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Geoscience and Remote Sensing, IEEE Transactions on

Issue 2  Part 2 • Date Mar 1999

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Displaying Results 1 - 25 of 33
  • Experimental and model investigation on radar classification capability

    Page(s): 960 - 968
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    The capability of multifrequency polarimetric synthetic aperture radar (SAR) to discriminate among nine vegetation classes is shown using both experimental data and model simulations. The experimental data were collected by the multifrequency polarimetric AIRSAR at the Dutch Flevoland site and the Italian Montespertoli site. Simulations are carried out using an electromagnetic model, developed at Tor Vergata University, Rome, Italy, which computes microwave vegetation scattering. The classes have been defined on the basis of geometrical differences among vegetation species, leading to different polarimetric signatures. It is demonstrated that, for each class, there are some combinations of frequencies and polarizations producing a significant separability. On the basis of this background, a simple, hierarchical parallelepiped algorithm is proposed View full abstract»

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  • Detection and estimation of reflectivity gradients in the radar resolution volume using multiparameter radar measurements

    Page(s): 1122 - 1127
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    Multiparameter radar measurements of rainfall, namely, reflectivity factor ZH, differential reflectivity ZDR , and specific differential phase KDP lie in a constrained three-dimensional (3D) space and therefore measurement of Z H, ZDR, or, KDP should be consistent with the other two. This self-consistency relationship between ZH , ZDR, and KDP is valid when the radar resolution volume is homogeneous. When there are reflectivity gradients within the radar resolution cell, the self-consistency relation is perturbed. This perturbation can be utilized to detect the presence of gradients in the radar resolution volume. This paper presents a technique to detect and estimate reflectivity gradients in the resolution cell. The technique is evaluated using theoretical analysis as well as experimental data collected by the NCAR CP-2 radar. It is demonstrated that the presence of reflectivity gradients larger than a few decibels can be detected using the algorithm developed in this paper View full abstract»

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  • Large-scale simulations of electromagnetic and acoustic measurements using the pseudospectral time-domain (PSTD) algorithm

    Page(s): 917 - 926
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    Recently, a pseudospectral time-domain (PSTD) algorithm was developed to simulate electromagnetic wave propagation. This technique uses the fast Fourier transform (FFT) algorithm for the spatial derivatives and uses the perfectly matched layer (PML) to eliminate the wraparound effect due to the spatial periodicity introduced by FFT. In this work, the author further analyzes this new method and compares it with the finite-difference time-domain (FDTD) and multiresolution time-domain (MRTD) methods for accuracy and efficiency. The PSTD algorithm is then applied to simulate large-scale problems for subsurface electromagnetic and acoustic measurements. For many problems encountered, since the spatial derivatives are obtained by the PSTD algorithm for continuous field components, this algorithm has a high order of accuracy in the spatial derivatives, and thus requires much fewer unknowns than the FDTD and MRTD methods. Numerical results confirm the efficacy of the PSTD method View full abstract»

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  • Meteorological structures shape description and tracking by means of BI-RME matching

    Page(s): 1151 - 1161
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    Images from meteorological satellites or weather radars must be often interpreted at a higher level than simple pixel classification, and shape analysis with reliable and fast methods may be necessary. For instance, it is useful to analyze the temporal evolution of a rain event by means of a reliable tracking of the rain patterns at different scales. However, this task of tracking objects continuously changing their shapes is challenging. In this paper, the author shows how the application of a recently introduced numerical technique, called boundary integral-resonant mode expansion (BI-RME), to weather radar and meteorological satellite data could be used to achieve more information about the evolution in time of rain patterns or other meteorological structures of interest. In order to demonstrate the efficiency and robustness of the approach, several examples of image processing are considered. Applications to both operational tracking of clouds to produce wind fields and hurricane tracking are presented View full abstract»

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  • A field goniometer system (FIGOS) for acquisition of hyperspectral BRDF data

