scattered for these targets. Comparison of DIRSIG imagery to field data shows good scene-wide qualitative agreement as well as Rayleigh distributed noise in the amplitude data, as expected for coherent imaging with speckle. A closer inspection of the Radar Cross Sections of canonical targets such as trihedrals and dihedrals, however, shows DIRSIG consistently underestimated the scattered return, especially away from specular observation angles. This underestimation was particularly pronounced for the dihedral targets which have a low acceptance angle in elevation, probably caused by the lack of a physical optics capability in DIRSIG. Powerlines were not apparent in the simulated data. For modeling powerlines outside of DIRSIG using a standalone approach, an Incremental Length Diffraction Coefficient (ILDC) method was used. Traditionally, this method is used to model the scattered radiation from the edge of a wedge, for example the edges on the wings of a stealth aircraft. The Physical Theory of Diffraction provides the 2D diffraction coefficient and the ILDC method performs an integral along the edge to extend this solution to three dimensions. This research takes the ILDC approach but instead of using the wedge diffraction coefficient, the exact far-field diffraction coefficient for scattering from a finite length cylinder is used. Wavenumber-diameter products are limited to less than or about 10. For typical powerline diameters, this translates to X-band frequencies and lower. The advantage of this method is it allows exact 2D solutions to be extended to powerline geometries where sag is present and it is shown to be more accurate than a pure physical optics approach for frequencies lower than millimeter wave. The Radar Cross Sections produced by this method were accurate to within the experimental uncertainty of measured RF anechoic chamber data for both X and C-band frequencies across an 80 degree arc for 5 different target types and diameters. For the X-band data, the mean error was 6.0% for data with 9.5% measurement uncertainty. For the C-band data, the mean error was 11.8% for data with 14.3% measurement uncertainty. The best results were obtained for X-band data in the HH polarization channel within a 20 degree arc about normal incidence. For this configuration, a mean error of 3.0% for data with a measurement uncertainty of 5.2% was obtained. The least accurate results were obtained for X-band data in the VV polarization channel within a 20 degree arc about normal incidence. For this configuration, a mean error of 8.9% for data with a measurement uncertainty of 5.9% was obtained. This error likely arose from making the smooth cylinder assumption, which neglects the semi-open waveguide TE contribution from the grooves in the helically wound powerline. For field data in an actual X-band circular SAR collection, a mean error of 3.3% for data with a measurement uncertainty of 3.3% was obtained in the HH channel. For the VV channel, a mean error of 9.9% was obtained for data with a measurement uncertainty of 3.4%. Future work for improving this method would likely entail adding a far-field semi-open waveguide contribution to the 2D diffraction coefficient for TE polarized radiation. Accounting for second order diffractions between closely spaced powerlines would also lead to improved accuracy for simulated field data.

Combining SAR with LANDSAT for Change Detection of Riparian Buffer Zone in a Semi-arid River Basin

NASA Astrophysics Data System (ADS)

Chang, N.

2006-12-01

A combination of RADARSAT-1 and Landsat 5 TM satellite images linking the soil moisture variation with Normalized Difference Vegetation Index (NDVI) measurements were used to accomplish remotely sensed change detection of riparian buffer zone in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The CCRW was selected as the study area contributing to the reservoir, which is mostly agricultural and range land in a semi-arid coastal environment. This makes the study significant due to the interception capability of non-point source impact within the riparian buffer zone and the maintenance of ecosystem integrity region wide. First of all, an estimation of soil moisture using RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery was conducted. With its all-weather capability, the RADARSAT-1 is a promising tool for measuring the surface soil moisture over seasons. The time constraint is almost negligible since the RADARSAT-1 is able to capture surface soil moisture over a large area in a matter of seconds, if the area is within its swath. RADARSAT-1 images presented at here were captured in two acquisitions, including April and September 2004. With the aid of five corner reflectors deployed by Alaska Satellite Facility (ASF), essential radiometric and geometric calibrations were performed to improve the accuracy of the SAR imagery. The horizontal errors were reduced from initially 560 meter down to less than 5 meter at the best try. Then two Landsat 5 TM satellite images were summarized based on its NDVI. The combination of and NDVI and SAR data obviously show that soil moisture and vegetation biomass wholly varies in space and time in the CCRW leading to identify the riparian buffer zone evolution over seasons. It is found that the seasonal soil moisture variation is highly tied with the NDVI values and the change detection of buffer zone is technically feasible. It will contribute to develop more effective management strategies for non-point source pollution control, bird habitat monitoring, and grazing and live stock handlings in the future. Future research focuses on comparison of soil moisture variability within RADARSAT-1 footprints and NDVI variations against interferometric SAR for studying riparian ecosystem functioning on a seasonal basis.

Interpretation of the Cosmo-SkyMed observations of the 2009 Tanaro river flood

NASA Astrophysics Data System (ADS)

Pulvirenti, L.; Pierdicca, N.; Chini, M.; Guerriero, L.

2010-09-01

The potentiality of spaceborne Synthetic Aperture Radar (SAR) for flood mapping was demonstrated by several past investigations. The synoptic view and the capability to operate in almost all-weather conditions and during both day and night are the key features that make the SAR images useful for monitoring inundation events. In addition, their high spatial resolution allows a fairly accurate delineation of the flood extent. The Cosmo-SkyMed (COnstellation of small Satellites for Mediterranean basin Observation) mission offers a unique opportunity to obtain radar images characterized by short revisit time, so that an operational use of Cosmo-SkyMed data in flood management systems can be envisaged. However, the interpretation of SAR images of flooded areas might be complex, because of the dependence of the radar response from flooded pixels on land cover, system parameters and environmental conditions. An example of radar data whose interpretation is not straightforward is represented by the Cosmo-SkyMed observations of the overflowing of the Tanaro river, close to the city of Alessandria (Northern Italy), occurred on April, 27-28 2009. Within the framework of a study, funded by the Italian Space Agency (ASI), aiming at evaluating the usefulness of Earth Observation techniques into operational flood prediction and assessment chains (named OPERA, civil protection from floods), ASI provided a number of Cosmo-SkyMed images of the Tanaro basin. In this study, we use three images that were acquired during three days in succession: from April, 29 to May, 1 2009, as well as other two acquisitions performed two weeks later (May, 16 and May, 17 2009), when the effects of the flood were disappeared. In this work, we firstly extract information on the spatial extension of homogeneous objects present in the scene through a segmentation procedure. In this way we cope with the speckle noise characteristic of SAR images and produce, from the multi-temporal series of five imagery we employ, a map formed by homogeneous regions. Among these regions we single out some areas presenting a fairly complex temporal evolution of the radar return. To correctly explain the multi-temporal radar signature of these segments, we use of a well-established electromagnetic model. Some reference multi-temporal backscattering trends are analyzed with the aid of the theoretical model to associate the segments to the classes of flooded or non-flooded areas. Using these reference trends as a training set, a classification algorithm is also developed to generate a map of the flood evolution. This study aims at demonstrating the importance and the feasibility of a method based on a joint use of a well-established electromagnetic scattering model and an advanced image processing technique to reliably interpreting SAR observations of floods.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature-tracking and pattern-matching

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.

Evaluating total inorganic nitrogen in coastal waters through fusion of multi-temporal RADARSAT-2 and optical imagery using random forest algorithm

NASA Astrophysics Data System (ADS)

Liu, Meiling; Liu, Xiangnan; Li, Jin; Ding, Chao; Jiang, Jiale

2014-12-01

Satellites routinely provide frequent, large-scale, near-surface views of many oceanographic variables pertinent to plankton ecology. However, the nutrient fertility of water can be challenging to detect accurately using remote sensing technology. This research has explored an approach to estimate the nutrient fertility in coastal waters through the fusion of synthetic aperture radar (SAR) images and optical images using the random forest (RF) algorithm. The estimation of total inorganic nitrogen (TIN) in the Hong Kong Sea, China, was used as a case study. In March of 2009 and May and August of 2010, a sequence of multi-temporal in situ data and CCD images from China's HJ-1 satellite and RADARSAT-2 images were acquired. Four sensitive parameters were selected as input variables to evaluate TIN: single-band reflectance, a normalized difference spectral index (NDSI) and HV and VH polarizations. The RF algorithm was used to merge the different input variables from the SAR and optical imagery to generate a new dataset (i.e., the TIN outputs). The results showed the temporal-spatial distribution of TIN. The TIN values decreased from coastal waters to the open water areas, and TIN values in the northeast area were higher than those found in the southwest region of the study area. The maximum TIN values occurred in May. Additionally, the estimation accuracy for estimating TIN was significantly improved when the SAR and optical data were used in combination rather than a single data type alone. This study suggests that this method of estimating nutrient fertility in coastal waters by effectively fusing data from multiple sensors is very promising.

Mass Movement Susceptibility Mapping Using Satellite Optical Imagery Compared With INSAR Monitoring: Zigui County, Three Gorges Region, China

NASA Astrophysics Data System (ADS)

Kincal, Cem; Singleton, Andrew; Liu, Peng; Li, Zhenhong; Drummond, Jane; Hoey, Trevor; Muller, Jan-Peter; Qu, Wei; Zeng, Qiming; Zhang, Jingfa; Du, Peijun

2010-10-01

Mass movements on steep slopes are a major hazard to communities and infrastructure in the Three Gorges region, China. Developing susceptibility maps of mass movements is therefore very important in both current and future land use planning. This study employed satellite optical imagery and an ASTER GDEM (15 m) to derive various parameters (namely geology; slope gradient; proximity to drainage networks and proximity to lineaments) in order to create a GIS-based map of mass movement susceptibility. This map was then evaluated using highly accurate deformation signals processed using the Persistent Scatterer (PS) InSAR technique. Areas of high susceptibility correspond well to points of high subsidence, which provides a strong support of our susceptibility map.

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

NASA Astrophysics Data System (ADS)

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

1988-04-01

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

Experimental 3-D SAR Human Target Signature Analysis

DTIC Science & Technology

2014-07-21

is a fairly transparent one constructed of drywall made of wood studs, gypsum, insulating material, and vinyl coating on the exterior. A LIDAR image...transparent wall such as drywall , there is a significant increase in the amount of clutter and multipath. Figure 8. LIDAR imagery of a human...standing inside a building constructed of drywall made of wood stud, gypsum, insulating material, and vinyl coating. In the human standing images

Space-variant filtering for correction of wavefront curvature effects in spotlight-mode SAR imagery formed via polar formatting

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

Jakowatz, C.V. Jr.; Wahl, D.E.; Thompson, P.A.

1996-12-31

Wavefront curvature defocus effects can occur in spotlight-mode SAR imagery when reconstructed via the well-known polar formatting algorithm (PFA) under certain scenarios that include imaging at close range, use of very low center frequency, and/or imaging of very large scenes. The range migration algorithm (RMA), also known as seismic migration, was developed to accommodate these wavefront curvature effects. However, the along-track upsampling of the phase history data required of the original version of range migration can in certain instances represent a major computational burden. A more recent version of migration processing, the Frequency Domain Replication and Downsampling (FReD) algorithm, obviatesmore » the need to upsample, and is accordingly more efficient. In this paper the authors demonstrate that the combination of traditional polar formatting with appropriate space-variant post-filtering for refocus can be as efficient or even more efficient than FReD under some imaging conditions, as demonstrated by the computer-simulated results in this paper. The post-filter can be pre-calculated from a theoretical derivation of the curvature effect. The conclusion is that the new polar formatting with post filtering algorithm (PF2) should be considered as a viable candidate for a spotlight-mode image formation processor when curvature effects are present.« less

Analysis of discriminants for experimental 3D SAR imagery of human targets

NASA Astrophysics Data System (ADS)

Chan, Brigitte; Sévigny, Pascale; DiFilippo, David D. J.

2014-10-01

Development of a prototype 3-D through-wall synthetic aperture radar (SAR) system is currently underway at Defence Research and Development Canada. The intent is to map out building wall layouts and to detect targets of interest and their location behind walls such as humans, arms caches, and furniture. This situational awareness capability can be invaluable to the military working in an urban environment. Tools and algorithms are being developed to exploit the resulting 3-D imagery. Current work involves analyzing signatures of targets behind a wall and understanding the clutter and multipath signals in a room of interest. In this paper, a comprehensive study of 3-D human target signature metrics in free space is presented. The aim is to identify features for discrimination of the human target from other targets. Targets used in this investigation include a human standing, a human standing with arms stretched out, a chair, a table, and a metallic plate. Several features were investigated as potential discriminants and five which were identified as good candidates are presented in this paper. Based on this study, no single feature could be used to fully discriminate the human targets from all others. A combination of at least two different features is required to achieve this.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multi-date and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands and only 18.6% of the wetland classes. The current inventory's poor performance demonstrates the value of incorporating a combination of new data sources into the provincial wetland mapping.

An improved synthesis and biological evaluation of a new cage-like bifunctional chelator, 4-((8-amino-3,6,10,13,16,19-hexaazabicyclo[6.6.6]icosane-1-ylamino)methyl)benzoic acid, for 64Cu radiopharmaceuticals.

PubMed

Cai, Hancheng; Li, Zibo; Huang, Chiun-Wei; Park, Ryan; Shahinian, Anthony H; Conti, Peter S

2010-01-01

Stable attachment of (64)Cu(2+) to a targeting molecule usually requires the use of a bifunctional chelator (BFC). Sarcophagine (Sar) ligands rapidly coordinate (64)Cu(2+) within the multiple macrocyclic rings comprising the cage structure under mild conditions, providing high stability in vivo. Previously, we have designed a new versatile cage-like BFC Sar ligand, 4-((8-amino-3,6,10,13,16,19-hexaazabicyclo[6.6.6]icosane-1-ylamino)methyl)benzoic acid (AmBaSar), for (64)Cu radiopharmaceuticals. Here we report the improved synthesis of AmBaSar, (64)Cu(2+) labeling conditions and its biological evaluation compared with the known BFC 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid (DOTA). The AmBaSar was synthesized in four steps starting from (1,8-diamine-Sar) cobalt(III) pentachloride ([Co(DiAmSar)]Cl(5)) using an improved synthetic method. The AmBaSar was labeled with (64)Cu(2+) in pH 5.0 ammonium acetate buffer solution at room temperature, followed by analysis and purification with HPLC. The in vitro stability of (64)Cu-AmBaSar complex was evaluated in phosphate buffered saline (PBS), fetal bovine serum and mouse blood. The microPET imaging and biodistribution studies of (64)Cu-AmBaSar were performed in Balb/c mice, and the results were compared with (64)Cu-DOTA. The AmBaSar was readily prepared and characterized by MS and (1)H NMR. The radiochemical yield of (64)Cu-AmBaSar was >or=98% after 30 min of incubation at 25 degrees C. The (64)Cu-AmBaSar complex was analyzed and purified by HPLC with a retention time of 17.9 min. The radiochemical purity of (64)Cu-AmBaSar was more than 97% after 26 h of incubation in PBS or serum. The biological evaluation of (64)Cu-AmBaSar in normal mouse demonstrated renal clearance as the primary mode of excretion, with improved stability in vivo compared to (64)Cu-DOTA. The new cage-like BFC AmBaSar was prepared using a simplified synthetic method. The (64)Cu-AmBaSar complex could be obtained rapidly with high radiochemical yield (>/=98%) under mild conditions. In vitro and in vivo evaluation of AmBaSar demonstrated its promising potential for preparation of (64)Cu radiopharmaceuticals. Copyright 2010. Published by Elsevier Inc.

High Resolution Full-Aperture ISAR Processing through Modified Doppler History Based Motion Compensation

PubMed Central

Song, Jung-Hwan; Lee, Kee-Woong; Lee, Woo-Kyung; Jung, Chul-Ho

2017-01-01

A high resolution inverse synthetic aperture radar (ISAR) technique is presented using modified Doppler history based motion compensation. To this purpose, a novel wideband ISAR system is developed that accommodates parametric processing over extended aperture length. The proposed method is derived from an ISAR-to-SAR approach that makes use of high resolution spotlight SAR and sub-aperture recombination. It is dedicated to wide aperture ISAR imaging and exhibits robust performance against unstable targets having non-linear motions. We demonstrate that the Doppler histories of the full aperture ISAR echoes from disturbed targets are efficiently retrieved with good fitting models. Experiments have been conducted on real aircraft targets and the feasibility of the full aperture ISAR processing is verified through the acquisition of high resolution ISAR imagery. PMID:28555036

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

1. Introduction Numerous large-scale offshore wind farms have been built in European waters and play an important role in providing renewable energy. Therefore, knowledge of behavior of wakes, induced by large wind turbines and their impact on wind power output is important. The spatial variation of offshore wind turbine wake is very complex, depending on wind speed, wind direction, ambient atmospheric turbulence and atmospheric stability. In this study we demonstrate the application of X-band TerraSAR-X (TS-X) data with high spatial resolution for studies on wind turbine wakes in the near and far field of the offshore wind farm Alpha Ventus, located in the North Sea. Two cases which different weather conditions and different wake pattern as observed in the TS-X image are presented. 2. Methods The space-borne synthetic aperture radar (SAR) is a unique sensor that provides two-dimensional information on the ocean surface. Due to their high resolution, daylight and weather independency and global coverage, SARs are particularly suitable for many ocean and coastal applications. SAR images reveal wind variations on small scales and thus represent a valuable means in detailed wind-field analysis. The general principle of imaging turbine wakes is that the reduced wind speed downstream of offshore wind farms modulates the sea surface roughness, which in turn changes the Normalized Radar Cross Section (NRCS, denoted by σ0) in the SAR image and makes the wake visible. In this study we present two cases at the offshore wind farm Alpha Ventus to investigate turbine-induced wakes and the retrieved sea surface wind field. Using the wind streaks, visible in the TS-X image and the shadow behind the offshore wind farm, induced by turbine wake, the sea surface wind direction is derived and subsequently the sea surface wind speed is calculated using the latest generation of wind field algorithm XMOD2. 3. Case study alpha ventus Alpha Ventus is located approximately 45 km from the coast of Borkum, Germany, and consists of twelve 5-Megawatt wind power turbines. The retrieved results are validated by comparing with QuikSCAT measurements, the results of the German Weather Service (DWD) atmospheric model and in-situ measurements of wind speed and wind direction, obtained from the research platform FiNO1, installed 400 m west of Alpha Ventus. 4. Conclusion In the presented case study we quantify the wake characteristics of wake length, wake width, maximum velocity de?cit, wake merging and wake meandering. We show that SAR has the capability to map the sea surface two-dimensionally in high spatial resolution which provides a unique opportunity to observe spatial characteristics of offshore wind turbine wakes. The SAR derived information can support offshore wind farming with respect to optimal siting and design and help to estimate their effects on the environment.

