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Geoscience and Remote Sensing, IEEE Transactions on

Issue 8 • Date Aug. 2010

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Displaying Results 1 - 25 of 30
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Page(s): C2
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  • Table of contents

    Page(s): 3057 - 3058
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  • Iterative Bayesian Retrieval of Hydrometeor Content From X-Band Polarimetric Weather Radar

    Page(s): 3059 - 3074
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2147 KB) |  | HTML iconHTML  

    Dual-polarized weather radars are capable to detect and identify different classes of hydrometeors, within stratiform and convective storms, exploiting polarimetric diversity. Among the various techniques, a model-supervised Bayesian method for hydrometeor classification, tuned for S- and X-band polarimetric weather radars, can be effectively applied. Once the hydrometeor class is estimated, the retrieval of their water content can also be statistically carried out. However, the critical issue of X-band radar data processing, and in general of any attenuating wavelength active system, is the intervening path attenuation, which is usually not negligible. Any approach aimed at estimating hydrometeor water content should be able to tackle, at the same time, path attenuation correction, hydrometeor classification uncertainty, and retrieval errors. An integrated iterative Bayesian radar algorithm (IBRA) scheme, based on the availability of the differential phase measurement, is presented in this paper and tested during the International H2O Project experiment in Oklahoma in 2002. During the latter campaign, two dual-polarized radars, at S- and X-bands, were deployed and jointly operated with closely matched scanning strategies, giving the opportunity to perform experimental comparisons between coincident measurements at different frequencies. Results of the IBRA technique at X-band are discussed, and the impact of path attenuation correction is quantitatively analyzed by comparing hydrometeor classifications and estimates with those obtained at S-band. The overall results in terms of error budget show a significant improvement with respect to the performance with no path attenuation correction. View full abstract»

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  • Raindrop Size Distribution Parameters of Distrometer Data With Different Bin Sizes

    Page(s): 3075 - 3080
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (575 KB) |  | HTML iconHTML  

    A 2D video distrometer (2DVD) provides raindrop size distribution (DSD) at nominal drop diameters that correspond to the mean of the bin sizes. Selection of bin width may influence the shape of DSD. Therefore, we investigated the effect of binning on the DSD parameter estimates. First, we studied the effect of binning by examining their ability to recover known parameters of simulated DSD. Second, real DSD data collected in the equatorial region by 2DVD were analyzed. We compared the DSD parameters calculated from binned DSD with those calculated from a drop-by-drop data basis. Both simulated and real DSDs were binned at 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, and 0.50 mm. In general, the DSD parameters increased with increasing bin width. With very large number of raindrop which should be accompanied by heavy rain, the bias due to bin width selection is small. However, the bias is significant in the opposite case. The average fractional error between a mass-weighted mean diameter (Dm) calculated from DSD and that derived from drop-by-drop data was relatively small for all rainfall rates. A rather high error was observed in the median volume diameter (D0) which may be due to moment method and interpolation error. Finally, using small bin widths (0.20-0.30 mm) may be the best choice because the DSD parameters of these bin widths were very close to those obtained from drop-by-drop data. View full abstract»

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  • Modified Monthly Oceanic Rain-Rate Algorithm to Account for TRMM Boost

    Page(s): 3081 - 3086
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (610 KB) |  | HTML iconHTML  

    We provide a modified algorithm for computing Tropical Rainfall Measuring Mission (TRMM) monthly oceanic rain rates (3A11) for TRMM Microwave Imager data using the Microwave Emission Brightness Temperature Histogram (METH) technique developed by Wilheit Shin and Chiu examined changes associated with TRMM boost by adjusting the microwave brightness temperature (Tb) for the postboost data to match the preboost data. We computed a new relation between Tb and rain rate (Tb-R) for the postboost characteristics using the same radiative transfer model of Wilheit and modified the algorithm by providing two Tb-R relations for the preboost and postboost era, respectively. The modified algorithm is applied to TRMM data without Tb adjustment. Preliminary results show a significant improvement over the unmodified algorithm in terms of biases and linear trends. Their differences on the application of the METH technique to other microwave data for climate-scale rainfall are discussed. View full abstract»

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  • Passive and Active L-Band Microwave Observations and Modeling of Ocean Surface Winds