    Page(s): 978 - 986
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    A new field goniometer system (FIGOS) is introduced that allows in situ measurements of hyperspectral bidirectional reflectance data under natural illumination conditions. Hyperspectral bidirectional reflectance distribution function (BRDF) data sets taken with FIGOS nominally cover the spectral range between 300 and 2450 nm in 704 bands. Typical targets are small-growing, dense, and homogeneous vegetation canopies, man-made surfaces, and soils. Field BRDF data of a perennial ryegrass surface reveal a strong spectral variability. In the blue and red chlorophyll absorption bands, BRDF effects are strong. Less-pronounced bidirectional reflectance effects are observed in the green and in most of the near-infrared range there surface reflectance is high. An anisotropy index (ANIX), defined as the ratio between the maximum and minimum bidirectional reflectance over the hemisphere, is introduced as a surrogate measurement for the extent of spectral BRDF effects. The ANIX data of the ryegrass surface show a very high correlation with nadir reflectance due to multiple scattering effects. Since canopy geometry, multiple scattering, and BRDF effects are related, these findings may help to derive canopy architecture parameters, such as leaf area index (LAI) or leaf angle distribution (LAD) from remotely sensed hyperspectral BRDF data. Furthermore, they show that normalized difference vegetation index (NDVI) data are strongly biased by the spectral variability of BRDF effects View full abstract»

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  • Full-range sea surface spectrum in nonfully developed state for scattering calculations

    Page(s): 1038 - 1051
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    A new form for the spectrum of the ocean surface vertical displacements is derived for the case of nonfully developed states. The gravity range is expressed as a function of the fetch x and the significant slope ∮ as well. The capillary-gravity range is assumed dependent on the wind friction velocity only. Recent wavenumber spectrum measurements in this spectral domain and ocean conditions are analyzed. Toba's spectral shape is shown to represent correctly these experimental data when updated with an equivalent amplitude factor. An expression for this factor is proposed. It is weakly wind friction velocity dependent, as observed by Mitsuyasu in the late 1970s. The proposed spectrum is then combined with a boundary perturbation model for electromagnetic scattering computations. Empirical scattering models and radar data collocated with assumed ground-truth data are used for comparison. This is shown to give consistent results for both C- and Ku-bands as well as large ranges of wind speeds and incidence angles. Comparisons of backscattering coefficients computed using other sea spectra from the literature are presented. The significant slope is found to be an important factor for scattering at low incidence angles. The proposed spectrum thus constitutes a useful basis for physically based inversion algorithms View full abstract»

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  • Supervised fuzzy analysis of single- and multichannel SAR data

    Page(s): 1023 - 1037
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    The paper proposes a new learning fuzzy classification for single and multichannel synthetic aperture radar (SAR) data. It consists of the fusion of a supervised learning fuzzy distribution estimator and an unsupervised learning fuzzy vector quantizer. The adaptive algorithm accommodates varying requirements and delivers classification results in near real time. In addition to the classification, the user gets the reliability of the classification. This knowledge can be used to fuse several sensor channels efficiently. Automatically, a rule base is developed to deliver the required information with the highest possible reliability. In the author's example, the channels of a full polarimetric SAR are used. However, the algorithm can be extended also to optic and infrared channels. The proposed fuzzy classification system forms one module of an adaptive remote-sensing system. A conceptual design of this system is given. System control relies on an expert knowledge base and allows automatic configuration of the system to the considered remote-sensing application. This will lead to an increased usefulness of remotely sensed data View full abstract»

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  • Smoothing effect of wavelet-based speckle filtering: the Haar basis case

    Page(s): 1168 - 1172
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    The smoothing effect of the wavelet-based speckle filtering that the authors proposed is investigated. The filtering reduces the amplitude of wavelet coefficients, and a theoretical investigation with the Haar basis derives a functional relation between the ENL and two parameters: the wavelet level and the degree of the amplitude reduction View full abstract»

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  • A technique for the selection of kernel-function parameters in RBF neural networks for classification of remote-sensing images