GTPase Sar1 regulates the trafficking and secretion of the virulence factor gp63 in Leishmania.

PubMed

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.

C- and L-band space-borne SAR incidence angle normalization for efficient Arctic sea ice monitoring

NASA Astrophysics Data System (ADS)

Mahmud, M. S.; Geldsetzer, T.; Howell, S.; Yackel, J.; Nandan, V.

2017-12-01

C-band Synthetic Aperture Radar (SAR) has been widely used effectively for operational sea ice monitoring, owing to its greater seperability between snow-covered first-year (FYI) and multi-year (MYI) ice types, during winter. However, during the melt season, C-band SAR backscatter contrast reduces between FYI and MYI. To overcome the limitations of C-band, several studies have recommended utlizing L-band SAR, as it has the potential to significantly improve sea ice classification. Given its longer wavelength, L-band can efficiently separate FYI and MYI types, especially during melt season. Therefore, the combination of C- and L-band SAR is an optimal solution for efficient seasonal sea ice monitoring. As SAR acquires images over a range of incidence angles from near-range to far-range, SAR backscatter varies substantially. To compensate this variation in SAR backscatter, incidence angle dependency of C- and L-band SAR backscatter for different FYI and MYI types is crucial to quantify, which is the objective of this study. Time-series SAR imagery from C-band RADARSAT-2 and L-band ALOS PALSAR during winter months of 2010 across 60 sites over the Canadian Arctic was acquired. Utilizing 15 images for each sites during February-March for both C- and L-band SAR, incidence angle dependency was calculated. Our study reveals that L- and C-band backscatter from FYI and MYI decreases with increasing incidence angle. The mean incidence angle dependency for FYI and MYI were estimated to be -0.21 dB/1° and -0.30 dB/1° respectively from L-band SAR, and -0.22 dB/1° and -0.16 dB/1° from C-band SAR, respectively. While the incidence angle dependency for FYI was found to be similar in both frequencies, it doubled in case of MYI from L-band, compared to C-band. After applying the incidence angle normalization method to both C- and L-band SAR images, preliminary results indicate improved sea ice type seperability between FYI and MYI types, with substantially lower number of mixed pixels; thereby offering more reliable sea ice classification accuracies. Research findings from this study can be utilized to improve seasonal sea ice classification with higher accuracy for operational Arctic sea ice monitoring, especially in regions like the Canadian Arctic, where MYI detection is crucial for safer ship navigations.

An integrated hyperspectral and SAR satellite constellation for environment monitoring

NASA Astrophysics Data System (ADS)

Wang, Jinnian; Ren, Fuhu; Xie, Chou; An, Jun; Tong, Zhanbo

2017-09-01

A fully-integrated, Hyperspectral optical and SAR (Synthetic Aperture Radar) constellation of small earth observation satellites will be deployed over multiple launches from last December to next five years. The Constellation is expected to comprise a minimum of 16 satellites (8 SAR and 8 optical ) flying in two orbital planes, with each plane consisting of four satellite pairs, equally-spaced around the orbit plane. Each pair of satellites will consist of a hyperspectral/mutispectral optical satellite and a high-resolution SAR satellite (X-band) flying in tandem. The constellation is expected to offer a number of innovative capabilities for environment monitoring. As a pre-launch experiment, two hyperspectral earth observation minisatellites, Spark 01 and 02 were launched as secondary payloads together with Tansat in December 2016 on a CZ-2D rocket. The satellites feature a wide-range hyperspectral imager. The ground resolution is 50 m, covering spectral range from visible to near infrared (420 nm - 1000 nm) and a swath width of 100km. The imager has an average spectral resolution of 5 nm with 148 channels, and a single satellite could obtain hyperspectral imagery with 2.5 million km2 per day, for global coverage every 16 days. This paper describes the potential applications of constellation image in environment monitoring.

The evolution of convective storms from their footprints on the sea as viewed by synthetic aperture radar from space

NASA Technical Reports Server (NTRS)

Atlas, David; Black, Peter G.

1994-01-01

SEASAT synthetic aperture radar (SAR) echoes from the sea have previously been shown to be the result of rain and winds produced by convective stroms; rain damps the surface waves and causes ech-free holes, while the diverging winds associated with downdraft generate waves and associated echoes surrounding the holes. Gust fronts are also evident. Such a snapshot from 8 July 1978 has been examined in conjunction with ground-based radar. This leads to the conclusion that the SAR storm footprints resulted from storm processes that occurred up to an hour or more prior to the snapshot. A sequence of events is discerned from the SAR imagery in which new cell growth is triggered in between the converging outflows of two preexisting cells. In turn, the new cell generates a mini-squall line along its expanding gust front. While such phenomena are well known over land, the spaceborne SAR now allows important inferences to be made about the nature and frequency of convective storms over the oceans. The storm effects on the sea have significant implications for spaceborne wind scatterometry and rainfall measurements. Some of the findings herein remain speculative because of the great distance to the Miami weather radar-the only source of corroborative data.

A computational analysis of SARS cysteine proteinase-octapeptide substrate interaction: implication for structure and active site binding mechanism

PubMed Central

Phakthanakanok, Krongsakda; Ratanakhanokchai, Khanok; Kyu, Khin Lay; Sompornpisut, Pornthep; Watts, Aaron; Pinitglang, Surapong

2009-01-01

Background SARS coronavirus main proteinase (SARS CoVMpro) is an important enzyme for the replication of Severe Acute Respiratory Syndrome virus. The active site region of SARS CoVMpro is divided into 8 subsites. Understanding the binding mode of SARS CoVMpro with a specific substrate is useful and contributes to structural-based drug design. The purpose of this research is to investigate the binding mode between the SARS CoVMpro and two octapeptides, especially in the region of the S3 subsite, through a molecular docking and molecular dynamics (MD) simulation approach. Results The one turn α-helix chain (residues 47–54) of the SARS CoVMpro was directly involved in the induced-fit model of the enzyme-substrate complex. The S3 subsite of the enzyme had a negatively charged region due to the presence of Glu47. During MD simulations, Glu47 of the enzyme was shown to play a key role in electrostatic bonding with the P3Lys of the octapeptide. Conclusion MD simulations were carried out on the SARS CoVMpro-octapeptide complex. The hypothesis proposed that Glu47 of SARS CoVMpro is an important residue in the S3 subsite and is involved in binding with P3Lys of the octapeptide. PMID:19208150

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Tracking lava flow emplacement on the east rift zone of Kīlauea, Hawai‘i, with synthetic aperture radar coherence

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Short peptides derived from the interaction domain of SARS coronavirus nonstructural protein nsp10 can suppress the 2'-O-methyltransferase activity of nsp10/nsp16 complex.

PubMed

Ke, Min; Chen, Yu; Wu, Andong; Sun, Ying; Su, Ceyang; Wu, Hao; Jin, Xu; Tao, Jiali; Wang, Yi; Ma, Xiao; Pan, Ji-An; Guo, Deyin

2012-08-01

Coronaviruses are the etiological agents of respiratory and enteric diseases in humans and livestock, exemplified by the life-threatening severe acute respiratory syndrome (SARS) caused by SARS coronavirus (SARS-CoV). However, effective means for combating coronaviruses are still lacking. The interaction between nonstructural protein (nsp) 10 and nsp16 has been demonstrated and the crystal structure of SARS-CoV nsp16/10 complex has been revealed. As nsp10 acts as an essential trigger to activate the 2'-O-methyltransferase activity of nsp16, short peptides derived from nsp10 may have inhibitory effect on viral 2'-O-methyltransferase activity. In this study, we revealed that the domain of aa 65-107 of nsp10 was sufficient for its interaction with nsp16 and the region of aa 42-120 in nsp10, which is larger than the interaction domain, was needed for stimulating the nsp16 2'-O-methyltransferase activity. We further showed that two short peptides derived from the interaction domain of nsp10 could inhibit the 2'-O-methyltransferase activity of SARS-CoV nsp16/10 complex, thus providing a novel strategy and proof-of-principle study for developing peptide inhibitors against SARS-CoV. Copyright © 2012 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

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

Rapid damage mapping for the 2015 M7.8 Gorkha earthquake using synthetic aperture radar data from COSMO-SkyMed and ALOS-2 satellites

USGS Publications Warehouse

Yun, Sang-Ho; Hudnut, Kenneth W.; Owen, Susan; Webb, Frank; Simons, Mark; Sacco, Patrizia; Gurrola, Eric; Manipon, Gerald; Liang, Cunren; Fielding, Eric; Milillo, Pietro; Hua, Hook; Coletta, Alessandro

2015-01-01

The 25 April 2015 Mw 7.8 Gorkha earthquake caused more than 8000 fatalities and widespread building damage in central Nepal. The Italian Space Agency’s COSMO–SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area four days after the earthquake and the Japan Aerospace Exploration Agency’s Advanced Land Observing Satellite-2 SAR satellite for larger area nine days after the mainshock. We used these radar observations and rapidly produced damage proxy maps (DPMs) derived from temporal changes in Interferometric SAR coherence. Our DPMs were qualitatively validated through comparison with independent damage analyses by the National Geospatial-Intelligence Agency and the United Nations Institute for Training and Research’s United Nations Operational Satellite Applications Programme, and based on our own visual inspection of DigitalGlobe’s WorldView optical pre- versus postevent imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Multitemporal L- and C-Band Synthetic Aperture Radar To Highlight Differences in Water Status Among Boreal Forest and Wetland Systems in the Yukon Flats, Interior Alaska

USGS Publications Warehouse

Balser, Andrew W.; Wylie, Bruce K.

2010-01-01

Tracking landscape-scale water status in high-latitude boreal systems is indispensible to understanding the fate of stored and sequestered carbon in a climate change scenario. Spaceborne synthetic aperture radar (SAR) imagery provides critical information for water and moisture status in Alaskan boreal environments at the landscape scale. When combined with results from optical sensor analyses, a complementary picture of vegetation, biomass, and water status emerges. Whereas L-band SAR showed better inherent capacity to map water status, C-band had much more temporal coverage in this study. Analysis through the use of L- and C-band SARs combined with Landsat Enhanced Thematic Mapper Plus (ETM+) enables landscape stratification by vegetation and by seasonal and interannual hydrology. Resultant classifications are highly relevant to biogeochemistry at the landscape scale. These results enhance our understanding of ecosystem processes relevant to carbon balance and may be scaled up to inform regional carbon flux estimates and better parameterize general circulation models (GCMs).

Characteristics of Forests in Western Sayani Mountains, Siberia from SAR Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Sun, Guoqing; Kharuk, V. I.; Kovacs, Katalin

1998-01-01

This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and

Global Rapid Flood Mapping System with Spaceborne SAR Data

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Study on Persistent Monitoring of Maritime, Great Lakes and St. Lawrence Seaway Border Regions

DTIC Science & Technology

2011-12-01

narcotics between both countries, particularly due to the burgeoning marijuana market originating in British Columbia (BC). Additionally, due to the...Sensors 2008, Vol. 8, pp. 2959-2973 Crisp D. J., The State-of-the-Art in Ship Detection in Synthetic Aperture Radar Imagery, DSTO– RR–0272...Network SAR – Synthetic Aperture radar SII-Surveillance Intelligence and Interdiction SNR - Signal-to-Noise SOLAS - Safety of Life at Sea

Evaluation of DOD Priority Species at Risk (SAR) and Applications for Remote Sensing

DTIC Science & Technology

2009-02-01

Species Type Common Name Scientific Name Fort McClellan AL fish coldwater darter Etheostoma ditrema Camp Shelby MS crustacean Camp Shelby burrowing...plant in the Aster family that exhibits mat-forming growth characteristics (Figure 15). B. tetraneuris in- habits barren, light colored shale and...vegetated areas within Fort Lewis, WA have the poten- tial to be mapped using high-resolution multispectral imagery. Other open (i.e., disturbed) habited

Development of an ATR Workbench for SAR Imagery

DTIC Science & Technology

2002-12-01

containing a representation of the object. Each image representation contains only a subset of information about t, and that information is often...GUI. In the case of HNeT under Windows, the native COM/ ActiveX automation interface is used. This provides Python with direct access to the many...that can contain other objects such as a menu bar, buttons, an image display area, text box etc. The library also provides an event handling mechanism

Remote Monitoring of Groundwater Overdraft Using GRACE and InSAR

NASA Astrophysics Data System (ADS)

Scher, C.; Saah, D.

2017-12-01

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

On the use of RADARSAT-1 for monitoring malaria risk in Kenya

NASA Astrophysics Data System (ADS)

Ross, S. G.; Thomson, M. C.; Pultz, T.; Mbogo, C. M.; Regens, J. L.; Swalm, C.; Githure, J.; Yan, G.; Gu, W.; Beier, J. C.

2002-01-01

The incidence and spread of vector-borne infectious diseases are increasing concerns in many parts of the world. Earth obervation techniques provide a recognised means for monitoring and mapping disease risk as well as correlating environmental indicators with various disease vectors. Because the areas most impacted by vector-borne disease are remote and not easily monitored using traditional, labor intensive survey techniques, high spatial and temporal coverage provided by spaceborne sensors allows for the investigation of large areas in a timely manner. However, since the majority of infectious diseases occur in tropical areas, one of the main barriers to earth observation techniques is persistent cloud-cover. Synthetic Aperture Radar (SAR) technology offers a solution to this problem by providing all-weather, day and night imaging capability. Based on SAR's sensitivity to target moisture conditions, sensors such as RADARSAT-1 can be readily used to map wetland and swampy areas that are conducive to functioning as aquatic larval habitats. Irrigation patterns, deforestation practises and the effects of local flooding can be monitored using SAR imagery, and related to potential disease vector abundance and proximity to populated areas. This paper discusses the contribution of C-band radar remote sensing technology to monitoring and mapping malaria. Preliminary results using RADARSAT-1 for identifying areas of high mosquito (Anopheles gambiae s.l.) abundance along the Kenya coast will be discussed. The authors consider the potential of RADARSAT-1 data based on SAR sensor characteristics and the preliminary results obtained. Further potential of spaceborne SAR data for monitoring vector-borne disease is discussed with respect to future advanced SAR sensors such as RADARSAT-2.

Linking goniometer measurements to hyperspectral and multisensor imagery for retrieval of beach properties and coastal characterization

NASA Astrophysics Data System (ADS)

Bachmann, Charles M.; Gray, Deric; Abelev, Andrei; Philpot, William; Montes, Marcos J.; Fusina, Robert; Musser, Joseph; Li, Rong-Rong; Vermillion, Michael; Smith, Geoffrey; Korwan, Daniel; Snow, Charlotte; Miller, W. David; Gardner, Joan; Sletten, Mark; Georgiev, Georgi; Truitt, Barry; Killmon, Marcus; Sellars, Jon; Woolard, Jason; Parrish, Christopher; Schwarzscild, Art

2012-06-01

In June 2011, a multi-sensor airborne remote sensing campaign was flown at the Virginia Coast Reserve Long Term Ecological Research site with coordinated ground and water calibration and validation (cal/val) measurements. Remote sensing imagery acquired during the ten day exercise included hyperspectral imagery (CASI-1500), topographic LiDAR, and thermal infra-red imagery, all simultaneously from the same aircraft. Airborne synthetic aperture radar (SAR) data acquisition for a smaller subset of sites occurred in September 2011 (VCR'11). Focus areas for VCR'11 were properties of beaches and tidal flats and barrier island vegetation and, in the water column, shallow water bathymetry. On land, cal/val emphasized tidal flat and beach grain size distributions, density, moisture content, and other geotechnical properties such as shear and bearing strength (dynamic deflection modulus), which were related to hyperspectral BRDF measurements taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). This builds on our earlier work at this site in 2007 related to beach properties and shallow water bathymetry. A priority for VCR'11 was to collect and model relationships between hyperspectral imagery, acquired from the aircraft at a variety of different phase angles, and geotechnical properties of beaches and tidal flats. One aspect of this effort was a demonstration that sand density differences are observable and consistent in reflectance spectra from GOPHER data, in CASI hyperspectral imagery, as well as in hyperspectral goniometer measurements conducted in our laboratory after VCR'11.