    Page(s): 3087 - 3100
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    L-band microwave backscatter and brightness temperature of sea surfaces acquired using the Passive/Active L-band Sensor during the High Ocean Wind campaign are reported in terms of their dependence on ocean surface wind speed and direction. We find that the L-band VV, HH, and HV radar backscatter data increase by 6-7 dB from 5 to 25 m/s wind speed at a 45° incidence angle. The data suggest the validity of Phased Array type L-band Synthetic Aperture Radar (PALSAR) HH model function between 5 and 15 m/s wind speeds, but show that the extrapolation of PALSAR model at above 20 m/s wind speeds overpredicts A0 and a1 coefficients. There is wind direction dependence in the radar backscatter with about 4 dB differences between upwind and crosswind observations at 24 m/s wind speed for VV and HH. The passive brightness temperatures show about a 5-K change for TV and a 7-K change for TH for a wind speed increasing from 5 to 25 m/s. Circle flight data suggest a wind direction response of about 1-2 K in TV and TH at 14 and 24 m/s wind speeds. The L-band microwave data show excellent linear correlation with the surface wind speed with a correlation better than 0.95. The results support the use of L-band radar data for estimating the wind-driven excess brightness temperature of sea surfaces. The data also support the applications of L-band microwave signals for high-resolution (kilometer scale) observation of ocean surface winds under high wind conditions (10-28 m/s). View full abstract»

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  • Obtaining Accurate Ocean Surface Winds in Hurricane Conditions: A Dual-Frequency Scatterometry Approach

    Page(s): 3101 - 3113
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1651 KB) |  | HTML iconHTML  

    We describe a method for retrieving winds from colocated Ku- and C-band ocean wind scatterometers. The method utilizes an artificial neural network technique to optimize the weighting of the information from the two frequencies and to use the extra degrees of freedom to account for rain contamination in the measurements. A high-fidelity scatterometer simulation is used to evaluate the efficacy of the technique for retrieving hurricane force winds in the presence of heavy precipitation. Realistic hurricane wind and precipitation fields were simulated for three Atlantic hurricanes, Katrina and Rita in 2005 and Helene in 2006, using the Weather Research and Forecasting model. These fields were then input into a radar simulation previously used to evaluate the Extreme Ocean Vector Wind Mission dual-frequency scatterometer mission concept. The simulation produced high-resolution dual-frequency normalized radar cross-section (NRCS) measurements. The simulated NRCS measurements were binned into 5 x 5 km wind cells. Wind speeds in each cell were estimated using an artificial neural network technique. The method was shown to retrieve accurate winds up to 50 m/s even in intense rain. View full abstract»

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  • A Neural Network Technique for Improving the Accuracy of Scatterometer Winds in Rainy Conditions

    Page(s): 3114 - 3122
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1133 KB) |  | HTML iconHTML  

    We exhibit a technique for improving wind accuracy in Ku-band ocean wind scatterometers in the presence of rain. The technique is autonomous in that it only makes use of measurements made by the scatterometer itself, so that no colocation of an external data set (e.g., rain radiometers) is required to perform the correction. The only inputs to the technique are the normalized radar cross-section measurements for each wind vector cell, the cross-track distance of the cell as a proxy for measurement geometry, and the nominal retrieved wind vector for the cell without rain correction. This last input is used to avoid modifying winds not contaminated by rain. The technique was applied to QuikSCAT data for the month of January 2008, resulting in a marked improvement to rainy data. For data that were determined to be rain contaminated by the Jet Propulsion Laboratory rain flag, the rms speed error with respect to National Data Buoy Center buoy winds improved from 8.9 to 3.5 m/s for colocations within 25 km. The rms speed error in rain also improved when compared with the European Centre Medium-Range Weather Forecast winds from 7 to 3 m/s. Data that were not flagged as rain contaminated were not significantly changed, despite the fact that the technique does not make use of the rain flag. The technique was able to distinguish between rain-contaminated wind cells and rain-free wind cells and to substantially improve the wind speed accuracy of the former using QuikSCAT data alone without recourse to any external information about the extent of the rain. View full abstract»

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  • Modeling Angular Dependences in Land Surface Temperatures From the SEVIRI Instrument Onboard the Geostationary Meteosat Second Generation Satellites

    Page(s): 3123 - 3133
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1487 KB) |  | HTML iconHTML  

    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing geometry of the geostationary Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager sensor across the African continent and compare it to a normalized view geometry. We use the modified geometric projection model that estimates the scene thermal infrared radiance from a surface covered by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions, but large variations occur both geographically and temporally. The sun zenith angle, the amount of vegetation, and the vegetation structure are all shown to affect the magnitude of the errors. The findings highlight the need for taking the angular effects into account when applying LST estimates in models and when comparing LST estimates from different sensors or from different times, both on the daily and seasonal scale. View full abstract»