    Page(s): 1179 - 1184
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    A supervised technique for training radial basis function (RBF) neural network classifiers is proposed. Such a technique, unlike traditional ones, considers the class memberships of training samples to select the centers and widths of the kernel functions associated with the hidden neurons of an RBF network. The result is twofold: a significant reduction in the overall classification error made by the classifier and a more stable behavior of the classification error versus variations in both the number of hidden units and the initial parameters of the training process View full abstract»

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  • Segmentation of satellite imagery of natural scenes using data mining

    Page(s): 1086 - 1099
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    The authors describe a segmentation technique that integrates traditional image processing algorithms with techniques adapted from knowledge discovery in databases (KDD) and data mining to analyze and segment unstructured satellite images of natural scenes. They have divided their segmentation task into three major steps. First, an initial segmentation is achieved using dynamic local thresholding, producing a set of regions. Then, spectral, spatial, and textural features for each region are generated from the thresholded image. Finally, given these features as attributes, an unsupervised machine learning methodology called conceptual clustering is used to cluster the regions found in the image into N classes-thus, determining the number of classes in the image automatically. They have applied the technique successfully to ERS-1 synthetic aperture radar (SAR). Landsat thematic mapper (TM), and NOAA advanced very high resolution radiometer (AVHRR) data of natural scenes View full abstract»

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  • Millimeter wave scattering from spatial and planar bullet rosettes

    Page(s): 1138 - 1150
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    The electromagnetic scattering characteristics of several bullet-rosette ice crystal forms are computationally evaluated at 35-, 94-, and 220-GHz frequencies and compared with those of stellar crystals, hexagonal plates, and columns. One of the bullet rosettes is a planar crystal with four branches, the other two are spatial rosettes with six and eight branches. Two orientation models are used, one represents highly oriented crystals for which side and vertical incidence directions are considered, and the other represents: randomly oriented crystals (the incidence direction does not affect this case). It is observed that the linear depolarization ratio (LDR), as well as the copolarized correlation coefficient (ρ), can be used to differentiate columns from planar (including plates and stellar crystals) and spatial crystals based on their values at vertical incidence or their trends as a function of the elevation angle. For the random orientation case, LDR and ρ can differentiate columns from spatial crystals (except for sizes larger than 1.2 mm at 220 GHz) but not from planar crystals. Furthermore, the elevation angle dependence of LDR and ZDR (differential reflectivity) has the potential for differentiating columnar, planar, and spatial crystals for sizes from a few tenths of a millimeter to 2 mm at 220 GHz, and from about 1 to 2 mm at 94 GHz. At 35 GHz, spatial crystals smaller than 2-mm resemble spherical particles in terms of their ZDR and LDR signatures. The results for high-density (0.9 g cm-3) and low-density (representing hollow crystals) crystal models show significant differences in the values of LDR, ZDR, ρ, and the backscattering cross sections View full abstract»

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  • Spatial characterization of remotely sensed soil moisture data using self organizing feature maps

    Page(s): 1162 - 1165
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    Compact characterization of soil moisture at a given scale using self-organizing feature maps is presented. The authors find that as few as 49 neurons capture the spatial structure of remotely sensed soil moisture images from the southern Great Plains. Average latent heat flux computed from the original image of 21204 pixels and from 49 neurons are comparable View full abstract»

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  • An exact analytic representation of a regular or interferometric SAR image of ocean swell

