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Geoscience and Remote Sensing, IEEE Transactions on

Issue 1 • Date Jan. 2012

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Displaying Results 1 - 25 of 34
  • [Front cover]

    Publication Year: 2012 , Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Publication Year: 2012 , Page(s): C2
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  • Table of contents

    Publication Year: 2012 , Page(s): 1 - 2
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  • Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

    Publication Year: 2012 , Page(s): 3 - 12
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1099 KB) |  | HTML iconHTML  

    Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 2-8-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the air/snow and snow/ice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform. View full abstract»

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  • Characterization of Arctic Sea Ice Thickness Using High-Resolution Spaceborne Polarimetric SAR Data

    Publication Year: 2012 , Page(s): 13 - 22
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1226 KB) |  | HTML iconHTML  

    In this paper, we have investigated the relationship between the depolarization effects and the wintertime sea ice thickness in the landfast ice region where smooth thick first-year ice (FYI) and deformed old ice coexisted by using C- and X-band spaceborne polarimetric synthetic aperture radar (SAR) data (RADARSAT-2 and TerraSAR-X). We have found a strong correlation between the in situ sea ice thickness and the SAR-derived depolarization factors (copolarized correlation and cross-polarized ratio). The observed relationships have demonstrated not only a categorical difference between FYI and multiyear ice (MYI) but also a one-to-one continuity in the scatter plots, rather than being clustered. It clearly shows that the observed correlations are not merely from the categorical difference in scattering mechanism between FYI and MYI and that there might exist a one-to-one relationship between thickness and depolarization factors at least in our deformed ice case. This suggests that depolarization factors could be effective SAR parameters in the estimation of wintertime sea ice thickness. Numerical model simulations explained some portions of the correlation by employing multiple scattering on the sea ice surface and volume scattering within the low-density subsurface layer. View full abstract»

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  • Merging and Analysis of Elevation Time Series Over Greenland Ice Sheet From Satellite Radar Altimetry

    Publication Year: 2012 , Page(s): 23 - 36
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1628 KB) |  | HTML iconHTML  

    Spatial-temporal variability and changes of Greenland ice sheet elevation from 1992 to 2008 are analyzed from merged ERS-1, ERS-2, and Envisat satellite radar altimeter data. A methodology for determining intersatellite biases was developed and applied in order to merge measurements from these different satellites and to create continuous and consistent time series. Intersatellite biases of elevation and backscatter coefficient have shown to be significantly affected by the bias between measurements in ascending and descending orbits. Adjustment of elevation time series for its dependence on backscatter coefficient and other waveform parameters performed in this paper substantially reduced the amplitude of elevation seasonal variations and locally corrected elevation change-rate estimates by up to several centimeters per year. It was found that the correction depends not only on the variations in the waveform parameters but also on the temporal variations of the correlation gradients, which represent the sensitivity of the elevation change to the change in the waveform parameters. An elevation change rate of +2.8 ±0.2 cm/year from 1992 to 2008 over 76% of the Greenland ice sheet area was found. Increases in surface elevation from 1995 observed over the high-elevation regions of Greenland were followed by an elevation decrease from 2006. For the whole period of 1992-2008, the elevation increase is 4.0 ± 0.2 cm/year over 87% of the area above 1500 m. In contrast, over 38% of the low-elevation areas below 1500 m, the rate of elevation change is -7.0 ±1.0 cm/year, and the surface elevation decrease that started from 2000 has continued. View full abstract»

    Open Access
  • Ice and Bedrock Characteristics Underneath Dome C (Antarctica) From Radio Echo Sounding Data Analysis

    Publication Year: 2012 , Page(s): 37 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (558 KB) |  | HTML iconHTML  

    The radio echo sounding (RES) system is one of the most widely used active remote sensing techniques for polar ice sheet exploration, including bedrock morphology studies and subglacial lake investigations. Recently, bedrock characterization has been improved through the analysis of radar echo strength. In this paper, the analysis of the RES signal amplitude has been used to collect information about the controversial problem of electromagnetic ice absorption to highlight areas of high reflectivity variation, ascribable to wet ice-bedrock interfaces. A method to distinguish a wet or dry bedrock-ice interface using a model to describe the internal ice absorption is proposed and discussed. Moreover, the comparison between the ice absorption rates from RES measurements and from European Project for Ice Coring in Antarctica Dome C (Antarctica) ice core conductivity data, the signal amplitude contributions of internal ice layers, and different kinds of rock interface is evaluated. Encouraged by the results, the data analysis led to obtaining a bedrock reflectivity variation map of the Dome C area. This map outlined a wide dispersion of wet/dry rock interfaces in the studied area, indicating the possibility of flowing water along both sides of the Concordia Trench. View full abstract»