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  • Acoustoseismic Method for Buried-Object Detection by Means of Surface-Acceleration Measurements and Audio Facilities

    Page(s): 3134 - 3138
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (618 KB) |  | HTML iconHTML  

    An experimental setup for acoustoseismic detection of shallow buried objects is presented. The seismic (Rayleigh) waves were generated by exciting an acoustic airborne source by a series of sine-wave bursts, which were designed to cover a frequency range (100-1000 Hz) large enough to distinguish the vibrational characteristics of buried compliant objects. The signals were recorded by means of contact-acceleration microelectromechanical-system sensors moved above different buried objects (compliant and rigid). Signal acquisitions on only sandy soil revealed the natural variability of the outdoor test bed. This variability of soil parameters pointed out the difficulties of buried-object detection based on the amplitude thresholding of the signal spectrum. For this aim, the signals were processed in both time and frequency domains. An audio-channel output was devised to avail of the human hearing apparatus in distinguishing the buried objects according to spatial variations of the acceleration signals obtained by scanning the soil surface. View full abstract»

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  • Electromagnetic Scattering by Bicontinuous Random Microstructures With Discrete Permittivities

    Page(s): 3139 - 3151
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2119 KB) |  | HTML iconHTML  

    For electromagnetic (EM) scattering by dense media, the traditional approach is to use particles of spheres or ellipsoids that are densely and randomly packed in a background medium. The particles have discrete permittivities that are different from the background medium. The dense-medium model has been applied to the microwave remote sensing of terrestrial snow. In this paper, we propose a different approach of using a bicontinuous medium with discrete permittivities and study the EM scattering properties using analytical and numerical methods. The bicontinuous medium is a continuous representation of interfaces between inhomogeneities within the medium. Discrete permittivities are then assigned to the inhomogeneities of the structure. The analytical approach is based on the Born approximation using the derived analytical correlation functions. The numerical method is based on the numerical Maxwell model of 3-D (NMM3D) approach. In particular, the discrete-dipole approximation and the conjugate gradient-squared method accelerated by the fast Fourier transform technique are used in solving the volume integral equation. Scattering results of analytical and numerical approaches are compared. Numerical results are illustrated using parameters in microwave remote sensing of terrestrial snow. In the NMM3D simulations, three kinds of convergence tests are conducted, viz., convergence with respect to the discretization size, convergence with respect to the sample size, and convergence with respect to the number of realization. The NMM3D results indicate that the scattering by the bicontinuous medium with a broader size distribution has a weaker frequency dependence than that by the medium with a more narrow size distribution. The frequency-dependence power law index can be lower than two, which is very much lower than the power of four in Rayleigh scattering. The NMM3D results also exhibit fairly large cross-polarization returns which account for the local nonisotropic mic- - rostructures of bicontinuous media, although the medium is statistically isotropic. View full abstract»

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  • Multimonostatic Shape Reconstruction of Two-Dimensional Dielectric Cylinders by a Kirchhoff-Based Approach

    Page(s): 3152 - 3161
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (746 KB) |  | HTML iconHTML  

    The inverse problem of reconstructing the shape of dielectric cylinders by aspect-limited multimonostatic multifrequency electromagnetic scattering data is dealt with. The problem is formulated as a linear one by means of the physical-optics approximation distributional approach. The difference with respect to the case of perfectly electrical conducting scatterers is pointed out, since the penetrability of the scatterers is taken into account by considering the contribution of the “shadowed” side to the local reflection coefficient. The adopted model allows one to predict that both the “illuminated” and “shadowed” sides of the scatterer provide contribution to the reconstructed image but with a delocalization depending on the relative dielectric permittivity. The numerical results confirm this expectation and show the effectiveness of the approach. View full abstract»

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  • Data Assimilation for Convective-Cell Tracking on Meteorological Image Sequences

    Page(s): 3162 - 3177
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (897 KB) |  | HTML iconHTML  