    Page(s): 1015 - 1022
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    The problem of obtaining quantitative data on spatial ocean wave spectra from the images of the ocean surface by either regular SAR or along-track interferometric SAR (INSAR) is studied. The dominant mechanism which allows imaging of ocean waves by SAR/INSAR is the so-called velocity bunching. This mechanism is essentially nonlinear. The theoretical analysis of SAR/INSAR imagery of the ocean surface due to velocity bunching is performed, and nonlinear solutions of the SAR/INSAR images of monochromatic waves and of the spectra of these images are obtained. Analytic expressions are presented which allow for the accurate simulation both SAR and INSAR images of waves with arbitrary lengths, heights and propagation directions. It is demonstrated that a monochromatic wave expands in the SAR/INSAR images into an infinite number of harmonics. In addition to the nonlinearity parameters of SAR which is related to the velocity bunching mechanism, it is shown that for complex INSAR, the degree of nonlinearity depends also on separation time between the two antennas. The results of the present study indicate that in addition to the prevailing practice to consider the phase component of the INSAR image, an analysis of the imaginary part of the complex INSAR map of the ocean surface may provide some supplementary information, beneficial, in particular, for rough sea View full abstract»

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  • Compression of synthetic aperture radar video phase history data using trellis-coded quantization techniques

    Page(s): 1080 - 1085
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    Synthetic aperture radar (SAR) is a remote-sensing technology that uses the motion of the radar transmitter to synthesize an antenna aperture much larger than the actual antenna aperture to yield high-spatial resolution radar images. In this paper, trellis-coded quantization (TCQ) techniques are shown to provide a high-performance, low bit-error sensitivity solution to the problem of downlink data rate reduction for SAR systems. Trellis-coded vector quantization (TCVQ) and universal TCQ coding systems are discussed, implemented, and compared with other data compression schemes [block adaptive quantization (BAQ) and VQ] that can be used to compress SAR phase history data View full abstract»

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  • Polarimetric radar covariance matrix algorithms and applications to meteorological radar data

    Page(s): 1128 - 1137
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    Characterization of backscatter from complex or nonstationary targets, which is partially polarized, is considered first. The possibility of constructing the covariance matrix from coherency matrix measurements is investigated, and examples using practical polarization diversity radar data from meteorological targets are given. From examining the practical data, it is found that, for this type of target, reflection symmetry exists, thus giving indication about the physical properties of the medium. In particular, this shows that models, in which symmetrical distributions of both canting angle and shapes are assumed, are sufficient. Using the obtained matrix, propagation effects are examined under that assumption. Since the theory developed is amenable to implementation using a unique microwave circuit, results should have direct practical applications View full abstract»

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  • Maximizing land cover classification accuracies produced by decision trees at continental to global scales

    Page(s): 969 - 977
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    Classification of land cover from remotely sensed data at continental to global scales requires sophisticated algorithms and feature selection techniques to optimize classifier performance. The authors examine methods to maximize classification accuracies using decision trees to map land cover from multitemporal AVHRR imagery at continental and global scales. As part of their analysis they test the utility of “boosting”, a new technique developed to increase classification accuracy by forcing the learning (classification) algorithm to concentrate on those training observations that are most difficult to classify. Their results show that boosting consistently reduces misclassification rates by 20-50% depending on the data set in question, and that most of the benefit gained by boosting is achieved after seven boosting iterations. They also assess the utility of including phenological metrics and geographic position as additional features to the classification algorithm. They find that using derived phenological metrics produces little improvement in classification accuracy relative to using an annual time series of NDVI data, but that geographic position provides substantial power for predicting land cover types at continental and global scales. However, in order to avoid generating spurious classification accuracies using geographic position, training data must be distributed evenly in geographic space View full abstract»

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  • Effects of snow crystal shape on the scattering of passive microwave radiation

    Page(s): 1165 - 1168
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    A discrete dipole scattering model is used to measure the passive microwave radiation scattered by snow particles having different shapes and sizes. The model results demonstrate that the shape of the snow crystal is insignificant in scattering microwave energy in the 37-GHz region of the spectrum View full abstract»

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  • Partially supervised classification using weighted unsupervised clustering