Natural Time Analysis and Complex Networks

NASA Astrophysics Data System (ADS)

Sarlis, Nicholas; Skordas, Efthimios; Lazaridou, Mary; Varotsos, Panayiotis

2013-04-01

Here, we review the analysis of complex time series in a new time domain, termed natural time, introduced by our group [1,2]. This analysis conforms to the desire to reduce uncertainty and extract signal information as much as possible [3]. It enables [4] the distinction between the two origins of self-similarity when analyzing data from complex systems, i.e., whether self-similarity solely results from long-range temporal correlations (the process's memory only) or solely from the process's increments infinite variance (heavy tails in their distribution). Natural time analysis captures the dynamical evolution of a complex system and identifies [5] when the system enters a critical stage. Hence, this analysis plays a key role in predicting forthcoming catastrophic events in general. Relevant examples, compiled in a recent monograph [6], have been presented in diverse fields, including Solid State Physics [7], Statistical Physics (for example systems exhibiting self-organized criticality [8]), Cardiology [9,10], Earth Sciences [11] (Geophysics, Seismology), Environmental Sciences (e.g. see Ref. [12]), etc. Other groups have proposed and developed a network approach to earthquake events with encouraging results. A recent study [13] reveals that this approach is strengthened if we combine it with natural time analysis. In particular, we find [13,14] that the study of the spatial distribution of the variability [15] of the order parameter fluctuations, defined in natural time, provides important information on the dynamical evolution of the system. 1. P. Varotsos, N. Sarlis, and E. Skordas, Practica of Athens Academy, 76, 294-321, 2001. 2. P.A. Varotsos, N.V. Sarlis, and E.S. Skordas, Phys. Rev. E, 66, 011902 , 2002. 3. S. Abe, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and P.A. Varotsos, Phys. Rev. Lett. 94, 170601, 2005. 4. P.A. Varotsos, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and M.S. Lazaridou, Phys. Rev. E, 74, 021123, 2006. 5. P.Varotsos, N. V. Sarlis, E. S. Skordas, S. Uyeda, and M. Kamogawa, Proc Natl Acad Sci USA 108, 11361-11364, 2011. 6. P.A.Varotsos, N.V.Sarlis and E.S.Skordas, NATURAL TIME ANALYSIS: THE NEW VIEW OF TIME. Precursory Seismic Electric Signals, Earthquakes and other Complex Time-Series, Springer-Verlag, Berlin, Heidelberg, 2011. 7. N.V. Sarlis, P.A. Varotsos, and E.S. Skordas, Phys. Rev. B 73, 054504, 2006. 8. N. V. Sarlis, E. S. Skordas, and P. A. Varotsos, EPL 96, 28006, 2011. 9. P.A. Varotsos, N.V. Sarlis, E.S. Skordas, and M.S. Lazaridou, Appl. Phys. Lett. 91, 064106, 2007. 10. N.V. Sarlis, E.S. Skordas and P.A. Varotsos, EuroPhysics Letters EPL, 87, 18003, (2009). 11. P.A. Varotsos, N. V. Sarlis and E. S. Skordas, EPL 96 59002, 2011; 99, 59001 2012; 100 39002, 2012. 12. C.A. Varotsos and C. Tzanis, Atmospheric Environment 47, 428-434, 2012. 13. P. Varotsos, N. Sarlis, E. Skordas and M. Lazaridou, Tectonophysics (DOI 10.1016/j.tecto.2012.12.020). 14. P. Varotsos, N. Sarlis and E. Skordas, EPL to be published. 15. N. V. Sarlis, E. S. Skordas and P. A. Varotsos, EPL 91, 59001, 2010.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

Besides their suitability for multi-temporal and spatial deformation analysis, the Synthetic Aperture Radar (SAR) image archives acquired by space-borne radar sensors can be exploited to support archaeological investigations over huge sites, even those partially or totally buried and still to be excavated. Amplitude information is one of the main properties of SAR data from which it is possible to retrieve evidences of buried structures, using feature extraction and texture analysis. Multi-temporality allows the reconstruction of past and recent evolution of both landscape and built-up environment, with the possibility to detect natural and/or anthropogenic changes, including human-induced damages to the conservation of cultural heritage. We present the methodology and first results of the experiments currently undertaken using SAR data in the Nasca region (Southern Peru), where two important civilizations such as Paracas and Nasca developed and flourished from 4th century BC to the 6th century AD. The study areas include a wide spectrum of archaeological and environmental elements to be preserved, among which: the archaeological site of Cahuachi and its surroundings, considered the largest adobe Ceremonial Centre in the World; the Nasca lines and geoglyphs in the areas of Palpa, Atarco and Nasca; the ancient networks of aqueducts and drainage galleries in the Puquios area, built by Nasca in the 1st-6th centuries AD. Archaeological prospection and multi-purpose remote sensing activities are currently carried out in the framework of the Italian mission of heritage Conservation and Archaeogeophysics (ITACA), with the direct involvement of researchers from the Institute for Archaeological and Monumental Heritage and the Institute of Methodologies for Environmental Analysis, Italian National Research Council. In this context, C- and L-band SAR images covering the Nasca region since 2001 were identified for the purposes of this research and, in particular, the following data stacks were selected: ERS-2 ascending data acquired in 2001-2011, ENVISAT ASAR ascending and descending data acquired in 2003-2007, and ALOS PALSAR descending and ascending data acquired in 2007 and 2008. The feature extraction was specifically addressed to the recognition of buried structures, archaeological deposits and the study of the buried networks of aqueducts, as well as the morphological study of the Nasca geoglyphs. Change detection analysis also included the multi-temporal reconstruction of the evolution of the Rio Nasca catchment basin, while specific tests were performed to demonstrate the usefulness of SAR imagery for monitoring looting activities. The results of the radar-interpretation compared and integrated with the field investigations will support the archaeological activities and contribute to the monitoring and enhancement of archaeological heritage and cultural landscape of the Nasca region.

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.

A post-processing system for automated rectification and registration of spaceborne SAR imagery

NASA Technical Reports Server (NTRS)

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

1987-01-01

An automated post-processing system has been developed that interfaces with the raw image output of the operational digital SAR correlator. This system is designed for optimal efficiency by using advanced signal processing hardware and an algorithm that requires no operator interaction, such as the determination of ground control points. The standard output is a geocoded image product (i.e. resampled to a specified map projection). The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes over the same target area. The output products have absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 per cent relative to local variations from the assumed geoid.

Complex phase error and motion estimation in synthetic aperture radar imaging

NASA Astrophysics Data System (ADS)

Soumekh, M.; Yang, H.

1991-06-01

Attention is given to a SAR wave equation-based system model that accurately represents the interaction of the impinging radar signal with the target to be imaged. The model is used to estimate the complex phase error across the synthesized aperture from the measured corrupted SAR data by combining the two wave equation models governing the collected SAR data at two temporal frequencies of the radar signal. The SAR system model shows that the motion of an object in a static scene results in coupled Doppler shifts in both the temporal frequency domain and the spatial frequency domain of the synthetic aperture. The velocity of the moving object is estimated through these two Doppler shifts. It is shown that once the dynamic target's velocity is known, its reconstruction can be formulated via a squint-mode SAR geometry with parameters that depend upon the dynamic target's velocity.

Global Crop Area Monitoring at High Resolution Exploiting Complementary Use of Free and Open SAR and VSNIR/SWIR Sensor Data Sets

NASA Astrophysics Data System (ADS)

Lemoine, G.; LEO, O.

2015-12-01

Earth Observation imaging sensors with spatial resolutions in the 10-30 m range allow for separation of the area and crop status contributions to the radiometric signatures, typically at parcel level for a wide range of arable crop production systems. These sensors complement current monitoring efforts that deploy low (100-1000 m) resolution VSNIR/SWIR sensors like MODIS, METOP or PROBA-V, which provide denser time series, but with aggregated and mixed radiometric information for cropped areas. "Free and Open" access to US Landsat imagery has recently been complemented by the European Union's Copernicus program with access to Sentinel-1A C-band SAR and Sentinel-2A visual, near and short-ware infrared (VSNIR/SWIR) sensor data in the 10-20 m resolution range. Sentinel-1A has already proven that consistent time series can be generated at its 12 day revisit frequency. The density of Sentinel-2 time series will greatly expand the availability of [partially cloud covered] VSNIR/SWIR imagery. The release of this large new data flow coincides with wider availability of "big data" processing capacity, the public release of ever more detailed ancillary data sets that support extraction of georeferenced and robust indicators on crop production and their spatial and temporal statistics and developments in crowd-sourced mobile data collection for data validation purposes. We will illustrate the use of hybrid SAR and VSNIR/SWIR data sets from Sentinel-1 and Landsat-8 (and initially released Sentinel-2 imagery) for a number of selected examples. These include crop area delineation and classification in the Netherlands with the support of detailed parcel delineation sets for validation, detection of winter cereal cultivation in Ukraine, impact of the Syrian civil war on irrigated summer crop cultivation and recent examples in support to crop anomaly detection in food insecure areas (North Korea, Sub-Saharan Africa). We discuss method implementation, operational issues and outline the needs for further research in support to our crop "knowledge inference" framework. Most of our work is based on the use of Google Earth Engine (GEE) and the first batch of 12,000 geocoded Sentinel-1A images that was recently included.

High Resolution Rapid Revisits Insar Monitoring of Surface Deformation

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Quantifying Fire Impact on Alaskan Tundra from Satellite Observations and Field Measurements

NASA Astrophysics Data System (ADS)

Loboda, T. V.; Chen, D.; He, J.; Jenkins, L. K.

2017-12-01

Wildfire is a major disturbance agent in Alaskan tundra. The frequency and extent of fire events obtained from paleo, management, and satellite records may yet underestimate the scope of tundra fire impact. Field measurements, collected within the NASA's ABoVE campaign, revealed unexpectedly shallow organic soils ( 15 cm) across all sampled sites of the Noatak valley with no significant difference between recently burned and unburned sites. In typical small and medium-sized tundra burns vegetation recovers rapidly and scars are not discernable in 30 m optical satellite imagery by the end of the first post-fire season. However, field observations indicate that vegetation and subsurface characteristics within fire scars of different ages vary across the landscape. In this study we develop linkages between fire-induced changes to tundra and satellite-based observations from optical, thermal, and microwave imagers to enable extrapolation of in-situ observations to cover the full extent of Alaskan tundra. Our results show that recent ( 30 years) fire history can be reconstructed from optical observations (R2 0.65, p<0.001) within a specific narrow temporal window or thermal signatures (R2 0.54, p < 0.001), in both cases controlled for slope and southern exposure. Using microwave SAR imagery fire history can be determined for 4 years post fire primarily due to increased soil moisture at burned sites. Field measurements suggest that the relatively quick SAR signal dissipation results from more even distribution of surface moisture through the soil column with increases in Active Layer Thickness (ALT). Similar to previous long-term field studies we find an increase in shrub fraction and shrub height within burns over time at the landscape scale; however, the strength and significance of the relationship between shrub fraction and time since fire is governed by burn severity with more severe burns predictably (p < 0.01) resulting in higher post-fire shrub cover. Although reasonably well-correlated to each other when adjusted for topography (R2 0.35, p < 0.001), neither ALT nor soil temperature can be directly linked to optical or thermal brightness observations with acceptable statistical significance, necessitating a more complex modeling environment for wall-to-wall mapping of subsurface parameters.

Effective Integration of Earth Observation Data and Flood Modeling for Rapid Disaster Response: The Texas 2015 Case

NASA Astrophysics Data System (ADS)

Schumann, G.

2016-12-01

Routinely obtaining real-time 2-D inundation patterns of a flood event at a meaningful spatial resolution and over large scales is at the moment only feasible with either operational aircraft flights or satellite imagery. Of course having model simulations of floodplain inundation available to complement the remote sensing data is highly desirable, for both event re-analysis and forecasting event inundation. Using the Texas 2015 flood disaster, we demonstrate the value of multi-scale EO data for large scale 2-D floodplain inundation modeling and forecasting. A dynamic re-analysis of the Texas 2015 flood disaster was run using a 2-D flood model developed for accurate large scale simulations. We simulated the major rivers entering the Gulf of Mexico and used flood maps produced from both optical and SAR satellite imagery to examine regional model sensitivities and assess associated performance. It was demonstrated that satellite flood maps can complement model simulations and add value, although this is largely dependent on a number of important factors, such as image availability, regional landscape topology, and model uncertainty. In the preferred case where model uncertainty is high, landscape topology is complex (i.e. urbanized coastal area) and satellite flood maps are available (in case of SAR for instance), satellite data can significantly reduce model uncertainty by identifying the "best possible" model parameter set. However, most often the situation is occurring where model uncertainty is low and spatially contiguous flooding can be mapped from satellites easily enough, such as in rural large inland river floodplains. Consequently, not much value from satellites can be added. Nevertheless, where a large number of flood maps are available, model credibility can be increased substantially. In the case presented here this was true for at least 60% of the many thousands of kilometers of river flow length simulated, where satellite flood maps existed. The next steps of this project is to employ a technique termed "targeted observation" approach, which is an assimilation based procedure that allows quantifying the impact observations have on model predictions at the local scale and also along the entire river system, when assimilated with the model at specific "overpass" locations.

ISCE: A Modular, Reusable Library for Scalable SAR/InSAR Processing

NASA Astrophysics Data System (ADS)

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

2016-12-01

Traditional community SAR/InSAR processing software tools have primarily focused on differential interferometry and Solid Earth applications. The InSAR Scientific Computing Environment (ISCE) was specifically designed to support the Earth Sciences user community as well as large scale operational processing tasks, thanks to its two-layered (Python+C/Fortran) architecture and modular framework. ISCE is freely distributed as a source tarball, allowing advanced users to modify and extend it for their research purposes and developing exploratory applications, while providing a relatively simple user interface for novice users to perform routine data analysis efficiently. Modular design of the ISCE library also enables easier development of applications to address the needs of Ecosystems, Cryosphere and Disaster Response communities in addition to the traditional Solid Earth applications. In this talk, we would like to emphasize the broader purview of the ISCE library and some of its unique features that sets it apart from other freely available community software like GMTSAR and DORIS, including: Support for multiple geometry regimes - Native Doppler (ALOS-1) as well Zero Doppler (ESA missions) systems. Support for data acquired by airborne platforms - e.g, JPL's UAVSAR and AirMOSS, DLR's F-SAR. Radiometric Terrain Correction - Auxiliary output layers from the geometry modules include projection angles, incidence angles, shadow-layover masks. Dense pixel offsets - Parallelized amplitude cross correlation for cryosphere / ionospheric correction applications. Rubber sheeting - Pixel-by-pixel offsets fields for resampling slave imagery for geometric co-registration/ ionospheric corrections. Preliminary Tandem-X processing support - Bistatic geometry modules. Extensibility to support other non-Solid Earth missions - Modules can be directly adopted for use with other SAR missions, e.g., SWOT. Preliminary support for multi-dimensional data products- multi-polarization, multi-frequency, multi-temporal, multi-baseline stacks via the PLANT and GIAnT toolboxes. Rapid prototyping - Geometry manipulation functionality at the python level allows users to prototype and test processing modules at the interpreter level before optimal implementation in C/C++/Fortran.

Ship Signatures in RADARSAT-1 ScanSAR Narrow B Imagery: Analysis with AISLive Data

DTIC Science & Technology

2007-03-01

desired target subscene contains image border “airballs” (i.e., the zero padded region around the image); • Multi-Signature Target Masking – A...of figures Figure 1. Histogram of latencies from AIS broadcast times by the originating vessels to the AISLive snapshot acquistion time for the... zero -th approximation, and first approximation courses are , , , and , respectively. The path length is a function of: a) the offset totalD iC fC

Sea Ice Classification Using Synthetic Aperture Radar

DTIC Science & Technology

1990-06-01

same as the correlation of VBI to VB2 . There are other considerations that will influence the strength of the discrimination. Some of these...high density data tapes that the images used in this thesis were extracted . The fact that the SAR was not calibrated may have some effect on the...imagery. These images were extracted from the data collected on missions flown on 5-8 April 1987. The areal coverage of these missions are shown in

Lithospheric Subduction on Earth and Venus?

NASA Astrophysics Data System (ADS)

Sandwell, D. T.; Garcia, E.; Stegman, D. R.; Schubert, G.

2016-12-01

There are three mechanisms by which terrestrial planets can shed excess heat: conduction across a surface thermal boundary layer; advection of heat through volcanic pipes; and mobile plates/subduction. On the Earth about 30% is released by conduction and 70% by subduction. The dominant mode of heat transport on Venus is largely unknown. Plate flexure models rule out significant heat loss by conduction and the resurfacing from active volcanism is in discordance with a surface age of 600 Ma. There are 9000 km of trenches on Venus that may have been subduction sites but they do not appear active today and are only 25% of the length of the subduction zones on the Earth. Turcotte and others have proposed an episodic recycling model that has short bursts ( 150 Ma) of plate tectonic activity followed by long periods ( 450 Ma) of stagnant lid convection. This talk will review the arguments for and against subduction zones on Venus and discuss possible new satellite observations that could help resolve the subduction issue. Figure Caption. (a) Global mosaic of Magellan SAR imagery. (b) Zoom of area along the Artemis trench, which has similar topography and fracture patterns as the Aleutian subduction zone on Earth. Trench and outer rise lines were digitized from the matching topography image (not shown). The Magellan SAR imagery and topography, displayed on Google Earth, can be downloaded at http://topex.ucsd.edu/venus/index.html

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

The Lampur Sidoarjo mud volcano (Java, Indonesia), colloquially called LUSI, first appeared in May 2006. Its cause, whether the result of natural or anthropogenic activities (or a combination of both), is still being debated within the academic, engineering and political communities.The mud volcano expels up to 150,000 m3 of mud per day; and over time, this large volume of mud has had a major environmental and economic impact on the region. The mud flow from LUSI has now covered 6 km2 to depths some tens of metres, displacing approximately 30,000 residents; and continues to threaten local communities, businesses and industry. With such a large volume of mud being expelled each day it is inevitable (as with onshore oil and gas production fields) that there will be some ground surface movement and instability issues at the mud source (the main vent), and in the vicinity of the mud volcano footprint.Due to the dynamic ground surface conditions, engineers and academics alike have found it difficult to reliably monitor ground surface movements within the effected region using conventional surveying techniques. Consequently, engineers responsible for the risk assessment of ground surface instabilities within the proximity of LUSI have called upon the use of satellite interferometry to continually monitor the hazard.The Advanced Land Observing Satellite (ALOS), launched on 24th January 2006, carries onboard an L- band Synthetic Aperture Radar (SAR) instrument called PALSAR (Phased Array type L-band Synthetic Aperture Radar). In contrast to established C-band (5.6cm wavelength) SAR instruments onboard ERS-1 & -2, Envisat, Radarsat-1, and the recently launched Radarsat-2 satellite, PALSAR's (L-band/23.8cm wavelength) instrument presents a number of advantages, including the ability to map larger-scale ground motions, over relatively short timeframes, in tropical environments, without suffering as significantly from signal decorrelation associated with C-band imagery.This paper presents the results of a 2-year ALOS PALSAR Differential Interferometric (DifSAR) monitoring campaign across the LUSI mud volcano. DifSAR processing was applied to a sequence of images acquired on a 3 to 6-month basis between May 2006 and May 2008. The results highlight the capability of ALOS PALSAR in detecting decimetres of coherent ground subsidence to assist engineers in their analysis of the structure, dynamics and overall stability of the mud volcano and the surrounding region.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

DOEpatents

Doerry, Armin W [Albuquerque, NM

2009-06-23

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

To assess the value of satellite photographs in the resource evaluation on a national scale

NASA Technical Reports Server (NTRS)

Hepworth, J. V. (Principal Investigator); Akehurst, S. M.

1973-01-01

The author has identified the following significant results. Some observations have been made on ERTS-1 color imagery and comparison of imagery. Results of geophysical work are correlated with ERTS-1 imagery and new lineaments are postuated in the northern Kalahari Desert. ERTS-1 imagery reveals complex structural trends in the Basement Complex in the Selebi-Pikwe area.

Synthesis of hexa aza cages, SarAr-NCS and AmBaSar and a study of their metal complexation, conjugation to nanomaterials and proteins for application in radioimaging and therapy.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

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

Feasibility of sea ice typing with synthetic aperture radar (SAR): Merging of Landsat thematic mapper and ERS 1 SAR satellite imagery

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.

An improved land mask for the SSM/I grid

NASA Technical Reports Server (NTRS)

Martino, Michael G.; Cavalieri, Donald J.; Gloersen, Per; Zwally, H. Jay; Acker, James G. (Editor)

1995-01-01

This paper discusses the development of a new land/ocean/coastline mask for use with Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) data, and other types of data which are mapped to the polar stereographic SSM/I grid. Pre-existing land masks were found to disagree, to lack certain land features, and to disagree with land boundaries that are visible in high resolution sensor imagery, such as imagery from the Synthetic Aperture Radar (SAR) on the Earth Resources Satellite (ERS-1). The Digital Chart of the World (DCW) database was initially selected as a source of shoreline data for this effort. Techniques for developing a land mask from these shoreline data are discussed. The resulting land mask, although not perfect, is seen to exhibit significant improvement over previous land mask products.

Geodetic Imaging and Tsunami Modeling of the 2017 Coupled Landslide-Tsunami Event in Karrat Fjord, West Greenland.

