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Geoscience and Remote Sensing, IEEE Transactions on

Issue 9 • Date Sept. 2007

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

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

    Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 2693 - 2694
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    Freely Available from IEEE
  • Approach of Adaptive Synchronization for Bistatic SAR Real-Time Imaging

    Page(s): 2695 - 2700
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (701 KB) |  | HTML iconHTML  

    The use of a novel synchronization link to compensate time, phase, and spatial synchronization errors is proposed, aiming at the development of a practical synchronization technique for bistatic synthetic aperture radar (BiSAR) real-time imaging. With the proposed technique, an amplitude-modulated signal emitting from the transmitter is received by a passive receiver and divided into two channels. One is passed through an envelope detector and then used to trigger the sampling clock, and the second is used to achieve spatial synchronization and phase synchronization. Finally, the residual time synchronization errors are compensated with a proposed high-precision range realignment method, and the residual phase synchronization errors are compensated with autofocus algorithms. This technique allows a passive receiver, which is teamed with an illuminator at a safe standoff distance, to receive the data reflected from potentially hostile areas of interest. Thus, this configuration, making real-time imaging possible, has a particular value in military applications. Simulation results show that successful adaptive synchronization for BiSAR real-time imaging is possible by using this dedicated synchronization link. View full abstract»

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  • Polarimetric Analysis of Bistatic SAR Images From Polar Decomposition: A Quaternion Approach

    Page(s): 2701 - 2714
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1277 KB) |  | HTML iconHTML  

    This paper focuses on polar decomposition, which is based on the quaternion formalism, in single-look and multilook synthetic aperture radar polarimetry. Polar decomposition is used to decompose a bistatic or monostatic polarimetric scattering matrix into a product of a Hermitian matrix (boost) and a unitary matrix (rotation). After an overview of polar decomposition principle and quaternion properties, coherent (single-look complex) and incoherent (multilook) polar decompositions are discussed. In single-look polar decomposition, we introduce the boost parameter and the rotation parameter with the purpose of classifying scattering mechanisms of different natures. New relationships between these geometrical parameters and the scattering matrix elements are obtained. We also briefly reexamine the standard coherent polarimetric target decomposition algorithms in the light of quaternions. Next, an original use of polar decomposition for incoherent polarimetric imaging is proposed, which leads to the definition of the multilook boost parameter and of the degree of polarization dispersion. Subsequently, a new approach is presented, which consists in decomposing the scattering matrix into boost and rotation components before vectorization, then in averaging to generate boost and rotation coherency matrices separately. This leads to new inferred parameters: the boost and rotation entropies, and the concurrent dominant scattering mechanisms. The link between these new parameters and standard polarimetric invariants from the Cloude and Pottier decomposition is discussed. Eventually, the multilook extension of polar decomposition may allow this to be applied to the classification of remote sensing data. In this framework, a set of five parameters reducing to four in the monostatic case can be considered. View full abstract»

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  • Ultrawideband Radar Measurements of Thickness of Snow Over Sea Ice

    Page(s): 2715 - 2724
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1152 KB) |  | HTML iconHTML  

    An accurate knowledge of snow thickness and its variability over sea ice is crucial in determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from satellite passive microwave data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultrawideband frequency-modulated continuous-wave radar to measure the snow thickness over sea ice. We synthesized a very linear chirp signal by using a phase-locked loop with a digitally generated chirp signal as a reference to obtain a fine-range resolution. The radar operates over the frequency range from 2-8 GHz. We made snow-thickness measurements over the Antarctic sea ice by operating the radar from a sled in September and October 2003. We performed radar measurements over 11 stations with varying snow thicknesses between 4 and 85 cm. We observed an excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm. Comparison of simulated radar waveforms using a simple transmission line model with the measurements confirms our expectations that echoes from snow-covered sea ice are dominated by reflections from air-snow and snow-ice interfaces. View full abstract»

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  • Along-Track Focusing of Airborne Radar Sounding Data From West Antarctica for Improving Basal Reflection Analysis and Layer Detection

    Page(s): 2725 - 2736
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1416 KB) |  | HTML iconHTML  