    Page(s): 1073 - 1079
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    This paper addresses a classification problem in which class definition through training samples or otherwise is provided a priori only for a particular class of interest. Considerable time and effort may be required to label samples necessary for defining all the classes existent in a given data set by collecting ground truth or by other means. Thus, this problem is very important in practice, because one is often interested in identifying samples belonging to only one or a small number of classes. The problem is considered as an unsupervised clustering problem with initially one known cluster. The definition and statistics of the other classes are automatically developed through a weighted unsupervised clustering procedure that keeps the known cluster from losing its identity as the “class of interest”. Once all the classes are developed, a conventional supervised classifier such as the maximum likelihood classifier is used in the classification. Experimental results with both simulated and real data verify the effectiveness of the proposed method View full abstract»

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  • Free and bound capillary waves as microwave scatterers: laboratory studies

    Page(s): 1052 - 1065
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    Laboratory measurements of the fine space-time structure of short gravity-capillary waves, as well as Ku-band scattering at grazing and moderate incidence from wind waves in the large Delft Hydraulics Laboratory wind-wave channel are presented. This study was stimulated by the need to verify the processes that significantly contribute to scattering at grazing and moderate incidence. A scanning laser slope gauge was used for measuring capillary waves from 2-mm to 2-cm wavelengths and frequencies ranging up to 100 Hz. A dual-polarized (vertical, VV, and horizontal, HH), coherent, pulsed Ku-band scatterometer with good temporal resolution (3 ns) was used to obtain simultaneous Doppler spectra and the absolute cross section of scattered signals for grazing angles 6 and 25° and for winds in the range 2.5-12.5 m/s. Two-dimensional (2D) filtering and bispectral analyses were used to separate and study the influence of free and bound surface waves. The results of this study demonstrate that the frequency-wavenumber spectra of capillary waves consist of two parts. The first corresponds to free capillary waves, which satisfy the dispersion relationship. The second corresponds to bound parasitic capillary waves, which are located near the crests of steep wind waves. The phase velocity of these capillary waves is approximately equal to the phase velocity of the steep waves. Measurements of the Doppler frequency of the scattered signals show that the Doppler spectra also have a bimodal structure. While the first low-frequency part of the spectrum corresponds to the Bragg scattering from the free capillary waves, the highfrequency part is associated with Bragg scattering from the bound capillary waves on the crests of the steep waves. This type of scattering is predominant for the upwind direction of illumination (especially for HH-polarization) View full abstract»

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  • An analytical hybrid GORT model for bidirectional reflectance over discontinuous plant canopies

    Page(s): 987 - 999
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    The geometric optical (GO) bidirectional reflectance model, combined with a new component spectral signature submodel, can be used to estimate the bidirectional reflectance distribution function (BRDF) of discontinuous canopies. This approach retains the GO approach of incorporating the effect of shadows cast by crowns on the background. The newly developed submodel uses an analytical approximation of the radiative transfer (RT) within the plant canopies to model the spectral properties of each scene component. A multiple scale-hotspot function that incorporates effects for smaller canopy objects like branches, stems and leaves was also well modeled. Comparison of model results with field measurements (ASAS, POLDER and PARABOLA) over an old black spruce forest in central Canada demonstrated that the model ran predict the basic features of the BRDF, i.e., bowl shape and the hotspot. The benefits of the model presented are simplicity, improved treatment of multiple scattering and a new method of estimating the component signatures View full abstract»

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  • Multitemporal behavior of L- and C-band SAR observations of boreal forests

    Page(s): 927 - 937
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    An analysis of L- and C-band boreal forest backscattering properties with respect to various temporally changing parameters is presented. The seasonal and weather dependent parameters considered include the depth of soil frost, topsoil moisture, snow water equivalent, air temperature and precipitation. The effect of these parameters on σ° are studied for various stem volume (biomass) classes by comparing the results against a cloud model-based semi-empirical modeling approach. Semi-empirical modeling is also used for a forest biomass retrieval experiment. The SAR data set includes 4 JERS-1 (L-band, HH-polarization) and 19 ERS-1 (C-band, VV-polarization) images for a test area in southern Finland. Additionally, a set of 2 JERS-1 and 3 ERS-1 images for another test area in northern Finland is employed. The results show that radar response to forest biomass is more sensitive to changes in temporally varying parameters at C-band than at L-band. The semi-empirical modeling approach describes well the behavior of σ° at both frequency bands when large forest areas are considered. Moreover, the modeling approach appears to be applicable for different conifer-dominated boreal forest types. Since the modeling approach explains satisfactorily the average backscattering behavior, the results in biomass retrieval show high accuracies (25-30% relative RMSE) when areas under investigation are large enough, i.e. about 20 ha View full abstract»