NASA Astrophysics Data System (ADS)

Barba, M.; Willis, M. J.; Tiampo, K. F.; Lynett, P. J.; Mätzler, E.; Thorsøe, K.; Higman, B. M.; Thompson, J. A.; Morin, P. J.

2017-12-01

We use a combination of geodetic imaging techniques and modelling efforts to examine the June 2017 Karrat Fjord, West Greenland, landslide and tsunami event. Our efforts include analysis of pre-cursor motions extracted from Sentinal SAR interferometry that we improved with high-resolution Digital Surface Models derived from commercial imagery and geo-coded Structure from Motion analyses. We produce well constrained estimates of landslide volume through DSM differencing by improving the ArcticDEM coverage of the region, and provide modeled tsunami run-up estimates at villages around the region, constrained with in-situ observations provided by the Greenlandic authorities. Estimates of run-up at unoccupied coasts are derived using a blend of high resolution imagery and elevation models. We further detail post-failure slope stability for areas of interest around the Karrat Fjord region. Warming trends in the region from model and satellite analysis are combined with optical imagery to ascertain whether the influence of melting permafrost and the formation of small springs on a slight bench on the mountainside that eventually failed can be used as indicators of future events.

Identification of sea ice types in spaceborne synthetic aperture radar data

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

InSAR observations of strain accumulation and fault creep along the Chaman Fault system, Pakistan and Afghanistan

NASA Astrophysics Data System (ADS)

Fattahi, Heresh; Amelung, Falk

2016-08-01

We use 2004-2011 Envisat synthetic aperture radar imagery and InSAR time series methods to estimate the contemporary rates of strain accumulation in the Chaman Fault system in Pakistan and Afghanistan. At 29 N we find long-term slip rates of 16 ± 2.3 mm/yr for the Ghazaband Fault and of 8 ± 3.1 mm/yr for the Chaman Fault. This makes the Ghazaband Fault one of the most hazardous faults of the plate boundary zone. We further identify a 340 km long segment displaying aseismic surface creep along the Chaman Fault, with maximum surface creep rate of 8.1 ± 2 mm/yr. The observation that the Chaman Fault accommodates only 30% of the relative plate motion between India and Eurasia implies that the remainder is accommodated south and east of the Katawaz block microplate.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed.

A portfolio of products from the rapid terrain visualization interferometric SAR

NASA Astrophysics Data System (ADS)

Bickel, Douglas L.; Doerry, Armin W.

2007-04-01

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

Optimal spatial filtering and transfer function for SAR ocean wave spectra

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Optimal spatial filtering and transfer function for SAR ocean wave spectra

NASA Technical Reports Server (NTRS)

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

1981-01-01

The Seasat Synthetic Aperture Radar (SAR) has proved to be an instrument of great utility in the sensing of ocean conditions on a global scale. An analysis of oceanographic and atmospheric aspects of Seasat data has shown that the features observed in the imagery are linked to ocean phenomena such as storm sources and their resulting swell systems. However, there remains one central problem which has not been satisfactorily solved to date. This problem is related to the accurate measurement of wind-generated ocean wave spectra. Investigations addressing this problem are currently being conducted. The problem has two parts, including the accurate measurement of the image spectra and the inference of actual surface wave spectra from these measurements. A description is presented of the progress made towards solving the first part of the problem, taking into account a digital rather than optical computation of the image transforms.

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

The Seasat SAR Wind and Ocean Wave Monitoring Capabilities: A case study for pass 1339m

NASA Technical Reports Server (NTRS)

Beal, R. C.

1980-01-01

A well organized low energy 11 sec. swell system off the East Coast of the U.S. was detected with the Seasat Synthetic Aperture Radar and successfully tracked from deep water, across the continental shelf, and into shallow water. In addition, a less organized 7 sec. system was tentatively identified in the imagery. Both systems were independently confirmed with simultaneous wave spectral measurements from a research pier, aircraft laser profilometer data, and Fleet Numerical Spectral Ocean Wave Models.

Current and Density Observations of Packets of Nonlinear Internal Waves on the Outer New Jersey Shelf

DTIC Science & Technology

2011-05-01

NUMBER 0602435N 6. AUTHOR(S) William Teague, Hemantha Wijesekera, W. Avera, Z.R. Hallock 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT...ABSTRACT uu 18. NUMBER OF PAGES 15 19a. NAME OF RESPONSIBLE PERSON William J. Teague 19b. TELEPHONE NUMBER (Include area code) 228-688-4734...satellite synthetic aperture radar (SAR) imagery (Jackson and Apel 2004). NLIWs can have a surface signature de- lectable by both ship and satellite

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.

Preliminary study of near surface detections at geothermal field using optic and SAR imageries

NASA Astrophysics Data System (ADS)

Kurniawahidayati, Beta; Agoes Nugroho, Indra; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Current remote sensing technologies shows that surface manifestation of geothermal system could be detected with optical and SAR remote sensing, but to assess target beneath near the surface layer with the surficial method needs a further study. This study conducts a preliminary result using Optic and SAR remote sensing imagery to detect near surface geothermal manifestation at and around Mt. Papandayan, West Java, Indonesia. The data used in this study were Landsat-8 OLI/TIRS for delineating geothermal manifestation prospect area and an Advanced Land Observing Satellite(ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) level 1.1 for extracting lineaments and their density. An assumption was raised that the lineaments correlated with near surface structures due to long L-band wavelength about 23.6 cm. Near surface manifestation prospect area are delineated using visual comparison between Landsat 8 RGB True Colour Composite band 4,3,2 (TCC), False Colour Composite band 5,6,7 (FCC), and lineament density map of ALOS PALSAR. Visual properties of ground object were distinguished from interaction of the electromagnetic radiation and object whether it reflect, scatter, absorb, or and emit electromagnetic radiation based on characteristic of their molecular composition and their macroscopic scale and geometry. TCC and FCC composite bands produced 6 and 7 surface manifestation zones according to its visual classification, respectively. Classified images were then compared to a Normalized Different Vegetation Index (NDVI) to obtain the influence of vegetation at the ground surface to the image. Geothermal area were classified based on vegetation index from NDVI. TCC image is more sensitive to the vegetation than FCC image. The later composite produced a better result for identifying visually geothermal manifestation showed by detail-detected zones. According to lineament density analysis high density area located on the peak of Papandayan overlaid with zone 1 and 2 of FCC. Comparing to the extracted lineament density, we interpreted that the near surface manifestation is located at zone 1 and 2 of FCC image.

Auditory Imagery: Empirical Findings

ERIC Educational Resources Information Center

Hubbard, Timothy L.

2010-01-01

The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d)…

Ocean Remote Sensing from Chinese Spaceborne Microwave Sensors

NASA Astrophysics Data System (ADS)

Yang, J.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Small GTPase Sar1 is crucial for proglutelin and α-globulin export from the endoplasmic reticulum in rice endosperm.

PubMed

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.

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.

Structural basis for the development of SARS 3CL protease inhibitors from a peptide mimic to an aza-decaline scaffold.

PubMed

Teruya, Kenta; Hattori, Yasunao; Shimamoto, Yasuhiro; Kobayashi, Kazuya; Sanjoh, Akira; Nakagawa, Atsushi; Yamashita, Eiki; Akaji, Kenichi

2016-11-04

Design of inhibitors against severe acute respiratory syndrome (SARS) chymotrypsin-like protease (3CL(pro) ) is a potentially important approach to fight against SARS. We have developed several synthetic inhibitors by structure-based drug design. In this report, we reveal two crystal structures of SARS 3CL(pro) complexed with two new inhibitors based on our previous work. These structures combined with six crystal structures complexed with a series of related ligands reported by us are collectively analyzed. To these eight complexes, the structural basis for inhibitor binding was analyzed by the COMBINE method, which is a chemometrical analysis optimized for the protein-ligand complex. The analysis revealed that the first two latent variables gave a cumulative contribution ratio of r(2)  = 0.971. Interestingly, scores using the second latent variables for each complex were strongly correlated with root mean square deviations (RMSDs) of side-chain heavy atoms of Met(49) from those of the intact crystal structure of SARS-3CL(pro) (r = 0.77) enlarging the S2 pocket. The substantial contribution of this side chain (∼10%) for the explanation of pIC50 s was dependent on stereochemistry and the chemical structure of the ligand adapted to the S2 pocket of the protease. Thus, starting from a substrate mimic inhibitor, a design for a central scaffold for a low molecular weight inhibitor was evaluated to develop a further potent inhibitor. © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 391-403, 2016. © 2015 Wiley Periodicals, Inc.

Quantifying the Floe Size Distribution in the Marginal Ice Zone from Satellite Imagery for use in Model Development and Validation

NASA Astrophysics Data System (ADS)

Schweiger, A. J.; Stern, H. L.; Stark, M.; Zhang, J.; Hwang, P.; Steele, M.

2013-12-01

Several key processes in the Marginal Ice Zone (MIZ) of the Arctic Ocean are related to the size of the ice floes, whose diameters range from meters to tens of kilometers. The floe size distribution (FSD) influences mechanical properties of the ice and thus its response to winds, currents, and waves, which is likely to modify the air-sea momentum transfer. The FSD also influences the air-sea heat transfer and the response of the MIZ ice cover to the thermal forcing. The FSD also has a significant role in lateral melting. No existing sea-ice/ocean models currently simulate the FSD in the MIZ. Significant uncertainties in FSD-related processes hinder model incorporation of the FSD, and model development must heavily depend on observations of the FSD for parameterization, calibration, and validation. To support the development and implementation of the FSD in the Marginal Ice Zone Modeling and Assimilation System (MIZMAS), we have conducted an analysis of the FSD in the Beaufort and Chukchi seas using three sources of satellite imagery: NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, the Canadian Space Agency's synthetic aperture radar (SAR) on RADARSAT, and declassified National Technical Means imagery from the Global Fiducials Library (GFL) of the U.S. Geological Survey. The MODIS visible and short-wave infrared bands have a pixel size of 250 meters, and are only useful in cloud-free regions. The SAR imagery is unaffected by clouds and darkness, and has a pixel size of 50 meters. The GFL visible imagery, with a pixel size of 1 meter, is only useful in cloud-free regions. The resolution and spatial extent of the various image products allows us to identify ice floes of all sizes from 10 meters to 100 kilometers. The general procedure for identifying ice floes in the imagery is as follows: delineate cloud-free regions (if necessary); choose a threshold to separate ice from water, and create a binary image; apply the morphological erosion operation to separate floes that touch each other; identify contiguous sets of pixels (floes) by a recursive algorithm; and apply the morphological dilation operation to restore (approximately) the floes to their original sizes and shapes. Once the floes in an image have been identified, any number of properties may be calculated: the centroid, length, width, area, perimeter, orientation, convexity, etc. We calculate the mean caliper diameter as a simple, single measure of the size of a floe. We report results on the observed FSD in the Beaufort and Chukchi seas, including its seasonal evolution and spatial variability. We outline how the results will be used in model development and validation of the FSD in the MIZMAS.

A G-quadruplex-binding macrodomain within the "SARS-unique domain" is essential for the activity of the SARS-coronavirus replication-transcription complex.

PubMed

Kusov, Yuri; Tan, Jinzhi; Alvarez, Enrique; Enjuanes, Luis; Hilgenfeld, Rolf

2015-10-01

The multi-domain non-structural protein 3 of SARS-coronavirus is a component of the viral replication/transcription complex (RTC). Among other domains, it contains three sequentially arranged macrodomains: the X domain and subdomains SUD-N as well as SUD-M within the "SARS-unique domain". The X domain was proposed to be an ADP-ribose-1"-phosphatase or a poly(ADP-ribose)-binding protein, whereas SUD-NM binds oligo(G)-nucleotides capable of forming G-quadruplexes. Here, we describe the application of a reverse genetic approach to assess the importance of these macrodomains for the activity of the SARS-CoV RTC. To this end, Renilla luciferase-encoding SARS-CoV replicons with selectively deleted macrodomains were constructed and their ability to modulate the RTC activity was examined. While the SUD-N and the X domains were found to be dispensable, the SUD-M domain was crucial for viral genome replication/transcription. Moreover, alanine replacement of charged amino-acid residues of the SUD-M domain, which are likely involved in G-quadruplex-binding, caused abrogation of RTC activity. Copyright © 2015 Elsevier Inc. All rights reserved.

Use of Movement Imagery in Neurorehabilitation: Researching Effects of a Complex Intervention

ERIC Educational Resources Information Center

Braun, Susy M.; Wade, Derick T.; Beurskens, Anna J. H. M.

2011-01-01

Since the beginning of the new millennium, the use of mental practice and movement imagery within several medical professions in rehabilitation and therapy has received an increased attention. Before this introduction in healthcare, the use of movement imagery was mainly researched in sports science. Mental practice is a complex intervention. When…

Despeckling Polsar Images Based on Relative Total Variation Model

NASA Astrophysics Data System (ADS)

Jiang, C.; He, X. F.; Yang, L. J.; Jiang, J.; Wang, D. Y.; Yuan, Y.

2018-04-01

Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

PubMed Central

Sun, Jian

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Operational Satellite-based Surface Oil Analyses (Invited)

NASA Astrophysics Data System (ADS)

Streett, D.; Warren, C.

2010-12-01

During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as Deepwater Horizon, (2) acquire a 24 x 7 oil spill response capability at least on a pre-operational basis, (3) acquire improved and expanded ancillary datasets, (4) reduce the number of false positives (analyzed oil that is not actually oil), (5) acquire the ability to reliably differentiate, at least in general qualitative terms, thick oil (“recoverable oil”) from oil sheens, and (6) join our Canadian counterparts (the Integrated Satellite Tracking of Pollution group in Environment Canada) to create a joint North American center for oil spill response.

Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

NASA Astrophysics Data System (ADS)

Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

2016-12-01

Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general indicators of environmental health, and can detect growth and changes in cities that are displacing historical agricultural zones.

An iterative approach to optimize change classification in SAR time series data

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2016-10-01

The detection of changes using remote sensing imagery has become a broad field of research with many approaches for many different applications. Besides the simple detection of changes between at least two images acquired at different times, analyses which aim on the change type or category are at least equally important. In this study, an approach for a semi-automatic classification of change segments is presented. A sparse dataset is considered to ensure the fast and simple applicability for practical issues. The dataset is given by 15 high resolution (HR) TerraSAR-X (TSX) amplitude images acquired over a time period of one year (11/2013 to 11/2014). The scenery contains the airport of Stuttgart (GER) and its surroundings, including urban, rural, and suburban areas. Time series imagery offers the advantage of analyzing the change frequency of selected areas. In this study, the focus is set on the analysis of small-sized high frequently changing regions like parking areas, construction sites and collecting points consisting of high activity (HA) change objects. For each HA change object, suitable features are extracted and a k-means clustering is applied as the categorization step. Resulting clusters are finally compared to a previously introduced knowledge-based class catalogue, which is modified until an optimal class description results. In other words, the subjective understanding of the scenery semantics is optimized by the data given reality. Doing so, an even sparsely dataset containing only amplitude imagery can be evaluated without requiring comprehensive training datasets. Falsely defined classes might be rejected. Furthermore, classes which were defined too coarsely might be divided into sub-classes. Consequently, classes which were initially defined too narrowly might be merged. An optimal classification results when the combination of previously defined key indicators (e.g., number of clusters per class) reaches an optimum.

C-band RISAT-1 imagery for geospatial mapping of cryospheric surface features in the Antarctic environment

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Panditrao, Satej N.; Luis, Alvarinho J.

2016-05-01

Cryospheric surface feature classification is one of the widely used applications in the field of polar remote sensing. Precise surface feature maps derived from remotely sensed imageries are the major requirement for many geoscientific applications in polar regions. The present study explores the capabilities of C-band dual polarimetric (HH & HV) SAR imagery from Indian Radar Imaging Satellite (RISAT-1) for land cryospheric surface feature mapping. The study areas selected for the present task were Larsemann Hills and Schirmacher Oasis, East Antarctica. RISAT-1 Fine Resolution STRIPMAP (FRS-1) mode data with 3-m spatial resolution was used in the present research attempt. In order to provide additional context to the amount of information in dual polarized RISAT-1 SAR data, a band HH+HV was introduced to make use of the original two polarizations. In addition to the data calibration, transformed divergence (TD) procedure was performed for class separability analysis to evaluate the quality of the statistics before image classification. For most of the class pairs the TD values were comparable, which indicated that the classes have good separability. Fuzzy and Artificial Neural Network classifiers were implemented and accuracy was checked. Nonparametric classifier Support Vector Machine (SVM) was also used to classify RISAT-1 data with an optimized polarization combination into three land-cover classes consisting of sea ice/snow/ice, rocks/landmass, and lakes/waterbodies. This study demonstrates that C-band FRS1 image mode data from the RISAT-1 mission can be exploited to identify, map and monitor land cover features in the polar regions, even during dark winter period. For better landcover classification and analysis, hybrid polarimetric data (cFRS-1 mode) from RISAT-1, which incorporates phase information, unlike the dual-pol linear (HH, HV) can be used for obtaining better polarization signatures.

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

NASA Astrophysics Data System (ADS)

Motagh, M.; Lubitz, C.

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

An oceanographic survey for oil spill monitoring and model forecasting validation using remote sensing and in situ data in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Pisano, A.; De Dominicis, M.; Biamino, W.; Bignami, F.; Gherardi, S.; Colao, F.; Coppini, G.; Marullo, S.; Sprovieri, M.; Trivero, P.; Zambianchi, E.; Santoleri, R.

2016-11-01

A research cruise was organized on board the Italian National Research Council (CNR) R/V Urania to test the oil spill monitoring system developed during the PRogetto pilota Inquinamento Marino da Idrocarburi project (PRIMI, pilot project for marine oil pollution). For the first time, this system integrated in a modular way satellite oil spill detection (Observation Module) and oil spill displacement forecasting (Forecast Module) after detection. The Observation Module was based on both Synthetic Aperture RADAR (SAR) and optical satellite detection, namely SAR and Optical Modules, while the Forecast Module on Lagrangian numerical circulation models. The cruise (Aug. 6-Sep. 7, 2009) took place in the Mediterranean Sea, around Sicily, an area affected by heavy oil tanker traffic with frequent occurrence of oil spills resulting from illegal tank washing. The cruise plan was organized in order to have the ship within the SAR image frames selected for the cruise, at acquisition time. In this way, the ship could rapidly reach oil slicks detected in the images by the SAR Module, and/or eventually by the Optical Module, in order to carry out visual and instrumental inspection of the slicks. During the cruise, several oil spills were detected by the two Observation Modules and verified in situ, with the essential aid of the Forecasting Module which provided the slick position by the time the ship reached the area after the alert given by the SAR and/or optical imagery. Results confirm the good capability of oil spill SAR detection and indicate that also optical sensors are able to detect oil spills, ranging from thin films to slicks containing heavily polluted water. Also, results confirm the useful potential of oil spill forecasting models, but, on the other hand, that further work combining satellite, model and in situ data is necessary to refine the PRIMI system.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

EARSEC SAR processing system

NASA Astrophysics Data System (ADS)

Protheroe, Mark; Sloggett, David R.; Sieber, Alois J.