    This paper focuses on the tracking and analysis of convective cloud systems from Meteosat Second Generation images. The highly deformable nature of convective clouds, the complexity of the physical processes involved, and also the partially hidden measurements available from image data make difficult the direct use of conventional image-analysis techniques for tasks of detection, tracking, and characterization. In this paper, we face these issues using variational-data-assimilation tools. Such techniques enable us to perform the estimation of an unknown state function according to a given dynamical model and to noisy and incomplete measurements. The system state we are setting in this study for the cloud representation is composed of two nested curves corresponding to the exterior frontiers of the clouds and to the interior coldest parts (core) of the convective clouds. Since no reliable simple dynamical model exists for such phenomena at the image grid scale, the dynamics on which we are relying has been directly defined from image-based motion measurements and takes into account an uncertainty modeling of the curve dynamics along time. In addition to this assimilation technique, we show in the Appendix how each cell of the recovered cloud system can be labeled and associated to characteristic parameters (birth or death time, mean temperature, velocity, growth, etc.) of great interest for meteorologists. View full abstract»

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  • Unsupervised Change Detection in Multispectral Remotely Sensed Imagery With Level Set Methods

    Page(s): 3178 - 3187
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1639 KB) |  | HTML iconHTML  

    In this paper, the unsupervised change-detection problem in remote sensing images is formulated as a segmentation issue where the discrimination between changed and unchanged classes in the difference image is achieved by defining a proper energy functional. The minimization of this functional is carried out by means of a level set method which iteratively seeks to find a global optimal contour splitting the image into two mutually exclusive regions associated with changed and unchanged classes, respectively. In order to increase the robustness of the method to noise and to the choice of the initial contour, a multiresolution implementation, which performs an analysis of the difference image at different resolution levels, is proposed. The experimental results obtained on three different multitemporal remote sensing images acquired by low- as well as high-spatial-resolution optical remote sensing sensors suggest a clear superiority of the proposed approach compared with state-of-the-art change-detection methods. View full abstract»

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  • Semisupervised One-Class Support Vector Machines for Classification of Remote Sensing Data

    Page(s): 3188 - 3197
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1215 KB) |  | HTML iconHTML  

    This paper presents two semisupervised one-class support vector machine (OC-SVM) classifiers for remote sensing applications. In one-class image classification, one tries to detect pixels belonging to one of the classes in the image and reject the others. When few labeled pixels of only one class are available, obtaining a reliable classifier is a difficult task. In the particular case of SVM-based classifiers, this task is even harder because the free parameters of the model need to be finely adjusted, but no clear criterion can be adopted. In order to improve the OC-SVM classifier accuracy and alleviate the problem of free-parameter selection, the information provided by unlabeled samples present in the scene can be used. In this paper, we present two state-of-the-art algorithms for semisupervised one-class classification for remote sensing classification problems. The first proposed algorithm is based on modifying the OC-SVM kernel by modeling the data marginal distribution with the graph Laplacian built with both labeled and unlabeled samples. The second one is based on a simple modification of the standard SVM cost function which penalizes more the errors made when classifying samples of the target class. The good performance of the proposed methods is illustrated in four challenging remote sensing image classification scenarios where the goal is to detect one of the classes present on the scene. In particular, we present results for multisource urban monitoring, hyperspectral crop detection, multispectral cloud screening, and change-detection problems. Experimental results show the suitability of the proposed techniques, particularly in cases with few or poorly representative labeled samples. View full abstract»

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  • Rule-Based Classification of a Very High Resolution Image in an Urban Environment Using Multispectral Segmentation Guided by Cartographic Data

    Page(s): 3198 - 3211
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2282 KB) |  | HTML iconHTML  

    Classification algorithms based on single-pixel analysis often do not give the desired result when applied to high-spatial-resolution remote-sensing data. In such cases, classification algorithms based on object-oriented image segmentation are needed. There are many segmentation algorithms in the literature, but few have been applied in urban studies to classify a high-spatial-resolution remote-sensing image. Furthermore, the user must specify the spectral and spatial parameters that are data dependent. In this paper, we propose an automatic multispectral segmentation algorithm inspired by the specific idea of guiding a classification process for a high-spatial-resolution remote-sensing image of an urban area using an existing digital map of the same area. The classification results could be used, for example, for high-scale database updating or change-detection studies. The algorithm developed uses digital maps and spectral data as inputs. It generates the segmentation parameters automatically. The algorithm is able to provide a segmented image with accuracy greater than 90%. The segmentation results are then used in a rule-based classification using spectral, geometric, textural, and contextual information. The classification accuracy of the proposed rule-based classification is at least 17% greater than the maximum-likelihood classification results. Results and future improvements will be discussed. View full abstract»