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  • Computer animation of remote sensing-based time series data sets

    Page(s): 1100 - 1106
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    Visualization has always played a major role in the exploitation of remote sensing data sets as well as in the confirmation of scientific hypotheses. With the new techniques available for two-dimensional (2D) and three-dimensional (3D) computer animation, the synthesis of different information layers as well as high quality visualizations for the presentation of research tasks and results are becoming increasingly important and popular. The German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR) is operationally generating remote-sensing-based time series data sets. This data can be used to generate long term, high quality computer animations for analyzing and presenting the information contained in Earth observation data. Due to clouds or to system specification, data gaps occur in satellite derived time series, which preclude the generation of highest quality computer animations. For this reason different interpolation techniques have been developed primarily for atmospheric research, and they now prove to be a valuable tool for interpolation of a wide range of remote sensing data sets to be used for computer animations View full abstract»

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  • A nonuniform cylindrical FDTD algorithm with improved PML and quasi-PML absorbing boundary conditions

    Page(s): 1066 - 1072
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    Many applications require time-domain solutions of Maxwell's equations in inhomogeneous, conductive media involving cylindrical geometries with both electrically small and large structures. The conventional finite-difference time-domain (FDTD) method with a uniform Cartesian grid will result in a staircasing error, and wastes many unnecessary cells in regions with large structures in order to accommodate the accurate geometrical representation in regions with small structures. In this work, an explicit FDTD method with a nonuniform cylindrical grid is developed for time-domain Maxwell's equations. A refined lattice is used near sharp edges and within fine geometrical details, while a larger lattice is used outside these regions. This provides an efficient use of limited computer memory and computation time. The authors use two absorbing boundary conditions to a nonuniform cylindrical grid: (1) the straightforward extension of Berenger's perfectly matched layer (PML) which is no longer perfectly matched for cylindrical interfaces, thus the name quasi-PML, (QPML); (2) the improved true PML based on complex coordinates. In practice, both PML schemes can provide a satisfactory absorbing boundary condition. Numerical results are shown to compare the two absorbing boundary conditions (ABCs) and to demonstrate the effectiveness of the nonuniform grid and the absorbing boundary conditions View full abstract»

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  • Unsupervised multispectral image classification using MRF models and VQ method

    Page(s): 1173 - 1176
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    An unsupervised contextual classification method using Markov random field (MRF) models and the vector quantization (VQ) is proposed. The VQ algorithm classifies the observed data preliminarily, and the contextual reclassification and the iterative classification follow. The proposed method was applied to a Landsat image to evaluate the classification accuracy View full abstract»

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  • Detection of shallowly buried objects using impulse radar

    Page(s): 875 - 886
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    The impulse radar has shown promising results for detecting buried objects, even nonmetallic ones. One problem with ground penetrating radars is the strong backscattered signal from the ground surface. If the object is buried deeply below the surface this is no problem since the backscattered signal from the surface will arrive earlier than the target signal and we only have to gate the time signal. When the objects are shallowly buried gating is not possible since the backscattered signal from target and the surface will arrive almost simultaneously. The detection problem is thus to a large extent the problem of separating the target signal from the ground backscatter. In the present paper, the authors introduce a signal model that exploits the different properties of the backscattered signals from target and ground surface. Different algorithms for separation of the different components in the signal model are presented together with a performance measure to evaluate the algorithms. After the signal components have been separated, both classical detection methods and some more ad hoc methods are applied and evaluated 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