1994-12-01

Traditionally, the production of high quality Synthetic Aperture Radar imagery has been an area where a potential user would have to expend large amounts of money in either the bespoke development of a processing chain dedicated to his requirements or in the purchase of a dedicated hardware platform adapted using accelerator boards and enhanced memory management. Whichever option the user adopted there were limitations based on the desire for a realistic throughput in data load and time. The user had a choice, made early in the purchase, for either a system that adopted innovative algorithmic manipulation, to limit the processing time of the purchase of expensive hardware. The former limits the quality of the product, while the latter excludes the user from any visibility into the processing chain. Clearly there was a need for a SAR processing architecture that gave the user a choice into the methodology to be adopted for a particular processing sequence, allowing him to decide on either a quick (lower quality) product or a detailed slower (high quality) product, without having to change the algorithmic base of his processor or the hardware platform. The European Commission, through the Advanced Techniques unit of the Joint Research Centre (JRC) Institute for Remote Sensing at Ispra in Italy, realizing the limitations on current processing abilities, initiated its own program to build airborne SAR and Electro-Optical (EO) sensor systems. This program is called the European Airborne Remote Sensing Capabilities (EARSEC) program. This paper describes the processing system developed for the airborne SAR sensor system. The paper considers the requirements for the system and the design of the EARSEC Airborne SAR Processing System. It highlights the development of an open SAR processing architecture where users have full access to intermediate products that arise from each of the major processing stages. It also describes the main processing stages in the overall architecture and illustrates the results of each of the key stages in the processor.

Utilizing feedback in adaptive SAR ATR systems

NASA Astrophysics Data System (ADS)

Horsfield, Owen; Blacknell, David

2009-05-01

Existing SAR ATR systems are usually trained off-line with samples of target imagery or CAD models, prior to conducting a mission. If the training data is not representative of mission conditions, then poor performance may result. In addition, it is difficult to acquire suitable training data for the many target types of interest. The Adaptive SAR ATR Problem Set (AdaptSAPS) program provides a MATLAB framework and image database for developing systems that adapt to mission conditions, meaning less reliance on accurate training data. A key function of an adaptive system is the ability to utilise truth feedback to improve performance, and it is this feature which AdaptSAPS is intended to exploit. This paper presents a new method for SAR ATR that does not use training data, based on supervised learning. This is achieved by using feature-based classification, and several new shadow features have been developed for this purpose. These features allow discrimination of vehicles from clutter, and classification of vehicles into two classes: targets, comprising military combat types, and non-targets, comprising bulldozers and trucks. The performance of the system is assessed using three baseline missions provided with AdaptSAPS, as well as three additional missions. All performance metrics indicate a distinct learning trend over the course of a mission, with most third and fourth quartile performance levels exceeding 85% correct classification. It has been demonstrated that these performance levels can be maintained even when truth feedback rates are reduced by up to 55% over the course of a mission.

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.

SAR11 Bacteria: The Most Abundant Plankton in the Oceans.

PubMed

Giovannoni, Stephen J

2017-01-03

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

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.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Retrieval of forest biomass for tropical deciduous mixed forest using ALOS PALSAR mosaic imagery and field plot data

NASA Astrophysics Data System (ADS)

Ningthoujam, Ramesh K.; Joshi, P. K.; Roy, P. S.

2018-07-01

Tropical forest is an important ecosystem rich in biodiversity and structural complexity with high woody biomass content. Longer wavelength radar data at L-band sensor provides improved forest biomass (AGB) information due to its higher penetration level and sensitivity to canopy structure. The study presents a regression based woody biomass estimation for tropical deciduous mixed forest dominated by Shorea robusta using ALOS PALSAR mosaic (HH, HV) and field data at the lower Himalayan belt of Northern India. For the purpose of understanding the scattering mechanisms at L-band from this forest type, Michigan Microwave Canopy Scattering model (MIMICS-I) was parameterized with field data to simulate backscatter across polarization and incidence range. Regression analysis between field measured forest biomass and L-band backscatter data from PALSAR mosaic show retrieval of woody biomass up to 100 Mg ha-1 with error between 92 and 94 Mg ha-1 and coefficient of determination (r2) between 0.53 and 0.55 for HH and HH + HV polarized channel at 0.25 ha resolution. This positive relationship could be due to strong volume scattering from ground/trunk interaction at HH-polarized while in combination with direct canopy scattering for HV-polarization at ALOS specific incidence angles as predicted by MIMICS-I model. This study has found that L-band SAR data from currently ALOS-1/-2 and upcoming joint NASA-ISRO SAR (NISAR) are suitable for mapping forest biomass ≤100 Mg ha-1 at 25 m resolution in far incidence range in dense deciduous mixed forest of Northern India.

The effect of radar azimuth angle on cultural data. [urban scene analysis and land use studies

NASA Technical Reports Server (NTRS)

Bryan, M. L.

1979-01-01

Emphasis is placed on the role that the orientation of observed features has on the grey tone of the resulting positive image. As an example it is shown that in the Los Angeles urbanized region, large areas have significantly lower grey tones than adjacent areas having similar land cover. It is determined that this effect is the result of the angle difference between the radar azimuth and the street pattern and especially the orientation of the walls of the structures imaged. Therefore, knowledge of this information is essential in order to ensure accurate interpretation of radar imagery. It is concluded that for radar systems operated from platforms which have fixed azimuth angles (e.g., satellite systems such as Seasat-A), an interpretation methodology, which considers street patterns, is considered especially critical for proper and accurate SAR imagery.

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.

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.

SAR405838: An optimized inhibitor of MDM2-p53 interaction that induces complete and durable tumor regression

DOE PAGES

Wang, Shaomeng; Sun, Wei; Zhao, Yujun; ...

2014-08-21

Blocking the MDM2-p53 protein-protein interaction has long been considered to offer a broad cancer therapeutic strategy, despite the potential risks of selecting tumors harboring p53 mutations that escape MDM2 control. In this study, we report a novel small molecule inhibitor of the MDM2-p53 interaction, SAR405838 (MI-77301) that has been advanced into Phase I clinical trials. SAR405838 binds to MDM2 with K i = 0.88 nM and has high specificity over other proteins. A co-crystal structure of the SAR405838:MDM2 complex shows that in addition to mimicking three key p53 amino acid residues, the inhibitor captures additional interactions not observed in themore » p53-MDM2 complex and induces refolding of the short, unstructured MDM2 N-terminal region to achieve its high affinity. SAR405838 effectively activates wild-type p53 in vitro and in xenograft tumor tissue of leukemia and solid tumors, leading to p53-dependent cell cycle arrest and/or apoptosis. At well-tolerated dose schedules, SAR405838 achieves either durable tumor regression or complete tumor growth inhibition in mouse xenograft models of SJSA-1 osteosarcoma, RS4;11 acute leukemia, LNCaP prostate cancer and HCT-116 colon cancer. Remarkably, a single oral dose of SAR405838 is sufficient to achieve complete tumor regression in the SJSA-1 model. Mechanistically, robust transcriptional up-regulation of PUMA induced by SAR405838 results in strong apoptosis in tumor tissue, leading to complete tumor regression. Lastly, our findings provide a preclinical basis upon which to evaluate SAR405838 as a therapeutic agent in patients whose tumors retain wild-type p53.« less

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

Li, Fang

It is believed that a novel coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV), was passed from palm civets to humans and caused the epidemic of SARS in 2002 to 2003. The major species barriers between humans and civets for SARS-CoV infections are the specific interactions between a defined receptor-binding domain (RBD) on a viral spike protein and its host receptor, angiotensin-converting enzyme 2 (ACE2). In this study a chimeric ACE2 bearing the critical N-terminal helix from civet and the remaining peptidase domain from human was constructed, and it was shown that this construct has the same receptor activity as civetmore » ACE2. In addition, crystal structures of the chimeric ACE2 complexed with RBDs from various human and civet SARS-CoV strains were determined. These structures, combined with a previously determined structure of human ACE2 complexed with the RBD from a human SARS-CoV strain, have revealed a structural basis for understanding the major species barriers between humans and civets for SARS-CoV infections. They show that the major species barriers are determined by interactions between four ACE2 residues (residues 31, 35, 38, and 353) and two RBD residues (residues 479 and 487), that early civet SARS-CoV isolates were prevented from infecting human cells due to imbalanced salt bridges at the hydrophobic virus/receptor interface, and that SARS-CoV has evolved to gain sustained infectivity for human cells by eliminating unfavorable free charges at the interface through stepwise mutations at positions 479 and 487. These results enhance our understanding of host adaptations and cross-species infections of SARS-CoV and other emerging animal viruses.« less

Uncertainty of InSAR velocity fields for measuring long-wavelength displacement

NASA Astrophysics Data System (ADS)

Fattahi, H.; Amelung, F.

2014-12-01

Long-wavelength artifacts in InSAR data are the main limitation to measure long-wavelength displacement; they are traditionally attributed mainly to the inaccuracy of the satellite orbits (orbital errors). However, most satellites are precisely tracked resulting in uncertainties of orbits of 2-10 cm. Orbits of these satellites are thus precise enough to obtain precise velocity fields with uncertainties better than 1 mm/yr/100 km for older satellites (e.g. Envisat) and better than 0.2 mm/yr/100 km for modern satellites (e.g. TerraSAR-X and Sentinel-1) [Fattahi & Amelung, 2014]. Such accurate velocity fields are achievable if long-wavelength artifacts from sources other than orbital errors are identified and corrected for. We present a modified Small Baseline approach to measure long-wavelength deformation and evaluate the uncertainty of these measurements. We use a redundant network of interferograms for detection and correction of unwrapping errors to ensure the unbiased estimation of phase history. We distinguish between different sources of long-wavelength artifacts and correct those introduced by atmospheric delay, topographic residuals, timing errors, processing approximations and hardware issues. We evaluate the uncertainty of the velocity fields using a covariance matrix with the contributions from orbital errors and residual atmospheric delay. For contributions from the orbital errors we consider the standard deviation of velocity gradients in range and azimuth directions as a function of orbital uncertainty. For contributions from the residual atmospheric delay we use several approaches including the structure functions of InSAR time-series epochs, the predicted delay from numerical weather models and estimated wet delay from optical imagery. We validate this InSAR approach for measuring long-wavelength deformation by comparing InSAR velocity fields over ~500 km long swath across the southern San Andreas fault system with independent GPS velocities and examine the estimated uncertainties in several non-deforming areas. We show the efficiency of the approach to study the continental deformation across the Chaman fault system at the western Indian plate boundary. Ref: Fattahi, H., & Amelung, F., (2014), InSAR uncertainty due to orbital errors, Geophys, J. Int (in press).

Synthetic aperture radar for a crop information system: A multipolarization and multitemporal approach

NASA Astrophysics Data System (ADS)

Ban, Yifang

Acquisition of timely information is a critical requirement for successful management of an agricultural monitoring system. Crop identification and crop-area estimation can be done fairly successfully using satellite sensors operating in the visible and near-infrared (VIR) regions of the spectrum. However, data collection can be unreliable due to problems of cloud cover at critical stages of the growing season. The all-weather capability of synthetic aperture radar (SAR) imagery acquired from satellites provides data over large areas whenever crop information is required. At the same time, SAR is sensitive to surface roughness and should be able to provide surface information such as tillage-system characteristics. With the launch of ERS-1, the first long-duration SAR system became available. The analysis of airborne multipolarization SAR data, multitemporal ERS-1 SAR data, and their combinations with VIR data, is necessary for the development of image-analysis methodologies that can be applied to RADARSAT data for extracting agricultural crop information. The overall objective of this research is to evaluate multipolarization airborne SAR data, multitemporal ERS-1 SAR data, and combinations of ERS-1 SAR and satellite VIR data for crop classification using non-conventional algorithms. The study area is situated in Norwich Township, an agricultural area in Oxford County, southern Ontario, Canada. It has been selected as one of the few representative agricultural 'supersites' across Canada at which the relationships between radar data and agriculture are being studied. The major field crops are corn, soybeans, winter wheat, oats, barley, alfalfa, hay, and pasture. Using airborne C-HH and C-HV SAR data, it was found that approaches using contextual information, texture information and per-field classification for improving agricultural crop classification proved to be effective, especially the per-field classification method. Results show that three of the four best per-field classification accuracies (\\ K=0.91) are achieved using combinations of C-HH and C-VV SAR data. This confirms the strong potential of multipolarization data for crop classification. The synergistic effects of multitemporal ERS-1 SAR and Landsat TM data are evaluated for crop classification using an artificial neural network (ANN) approach. The results show that the per-field approach using a feed-forward ANN significantly improves the overall classification accuracy of both single-date and multitemporal SAR data. Using the combination of TM3,4,5 and Aug. 5 SAR data, the best per-field ANN classification of 96.8% was achieved. It represents an 8.5% improvement over a single TM3,4,5 classification alone. Using multitemporal ERS-1 SAR data acquired during the 1992 and 1993 growing seasons, the radar backscatter characteristics of crops and their underlying soils are analyzed. The SAR temporal backscatter profiles were generated for each crop type and the earliest times of the year for differentiation of individual crop types were determined. Orbital (incidence-angle) effects were also observed on all crops. The average difference between the two orbits was about 3 dB. Thus attention should be given to the local incidence-angle effects when using ERS-1 SAR data, especially when comparing fields from different scenes or different areas within the same scene. Finally, early- and mid-season multitemporal SAR data for crop classification using sequential-masking techniques are evaluated, based on the temporal backscatter profiles. It was found that all crops studied could be identified by July 21.

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

Pak, J.; Sharon, C; Satkunarajah, M

The spike (S) protein of the severe acute respiratory syndrome coronavirus (SARS-CoV) is responsible for host cell attachment and fusion of the viral and host cell membranes. Within S the receptor binding domain (RBD) mediates the interaction with angiotensin-converting enzyme 2 (ACE2), the SARS-CoV host cell receptor. Both S and the RBD are highly immunogenic and both have been found to elicit neutralizing antibodies. Reported here is the X-ray crystal structure of the RBD in complex with the Fab of a neutralizing mouse monoclonal antibody, F26G19, elicited by immunization with chemically inactivated SARS-CoV. The RBD-F26G19 Fab complex represents the firstmore » example of the structural characterization of an antibody elicited by an immune response to SARS-CoV or any fragment of it. The structure reveals that the RBD surface recognized by F26G19 overlaps significantly with the surface recognized by ACE2 and, as such, suggests that F26G19 likely neutralizes SARS-CoV by blocking the virus-host cell interaction.« less

Evolutions Of Diff-Tomo For Sensing Subcanopy Deformations And Height-Varying Temporal Coherence

NASA Astrophysics Data System (ADS)

Lombardini, Fabrizio; Cai, Francesco

2012-01-01

Interest is continuing to grow in advanced interferometric SAR methods for sensing complex scenarios with multiple (layover or volumetric) scatterers mapped in the SAR cell. Multibaseline SAR tomographic (3D) elevation beam forming is a promising technique in this field. Recently, the Tomo concept has been integrated with the differential interferometry concept, producing the advanced “differential tomography” (Diff-Tomo, “4D”) processing mode which furnishes “space-time” signatures of multiple scatterer dynamics in the SAR cell. Advances in the application of this new framework are investigated for complex volume scattering scenarios including temporal signal variations, both from scatterer temporal decorrelation and deformation motions. In particular, new results are reported concerning the potentials of Diff-Tomo for the analysis of forest scenarios, based on the original concept of the space-time signatures of temporal decorrelation. E-SAR P-band data results are expanded of tomography robust to temporal decorrelation, and first trials are reported of separation of different temporal decorrelation mechanisms of canopy and ground, and of sensing possible sub-canopy subsidences.

Measurement of Seaward Ground Displacements on Coastal Landfill Area Using Radar Interferometry

NASA Astrophysics Data System (ADS)

Baek, W.-K.; Jung, H.-S.

2018-04-01

In order to understand the mechanism of subsidence and help reducing damage, researchers has been observed the line-of-sight subsidence on the Noksan industrial complex using SAR Interferometry(InSAR) and suggested subsidence prediction models. Although these researches explained a spatially uneven ground subsidence near the seaside, they could not have been explained the occurrence of the newly proposed seaward horizontal, especially nearly north-ward, displacement because of the geometric limitation of InSAR measurements. In this study, we measured the seaward ground displacements trend on the coastal landfill area, Noksan Industrial Complex. We set the interferometric pairs from an ascending and a descending orbits strip map data of ALOS PALSAR2. We employed InSAR and MAI stacking approaches for the both orbits respectively in order to improve the measurement. Finally, seaward deformation was estimated by retrieving three-dimensional displacements from multi-geometric displacements. As a results, maximally 3.3 and 0.7 cm/year of ground displacements for the vertical and seaward directions. In further study, we plan to generate InSAR and MAI stacking measurements with additional SAR data to mitigate tropospheric effect and noise well. Such a seaward observation approach using spaceborne radar is expected to be effective in observing the long-term movements on coastal landfill area.

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

NASA Technical Reports Server (NTRS)

Rignot, E.; Chellappa, R.

1993-01-01

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

Recovering Seasat SAR Data

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 supposedly 'steadily' changing millisecond (MSEC) timing values. The elevated BER made even a basic linear fit difficult. In addition, the MSEC field often shows a 'stair step' function, assumed to be a spacecraft clock malfunction. To fix these issues, three separate levels of time filtering were applied. After the initial three-pass time filter, a fourth procedure located and removed discontinuities - missing data sections that occurred randomly throughout the data takes - by inserting random valued lines into the effected data file and repeated value lines into the corresponding header file. Finally, a fifth pass through the metadata was required to fix remaining start time anomalies. After the data were filtered, all times were linearly increasing, and all discontinuities filled, images could finally be formed. ASF DAAC utilized a custom version of ROI, the Repeat Orbit Interferometric SAR processor, to focus the data. Special focusing tasks for Seasat included dealing with Doppler ambiguity issues and filtering out 'spikes' in the power spectra. Once these obstacles were overcome via additional pre-processing software developed in house, well-focused SAR imagery was obtained from approximately 80% the ASF DAAC archives. These focused products, packaged in either HDF5 or geotiff formats with XML metadata, are downloadable from ASF DAAC free of charge.

