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Geoscience and Remote Sensing, IEEE Transactions on

Issue 11 • Date Nov. 2007

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Displaying Results 1 - 25 of 27
  • [Front cover]

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

    Page(s): C2
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  • Table of contents

    Page(s): 3597 - 3598
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  • Polarimetric and Interferometric SAR Image Partition Into Statistically Homogeneous Regions Based on the Minimization of the Stochastic Complexity

    Page(s): 3599 - 3609
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1370 KB) |  | HTML iconHTML  

    In this paper, we show that polarimetric and interferometric SAR (PolInSAR) images can be efficiently partitioned into homogeneous regions with a statistical technique based on minimization of a parameter-free criterion. This technique consists of finding a polygonal partition of the image that minimizes the stochastic complexity, assuming that the image is made of a tessellation of statistically homogeneous regions. The obtained results demonstrate that a global partition in statistically homogeneous regions of PolInSAR images can provide better results than a partition based on a single characteristic such as polarimetry or interferometry only. View full abstract»

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  • Sea-Ice Deformation State From Synthetic Aperture Radar Imagery—Part I: Comparison of C- and L-Band and Different Polarization

    Page(s): 3610 - 3622
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1416 KB) |  | HTML iconHTML  

    In this paper, we present a quantitative comparison of L- and C-band airborne synthetic aperture radar imagery acquired at like- and cross-polarizations over deformed sea ice under winter conditions. The parameters characterizing the deformation state of the ice are determined at both radar bands and at different polarizations. The separation of deformed and level ice is based on a target detection technique. The threshold is set such that image pixels with intensities equal to or larger than the highest 2% of the level-ice intensity distribution are classified as deformed ice, independent of the radar configuration and ice conditions. Optical imagery of sufficient quality for comparison is available only in a very few cases. To characterize the deformation state, the areal fraction of deformation features and the average distance between these features are evaluated. The values obtained for both parameters are very sensitive to the radar frequency. Aeral fractions are larger, and average distances are smaller at L-band than at C-band because of the much higher intensity contrast between the deformed and level ice at L-band. The differences between polarizations at one radar band are smaller but not always negligible. In comparison to optical images, it was observed that deformed-ice areas can be distinguished from level ice over their whole length and extension at L-band, whereas at C-band, often, only prominent parts are visible. View full abstract»

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  • Initial Images of the Synthetic Aperture Radiometer 2D-STAR

    Page(s): 3623 - 3632
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1277 KB) |  | HTML iconHTML  

    Initial results are presented for the new synthetic aperture radiometer, 2D-STAR, which is a dual-polarized L-band radiometer that employs aperture synthesis in two dimensions. This airborne instrument is the natural evolution of the Electronically Scanned Thinned Array Radiometer, which employs aperture synthesis only in the across-track dimension, and represents a further step in the development of aperture synthesis for remote sensing applications. 2D-STAR was successfully tested in June 2003 and, then, participated in the SMEX03 and SMEX04 soil moisture experiments. A description of the instrument and initial results in the form of first images and a preliminary comparison with changes in soil moisture during SMEX03 are presented here. View full abstract»

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  • Focusing Parallel Bistatic SAR Data Using the Analytic Transfer Function in the Wavenumber Domain

    Page(s): 3633 - 3645
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (471 KB) |  | HTML iconHTML  

    In recent years, bistatic synthetic aperture radar (BiSAR) has attracted the attention of many radar researchers. It is well known that the slant range history of BiSAR is the sum of two square-rooted terms, which correspond to the transmitting and receiving slant ranges, respectively. For a point target in the SAR scene, it is quite difficult, if not impossible, to obtain an analytic formula to describe the target echo data in the 2-D frequency domain without any approximation by using the conventional stationary phase method, which makes it very difficult to develop fast-focusing algorithms for BiSAR. In this paper, based on the concept of an instantaneous Doppler wavenumber and by defining a new variable called half quasi-bistatic angle, an analytic formula of the point target response in the spectral domain is developed for BiSAR with parallel trajectory (referred to as parallel BiSAR for simplicity). Relying on a first-order Taylor expansion of the above formula with respect to the parameter called the sum of closest distances on the swath center, a bistatic range migration algorithm is proposed for any azimuth-shift-invariant BiSAR data processing. Simulation results have confirmed the effectiveness of the proposed novel approach. View full abstract»

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  • Power Optimization for Polarimetric Bistatic Random Mechanisms

    Page(s): 3646 - 3660
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (948 KB) |  | HTML iconHTML  