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  • Analysis of the Sources of Variation in L-band Backscatter From Terrains With Permafrost

    Publication Year: 2012 , Page(s): 44 - 54
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1097 KB) |  | HTML iconHTML  

    Simultaneous field data collections and Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (PALSAR) full polarimetry observations were performed in Ulaanbaatar (Mongolia) and Alaska (USA). Permafrost is present at the Alaska test sites. Backscattering copolarization ( σco-pol0) values derived from the PALSAR data were compared with those calculated using the integrated equation method (IEM) model, a popular theoretical model describing surface scattering. PALSAR data taken in Ulaanbaatar matched the IEM model results to within a few decibels, whereas data taken in Alaska were 5 to 7 dB lower than those calculated using the IEM model. On the other hand, the σcross-pol0VH0) components estimated from the Oh model were well matched to the PALSAR data in both Ulaanbaatar and Alaska. Moisture levels of the sphagnum moss layer in Alaska were estimated to be about 10% while moisture levels of the underlying organic and mineral layers were 25% to 79%; the moisture values of the organic and mineral layers were factored into the IEM and Oh models. When surface moisture levels of 10% were assumed for Alaska ground conditions, the σco-pol0 values calculated using the IEM model and those derived from the PALSAR data were well matched. From these observations, we conclude that the sphagnum moss layer, which is a seasonally unfrozen layer that occurs above permafrost, plays an important role in radar backscattering processes in permafrost regions and is a main contributor to the σco-pol0 backscattering component; the underlying organic and mineral layers contribute mainly to the σcross-pol0 backscattering component. A two-layer model was applied to the data from a test site in Alaska; the model described the co- and cross-polarization backscatter (σ0- derived from PALSAR data with off-nadir angles of 21.5° and 34.3°. View full abstract»

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  • Joint Processing of Landsat and ALOS-PALSAR Data for Forest Mapping and Monitoring

    Publication Year: 2012 , Page(s): 55 - 67
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2099 KB) |  | HTML iconHTML  

    Recent technological advances in the field of radar remote sensing have allowed the deployment of an increasing number of new satellite sensors. These provide an important source of Earth observation data, which add to the currently existing optical data sets. In parallel, the development of robust methods for global forest monitoring and mapping is becoming increasingly important. As a consequence, there is significant interest in the development of global monitoring systems that are able to take advantage of the potential synergies and complementary nature of optical and radar data. This paper proposes an approach for the combined processing of Landsat and ALOS-PALSAR data for the purpose of forest mapping and monitoring. This is achieved by incorporating the PALSAR data into an existing operational Landsat-based processing system. Using a directed discriminant technique, a probability map of forest presence/absence is first generated from the PALSAR imagery. This SAR classification data is then combined with a time series of similar Landsat-based maps within a Bayesian multitemporal processing framework, leading to the production of a time series of joint radar-optical maps of forest extents. This approach is applied and evaluated over a pilot study area in northeastern Tasmania, Australia. Experimental outcomes of the proposed joint processing framework are provided, demonstrating its potential for the integration of different types of remote sensing data for forest monitoring purposes. View full abstract»

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  • Airborne Estimation of Boreal Forest LAI in Winter Conditions: A Test Using Summer and Winter Ground Truth

    Publication Year: 2012 , Page(s): 68 - 74
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (930 KB) |  | HTML iconHTML  

    A recently developed airborne method for estimation of leaf area index (LAI) in coniferous forests is used for comparing the LAI values in summer and winter conditions. The airborne measurements based on a wide-optic camera are carried out in winter when the forest floor is completely snow covered and thus acts as a light background for the image analysis. The photographs are taken automatically and stored on a laptop during the flights. The R2 value of the linear regression between the airborne and ground-based LAI measurements was 0.97 for all plots. Despite the unfavorable weather conditions, the average difference between the ground-based and airborne regression-based LAI estimates was 0.08, and in 90% of the cases, it was smaller than 0.13. The corresponding relative differences were 14% and 23%. The standard deviation of the ground-based LAI values measured within a plot was, on the average, of the same order. The winter-time values of the LAI of coniferous trees were estimated to be 24% smaller than the preceding summer-time values. View full abstract»