A multifrequency evaluation of active and passive microwave sensors for oil spill detection and assessment

NASA Technical Reports Server (NTRS)

Fenner, R. G.; Reid, S. C.; Solie, C. H.

1980-01-01

An evaluation is given of how active and passive microwave sensors can best be used in oil spill detection and assessment. Radar backscatter curves taken over oil spills are presented and their effect on synthetic aperture radar (SAR) imagery are discussed. Plots of microwave radiometric brightness variations over oil spills are presented and discussed. Recommendations as to how to select the best combination of frequency, viewing angle, and sensor type for evaluation of various aspects of oil spills are also discussed.

Wind and Wave Influences on Sea Ice Floe Size and Leads in the Beaufort and Chukchi Seas During the Summer-Fall Transition 2014

DTIC Science & Technology

2016-01-26

However, validation and parameterization of these theories present significant observational challenges. Starting from Rothrock and Thorndike [1984...Rothrock and Thorndike , 1984] remained in the 1.8–2.9 range, and did not change by the storm passage. In Holt and Martin [2001] ERS-1 SAR imagery at 25...cumulative FSD as defined in Rothrock and Thorndike [1984]. The vertical axis is NðdÞ, the number of floes per square kilometer with diameter no less

Demonstration of Reduced False Alarm Rates using Simulated L-Band Polarimetric SAR Imagery of Concealed Targets

DTIC Science & Technology

2005-04-14

of Joensuu, Finland. These take the form of collections of dielectric cylinders, with detailed information concerning sapwood and heartwood dimensions...centre, and at 3km height above the minimum height of the DEM. The imaged area was 91m square, with pixels spaced at 0.5m. A Hamming weighted PSF was...correlation length was 0.1510m. Wood permittivity ranged from 2.2-i0.4 (deadwood) to 26.8-i5.3 ( sapwood ) via 6.7-i1.9 (heartwood). Total attenuation

Local SAR in Parallel Transmission Pulse Design

PubMed Central

Lee, Joonsung; Gebhardt, Matthias; Wald, Lawrence L.; Adalsteinsson, Elfar

2011-01-01

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 RF 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 MRI scan. Additionally, the algorithm yields a Protocol-specific Ultimate Peak in Local SAR (PUPiL 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 7T eight-channel transmit array. The method reduced peak local 10g 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. PMID:22083594

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

NASA Astrophysics Data System (ADS)

Wang, SuYun; Sun, Z. C.

2017-02-01

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

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.

New insights into earthquake precursors from InSAR.

PubMed

Moro, Marco; Saroli, Michele; Stramondo, Salvatore; Bignami, Christian; Albano, Matteo; Falcucci, Emanuela; Gori, Stefano; Doglioni, Carlo; Polcari, Marco; Tallini, Marco; Macerola, Luca; Novali, Fabrizio; Costantini, Mario; Malvarosa, Fabio; Wegmüller, Urs

2017-09-20

We measured ground displacements before and after the 2009 L'Aquila earthquake using multi-temporal InSAR techniques to identify seismic precursor signals. We estimated the ground deformation and its temporal evolution by exploiting a large dataset of SAR imagery that spans seventy-two months before and sixteen months after the mainshock. These satellite data show that up to 15 mm of subsidence occurred beginning three years before the mainshock. This deformation occurred within two Quaternary basins that are located close to the epicentral area and are filled with sediments hosting multi-layer aquifers. After the earthquake, the same basins experienced up to 12 mm of uplift over approximately nine months. Before the earthquake, the rocks at depth dilated, and fractures opened. Consequently, fluids migrated into the dilated volume, thereby lowering the groundwater table in the carbonate hydrostructures and in the hydrologically connected multi-layer aquifers within the basins. This process caused the elastic consolidation of the fine-grained sediments within the basins, resulting in the detected subsidence. After the earthquake, the fractures closed, and the deep fluids were squeezed out. The pre-seismic ground displacements were then recovered because the groundwater table rose and natural recharge of the shallow multi-layer aquifers occurred, which caused the observed uplift.

Using TerraSAR-X satellite data to detect road age and degradation

NASA Astrophysics Data System (ADS)

Necsoiu, Marius; Longepe, Nicolas; Parra, Jorge O.; Walter, Gary R.

2017-05-01

Analysis of satellite-acquired synthetic aperture radar (SAR) data provides a way to rapidly survey road conditions over large areas. This capability could be useful for identifying road segments that potentially require repair or at least onsite inspection of their condition due to changes in vehicular traffic associated with change in land use. We conducted a feasibility study focused on urban roads near the Southwest Research Institute (SwRI) campus in San Antonio, Texas. The roads near SwRI were affected by heavy truck traffic, they were easily inspected, and the age and construction of the pavement was known. TerraSAR-X (TSX) SpotLight (ST) satellite data were used to correlate radar backscattering response to pavement age and condition. Our preliminary results indicate that TSX radar imagery can be useful for detecting changes in pavement type, damage to pavement, such as cracking and scaling, and, occasionally, severe rutting. In addition, multitemporal interferometric analysis showed patches of settlement along two roads south of the SwRI campus. Further development of an automated approach to detect degradation of roads could allow transportation departments to prioritize inspection and repair efforts. The techniques also could be used to detect surreptitious heavy truck traffic in areas where direct inspection is not possible.

SAR ice thickness mapping in the Beaufort Sea during autumn 2015 using wave dispersion in pancake ice

NASA Astrophysics Data System (ADS)

Wadhams, Peter; Aulicino, Giuseppe; Parmiggiani, Flavio

2017-04-01

Pancake and frazil ice represent an important component of the Arctic and Antarctic cryosphere, especially in the Marginal Ice Zones. In particular, pancake ice is the result of a freezing process that takes place in turbulent surface conditions, typically associated with wind and wave fields. The retrieval of its thickness by remote sensing is, in general, a very difficult task. This study presents our ongoing work in the EU SPICES project, in which we aim to use the results of theory and observations developed so far in order to refine a processing system for routinely deriving ice thicknesses in frazil-pancake regions of the Arctic and Antarctic. The change in dispersion of ocean waves as they penetrate into pancake icefield is analyzed in order to derive ice thickness estimation. The spectral changes in wave spectra from imagery provided by space-borne SAR systems (mainly Cosmo-SkyMed and Sentinel-1 satellites) is used to retrieve pancake ice thickness run trough by the R/V Sikuliaq research cruise in the Beaufort Sea (October-November 2015). During several experiments, a line of wave buoys was deployed along a pre-declared line, which could thus be covered by simultaneous overhead Cosmo-SkyMed images. The inversion procedures was then applied to SAR images, the final goal being the comparison between the ice thicknesses measured in situ and those inferred from SAR wave number analysis with the application of a viscous theory. Results show a broad agreement between observed thicknesses and those retrieved from the SAR, the latter slightly overestimating the former in several case studies. In the case of November 1, for example, the agreement is excellent (SAR retrievals 4.9, 5.0, 6.5 cm; observed mean 6.7 cm); on October 11 the agreement is also very good between the SAR retriveal (21 cm) and the output from an along-track EM-sounder; on October 23-24 the SAR retrieval of 18.1 cm is double the observed pancake thickness of 8.7 cm, but this difference can be ascribed to the presence of large floes in the icefield. Even though quite resilient to relatively large changes in viscosity, the method resulted very sensitive to i) the input wind speed accuracy, ii) the presence of different ice types than frazil-pancake in the enquired region, iii) the exact co-location between the SAR extracted sub-scenes and the in situ measurements.

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.

The Primi Project: August-September 2009 Validation Cruise On Oil Spill Detection And Fate

NASA Astrophysics Data System (ADS)

Santoleri, R.; Bignami, F.; Bohm, E.; Nichio, F.; De Dominicis, M.; Ruggieri, G.; Marulllo, S.; Trivero, P.; Zambianchi, E.; Archetti, R.; Adamo, M.; Biamino, W.; Borasi, M.; Buongiorno Nardelli, B.; Cavagnero, M.; Colao, F.; Colella, S.; Coppini, G.; Debettio, V.; De Carolis, G.; Forneris, V.; Griffa, A.; Iacono, R.; Lombardi, E.; Manzella, G.; Mercantini, A.; Napolitano, E.; Pinardi, N.; Pandiscia, G.; Pisano, A.; Rupolo, V.; Reseghetti, F.; Sabia, L.; Sorgente, R.; Sprovieri, M.; Terranova, G.; Trani, M.; Volpe, G.

2010-04-01

In the framework of the ASI PRIMI Project, CNR- ISAC, in collaboration with the PRIMI partners, organized a validation cruise for the PRIMI oil spill monitoring and forecasting system on board the CNR R/V Urania. The cruise (Aug. 6 - Sept. 7 2009) took place in the Sicily Strait, an area affected by large oil tanker traffic. The cruise plan was organized in order to have the ship within the selected SAR image frames at acquisition time so that the ship could move toward the oil slick and verify it via visual and instrumental inspection. During the cruise, several oil spills, presumably being the result of illegal tank washing, were detected by the PRIMI system and were verified in situ. Preliminary results indicate that SAR and optical satellites are able to detect heavy and thin film oil spills, the maturity of oil spill forecasting models and that further work combining satellite, model and in situ data is necessary to assess the spill severity from the signature in satellite imagery.

Fusion of SAR and Optical Imagery for Studying the Eco-Epidemiology of Vector-Borne Diseases in Tropical Countries

NASA Astrophysics Data System (ADS)

Catry, Thibault; Li, Zhichao; Roux, Emmanuel; Herreteau, Vincent; Revillion, Christophe; Dessay, Nadine

2016-08-01

Vector-borne diseases like malaria represent a major public health issue worldwide. Other mosquito-borne diseases affect more and more countries and people, with effects on health which are not all identified yet. Recent developments in the field of remote-sensing allow to consider overriding the existing limits of studying such diseases in tropical regions, where cloud and vegetation cover often prevent to identify and characterize environmental features.We highlight the potential of SAR-optical fusion for the mapping of land cover, the identification of wetlands, and the monitoring of environmental changes in different habitats related to vector-borne diseases in the French Guiana - Brazil cross-border area. This study is the foundation of a landscape-based model of malaria transmission risk. Environmental factors, together with epidemiological, socio-economic, behavioral, demographics, and entomological ones, contribute to assess risks related to such pathologies and support disease control and decision-making by local public health actors.

Low Latency DESDynI Data Products for Disaster Response, Resource Management and Other Applications

NASA Technical Reports Server (NTRS)

Doubleday, Joshua R.; Chien, Steve A.; Lou, Yunling

2011-01-01

We are developing onboard processor technology targeted at the L-band SAR instrument onboard the planned DESDynI mission to enable formation of SAR images onboard opening possibilities for near-real-time data products to augment full data streams. Several image processing and/or interpretation techniques are being explored as possible direct-broadcast products for use by agencies in need of low-latency data, responsible for disaster mitigation and assessment, resource management, agricultural development, shipping, etc. Data collected through UAVSAR (L-band) serves as surrogate to the future DESDynI instrument. We have explored surface water extent as a tool for flooding response, and disturbance images on polarimetric backscatter of repeat pass imagery potentially useful for structural collapse (earthquake), mud/land/debris-slides etc. We have also explored building vegetation and snow/ice classifiers, via support vector machines utilizing quad-pol backscatter, cross-pol phase, and a number of derivatives (radar vegetation index, dielectric estimates, etc.). We share our qualitative and quantitative results thus far.

Data and Information Exchange System for the "Reindeer Mapper" Project

NASA Technical Reports Server (NTRS)

Maynard, Nancy; Yurchak, Boris

2005-01-01

During this past year, the Reindeer Mapper Intranet system has been set up on the NASA system, 8 team members have been established, a Reindeer Mapper reference list containing 696 items has been entered, 6 power point presentations have been put on line for review among team members, 304 satellite images have been catalogued (including 16 Landsat images, 288 NDVI 10-day composited images and an anomaly series- May 1998 to December 2002, and 56 SAR CEOS S A R format files), schedules and meeting dates are being shared, students at the Nordic Sami Institute are experimenting with the system for reindeer herder indigenous knowledge sharing, and an "address book" is being developed. Several documents and presentations have been translated and made available in Russian for our Russian colleagues. This has enabled our Russian partners to utilize documents and presentations for use in their research (e.g., SAR imagery comparisons with Russian GIS of specific study areas) and discussion with local colleagues.

Ocean Classification of Dynamical Structures Detected by SAR and Spectral Methods

NASA Astrophysics Data System (ADS)

Redondo, J. M.; Martinez-Benjamin, J. J.; Tellez, J. D.; Jorge, J.; Diez, M.; Sekula, E.

2016-08-01

We discuss a taxonomy of different dynamical features in the ocean surface and provide some eddy and front statistics, as well as describing some events detected by several satellites and even with additional cruise observations and measurements, in the North-west Mediterranean Sea area between 1996 and 2012. The structure of the flows are presented using self-similar traces that may be used to parametrize mixing at both limits of the Rossby Deformation Radius scale, RL. Results show the ability to identify different SAR signatures and at the same time provide calibrations for the different local configurations of vortices, spirals, Langmuir cells, oil spills and tensioactive slicks that eventually allow the study of the self-similar structure of the turbulence. Depending on the surface wind and wave level, and also on the fetch. the bathimetry, the spiral parameters and the resolution of vortical features change. Previous descriptions did not include the new wind and buoyancy features. SAR images also show the turbulence structure of the coastal area and the Regions of Fresh Water Influence (ROFI). It is noteworthy tt such complex coastal field-dependent behavior is strongly influenced by stratification and rotation of the turbulence spectrum is observed only in the range smaller than the local Rossby deformation radius, RL. The measures of diffusivity from buoy or tracer experiments are used to calibrate the behavior of different tracers and pollutants, both natural and man-made in the NW Mediterranean Sea. Thanks to different polarization and intensity levels in ASAR satellite imagery, these can be used to distinguish between natural and man-made sea surface features due to their distinct self-similar and fractal as a function of spill and slick parameters, environmental conditions and history of both oil releases and weather conditions. Eddy diffusivity map derived from SAR measurements of the ocean surface, performing a feature spatial correlation of the available images of the region are presented. Both the multi fractal discrimination of the local features and the diffusivity measurements are important to evaluate the state of the environment. The distribution of meso-scale vortices of size, the Rossby deformation scale and other dominant features can be used to distinguish features in the ocean surface. Multi-fractal analysis is then very usefull. The SAR images exhibited a large variation of natural features produced by winds, internal waves, the bathymetric distribution, by convection, rain, etc as all of these produce variations in the sea surface roughness so that the topological changes may be studied and classified. In a similar way bathimetry may be studied with the methodology described here using the coastline and the thalwegs as generators of local vertical vorticity.

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

USGS Publications Warehouse

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

2007-01-01

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

Modelling above Ground Biomass of Mangrove Forest Using SENTINEL-1 Imagery

NASA Astrophysics Data System (ADS)

Labadisos Argamosa, Reginald Jay; Conferido Blanco, Ariel; Balidoy Baloloy, Alvin; Gumbao Candido, Christian; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Many studies have been conducted in the estimation of forest above ground biomass (AGB) using features from synthetic aperture radar (SAR). Specifically, L-band ALOS/PALSAR (wavelength 23 cm) data is often used. However, few studies have been made on the use of shorter wavelengths (e.g., C-band, 3.75 cm to 7.5 cm) for forest mapping especially in tropical forests since higher attenuation is observed for volumetric objects where energy propagated is absorbed. This study aims to model AGB estimates of mangrove forest using information derived from Sentinel-1 C-band SAR data. Combinations of polarisations (VV, VH), its derivatives, grey level co-occurrence matrix (GLCM), and its principal components were used as features for modelling AGB. Five models were tested with varying combinations of features; a) sigma nought polarisations and its derivatives; b) GLCM textures; c) the first five principal components; d) combination of models a-c; and e) the identified important features by Random Forest variable importance algorithm. Random Forest was used as regressor to compute for the AGB estimates to avoid over fitting caused by the introduction of too many features in the model. Model e obtained the highest r2 of 0.79 and an RMSE of 0.44 Mg using only four features, namely, σ°VH GLCM variance, σ°VH GLCM contrast, PC1, and PC2. This study shows that Sentinel-1 C-band SAR data could be used to produce acceptable AGB estimates in mangrove forest to compensate for the unavailability of longer wavelength SAR.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km2, 720 km2, and 673 km2 respectively. Pixels determined to be flooded in vegetation were typically <0.5 % of the entire scene, with the exception of 2009 where the detection of flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes.

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

NASA Astrophysics Data System (ADS)

Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

2016-04-01

Optical and radar satellite remote sensing have proven to provide essential crisis information in case of natural disasters, humanitarian relief activities and civil security issues in a growing number of cases through mechanisms such as the Copernicus Emergency Management Service (EMS) of the European Commission or the International Charter 'Space and Major Disasters'. The aforementioned programs and initiatives make use of satellite-based rapid mapping services aimed at delivering reliable and accurate crisis information after natural hazards. Although these services are increasingly operational, they need to be continuously updated and improved through research and development (R&D) activities. The principal objective of ASAPTERRA (Advancing SAR and Optical Methods for Rapid Mapping), the ESA-funded R&D project being described here, is to improve, automate and, hence, speed-up geo-information extraction procedures in the context of natural hazards response. This is performed through the development, implementation, testing and validation of novel image processing methods using optical and Synthetic Aperture Radar (SAR) data. The methods are mainly developed based on data of the German radar satellites TerraSAR-X and TanDEM-X, the French satellite missions Pléiades-1A/1B as well as the ESA missions Sentinel-1/2 with the aim to better characterize the potential and limitations of these sensors and their synergy. The resulting algorithms and techniques are evaluated in real case applications during rapid mapping activities. The project is focussed on three types of natural hazards: floods, landslides and fires. Within this presentation an overview of the main methodological developments in each topic is given and demonstrated in selected test areas. The following developments are presented in the context of flood mapping: a fully automated Sentinel-1 based processing chain for detecting open flood surfaces, a method for the improved detection of flooded vegetation in Sentinel-1data using Entropy/Alpha decomposition, unsupervised Wishart Classification, and object-based post-classification as well as semi-automatic approaches for extracting inundated areas and flood traces in rural and urban areas from VHR and HR optical imagery using machine learning techniques. Methodological developments related to fires are the implementation of fast and robust methods for mapping burnt scars using change detection procedures using SAR (Sentinel-1, TerraSAR-X) and HR optical (e.g. SPOT, Sentinel-2) data as well as the extraction of 3D surface and volume change information from Pléiades stereo-pairs. In the context of landslides, fast and transferable change detection procedures based on SAR (TerraSAR-X) and optical (SPOT) data as well methods for extracting the extent of landslides only based on polarimetric VHR SAR (TerraSAR-X) data are presented.