    This paper presents focused synthetic aperture radar (SAR) processing of airborne radar sounding data acquired with the High-Capability Radar Sounder system at 60 MHz. The motivation is to improve basal reflection analysis for water detection and to improve layer detection and tracking. The processing and reflection analyses are applied to data from Kamb Ice Stream, West Antarctica. The SAR processor correlates the radar data with reference echoes from subsurface point targets. The references are 1-D responses limited by the pulse nadir footprint or 2-D responses that include echo tails. Unfocused SAR and incoherent integration are included for comparison. Echoes are accurately preserved from along-track slopes up to about 0.5deg for unfocused SAR, 3deg for 1-D correlations, and 10deg for 2-D correlations. The noise/clutter levels increase from unfocused SAR to 1-D and 2-D correlations, but additional gain compensates at the basal interface. The basal echo signal-to-noise ratio improvement is typically about 5 dB, and up to 10 dB for 2-D correlations in rough regions. The increased noise degrades the clarity of internal layers in the 2-D correlations, but detection of layers with slopes greater than 3deg is improved. Reflection coefficients are computed for basal water detection, and the results are compared for the different processing methods. There is a significant increase in the detected water from unfocused SAR to 1-D correlations, indicating that substantial basal water exists on moderately sloped interfaces. Very little additional water is detected from the 2-D correlations. The results from incoherent integration are close to the focused SAR results, but the noise/clutter levels are much greater. View full abstract»

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  • The Influence of Antenna Pattern on Faraday Rotation in Remote Sensing at L-Band

    Page(s): 2737 - 2746
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (912 KB) |  | HTML iconHTML  

    The influence of the pattern of the receive antenna on measured Faraday rotation is examined in the context of passive remote sensing of soil moisture and ocean salinity at L-band. Faraday rotation is an important consideration for radiometers on future missions in space, such as SMOS and Aquarius. Using the radiometer on Aquarius as an example, it is shown that, while I = Tv + Th is independent of Faraday rotation to first order, it has rotation dependence when realistic antenna patterns are included in the analysis. In addition, it is shown that using the third Stokes parameter to measure the rotation angle can yield a result that is biased by as much as 1deg by purely geometrical issues that are associated with the finite width of the main beam. View full abstract»

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  • Cloud Properties Derived From GOME/ERS-2 Backscatter Data for Trace Gas Retrieval

    Page(s): 2747 - 2758
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (707 KB) |  | HTML iconHTML  

    We focus on the retrieval of cloud properties appropriate for trace gas retrieval from sun-normalized ultraviolet/visible backscatter spectra obtained from the Global Ozone Monitoring Experiment (GOME) onboard the European Space Agency's European Remote Sensing 2 Satellite (ERS-2). Retrieved quantities are the fractional cloud coverage of the GOME footprint, the cloud-top albedo, and the cloud-top height. A data fusion technique is applied to calculate the fractional cloud cover of GOME footprints from GOME's polarization measurement devices. Furthermore, cloud-top albedo and cloud-top height are retrieved simultaneously from GOME measurements around the oxygen A-band by a neural network approach. We compare our results with corresponding results from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer onboard the first European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) METEOSAT Second Generation 1 geostationary spacecraft. Our analysis revealed that GOME-derived basic cloud properties are of remarkably high quality. GOME slightly underestimates the cloud coverage of footprints, which was expected since GOME is mainly sensitive to optically thick water clouds. GOME measurements are limited to the ultraviolet and visible part of the solar spectrum, which hampers the detection of optically thin clouds. For both the cloud-top height and the cloud-top albedo, we found a small bias relative to SEVIRI results. The overall uncertainty of retrieved total ozone columns with respect to cloud parameters is about 1%-2%. Our approach is applied to the operational processing of GOME/ERS-2 and will be applied to GOME-2/METOP (launched in 2006) in the framework of EUMETSAT's Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). View full abstract»

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  • The Ground-Based Scanning Radiometer: A Powerful Tool for Study of the Arctic Atmosphere

    Page(s): 2759 - 2777
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1618 KB) |  | HTML iconHTML  