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  • Level Set Algorithm for Shape Reconstruction of Non-Overlapping Three-Dimensional Penetrable Targets

    Publication Year: 2012 , Page(s): 75 - 86
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1193 KB) |  | HTML iconHTML  

    This paper presents a 3-D shape reconstruction algorithm based on the level set method. Multiple dielectric and non-overlapping objects are considered. The level set algorithm is a gradient-type optimization approach that aims to minimize a cost function between measurements and computer-simulated data. The algorithm is capable of retrieving the shape and location of multiple targets made of two different and slightly lossy materials. An appropriate form of the deformation velocity based on the forward and adjoint fields is calculated. The method of moment surface integral equation is implemented to calculate the deformation velocity of the evolving objects. Two sets of Hamilton-Jacobi equations, associated with the two dielectric materials, are solved simultaneously to update the evolving objects. During the inversion scheme, the marching cubes method is employed to restore the surface meshes necessary for the forward solver. The algorithm is tested on corrupted synthetic data with signal-to-noise ratio of 10 dB. View full abstract»

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  • 3-D Vector Electromagnetic Scattering From Arbitrary Random Rough Surfaces Using Stabilized Extended Boundary Condition Method for Remote Sensing of Soil Moisture

    Publication Year: 2012 , Page(s): 87 - 103
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2236 KB) |  | HTML iconHTML  

    We develop the stabilized extended boundary condition method (SEBCM) based on the classical EBCM to solve the 3-D vector electromagnetic scattering problem from arbitrary random rough surfaces. Similar to the classical EBCM, we expand the fields in terms of Floquet modes and match the extended boundary conditions at test surfaces away from the actual rough surface to retrieve the surface currents and therefore the scattered fields. However, to solve long-standing stability problems of the classical EBCM, we introduce a z-coordinate transformation to restrict and control the test surface locations explicitly. We also introduce the concepts of moderated test surface locations and balanced k-charts for further stabilization and optimization of the solutions. The computational efficiency is optimized by judicious submatrix decomposition. The resulting bistatic scattering cross sections are validated by comparing with analytical and numerical solutions. Specifically, the solutions are compared with those from the small perturbation method and small-slope approximation within their validity region, and with those from the method of moments outside the validity domains of analytical solutions. It is shown that SEBCM gives accurate, numerically efficient, full-wave solutions over a large range of surface roughnesses and medium losses, which are far beyond the validity range of analytical methods. These properties are expected to make SEBCM a competitive forward solver for soil moisture retrieval from radar measurements. View full abstract»

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  • A New Maximum Simplex Volume Method Based on Householder Transformation for Endmember Extraction

    Publication Year: 2012 , Page(s): 104 - 118
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1210 KB) |  | HTML iconHTML  

    Endmember extraction is very important in hyperspectral image analysis. The accurate identification of endmembers enables target detection and classification and efficient spectral unmixing. Although a number of endmember extraction algorithms have been proposed, such as two state-of-the-art algorithms-vertex component analysis (VCA) and simplex growing algorithm (SGA)-it is still a rather challenging task. In this paper, a new maximum simplex volume method based on Householder transformation (HT), referred to as maximum volume by HT (MVHT), is presented for endmember extraction. The proposed algorithm provides consistent results with low computational complexity, which overcomes the disadvantage of the inconsistent result of VCA and the shortcoming of the high computational cost of SGA resulted from calculating the simplex volume. A comparative study and analysis are conducted among the three endmember extraction algorithms, VCA, SGA, and MVHT, on both simulated and real hyperspectral data. The obtained experimental results demonstrate that the proposed MVHT algorithm generally provides a competitive or even better performance over VCA and SGA. View full abstract»

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  • A Target Discrimination Methodology Utilizing Wavelet-Based and Morphological Feature Extraction With Metal Detector Array Data

    Publication Year: 2012 , Page(s): 119 - 129
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1881 KB) |  | HTML iconHTML  