Interferometric synthetic aperture radar: Building tomorrow's tools today

USGS Publications Warehouse

Lu, Zhong

2006-01-01

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

Internal solitary waves on the Saya de Malha bank of the Mascarene Plateau: SAR observations and interpretation

NASA Astrophysics Data System (ADS)

New, A. L.; Magalhaes, J. M.; da Silva, J. C. B.

2013-09-01

Energetic Internal Solitary Waves (ISWs) were recently discovered radiating from the central region of the Mascarene Plateau in the south-western Indian Ocean (da Silva et al., 2011). SAR imagery revealed the two-dimensional structure of the waves which propagated for several hundred kilometres in deep water both to the east and west of a sill, located near 12.5°S, 61°E between the Saya de Malha and Nazareth banks. These waves were presumed to originate from the disintegration of a large lee wave formed on the western side of the sill at the time of maximum barotropic flow to the west. In the present paper we focus instead on ISWs propagating in the shallow water above the Saya da Malha (SM) bank (to the north of the sill), rather than on those propagating in deep water (here denominated as type-I or -II waves if propagating to the west or east respectively). Analysis of an extended SAR image dataset reveals strong sea surface signatures of complex patterns of ISWs propagating over the SM bank arising from different sources. We identify three distinct types of waves, and propose suitable generation mechanisms for them using synergy from different remotely sensed datasets, together with analyses of linear phase speeds (resulting from local stratification and bathymetry). In particular, we find a family of ISWs (termed here A-type waves) which results from the disintegration of a lee wave which forms on the western slopes of SM. We also identify two further wave trains (B- and C-type waves) which we suggest result from refraction of the deep water type-I and -II waves onto the SM bank. Therefore, both B- and C-type waves can be considered to result from the same generation source as the type-I and -II waves. Finally, we consider the implications of the ISWs for mixing and biological production over the SM bank, and provide direct evidence, from ocean colour satellite images, of enhanced surface chlorophyll over a shallow topographic feature on the bank, which is consistent with the breaking of the ISWs.

Surface vimentin is critical for the cell entry of SARS-CoV.

PubMed

Yu, Yvonne Ting-Chun; Chien, Ssu-Chia; Chen, I-Yin; Lai, Chia-Tsen; Tsay, Yeou-Guang; Chang, Shin C; Chang, Ming-Fu

2016-01-22

Severe acute respiratory syndrome coronavirus (SARS-CoV) caused a global panic due to its high morbidity and mortality during 2002 and 2003. Soon after the deadly disease outbreak, the angiotensin-converting enzyme 2 (ACE2) was identified as a functional cellular receptor in vitro and in vivo for SARS-CoV spike protein. However, ACE2 solely is not sufficient to allow host cells to become susceptible to SARS-CoV infection, and other host factors may be involved in SARS-CoV spike protein-ACE2 complex. A host intracellular filamentous cytoskeletal protein vimentin was identified by immunoprecipitation and LC-MS/MS analysis following chemical cross-linking on Vero E6 cells that were pre-incubated with the SARS-CoV spike protein. Moreover, flow cytometry data demonstrated an increase of the cell surface vimentin level by 16.5 % after SARS-CoV permissive Vero E6 cells were treated with SARS-CoV virus-like particles (VLPs). A direct interaction between SARS-CoV spike protein and host surface vimentin was further confirmed by far-Western blotting. In addition, antibody neutralization assay and shRNA knockdown experiments indicated a vital role of vimentin in cell binding and uptake of SARS-CoV VLPs and the viral spike protein. A direct interaction between vimentin and SARS-CoV spike protein during viral entry was observed. Vimentin is a putative anti-viral drug target for preventing/reducing the susceptibility to SARS-CoV infection.

A first assessment of Sentinel-3 SAR altimetry over ice sheets

NASA Astrophysics Data System (ADS)

McMillan, M.; Muir, A. S.; Shepherd, A.

2017-12-01

The first Sentinel-3 satellite was launched in 2016 and carries onboard a Ku-band Synthetic Aperture Radar (SAR) altimeter. With coverage up to a latitude of 81.5 degrees and a repeat period of 27 days, it offers the opportunity to measure surface topography and elevation change across much of the Antarctic and Greenland Ice Sheets, therefore continuing the existing 25 year radar altimeter record. The global operation of Sentinel-3 in SAR mode differs from all past Ku-band instruments; for the first time SAR measurements are routinely acquired across the interiors of the ice sheets; however unlike CryoSat-2 it does not carry an interferometer to aid signal retrieval in regions of complex coastal terrain. In view of these differences and the novel characteristics of the Sentinel-3 system, assessments of the performance of the instrument are required, to evaluate the satellite's utility for monitoring Earth's Polar regions. Here, we analyse data acquired during the first year of routine operations, to assess the performance of the Sentinel-3 SAR altimeter to date. We focus both on inland ice sheet regions, where Sentinel-3 provides the first operational SAR altimeter measurements, and also on coastal areas with more complex topography. We investigate SAR waveforms and retrieved elevations in both regions, and through comparison to measurements from earlier missions examine the impact of the different modes of operation. We also conduct a high level evaluation of the data, by comparing it to reference airborne altimetry, to provide an assessment of Sentinel-3 performance to date over ice sheets.

Change detection in a time series of polarimetric SAR data by an omnibus test statistic and its factorization (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nielsen, Allan A.; Conradsen, Knut; Skriver, Henning

2016-10-01

Test statistics for comparison of real (as opposed to complex) variance-covariance matrices exist in the statistics literature [1]. In earlier publications we have described a test statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated p-value [2]. We showed their application to bitemporal change detection and to edge detection [3] in multilook, polarimetric synthetic aperture radar (SAR) data in the covariance matrix representation [4]. The test statistic and the associated p-value is described in [5] also. In [6] we focussed on the block-diagonal case, we elaborated on some computer implementation issues, and we gave examples on the application to change detection in both full and dual polarization bitemporal, bifrequency, multilook SAR data. In [7] we described an omnibus test statistic Q for the equality of k variance-covariance matrices following the complex Wishart distribution. We also described a factorization of Q = R2 R3 … Rk where Q and Rj determine if and when a difference occurs. Additionally, we gave p-values for Q and Rj. Finally, we demonstrated the use of Q and Rj and the p-values to change detection in truly multitemporal, full polarization SAR data. Here we illustrate the methods by means of airborne L-band SAR data (EMISAR) [8,9]. The methods may be applied to other polarimetric SAR data also such as data from Sentinel-1, COSMO-SkyMed, TerraSAR-X, ALOS, and RadarSat-2 and also to single-pol data. The account given here closely follows that given our recent IEEE TGRS paper [7]. Selected References [1] Anderson, T. W., An Introduction to Multivariate Statistical Analysis, John Wiley, New York, third ed. (2003). [2] Conradsen, K., Nielsen, A. A., Schou, J., and Skriver, H., "A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 41(1): 4-19, 2003. [3] Schou, J., Skriver, H., Nielsen, A. A., and Conradsen, K., "CFAR edge detector for polarimetric SAR images," IEEE Transactions on Geoscience and Remote Sensing 41(1): 20-32, 2003. [4] van Zyl, J. J. and Ulaby, F. T., "Scattering matrix representation for simple targets," in Radar Polarimetry for Geoscience Applications, Ulaby, F. T. and Elachi, C., eds., Artech, Norwood, MA (1990). [5] Canty, M. J., Image Analysis, Classification and Change Detection in Remote Sensing,with Algorithms for ENVI/IDL and Python, Taylor & Francis, CRC Press, third revised ed. (2014). [6] Nielsen, A. A., Conradsen, K., and Skriver, H., "Change detection in full and dual polarization, single- and multi-frequency SAR data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(8): 4041-4048, 2015. [7] Conradsen, K., Nielsen, A. A., and Skriver, H., "Determining the points of change in time series of polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 54(5), 3007-3024, 2016. [9] Christensen, E. L., Skou, N., Dall, J., Woelders, K., rgensen, J. H. J., Granholm, J., and Madsen, S. N., "EMISAR: An absolutely calibrated polarimetric L- and C-band SAR," IEEE Transactions on Geoscience and Remote Sensing 36: 1852-1865 (1998).

Forest Biomass Mapping from Stereo Imagery and Radar Data

NASA Astrophysics Data System (ADS)

Sun, G.; Ni, W.; Zhang, Z.

2013-12-01

Both InSAR and lidar data provide critical information on forest vertical structure, which are critical for regional mapping of biomass. However, the regional application of these data is limited by the availability and acquisition costs. Some researchers have demonstrated potentials of stereo imagery in the estimation of forest height. Most of these researches were conducted on aerial images or spaceborne images with very high resolutions (~0.5m). Space-born stereo imagers with global coverage such as ALOS/PRISM have coarser spatial resolutions (2-3m) to achieve wider swath. The features of stereo images are directly affected by resolutions and the approaches use by most of researchers need to be adjusted for stereo imagery with lower resolutions. This study concentrated on analyzing the features of point clouds synthesized from multi-view stereo imagery over forested areas. The small footprint lidar and lidar waveform data were used as references. The triplets of ALOS/PRISM data form three pairs (forward/nadir, backward/nadir and forward/backward) of stereo images. Each pair of the stereo images can be used to generate points (pixels) with 3D coordinates. By carefully co-register these points from three pairs of stereo images, a point cloud data was generated. The height of each point above ground surface was then calculated using DEM from National Elevation Dataset, USGS as the ground surface elevation. The height data were gridded into pixel of different sizes and the histograms of the points within a pixel were analyzed. The average height of the points within a pixel was used as the height of the pixel to generate a canopy height map. The results showed that the synergy of point clouds from different views were necessary, which increased the point density so the point cloud could detect the vertical structure of sparse and unclosed forests. The top layer of multi-layered forest could be captured but the dense forest prevented the stereo imagery to see through. The canopy height map exhibited spatial patterns of roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlation with RH50 of LVIS data at 30m pixel size with a gain of 1.04, bias of 4.3m and R2 of 0.74 (Fig. 1). The canopy height map from PRISM and dual-pol PALSAR data were used together to map biomass in our study area near Howland, Maine, and the results were evaluated using biomass map generated from LVIS waveform data independently. The results showed that adding CHM from PRISM significantly improved biomass accuracy and raised the biomass saturation level of L-band SAR data in forest biomass mapping.

Local SAR in parallel transmission pulse design.

PubMed

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.

A strategy for Local Surface Stability Monitoring Using SAR Imagery

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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 successfully estimates the dependency of radar backscatter to observation angle with statistical parameters from the Sentinel-1 SAR time series archive. We present the Sentinel-1 1km-SSM product generated by the adopted change detection algorithm. The dataset covers the European continent and holds data from October 2014 ongoing. In addition to a validation of the SSM product, the statistical SAR parameters used during SSM retrieval are examined.

Rapid Flood Map Generation from Spaceborne SAR Observations

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Advanced Rapid Imaging and Analysis (ARIA) team has responded to the January 2016 US Midwest Floods along the Mississippi River. Daily teleconferences with FEMA, NOAA, NGA, and USGS, provided information on precipitation and flood crest migration, based on which we coordinated with the Japanese Aerospace Exploration Agency (JAXA) through NASA headquarters for JAXA's ALOS-2 timely tasking over two paths. We produced flood extent maps using ALOS-2 SM3 mode Level 1.5 data that were provided through the International Charter and stored at the US Geological Survey's Hazards Data Distribution System (HDDS) archive. On January 6, the first four frames (70 km x 240 km) were acquired, which included the City of Memphis. We registered post-event SAR images to pre-event images, applied radiometric calibration, took a logarithm of the ratio of the two images. Two thresholds were applied to represent flooded areas that became open water (colored in blue) and flooded areas with tall vegetation (colored in red). The second path was acquired on January 11 further down along the Mississippi River. Seven frames (70 km x 420 km) were acquired and flood maps were created in the similar fashion. The maps were delivered to the FEMA as well as posted on ARIA's public website. The FEMA stated that SAR provides inspection priority for optical imagery and ground response. The ALOS-2 data and the products have been a very important source of information during this response as the flood crest has moved down stream. The SAR data continue to be an important resource during times when optical observations are often not useful. In close collaboration with FEMA and USGS, we also work on other flood events including June 2016 China Floods using European Space Agency's (ESA's) Sentienl-1 data, to produce flood extent maps and identify algorithmic needs and ARIA system's requirements to automate and rapidly produce and deliver flood maps for future events. With the addition of Sentinel-1B satellite, the composite expected wait time until a SAR satellite to fly over a flooded area became smaller than 12 hours. With more SAR missions, such as SAOCOM, RADARSAT Constellation, Sentinel-1C/D, ALOS-3, and NISAR, SAR data are becoming more useful for rapid mapping of devastating floods, which are becoming more frequent and more severe around the world.

InSAR atmospheric correction using Himawari-8 Geostationary Meteorological Satellite

NASA Astrophysics Data System (ADS)

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

2017-12-01

The atmospheric delay effect is one of the limitations for the accurate surface displacement detection by Synthetic Aperture Radar Interferometry (InSAR). Many previous studies have attempted to mitigate the neutral atmospheric delay in InSAR (e.g. Jolivet et al. 2014; Foster et al. 2006; Kinoshita et al. 2013). Hanssen et al. (2001) investigated the relationship between the 27 hourly observations of GNSS precipitable water vapor (PWV) and the infrared brightness temperature derived from visible satellite imagery, and showed a good correlation. Here we showed a preliminary result of the newly developed method for the neutral atmospheric delay correction using the Himawari-8 Japanese geostationary meteorological satellite data. The Himawari-8 satellite is the Japanese state-of-the-art geostationary meteorological satellite that has 16 observation channels and has spatial resolutions of 0.5 km (visible) and 2.0 km (near-infrared and infrared) with an time interval of 2.5 minutes around Japan. To estimate the relationship between the satellite brightness temperature and the atmospheric delay amount. Since the InSAR atmospheric delay is principally the same as that in GNSS, we at first compared the Himawari-8 data with the GNSS zenith tropospheric delay data derived from the Japanese dense GNSS network. The comparison of them showed that the band with the wavelength of 6.9 μm had the highest correlation to the GNSS observation. Based on this result, we developed an InSAR atmospheric delay model that uses the Himawari-8 6.9 μm band data. For the model validation, we generated InSAR images from the ESA's C-band Sentinel-1 SLC data with the GAMMA SAR software. We selected two regions around Tokyo and Sapporo (both in Japan) as the test sites because of the less temporal decorrelation. The validation result showed that the delay model reasonably estimate large scale phase variation whose spatial scale was on the order of over 20 km. On the other hand, phase variations of a few km scale were not estimated by the model. This would be due to the horizontal resolution of the input data (2 km in the 6.9 μm band). In the presentation we will show these results and the progress after the abstract submission, and discuss the limitation of our method and the future research plan.

Scanning silence: mental imagery of complex sounds.

PubMed

Bunzeck, Nico; Wuestenberg, Torsten; Lutz, Kai; Heinze, Hans-Jochen; Jancke, Lutz

2005-07-15

In this functional magnetic resonance imaging (fMRI) study, we investigated the neural basis of mental auditory imagery of familiar complex sounds that did not contain language or music. In the first condition (perception), the subjects watched familiar scenes and listened to the corresponding sounds that were presented simultaneously. In the second condition (imagery), the same scenes were presented silently and the subjects had to mentally imagine the appropriate sounds. During the third condition (control), the participants watched a scrambled version of the scenes without sound. To overcome the disadvantages of the stray acoustic scanner noise in auditory fMRI experiments, we applied sparse temporal sampling technique with five functional clusters that were acquired at the end of each movie presentation. Compared to the control condition, we found bilateral activations in the primary and secondary auditory cortices (including Heschl's gyrus and planum temporale) during perception of complex sounds. In contrast, the imagery condition elicited bilateral hemodynamic responses only in the secondary auditory cortex (including the planum temporale). No significant activity was observed in the primary auditory cortex. The results show that imagery and perception of complex sounds that do not contain language or music rely on overlapping neural correlates of the secondary but not primary auditory cortex.

Inventory of anthropogenic surface deformation measured by InSAR in the western U.S./Mexico and possible impacts on GPS measurements

NASA Astrophysics Data System (ADS)

Semple, A.; Pritchard, M. E.; Taylor, H.

2014-12-01

The western US and Mexico are deforming at several spatial scales that can be measured by ground and satellite observations like GPS and Interferometric Synthetic Aperture Radar (InSAR). Many GPS stations have been installed throughout this area to monitor ground deformation caused by large scale tectonic processes; however, several studies have noted that the data recorded at a GPS station can be contaminated by local, non-tectonic ground deformation. In this study, we use InSAR to examine deformation from various sources in the western US and Mexico. We chose this method due to the spatially large study area and the availability and temporal coverage of SAR imagery. We use SAR images acquired by the satellites Envisat, ERS-1 and ERS-2 over a time period from 1992-2010 to create several time series. Data from the ALOS satellite between 2006-2011 are also used in some areas. We use these time series analysis along with previously published results to observe and catalogue various sources of surface deformation in the western US and Mexico - from groundwater pumping, geothermal activity, mining, hydrocarbon production, and other sources. We then use these results to identify GPS stations that have potentially been contaminated by non-tectonic deformation signals. We document more than 150 distinct regions of non-tectonic and likely anthropogenic deformation. We have located 82 GPS stations within 20km of the center of at least one of the non-tectonic deformation signals we have identified. It is likely that the data from these 82 GPS stations have been contaminated by local anthropogenic deformation. Some examples of previously unpublished non-tectonic deformation we have seen in this study include but are not limited to, subsidence due to groundwater extraction in Jesus Garcia, Mexico, both uplift and subsidence due to natural gas extraction at Jonah Field in Sublette County, WY, and uplift due to a water recharge project in Tonopah, AZ.

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.

Different residues in the SARS-CoV spike protein determine cleavage and activation by the host cell protease TMPRSS2

PubMed Central

Reinke, Lennart Michel; Hartleib, Anika; Nehlmeier, Inga; Gierer, Stefanie; Hoffmann, Markus; Hofmann-Winkler, Heike; Winkler, Michael

2017-01-01

The spike (S) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) mediates viral entry into target cells. Cleavage and activation of SARS S by a host cell protease is essential for infectious viral entry and the responsible enzymes are potential targets for antiviral intervention. The type II transmembrane serine protease TMPRSS2 cleaves and activates SARS S in cell culture and potentially also in the infected host. Here, we investigated which determinants in SARS S control cleavage and activation by TMPRSS2. We found that SARS S residue R667, a previously identified trypsin cleavage site, is also required for S protein cleavage by TMPRSS2. The cleavage fragments produced by trypsin and TMPRSS2 differed in their decoration with N-glycans, suggesting that these proteases cleave different SARS S glycoforms. Although R667 was required for SARS S cleavage by TMPRSS2, this residue was dispensable for TMPRSS2-mediated S protein activation. Conversely, residue R797, previously reported to be required for SARS S activation by trypsin, was dispensable for S protein cleavage but required for S protein activation by TMPRSS2. Collectively, these results show that different residues in SARS S control cleavage and activation by TMPRSS2, suggesting that these processes are more complex than initially appreciated. PMID:28636671

Different residues in the SARS-CoV spike protein determine cleavage and activation by the host cell protease TMPRSS2.