    The aim of this paper is to investigate the optimal polarizations (i.e., emitted and received polarizations for which the received power is maximum or minimum) in the general case of random mechanisms observed by a bistatic full-polarimetric radar. We are particularly interested in the methods leading to analytical solution as far as this is possible. It is the reason why the Kennaugh matrix is taken as the starting point of the optimizations. The optimal polarizations corresponding to the monostatic and bistatic deterministic cases are found again as particular cases. View full abstract»

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  • Localization of Interfaces Embedded in a Half-Space by a Linear Inverse Scattering Algorithm

    Page(s): 3661 - 3671
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (414 KB) |  | HTML iconHTML  

    The localization of a slab embedded within a homogeneous half-space is dealt with. A multifrequency plane wave incidence is assumed, and the locations of the slab interfaces are represented as the support of "distributions." A simplified model of the electromagnetic scattering is adopted, and the problem is cast as the inversion of a linear integral relationship. This inversion is regularized by means of the singular value decomposition tool. Numerical tests allow to analyze the reconstruction capabilities of the reconstruction algorithm, i.e., the maximum depth of investigation and the resolution limits, which depend on the properties of the investigated medium and on the exploited work frequency band. Finally, experimental results are shown. View full abstract»

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  • Time and Frequency Blanking for Radio-Frequency Interference Mitigation in Microwave Radiometry

    Page(s): 3672 - 3679
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    Radio-frequency interference (RFI) is a major limiting factor in passive microwave remote sensing and radio astronomy. A digitally based radiometer system has been developed to improve RFI mitigation through the use of high temporal and spectral resolution. The system includes a pulse-blanking algorithm that is capable of removing pulsed time-domain sources in real time. Cross-frequency mitigation is also possible in postprocessing through the use of the system's high spectral resolution. Several experiments have been conducted at L- and C-bands in recent years. Datasets from two particular campaigns are analyzed in this paper: ground-based observations at L-band in Canton, Michigan that emphasize pulse blanking and an airborne campaign at C-band over Texas and the Gulf of Mexico that emphasizes cross-frequency mitigation. Results and analyses are presented to quantify the RFI mitigation performance achieved. View full abstract»

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  • Retrieving Liquid Wat0er Path and Precipitable Water Vapor From the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

    Page(s): 3680 - 3690
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (960 KB) |  | HTML iconHTML  

    Ground-based two-channel microwave radiometers (MWRs) have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) - two geophysical parameters critical for many areas of atmospheric research - are retrieved. An algorithm that incorporates output from two advanced retrieval techniques, namely, a physical-iterative approach and a computationally efficient statistical method, has been developed to retrieve these parameters. The forward model used in both methods is the monochromatic radiative transfer model MonoRTM. An important component of this MWR RETrieval (MWRRET) algorithm is the determination of small (< 1 K) offsets that are subtracted from the observed brightness temperatures before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm significantly provides more accurate retrievals than the original ARM statistical retrieval, which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm significantly provides better retrievals of PWV and LWP from the ARM two-channel MWRs compared to the original ARM product. View full abstract»

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  • SMOS Calibration Subsystem

    Page(s): 3691 - 3700
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    Interferometric radiometry is a novel concept in remote sensing that is also presenting particular challenges for calibration methods. In this paper, we describe the calibration subsystem (CAS) developed for the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) interferometer of the Soil Moisture and Ocean Salinity (SMOS) satellite. CAS is important for the overall performance of the payload as it calibrates out the differences between the multiple receivers of MIRAS. SMOS is in the final phase of development and is due to launch in 2008. View full abstract»

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  • Evaluation of a New Airborne Microwave Remote Sensing Radiometer by Measuring the Salinity Gradients Across the Shelf of the Great Barrier Reef Lagoon

    Page(s): 3701 - 3709
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (314 KB) |  | HTML iconHTML  

    Over the last ten years, some operational airborne remote sensing systems have become available for mapping surface salinity over large areas in near real time. A new dual-polarized Polarimetric L-band Multibeam Radiometer (PLMR) has been developed to improve accuracy and precision when compared with previous instrument generations. This paper reports on the first field evaluation of the performance of the PLMR by measuring salinity gradients in the central Great Barrier Reef. Before calibration, the raw salinity values of the PLMR and conductivity-temperature-depth (CTD) differed by 3-6 psu. The calibration, which uses in situ salinity data to remove long-term drifts in the PLMR as well as environmental effects such as surface roughness and radiation from the sky and atmosphere, was carried out by equating the means of the PLMR and CTD salinity data over a subsection of the transect, after which 85% of the salinity values between the PLMR and CTD are within 0.1 psu along the complete transect. From offshore to inshore across the shelf, the PLMR shows an average cross-shelf salinity increase of about 0.4 psu and a decrease of 2 psu over the inshore 20 km at -19deg S (around Townsville) and -18deg S (around Lucinda), respectively. The average cross-shelf salinity increase was 0.3 psu for the offshore 100 km over all transects. These results are consistent with the in situ CTD results. This survey shows that PLMR provided an effective method of rapidly measuring the surface salinity in near real time when a calibration could be made. View full abstract»