    In this paper, a methodology for target discrimination utilizing wavelet-based and morphological feature extraction is proposed. The proposed methodology is implemented into a landmine classification decision system utilizing metal detector array data as input. The classification performances of a number of feature vectors composed of different combinations of feature elements are assessed. This is conducted using a Fuzzy ARTMAP neural network classifier and majority voting decision fusion. The classification classes trialled during processing are target type and burial depth, both combined and individually. The majority of the results achieve correct classification percentages of above 80% both prior to and after decision fusion, with generally higher accuracies and lower misclassification percentages achieved after decision fusion. View full abstract»

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  • A Genetic Fuzzy-Rule-Based Classifier for Land Cover Classification From Hyperspectral Imagery

    Publication Year: 2012 , Page(s): 130 - 148
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1947 KB) |  | HTML iconHTML  

    This paper proposes the use of a genetic fuzzy-rule-based classification system for land cover classification from hyperspectral images. The proposed classifier, namely, Feature Selective Linguistic Classifier, is constructed through a three-stage learning process. The first stage produces a preliminary fuzzy rule base in an iterative fashion. During this stage, a local feature selection scheme is employed, designed to guide the genetic evolution, through the evaluation of deterministic information about the relevance of each feature with respect to its classification ability. The structure of the model is then simplified in a subsequent postprocessing stage. The performance of the classifier is finally optimized through a genetic tuning stage. An extensive comparative analysis, using an Earth Observing-1 Hyperion satellite image, highlights the quality advantages of the proposed system, when compared with nonfuzzy classifiers, commonly employed in hyperspectral classification tasks. View full abstract»

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  • SVM-Based Fuzzy Decision Trees for Classification of High Spatial Resolution Remote Sensing Images

    Publication Year: 2012 , Page(s): 149 - 169
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1963 KB) |  | HTML iconHTML  

    A novel fuzzy decision tree is proposed in this paper (the FDT-support vector machine (SVM) classifier), where the node discriminations are implemented via binary SVMs. The tree structure is determined via a class grouping algorithm, which forms the groups of classes to be separated at each internal node, based on the degree of fuzzy confusion between the classes. In addition, effective feature selection is incorporated within the tree building process, selecting suitable feature subsets required for the node discriminations individually. FDT-SVM exhibits a number of attractive merits such as enhanced classification accuracy, interpretable hierarchy, and low model complexity. Furthermore, it provides hierarchical image segmentation and has reasonably low computational and data storage demands. Our approach is tested on two different tasks: natural forest classification using a QuickBird multispectral image and urban classification using hyperspectral data. Exhaustive experimental investigation demonstrates that FDT-SVM is favorably compared with six existing methods, including traditional multiclass SVMs and SVM-based binary hierarchical trees. Comparative analysis is carried out in terms of testing rates, architecture complexity, and computational times required for the operative phase. View full abstract»

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  • Laplacian Eigenmaps-Based Polarimetric Dimensionality Reduction for SAR Image Classification

    Publication Year: 2012 , Page(s): 170 - 179
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1888 KB) |  | HTML iconHTML  

    In this paper, we propose a novel scheme of polarimetric synthetic aperture radar (PolSAR) image classification. We apply Laplacian eigenmaps (LE), a nonlinear dimensionality reduction (NDR) technique, to a high-dimensional polarimetric feature representation for PolSAR land-cover classification. A wide variety of polarimetric signatures are chosen to construct a high-dimensional polarimetric manifold which can be mapped into the most compact low-dimensional structure by manifold-based dimensionality reduction techniques. This NDR technique is employed to obtain a low-dimensional intrinsic feature vector by the LE algorithm, which is beneficial to PolSAR land-cover classification owing to its local preserving property. The effectiveness of our PolSAR land-cover classification scheme with LE intrinsic feature vector is demonstrated with the RadarSat-2 C-band PolSAR data set and the 38th Research Institute of China Electronics Technology Group Corporation X-band PolInSAR data set. The performance of our method is measured by the separability in the feature space and the accuracy of classification. Comparisons on the feature space show that the LE intrinsic feature vector is more separable than different original feature vectors. Our LE intrinsic feature vector also improves the classification accuracy. View full abstract»

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  • Hurricane Wind Speed Measurements in Rainy Conditions Using the Airborne Hurricane Imaging Radiometer (HIRAD)

    Publication Year: 2012 , Page(s): 180 - 192
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2460 KB) |  | HTML iconHTML  