PubMed

Reinke, Lennart Michel; Spiegel, Martin; Plegge, Teresa; Hartleib, Anika; Nehlmeier, Inga; Gierer, Stefanie; Hoffmann, Markus; Hofmann-Winkler, Heike; Winkler, Michael; Pöhlmann, Stefan

2017-01-01

The spike (S) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) mediates viral entry into target cells. Cleavage and activation of SARS S by a host cell protease is essential for infectious viral entry and the responsible enzymes are potential targets for antiviral intervention. The type II transmembrane serine protease TMPRSS2 cleaves and activates SARS S in cell culture and potentially also in the infected host. Here, we investigated which determinants in SARS S control cleavage and activation by TMPRSS2. We found that SARS S residue R667, a previously identified trypsin cleavage site, is also required for S protein cleavage by TMPRSS2. The cleavage fragments produced by trypsin and TMPRSS2 differed in their decoration with N-glycans, suggesting that these proteases cleave different SARS S glycoforms. Although R667 was required for SARS S cleavage by TMPRSS2, this residue was dispensable for TMPRSS2-mediated S protein activation. Conversely, residue R797, previously reported to be required for SARS S activation by trypsin, was dispensable for S protein cleavage but required for S protein activation by TMPRSS2. Collectively, these results show that different residues in SARS S control cleavage and activation by TMPRSS2, suggesting that these processes are more complex than initially appreciated.

Performance of the SIR-B digital image processing subsystem

NASA Technical Reports Server (NTRS)

Curlander, J. C.

1986-01-01

A ground-based system to generate digital SAR image products has been developed and implemented in support of the SIR-B mission. This system is designed to achieve the maximum throughput while meeting strict image fidelity criteria. Its capabilities include: automated radiometric and geometric correction of the output imagery; high-precision absolute location without tiepoint registration; filtering of the raw data to remove spurious signals from alien radars; and automated catologing to maintain a full set of radar and image production facility in support of the SIR-B science investigators routinely produces over 80 image frames per week.

Aeromagnetic survey over US to advance geomagnetic research

USGS Publications Warehouse

Hildenbrand, T.G.; Blakely, R.J.; Hinze, W. J.; Keller, Gordon R.; Langel, R.A.; Nabighian, M.; Roest, W.

1996-01-01

A proposed high-altitude survey of the US offers an exciting and cost effective opportunity to collect magnetic-anomaly data. Lockheed Martin Missile and Space Company is considering funding a reimbursable ER-2 aircraft mission to collect synthetic aperture radar (SAR) imagery at an altitude of about 21 km over the conterminous US and Alaska. The collection of total and vector magnetic field data would be a second objective of the flight. These data would provide insight on fundamental tectonic and thermal processes and give a new view of the structural and lithologic framework of the crust and upper mantle.

Application of IEM model on soil moisture and surface roughness estimation

NASA Technical Reports Server (NTRS)

Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

1995-01-01

Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

Timing of recent accelerations of Pine Island Glacier, Antarctica

USGS Publications Warehouse

Joughin, I.; Rignot, E.; Rosanova, C.E.; Lucchitta, B.K.; Bohlander, J.

2003-01-01

We have used Interferometric Synthetic Aperture Radar (InSAR) data and sequential Landsat imagery to identify and temporally constrain two acceleration events on Pine Island Glacier (PIG). These two events are separated by a period of at least seven years (1987 - 1994). The change in discharge between two flux gates indicates that the majority of the increase in discharge associated with the second acceleration originates well inland (>80 km) from the grounding line. An analysis indicates that changes in driving stress consistent with observed thinning rates are sufficient in magnitude to explain much of the acceleration.

Satellite observations of eddies in the Baltic, Black and Caspian seas

NASA Astrophysics Data System (ADS)

Karimova, S.

2012-04-01

In the present paper mesoscale and sub-mesoscale eddies in the Baltic, Black and Caspian seas are studied by means of satellite radiometer and radar images. Using these data makes it possible to investigate the vortical structures of a wide spatial range, from the basin scale through mesoscale to a small scale with a few kilometers in size. Over 2000 Envisat ASAR and ERS-2 SAR images with two-year time coverage (2009-2010) and spatial resolution of 75 m obtained in different parts of the Baltic, Black and Caspian Seas were applied to study submesoscale (with a diameter less than ca. 20 km) eddies in the basins mentioned. As a result of the analysis performed the role of different mechanisms (ones due to surfactant films, wave/current interactions and thermal fronts) in eddy visualization in SAR imagery was revealed. In every basin studied the main eddy characteristics such as number of eddies, frequency of their occurrence in SAR imagery, sign of vorticity, typical length scale and lifetime as well as spatial distribution patterns were investigated. Spatio-temporal parameters of the vortices were subjected to statistical analysis. Interannual and seasonal variabilities of the eddy parameters were traced. Hypotheses about the most important mechanisms of generation of the eddies observed were proposed. Among them there are barotropic, baroclinic and topographic instabilities, convection in the surface layer and heterogeneous wind forcing. Satellite infrared and visible images were used for retrieving statistical information on the Black Sea mesoscale vortical structures. The dataset used included ~5000 AVHRR NOAA Sea Surface Temperature (SST) images covering the entire Black Sea with time coverage since September, 2004 to December, 2010 and ~1500 MODIS Aqua (SST, normalized water-leaving radiance at 551 nm, chlorophyll-a concentration) images obtained in 2006-2010. Spatial resolution of the images was 1 km. Analysis performed revealed that numerous vortical structures could be detected in the imagery mentioned. These structures were very different in their spatio-temporal scales and mechanisms of generation. It was discovered that the eddy types which could be especially frequently observed were the Rim Current meanders and rings, quasi-permanent anticyclonic eddies, near-shore anticyclonic eddies, mushroom-like currents (eddy dipoles), eddies of the Anatolian coast, and eddy chains. For each type of non-stationary eddies (the last four groups of eddies just mentioned), their spatio-temporal characteristics were retrieved such as areas of the most frequent generation and typical length scale as well as their seasonality and interannual variability. This work was implemented within the framework of the Federal Target Program "Scientific and scientific-pedagogical personnel of innovative Russia" in 2009-2013 and partly supported by the Russian Foundation for Basic Research (grants #10-05-00428, #11-07-12025).

SAR Coherence Change Detection of Urban Areas Affected by Disasters Using SENTINEL-1 Imagery

NASA Astrophysics Data System (ADS)

Washaya, P.; Balz, T.

2018-04-01

The study focuses on two study areas: San Juan in Puerto Rico, which was affected by Hurricane Maria in September 2017, and Sarpol Zahab in Iran, which was one of the towns affected by an earthquake in November 2017. In our study, we generate coherence images, and classify them into areas of `change' and `no-change'. A statistical analysis is made by converting the coherence results into point data, creating street blocks for the study areas and integrating the point data into the street blocks to calculate the standard deviation over the whole stack of images. Additionally, Landsat imagery is used to create land-use classes, convert them to polygons and integrate the polygon classes to the coherence maps to determine the average coherence loss per class for each disaster. Results show 65 % loss in coherence after the earthquake in Sarpol-e-Zahab and 75 % loss in Puerto Rico after the Hurricane. Land-use classes show coherence losses to below 0.5 for each disaster.

Significant results from using earth observation satellites for mineral and energy resource exploration

USGS Publications Warehouse

Carter, William D.

1981-01-01

Launched in June 1978, Seasat operated for only 100 days, but successfully acquired much information over both sea and land. The collection of synthetic aperture radar (SAR) imagery and radar altimetry was particularly important to geologists. Although there are difficulties in processing and distributing these data in a timely manner, initial evaluations indicate that the radar imagery supplements Landsat data by increasing the spectral range and offering a different look angle. The radar altimeter provides accurate profiles over narrow strips of land (1 km wide) and has demonstrated usefulness in measuring icecap surfaces (Greenland, Iceland, and Antarctica). The Salar of Uyuni in southern Bolivia served as a calibration site for the altimeter and has enabled investigators to develop a land-based smoothing algorithm that is believed to increase the accuracy of the system to 10 cm. Data from the altimeter are currently being used to measure subsidence resulting from ground water withdrawal in the Phoenix-Tucson area.

Contribution of SAR interferometry (InSAR) to the study of alpine glaciers. The example of Forni Glacier (Central Alps, Italy): preliminary results

NASA Astrophysics Data System (ADS)

Sterzai, P.; Mancini, F.; Corazzato, C.; D Agata, C.; Diolaiuti, G.

2003-04-01

Aiming at reconstructing superficial velocity and volumetric variations of alpine glaciers, SAR interferometry (InSAR) technique is, for the first time in Italy, applied jointly with the glaciological classic field methods. This methodology with its quantitative results provides, together with other space geodesy techniques like GPS, some fundamental elements for the estimation of the climate forcing and the evaluation of the future glacier trend. InSAR is usually applied to antarctic glaciers and to other wide extralpine glaciers, detectable by the SAR orbits; in the Italian Alps, the limited surface area of the glaciers and the deformation of radar images due to strong relief effect, reduce the applicability of this tecnique. The chosen glacier is suitable for this kind of study both for its large size and for the many field data collected and available for the interferometric results validation. Forni Glacier is the largest valley glacier in the Italian Alps and represents a good example of long term monitoring of a valley glacier in the Central Alps. It is a north facing valley glacier formed by 3 ice streams, located in Italian Lombardy Alps (46 23 50 N, 10 35 00 E). In 2002 its area was approximately 13 km2, extending from 2500 to 3684 m a.s.l., with a maximum width of approximately 7500 m and a maximum length of about 5000 m. Available data include mass-balance measurements on the glacier tongue (from the hydrological year 1992-1993 up to now), frontal variations data from 1925 up to now, topographical profiling by means of GPS techniques and profiles of the glacier bed by geoelectrical surveys (VES) (Guglielmin et alii, 1995) and by seismic surveys (Merlanti et alii, 2001). In order to apply radar interferometry on this glacier eight ERS SAR RAW images have been purchased, in addition to the Digital Elevation Model from IGM (Geographic Military Institute), and repeat pass interferometry used. Combining the different passes, differential interferograms are computed and velocity map obtained. The validation of interferometric data was possible comparing them with the field glaciological data obtained by GPS velocity surveys in the years 1992-1993 (Vittuari and Smiraglia, unpublished) and 1996-1997, which resulted of about 20m/y. The InSAR results give further contributions in the estimation of the velocity field of Forni Glacier for a deeper understanding of the different flow lines of the glacier. Problems related to relief effect, loss of coherence, geometry of satellite imagery and geocoding, are also discussed.

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

NASA Astrophysics Data System (ADS)

Wei, Xiangfei; Wang, Xiaoqing; Chong, Jinsong

2018-01-01

Ships on synthetic aperture radar (SAR) images will be severely defocused and their energy will disperse into numerous resolution cells under long SAR integration time. Therefore, the image intensity of ships is weak and sometimes even overwhelmed by sea clutter on SAR image. Consequently, it is hard to detect the ships from SAR intensity images. A ship detection method based on local region power spectrum of SAR complex image is proposed. Although the energies of the ships are dispersed on SAR intensity images, their spectral energies are rather concentrated or will cause the power spectra of local areas of SAR images to deviate from that of sea surface background. Therefore, the key idea of the proposed method is to detect ships via the power spectra distortion of local areas of SAR images. The local region power spectrum of a moving target on SAR image is analyzed and the way to obtain the detection threshold through the probability density function (pdf) of the power spectrum is illustrated. Numerical P- and L-band airborne SAR ocean data are utilized and the detection results are also illustrated. Results show that the proposed method can well detect the unfocused ships, with a detection rate of 93.6% and a false-alarm rate of 8.6%. Moreover, by comparing with some other algorithms, it indicates that the proposed method performs better under long SAR integration time. Finally, the applicability of the proposed method and the way of parameters selection are also discussed.

Surface Deformation During a Magmatic Intrusion: the Example of the Dabba'hu Rift Crisis of 2005-2006 (Afar, Ethiopia)

NASA Astrophysics Data System (ADS)

Grandin, R.; Socquet, A.; Binet, R.; Jacques, E.; Klinger, Y.; de Chabalier, J.; King, G.; Tait, S.; Tapponnier, P.; Delorme, A.; Elissalde, C.

2007-12-01

In September 2005, a magmato-tectonic episode initiated in Western Afar (Ethiopia) when a swarm of moderate magnitude earthquakes (M<5.6) was recorded for several days. A small eruption also occurred on the eastern flank of Dabba'hu, a large silicic volcano located at the northern extremity of the Dabba'hu rift segment. The terrain is exceptionally favorable for InSAR imagery and surface fault mapping, making this event a rare opportunity to study how surface faulting and dike injection were mechanically coupled during the rifting event. Based on the combination of InSAR images shot on both ascending and descending tracks, and the correlation of SAR amplitude images, we deduced the vertical motions inside the rift during the main intrusion event. Together with the correlation of SPOT optical images, the horizontal component of opening can be retrieved. We provide evidence for an average of 6 m of opening across the 40 km northern Dabba'hu segment, during the September crisis. The inner floor of the rift subsided by ~ 2m, while the shoulders were uplifted by ~ 2m. A deficit of opening was observed in the southern segment during the main crisis. However, a second intrusive event occurred in mid-2006, leading to the further opening of this 20 km segment by an additional ~ 2m. A series of interferograms covering the post-crises periods show that significant motion also occurred between the crises and after the second crisis. Using a comparison between pre-crisis aerial photographs and post-crisis high-resolution Quickbird images, combined with SAR coherence images, we are able to map the structures that were reactivated during the crisis, and show extensive evidence of newly exposed fractures in recent basalts. The motion on a large number of en echelon faults and fissures could be observed with much greater detail than during the main rifting event. Using a DEM of the area, generated using SPOT images, the relation between faulting and rift morphology is addressed. Concentric subsidence and/or uplift occurred at various stages of the crisis on distinct volcanic edifices, pointing to a complex scenario for the possible connection between shallow and deep magmatic chambers. The estimated extension rate of 15 mm/year across the plate boundary [Vigny et al., 2006] yields a recurrence time of the order of 500 years for events of this magnitude. Surprisingly, despite the large volume of magma intruded during the September 2005 event (~ 15 km2), no basalt flows were observed.

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.

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

USGS Publications Warehouse

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

2009-01-01

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

Bridging the Past with Today's Microwave Remote Sensing: A Case Study of Long Term Inundation Patterns in Two River Deltas

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Jensen, K.; Schroeder, R.; Tessler, Z. D.

2016-12-01

Surface inundation extent and its predictability vary tremendously across the globe. This dynamic is being and has been captured by three general categories of satellite imagery: a) low-spatial-resolution microwave sensors with global coverage and a long record of observations (e.g., SSM/I), b) optical sensors with high spatial and temporal resolution and global coverage as well, but with cloud contamination (e.g. MODIS), and also c) less frequently in ``snapshot'' form by high-resolution synthetic aperture radar (SAR) sensors. We explore the ability to bridge techniques that can exploit the higher spatial resolution of more recent data products back in time with the help of the temporal evolution of lower resolution products. We present a study of long term (20+ yrs) inundation patterns in two river deltas: (1) the Mekong, and (2) the Ganges-Brahmaputra. This research utilizes baseline observations from the Surface Water Microwave Product Series (SWAMPS), an inundation area fraction product derived at 25km scale from active and passive microwave instruments (ERS, QuikSCAT, ASCAT, and SSM/I) that spans from Jan 1992 to the present. Every hydrological basin has unique characteristics - such as its topography, land cover / land use, and spatio-temporal variability - thus, a downscaling algorithm needs to take into account these idiosyncrasies. We merge SWAMPS with topographical information derived from 30m SRTM DEM, river networks from USGS HydroSHEDS, and train a downscaling algorithm to learn from two sets of classified SAR data: (1) L-band imaging radar from ALOS PALSAR, 2007-2010, and (2) more recent C-band imagery from the Sentinel-1 mission (2014 to present). We present an accuracy assessment of retrospective downscaled flood extent with Landsat imagery and address potential sources of biases. With a higher spatial resolution of past flooding extent, we can improve our understanding of how delta surface hydrology has responded to climate events and human activities. This is important both in the short-term for accurate flood prediction, as well as on longer-term planning horizons.

Farming the Tropics: Visualizing Landscape Changes Through the Clouds, in the Cloud

NASA Astrophysics Data System (ADS)

Kontgis, C.; Brumby, S. P.; Chartrand, R.; Franco, E.; Keisler, R.; Kelton, T.; Mathis, M.; Moody, D.; Raleigh, D.; Rudelis, X.; Skillman, S.; Warren, M. S.

2016-12-01

A key component of studying land cover and land use change is analyzing trends in spectral signatures through time. For vegetation, the standard method of doing this involves the normalized difference vegetation index (NDVI) or near infrared signal during a growing season, as both increase while plants grow and decrease during senescence. If temporal resolution were high and clouds did not obstruct landscape views, this approach could work across the globe. However, in tropical regions that are increasingly important for global food production, often there is not enough spectral information to monitor landscape change due to persistent cloud cover. In these instances, synthetic aperture radar (SAR) data provides a useful alternative to shorter wavelength components of the spectrum since its longer wavelengths can penetrate clouds. This analysis uses the cloud-based platform developed by Descartes Labs to explore the utility of Sentinel-1 data in cloudy tropical regions, using the Mekong River Delta in southern Vietnam as a case study. We compare phenological growing patterns derived from Sentinel-1 data with those from Landsat and MODIS imagery, which are the most commonly used sensors to map land cover and land use across the globe. Using these SAR-derived phenology curves, it is possible to monitor landscape changes in near real-time, while also visualizing and quantifying the rates of agricultural intensification. Descartes Labs is a venture-backed remote sensing startup founded in 2014 by a group of scientists from the Los Alamos National Laboratory in New Mexico. Since its inception, the team at Descartes has assembled all available satellite imagery from the USGS Landsat and NASA MODIS programs, and has analyzed over 2.8 quadrillion pixels of satellite imagery. With a focus on food security and climate change, the company has succeeded at estimating United States corn yields earlier and more accurately than USDA estimates. Now, this technology is being applied to within-season forecasting of acreage and yields in near real-time, while also branching out beyond the US to other regions including South America and Asia.