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  • DEM Control in Arctic Alaska With ICESat Laser Altimetry

    Page(s): 3710 - 3720
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1351 KB) |  | HTML iconHTML  

    Use of Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry is demonstrated for control of a digital elevation model (DEM) that is synthesized from repeat-pass ERS-1 and 2 synthetic aperture radar (SAR) imagery using interferomet-ric SAR (InSAR). Our study area is 15 650 km2 of the Barrow, AK coastal plain adjacent to the Arctic Ocean; a vast expanse of tundra, lakes, and arctic wetlands of such low relief as to be nearly devoid of terrain features. The accuracy of the ICESat-derived elevation measurements is assessed by comparison with differential global positioning system (DGPS) data acquired along ICESat ground tracks. The ICESat-derived elevations have a mean accuracy, relative to the DGPS elevations, of -0.01 plusmn 0.18 m. ICESat-derived elevations on the Arctic coastal plain provide an excellent source for DEM control. We employ the ICESat-derived ground control points (GCPs) in two distinct InSAR processing steps: 1) selected points are used to perform baseline refinements, which improves the ERS-1 and 2 interfero-grams and 2) the ICESat-derived GCP position data (latitude, longitude, elevation) are then used as control in mosaicking multiple InSAR-derived DEMs. The resulting ICESat-controlled DEM has a mean accuracy of -1.11plusmn 6.3 m relative to an independent standard, which is a commercial airborne InSAR-derived DEM having 0.5 m rms accuracy. This easily meets DTED-2 standards and suggests that DEMs derived using only ICESat altimetry for ground control would meet similar standards in other regions of low relief. View full abstract»

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  • Modeling Directional Brightness Temperature of the Winter Wheat Canopy at the Ear Stage

    Page(s): 3721 - 3739
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    The ear is the top layer of mature wheat and has very different geometric and thermal characteristics from that of leaves. Compared to the directional brightness temperature (DBT) of wheat canopy without ears, the DBT at the ear stage has specific features, and the ear effects could not be explained by previous models. This paper proposes a hybrid geometric optical and radiative transfer model to reveal the combined influences of the geometric structure of ears and leaf; the temperature distribution of ear, leaf, and soil; and the Sun-target-sensor geometry on the canopy DBT. The soil, leaf, and ear layers are taken into account in the model so it is named as the Soil Leaf Ear Combined (SLEC) DBT model. We compare the model prediction with the field measurement data. The results show that the new SLEC DBT model can simulate the DBT of wheat at the ear stage with an accuracy of 0.78 K. View full abstract»

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  • A Novel Clutter Suppression Algorithm for Landmine Detection With GPR

    Page(s): 3740 - 3751
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (891 KB) |  | HTML iconHTML  

    In this paper, we propose a new algorithm for the enhancement of plastic-cased antipersonnel mine detection using a video-impulse ground-penetrating radar (GPR). The algorithm is implemented as a nonlinear signal processor, which searches for the presence of a reference waveform in a 1D GPR echo return. The reference waveform represents a class of targets within a certain environment. The processor marks the presence of all responses similar to the reference waveform with a sharp mono-cycle. Simultaneously, responses with different waveforms, which presumably correspond to clutter, are suppressed. The reference waveform and other algorithm parameters are determined from training data sets acquired in a controlled environment. After training, the algorithm can be successfully applied at sites where soil, targets, and measurement scenarios are similar but not identical to those of the training site. The processor is integrated into an automated data processing and mine detection scheme as an additional clutter suppression step. The scheme consists of clutter suppression, synthetic aperture radar focusing, construction of a confidence map, and automated detection in it. The suggested algorithm is tested on experimental data, and its performance is compared against schemes where clutter suppression is organized by means of background removal and the cross correlation with a reference wavelet. The performance comparison is done in terms of receiver operating characteristic curves. It has been found that the suggested algorithm reduces the false alarm rate in about two and a half times in comparison to the cross-correlation-based clutter suppression. View full abstract»

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  • Surface Nuclear Magnetic Resonance Tomography