    This paper describes a realistic computer simulation of airborne hurricane surveillance using the recently developed microwave remote sensor, the hurricane imaging radiometer (HIRAD). An end-to-end simulation is described of HIRAD wind speed and rain rate measurements during two hurricanes while flying on a high-altitude aircraft. This simulation addresses the particular challenge which is accurate hurricane wind speed measurements in the presence of intense rain rates. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for future hurricane flights including the NASA GRIP hurricane field program that was conducted in summer of 2010. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with two different numerical hurricane models data are made. Special emphasis is provided on the wind speed measurement error, and statistical results are presented over a broad range of wind and rain conditions over the full measurement swath (earth incidence angle). View full abstract»

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  • Synthetic Signatures of Volcanic Ash Cloud Particles From X-Band Dual-Polarization Radar

    Publication Year: 2012 , Page(s): 193 - 211
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2440 KB) |  | HTML iconHTML  

    Weather radar retrieval, in terms of detection, estimation, and sensitivity, of volcanic ash plumes is dependent not only on the radar system specifications but also on the range and ash cloud distribution. The minimum detectable signal can be increased, for a given radar and ash plume scenario, by decreasing the observation range and increasing the operational frequency and also by exploiting possible polarimetric capabilities. For short-range observations in proximity of the volcano vent, a compact portable system with relatively low power transmitter may be evaluated as a suitable compromise between observational and technological requirements. This paper, starting from the results of a previous study and from the aforementioned issues, is aimed at quantitatively assessing the optimal choices for a portable X-band system with a dual-polarization capability for real-time ash cloud remote sensing. The physical-electromagnetic model of ash particle distributions is systematically reviewed and extended to include nonspherical particle shapes, vesicular composition, silicate content, and orientation phenomena. The radar backscattering response at X-band is simulated and analyzed in terms of self-consistent polarimetric signatures for ash classification purposes and correlation with ash concentration for quantitative retrieval aims. An X-band radar system sensitivity analysis to ash concentration, as a function of radar specifications, range, and ash category, is carried out in trying to assess the expected system performances and limitations. View full abstract»

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  • Ultrawideband Gated Step Frequency Ground-Penetrating Radar

    Publication Year: 2012 , Page(s): 212 - 220
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1377 KB) |  | HTML iconHTML  

    We describe a prototype ultrawideband radar. We show how the system was designed and how the hardware was developed for the radar prototype. Waveform generation, radar parameters, and signal processing for the stepped frequency waveform are discussed. The radar operates from 500 MHz to 3 GHz with a nominal resolution of 6 cm in air. The advantage of the stepped frequency approach over an impulse radar is better matching between the transmitted waveform and the receiver. We use range gating to improve the system dynamic range. The advantages are illustrated with laboratory measurements and field measurements from glacial ice and permafrost in Svalbard, showing penetration depths of 11 m. Antennas which do not require contact with the ground were developed and used in the experiments. View full abstract»

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  • A Novel Method for Imaging of Group Targets Moving in a Formation

    Publication Year: 2012 , Page(s): 221 - 231
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1206 KB) |  | HTML iconHTML  

    This paper proposes a novel method for high-resolution imaging of group targets moving in a formation with constant accelerated rectilinear motion. In this method, the first- and second-order phase terms are compensated simultaneously to obtain a “bulk” image of group targets. Then, regions of subtargets are determined by the segmentation method based on clustering number estimation and normalized cuts. Finally, refined compensation of the second- and third-order phase terms is carried out jointly to obtain a well-focused image of group targets, following the minimum local image entropy criterion. Simulation results have proved the validity of the proposed method. View full abstract»

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  • Multibaseline Polarimetric SAR Tomography of a Boreal Forest at P- and L-Bands

    Publication Year: 2012 , Page(s): 232 - 246
    Cited by:  Papers (26)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2519 KB) |  | HTML iconHTML  