    Measurements of water vapor and clouds in the polar regions are difficult, because conventional instruments show little sensitivity (~1.3 K/mm) to low amounts. On the other hand, millimeter- and submillimeter-wavelength radiometry offers greatly enhanced sensitivity (up to 51.4 K/mm, depending upon frequency). For this reason, the National Oceanic and Atmospheric Administration's Physical Science Division designed a new instrument, the Ground-Based Scanning Radiometer (GSR), for continuous and unattended observations at millimeter and submillimeter wavelengths (50-380 GHz). The GSR was deployed for the first time during the Arctic winter radiometric experiment in March-April 2004. In this paper, we discuss the GSR calibration procedure, which allows for accurate measurements during clear and cloudy skies. Error-budget analysis and comparison with independent measurements show an absolute accuracy on the order of 1-2 K. Examples of multifrequency and multiangle GSR observations are illustrated, representing a valuable new data set for the study of water vapor, clouds, and atmospheric absorption models in the Arctic. View full abstract»

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  • Atmospheric Components Determination From Ground-Level Measurements During the Spectra Barax Campaigns (SPARC) Field Campaigns

    Page(s): 2778 - 2793
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1255 KB) |  | HTML iconHTML  

    The surface processes and ecosystem changes through response analysis (SPECTRA) Barrax campaigns were validation campaigns developed in the framework of the SPECTRA mission in order to verify that the geophysical data products provided by satellite imagery are consistent with the measurements made by independent means. Two campaigns took place in Barrax, Spain, during the summers of 2003 and 2004. This paper presents the results of the characterization of the atmospheric composition from solar radiation, radiosoundings, and lidar measurements. Several potentially interesting situations involving atmospheric layers with different types of aerosols and water content are discussed. The presence of a residual layer capping the mixing layer during some days of the 2003 campaign and the arrival of a dust-rich air mass from the Sahara on the last two days of the 2004 campaign provide some relevant aerosol vertical profiles to test atmospheric correction algorithms. The study of the effects of these atmospheric situations on radiative transfer calculations is required in the development and validation of advanced atmospheric correction codes for the new generation of Earth observation systems. View full abstract»

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  • Statistical Classification of Buried Unexploded Ordnance Using Nonparametric Prior Models

    Page(s): 2794 - 2806
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (879 KB) |  | HTML iconHTML  

    We used kernel density estimation (KDE) methods to build a priori probability density functions (pdfs) for the vector of features that are used to classify unexploded ordnance items given electromagnetic-induction sensor data. This a priori information is then used to develop a new suite of estimation and classification algorithms. As opposed to the commonly used maximum-likelihood parameter estimation methods, here we employ a maximum a posteriori (MAP) estimation algorithm that makes use of KDE-generated pdfs. Similarly, we use KDE priors to develop a suite of classification schemes operating in both "feature" space as well as ldquosignal/datardquo space. In terms of feature-based methods, we construct a support vector machine classifier and its extension to support M-ary classification. The KDE pdfs are also used to synthesize a MAP feature-based classifier. To address the numerical challenges associated with the optimal data-space Bayesian classifier, we have used several approximation techniques, including Laplacian approximation and generalized likelihood ratio tests employing the priors. Using both simulations and real field data, we observe a significant improvement in classification performance due to the use of the KDE-based prior models. View full abstract»

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  • Full-Waveform Inversion of Crosshole Radar Data Based on 2-D Finite-Difference Time-Domain Solutions of Maxwell's Equations

    Page(s): 2807 - 2828
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3410 KB) |  | HTML iconHTML  

    Crosshole radar techniques are important tools for a wide range of geoscientific and engineering investigations. Unfortunately, the resolution of crosshole radar images may be limited by inadequacies of the ray tomographic methods that are commonly used in inverting the data. Since ray methods are based on high-frequency approximations and only account for a small fraction of the information contained in the radar traces, they are restricted to resolving relatively large-scale features. As a consequence, the true potential of crosshole radar techniques has yet to be realized. To address this issue, we introduce a full-waveform inversion scheme that is based on a finite-difference time-domain solution of Maxwell's equations. We benchmark our new scheme on synthetic crosshole data generated from suites of increasingly complex models. The full-waveform tomographic images accurately reconstruct the following: (1) the locations, sizes, and electrical properties of isolated subwavelength objects embedded in homogeneous media; (2) the locations and sizes of adjacent subwavelength objects embedded in homogeneous media; (3) abrupt media boundaries and average and stochastic electrical property variations of heterogeneous layered models; and (4) the locations, sizes, and electrical conductivities of water-filled tunnels and closely spaced subwavelength pipes embedded in heterogeneous layered models. The new scheme is shown to be remarkably robust to the presence of uncorrelated noise in the radar data. Several limitations of the full-waveform tomographic inversion are also identified. For typical crosshole acquisition geometries and parameters, small resistive bodies and small closely spaced dielectric objects may be difficult to resolve. Furthermore, electrical property contrasts may be underestimated. Nevertheless, the full-waveform inversions usually provide substantially better results than those supplied by traditional ray methods. View full abstract»