    Page(s): 3752 - 3759
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    Groundwater is the principal source of freshwater in many regions worldwide. Expensive drilling, borehole logging, and hydrological testing are the standard techniques employed in groundwater exploration and management. It would be logistically beneficial and cost-effective to have surface-based nonintrusive methods to locate and quantify groundwater occurrences and to estimate other key hydrological parameters. Surface nuclear magnetic resonance (SNMR) techniques, which are based on the spin magnetic-moment precession of protons in the hydrogen atoms of water, offer the possibility of achieving these goals. Current SNMR practices are based on 1D inversion strategies. These simple strategies impede applications of SNMR techniques in hydrologically complex areas. To address this issue, we introduce a very fast 2D SNMR tomographic-inversion scheme and apply it to four series of measurements simulated for a perched water-lens model. Whereas the new 2D scheme correctly reconstructs all important characteristics of the original model, 1D strategies produce highly inaccurate/misleading results. View full abstract»

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  • Least Squares Estimation of Doppler and Polarimetric Parameters for Weather Targets

    Page(s): 3760 - 3772
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1552 KB) |  | HTML iconHTML  

    Doppler and polarimetric parameters have shown to be of great utility in weather radar applications. Different measurement schemes have been proposed and implemented to obtain Doppler and polarimetric information of the sensed weather target. To date, none of these methods is capable of providing all polarimetric and Doppler parameters of interest for the whole range of temporal correlation conditions. To obtain all parameters, some of the systems require to assume different hypotheses about the Doppler or polarimetric characteristics of the targets. Failure of the assumed hypotheses leads to unacceptable bias and loss of performance of the estimated parameters. Other methods reach a tradeoff, reducing either the number of polarimetric parameters to be estimated or the maximum measurable range of Doppler parameters. With respect to polarimetric parameter estimation, it has already been shown that alternate transmission of three different polarizations improves polarimetric parameter estimation through decoupling of temporal and polarimetric effects. In this paper, this measurement system is generalized by means of a new data processing algorithm and a least squares estimation to provide joint estimates of all Doppler and polarimetric parameters for all temporal correlation conditions. No hypotheses are required. In fact, this method provides minimum variance unbiased linear estimates of all elements of the polarimetric covariance matrix. It also allows Doppler parameter estimation within their corresponding maximum measurable ranges, which are determined by the radar base pulse repetition frequency. The performance of Doppler parameter estimates is comparable to that reached by nonpolarimetric systems. Implementation of the method requires transmitting three known polarizations. Moreover, phase shifts between them should be either known or measured. View full abstract»

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  • Extreme Compression of Weather Radar Data

    Page(s): 3773 - 3783
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (741 KB) |  | HTML iconHTML  

    A method for achieving extreme levels of compression of high-volume weather radar data is presented. Weather reflectivity contours, as per National Weather Service or custom thresholds, are processed by tracing their departure from a smoothed version to obtain the local extrema which serve as control points. The control points, which are transmitted in relative coordinates for further compression, are interpolated using a second-degree B-spline to retrieve the contours. The encoding-decoding method is capable of capturing the random undulations inherent in weather contours. It is shown that over two orders of magnitude of compression is possible without perceptible loss of meteorological information. Multiple enhancements to the basic method are quantitatively studied and compared with the existing methods for radar data compression. View full abstract»

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  • Supervised Fuzzy-Logic Classification of Hydrometeors Using C-Band Weather Radars

    Page(s): 3784 - 3799
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    A model-based fuzzy-logic method for hydrometeor classification using C-band polarimetric radar data is presented and discussed. Membership functions of the fuzzy-logic algorithm are designed for best fitting simulated radar signatures at C-band. Such signatures are derived for ten supervised hydrometeor classes by means of a fully polarimetric radar scattering model. The Fuzzy-logic Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC) is designed to use a relatively small set of polarimetric observables, i.e., copolar reflectivity and differential reflectivity, but a version of the algorithm based on the use of specific differential phase is also numerically tested and documented. The classification methodology is applied to volume data coming from a C-band two-radar network that is located in north Italy within the Po valley. Numerical and experimental results clearly show the improvements of hydrometeor classification, which were obtained by using FRAHCC with respect to the direct use of fuzzy-logic-based algorithms that are specifically tuned for S-band radar data. Moreover, the availability of two C-band rainfall observations of the same event allowed us to implement a path-integrated attenuation correction procedure, based on either a composite radar field approach or a network-constrained variational algorithm. The impact of these correction procedures on hydrometeor classification is qualitatively discussed within the considered case study. View full abstract»

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  • Rainfall Nowcasting From Multisatellite Passive-Sensor Images Using a Recurrent Neural Network

    Page(s): 3800 - 3812
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1498 KB) |  | HTML iconHTML  