    Longer wavelength synthetic aperture radars (SARs) are precious in the remote sensing of forested areas, being sensitive to contributions from the whole vegetation layer and from the ground below. The electromagnetic properties of such contributions are retrieved from multipolarimetric acquisitions, whereas their vertical structure is retrieved from multibaseline acquisitions through tomographic imaging. Combining baseline and polarization diversity provides most information, allowing the decomposition of the SAR signal into ground- and volume-only contributions. A formal treatment of this problem is provided with the algebraic synthesis technique, which extends the concepts of PolInSAR. The decomposition, however, is shown to be ambiguous in that different solutions are equally consistent with the data. The main goal of this paper is to discuss this topic in light of the experimental results from a tomographic and polarimetric analysis of the boreal forest within the Krycklan River catchment, Northern Sweden, investigated at P- and L-bands during the ESA campaign BioSAR 2008. Different solutions to the decomposition problem will be discussed by examining the corresponding vertical structures accessible through tomographic techniques. Elements are shown supporting the idea that ground-volume interactions play a nonnegligible role at P-band, and a solution is proposed to isolate contributions from direct volume backscattering. The retrieval of forest top height is discussed as well, leading to the conclusion that such parameter is robust against erroneous choices in the identification of volume-only contributions, thus corroborating the PolInSAR approach for the analysis of single-baseline data. View full abstract»

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  • Super-Resolution Power and Robustness of Compressive Sensing for Spectral Estimation With Application to Spaceborne Tomographic SAR

    Publication Year: 2012 , Page(s): 247 - 258
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (894 KB) |  | HTML iconHTML  

    We address the problem of resolving two closely spaced complex-valued points from N irregular Fourier do- main samples. Although this is a generic super-resolution (SR) problem, our target application is SAR tomography (TomoSAR), where typically the number of acquisitions is N = 10 - 100 and SNR = 0-10 dB. As the TomoSAR algorithm, we introduce "Scale-down by LI norm Minimization, Model selection, and Estimation Reconstruction" (SL1MMER), which is a spectral estimation algorithm based on compressive sensing, model order selection, and final maximum likelihood parameter estimation. We investigate the limits of SLIMMER concerning the following questions. How accurately can the positions of two closely spaced scatterers be estimated? What is the closest distance of two scat- terers such that they can be separated with a detection rate of 50% by assuming a uniformly distributed phase difference? How many acquisitions N are required for a robust estimation (i.e., for separating two scatterers spaced by one Rayleigh resolution unit with a probability of 90%)? For all of these questions, we provide numerical results, simulations, and analytical approxima- tions. Although we take TomoSAR as the preferred application, the SLIMMER algorithm and our results on SR are generally applicable to sparse spectral estimation, including SR SAR focus- ing of point-like objects. Our results are approximately applicable to nonlinear least-squares estimation, and hence, although it is derived experimentally, they can be considered as a fundamental bound for SR of spectral estimators. We show that SR factors are in the range of 1.5-25 for the aforementioned parameter ranges of N and SNR. View full abstract»

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  • Long-Term Consecutive DInSAR for Volume Change Estimation of Land Deformation

    Publication Year: 2012 , Page(s): 259 - 270
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1662 KB) |  | HTML iconHTML  

    In this paper, the long-term consecutive differential interferometric synthetic aperture radar (SAR) technique is used to measure the volume change during land deformation. This technique was used to investigate the subsidence of Bandung city, Indonesia, by assessing the data from two Japanese L-band spaceborne SARs (Japanese Earth Resources Satellite 1 SAR and Advanced Land Observation Satellite Phased Array type L-band Synthetic Aperture Radar) during the periods of 1993-1997 and 2007-2010. The results are confirmed using GPS observation data, ground survey data, local statistics, ground water level trend data, and the geological formation of the study area. The obtained results reveal a close correlation between the subsidence measurements and changes in the ground water level due to water pumping, population growth, industry growth, and urbanization of the study area. View full abstract»

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  • Repeat-Pass SAR Interferometry With Partially Coherent Targets

    Publication Year: 2012 , Page(s): 271 - 280
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2002 KB) |  | HTML iconHTML  

    By means of the permanent scatterer (PS) technique, repeated spaceborne synthetic aperture radar (SAR) images with relatively low resolution (about 25 m × 5 m for the European Remote Sensing (ERS) and Envisat satellites) can be used to estimate the displacement (1-mm precision) and 3-D location (1-m precision) of targets that show an unchanged electromagnetic signature. The main drawback of the PS technique is the limited spatial density of targets that behave coherently during the whole observation span (hundreds of PSs per square kilometer in urban site and up to few points in vegetated areas). In this paper, we describe a new approach for multitemporal analysis of SAR images that also allows extracting information from partially coherent targets. The basic idea is to loosen the restrictive conditions imposed by the PS technique. The results obtained in different test sites allowed to increase significantly the spatial coverage of the estimate of height and deformation trend, particularly in extraurban areas. View full abstract»

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