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  • Ionospheric Response to the Geomagnetic Storm on August 21, 2003 Over China Using GNSS-Based Tomographic Technique

    Page(s): 3212 - 3217
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (441 KB) |  | HTML iconHTML  

    The impacts of the August 21, 2003 geomagnetic storm on the ionosphere over China have been first investigated by using the so-called computerized ionospheric tomography (CIT) technique and the observations of the Crustal Movement Observation Network of China. Tomographic results show that the main ionospheric effects of this geomagnetic storm over China are as follows: (1) the negative storm phase effect appears in the F region and (2) the positive storm phase effect occurs above the F region. Meanwhile, some key features in the ionospheric structure have been revealed in the ionospheric images during the storm; this includes the disturbances and an elongated region of the reduced electron density at the latitude around 32°N. Statistical comparisons are carried out to confirm the reliability of the global-navigation-satellite-system-based CIT reconstruction results using the profile obtained from ionosonde observations. View full abstract»

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  • A Monte Carlo Study of Altimeter Pulse Returns and the Electromagnetic Bias

    Page(s): 3218 - 3224
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (281 KB) |  | HTML iconHTML  

    The electromagnetic (EM) bias is an important error term in sea-surface height estimation from satellite radar altimetry. While the EM bias has been studied extensively, previous studies have utilized hydrodynamic and EM models that require an a priori separation of the sea surface into “long” and “short” waves that are then treated separately. This paper presents a study of the EM bias that avoids this decomposition by employing a Monte Carlo procedure with numerical nonlinear hydrodynamic simulations coupled with numerical physical-optics methods for EM scattering from the sea surface. Due to the computational complexity of the approach, only long-crested surfaces (i.e., 2-D scattering problems) are considered. The formulation of the physical-optics model utilized is presented, along with a derivation of the standard Brown model for the long-crested surface case for comparison. The simulated pulse returns generally are in good agreement with the Brown model using the specular surface height probability density function. However, the influence of the EM frequency on the EM bias obtained is much smaller than that reported from satellite observations. Predicted biases are also examined as the range of length scales included in the surface profile is varied, in order to determine any apparent cutoff or length-scale separations that occur. It is found that the bias continues to increase as additional short waves are included in the surface spectrum, although a saturation occurs for surface length scales shorter than the EM wavelength. View full abstract»

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  • Development and Initial Observation of High-Resolution Volume-Scanning Radar for Meteorological Application

    Page(s): 3225 - 3235
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1628 KB) |  | HTML iconHTML  

    A new high-resolution Doppler radar, called Ku-band broadband radar (BBR), with fast scanning capability for meteorological application has been developed. Due to the new system design, the BBR can accurately measure the radar reflectivity factor with a range resolution of several meters and a time resolution of 55 s per volume scan from the nearest range of 50 m to 15 km for 10-W power using pulse compression. In this paper, the basic concepts, configuration, and signal processing of the BBR are described. In the initial observation, the observation accuracy of reflectivity is evaluated using Joss-Waldvogel disdrometer (JWD). As a result, the reflectivity of the BBR is in fairly good agreement with that of JWD. In addition, in the spiral observation, a fine structure of a thunderstorm obtained by the BBR is presented. View full abstract»

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  • Radiometric Calibration of the Advanced Wind Scatterometer Radar ASCAT Carried Onboard the METOP-A Satellite

    Page(s): 3236 - 3255
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3607 KB) |  | HTML iconHTML  

    The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument is carried by each of the three METOP satellites. The ASCAT calibration strategy is described and detailed results are presented concerning the radiometric calibration achieved. View full abstract»

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  • C-Band Polarimetric Backscattering Signatures of Newly Formed Sea Ice During Fall Freeze-Up

    Page(s): 3256 - 3267
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1191 KB) |  | HTML iconHTML  

    A study of the polarimetric backscattering response of newly formed sea ice types under a large assortment of surface coverage was conducted using a ship-based C-band polarimetric radar system. Polarimetric backscattering results and physical data for 40 stations during the fall freeze-up of 2003, 2006, and 2007 are presented. Analysis of the copolarized correlation coefficient showed its sensitivity to both sea ice thickness and surface coverage and resulted in a statistically significant separation of ice thickness into two regimes: ice less than 6 cm thick and ice greater than 8 cm thick. A case study quantified the backscatter of a layer of snow infiltrated frost flowers on new sea ice, showing that the presence of the old frost flowers can enhance the backscatter by more than 6 dB. Finally, a statistical analysis of a series of temporal-spatial measurements over a visually homogeneous frost-flower-covered ice floe identified temperature as a significant, but not exclusive, factor in the backscattering measurements. View full abstract»