    The term now cast in hydro meteorology reflects the need for timely and accurate predictions of risky environmental situations, which are related to the development of severe meteorological events at short time scales. The objective of this paper is to apply a fully neural-network approach to the rainfall field now casting from infrared (IR) and microwave (MW) passive-sensor imagery aboard, respectively, geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellites. The multisatellite space-time prediction procedure, which is named Neural Combined Algorithm for Storm Tracking (NeuCAST), consists of two consecutive steps. First, the IR radiance field measured from a geostationary satellite radiometer (e.g., Meteosat) is projected ahead in time (e.g., 30 min); second, the projected radiance field is used in estimating the rainfall field by means of an MW-IR combined rain retrieval algorithm exploiting GEO-LEO observations. The NeuCAST methodology is extensively illustrated and discussed in this paper. Its accuracy is quantified by means of quantitative error indexes, which are evaluated on selected case studies of rainfall events in Southern Europe in 2003 and 2005. View full abstract»

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  • FORMOSAT-3/COSMIC GPS Radio Occultation Mission: Preliminary Results

    Page(s): 3813 - 3826
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (960 KB) |  | HTML iconHTML  

    The Formosa Satellite-3 and Constellation Observing System for the Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC) radio occultation (RO) mission has been successfully launched on April 14, 2006. The FORMOSAT-3/COSMIC mission uses global positioning system (GPS) signals to study the atmosphere and the ionosphere with global coverage. Receivers that are installed onboard of the six small FORMOSAT-3/COSMIC satellites register the phase and the amplitude of radio waves at two GPS frequencies. We give a preliminary analysis of the first RO measurements that are provided by the FORMOSAT-3/COSMIC mission. The geographical distribution of the first FORMOSAT-3/COSMIC RO experiments is shown. We demonstrate that the performance of the first measurements allows obtaining the vertical profiles of the refractivity, temperature, and pressure for the considered FORMOSAT-3/COSMIC RO events with expected accuracy, which is quite similar to the accuracy of the previous Challenging Mini-Satellite Payload and Gravity Recovery and Climate Experiment RO missions. New elements in the RO technology are suggested for further improving the accuracy and broadening the application range of the RO method. We emphasize new directions in applying the RO method to measure the vertical gradients of the refractivity in the atmosphere, to determine the temperature regime in the upper stratosphere, and to investigate the internal wave activity in the atmosphere. We find a significant correlation between the phase acceleration and the intensity variations in the RO signals that are emitted by GPS satellites and registered by the FORMOSAT-3/COSMIC satellites. This correlation opens a way to locate the layered structures in the propagation medium based on simultaneous observations of the radio wave intensity and the phase variations in trans-ionospheric satellite-to-satellite links. View full abstract»

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  • On Automatic Absorption Detection for Imaging Spectroscopy: A Comparative Study

    Page(s): 3827 - 3844
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    In this paper, we aim at presenting a survey on automatic absorption recovery methods for imaging spectroscopy. We commence by viewing the algorithms in the literature from a technical perspective and presenting an overview of the derivative analysis, fingerprint, and maximum modulus wavelet transform techniques. In addition to these methods, we also present a novel absorption recovery approach based upon unimodal regression and continuum removal. With this technical review of the methods under study, we perform a complexity analysis and examine the implementation issues pertaining to each of the alternatives. We show how detected absorption bands can be used for purposes of material identification. We conclude this paper by providing a performance study and providing identification results on hyperspectral imagery. To this end, we make use of a number of distance measures to evaluate the quality of the recovered absorptions, as compared to continuum-removed spectra. View full abstract»

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  • Hyperspectral Image Classification by Bootstrap AdaBoost With Random Decision Stumps

    Page(s): 3845 - 3851
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (394 KB) |  | HTML iconHTML  

    We consider a supervised classification of hyperspectral data using AdaBoost with stump functions as base classifiers. We used the bootstrap method without replacement to improve stability and accuracy and to reduce overtraining. We randomly split a data set into two subsets: one for training and the other one for validation. Subsampling and training/validation steps were repeated to derive the final classifier by the majority vote of the classifiers. This method enabled us to estimate variable relevance to the classification. The relevance measure was used to estimate prior probabilities of the variables for random combinations. In numerical experiments with multispectral and hyperspectral data, the proposed method performed extremely well and showed itself to be superior to support vector machines, artificial neural networks, and other well-known classification methods. View full abstract»

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  • IEEE Geoscience and Remote Sensing Society announces the creation of TGARS letters section

    Page(s): 3852
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    Freely Available from IEEE

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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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Antonio J. Plaza
University of Extremadura