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  • Bistatic SAR Experiments With PAMIR and TerraSAR-X—Setup, Processing, and Image Results

    Page(s): 3268 - 3279
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2921 KB) |  | HTML iconHTML  

    The spatial separation of the transmitter and the receiver in bistatic synthetic aperture radar (SAR) enables a variety of data acquisition geometries to achieve benefits like the increased information content of bistatic SAR data. In the case of hybrid bistatic SAR constellations where the transmitter is spaceborne and the receiver is onboard an aircraft, one has to deal with a huge discrepancy between platform velocities. This paper presents bistatic spaceborne/airborne SAR experiments, where the radar satellite TerraSAR-X is used as a transmitter and the airborne SAR sensor Phased Array Multifunctional Imaging Radar (PAMIR) of the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR) is used as a receiver. Both sensors are equipped with phased-array antennas, which offer the possibility of beam steering and could be used for the first time for the “double sliding spotlight mode.” In this mode, the space- and airborne sensors operate with different sliding factors (ratio between footprint and platform velocity). The performance of two different experiments is analyzed, and the novel double sliding spotlight mode is presented. This paper describes the experimental setups, the synchronization system, and the data acquisition. The image results were processed by a modified backprojection algorithm and a frequency-domain algorithm. The analysis of the final bistatic images comprises the spatial resolution and the scattering behavior of selected objects. Parts of the bistatic SAR images are compared with the corresponding monostatic images of PAMIR and TerraSAR-X. It will be shown that hybrid bistatic SAR is a worthwhile and helpful addition to current monostatic SAR. View full abstract»

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  • Imaging of Fractal Profiles

    Page(s): 3280 - 3289
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (258 KB) |  | HTML iconHTML  

    In this paper, a model for radar images of fractal (topologically 1-D) profiles is introduced. A twofold approach is followed: on one hand, we analytically solve the problem whenever small-slope profiles are in order; on the other hand, we present a partly analytical and partly numerical setup to cope with the general-slope case. By means of the analytical approach, we evaluate in closed form both the structure function and the power density spectrum of the radar signal. An appropriately smoothed (physical) fractional Brownian model (fBm) process is employed; its introduction is justified by the finite sensor resolution. A fractal scattering model is employed. It is shown that for a fractal profile modeled as an fBm stochastic process, the backscattered signal turns out to be strictly related to the associated fractional Gaussian noise process if a small-slope regime for the observed profile can be assumed. In the analytical-numerical framework, a profile with prescribed fractal parameters is first synthesized; then, fractal scattering methods (applicable to wider slope regimes with respect to the previous case) are employed to compute the signal backscattered toward the sensor. Finally, the power density spectrum of the acquired radar image is estimated. The obtained spectra are favorably compared with the theoretical results, and a parametric study is performed to assess the overall method behavior. View full abstract»

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  • An ISAR Imaging Method Based on MIMO Technique

    Page(s): 3290 - 3299
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1046 KB) |  | HTML iconHTML  

    With the inverse synthetic aperture radar (ISAR) imaging model, targets should move smoothly during the coherent processing interval (CPI). Since the CPI is quite long, fluctuations of a target's velocity and gesture will deteriorate image quality. This paper presents a multiple-input-multiple-output (MIMO)-ISAR imaging method by combining MIMO techniques and ISAR imaging theory. By using a special M-transmitter N-receiver linear array, a group of M orthogonal phase-code modulation signals with identical bandwidth and center frequency is transmitted. With a matched filter set, every target response corresponding to the orthogonal signals can be isolated at each receiving channel, and range compression is completed simultaneously. Based on phase center approximation theory, the minimum entropy criterion is used to rearrange the echo data after the target's velocity has been estimated, and then, the azimuth imaging will finally finish. The analysis of imaging and simulation results show that the minimum CPI of the MIMO-ISAR imaging method is 1/MN of the conventional ISAR imaging method under the same azimuth-resolution condition. It means that most flying targets can satisfy the condition that targets should move smoothly during CPI; therefore, the applicability and the quality of ISAR imaging will be improved. View full abstract»

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Aims & Scope

 

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

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Meet Our Editors

Editor-in-Chief
Antonio J. Plaza
University of Extremadura