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  • Retrieval of Wind Wave Elevation Spectra From Sunglint Data

    Page(s): 2829 - 2836
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (393 KB) |  | HTML iconHTML  

    A new expression for the mean value of ocean surface sunglint, modeled as a binary-valued random process, is calculated. Multiple sunglint realizations are generated by applying the specular condition for particular viewing geometries to ocean surface elevations with Gaussian roughness spectra. The sunglint mean value is used to determine the relationship between the second-order statistics of the surface slope and sunglint random processes, and this relationship is successfully inverted to retrieve the slope autocorrelation and power spectrum from the simulated sunglint data. The inversion model is then applied to an image recorded coincident with the NASA AIRSAR PACRIM2 field campaign, to retrieve the 1-D elevation power spectrum. View full abstract»

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  • Paddy Fields as Electrically Dense Media: Theoretical Modeling and Measurement Comparisons

    Page(s): 2837 - 2849
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB) |  | HTML iconHTML  

    Early models for paddy fields consist of a single-layered medium in which coherent effects within clusters of leaves are considered but multiple volume scattering is not. In this paper, the paddy canopy is modeled as a multilayered dense discrete random medium consisting of cylindrical and needle-shaped scatterers. Consideration is given to the coherent and near-field effects of the closely spaced scatterers through the Dense Medium Phase and Amplitude Correction Theory and Fresnel corrections, respectively, in the phase matrix. Then, this dense medium phase matrix is applied in the radiative transfer equations and solved up to the second order to consider double-volume scattering. Ground truth measurements of paddy fields were acquired at Sungai Burung, Selangor, Malaysia, for an entire season from the early vegetative stage of the plants to their reproductive stage. Measured parameters are used in the theoretical model to calculate the backscattering coefficients of paddy fields. Theoretical analysis of the simulation results shows in particular that second-order effects are important for cross-polarized backscatter data and that coherent effects need to be considered at lower frequencies. However, the use of needles to represent paddy leaves tends to underestimate the HH-polarized backscattering coefficients especially at the latter stages of plant growth, i.e., when the leaves are broader. The results are also used for comparisons with the backscattering coefficients obtained from RADARSAT images as well as that of earlier models to test the validity of the dense medium model with promising results. View full abstract»

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  • A Two-Step Procedure for Characterizing Obstacles Under a Rough Surface From Bistatic Measurements

    Page(s): 2850 - 2858
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    A two-step electromagnetic detection procedure is proposed to characterize a dielectric obstacle buried at low depth under a rough surface from single-frequency and multistatic data. First, we have developed, in the framework of the small perturbation theory, a correlation procedure of the scattered field, which enables us to recover an estimation of the roughness profile. This method is tested for various cases with synthetic data provided by a rigorous boundary integral solver. Second, the obtained surface profile is introduced into the numerical simulation due to a finite-element code. An iterative process is then used, based on a level-set formulation, to obtain the shape of the buried target. The influence of the prior step on the accuracy of the reconstruction of the target is studied via various criteria and for different configurations. View full abstract»

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  • Correlation Properties of Signals Backscattered From Fractal Profiles

    Page(s): 2859 - 2868
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (720 KB) |  | HTML iconHTML  

    A successful mathematical description of natural landscapes relies upon a class of random processes known as fractional Brownian motions (fBms), which may exhibit correlation with long-range dependence (LRD). In remote sensing applications, the sensor observes a certain real scene B and records data I for successive signal processing tasks. Assuming that B is modeled as an fBm, does the recorded signal I preserve the LRD character of B? More in general, can we relate the Hurst coefficient (an index of LRD) of the real scene to that of the recorded data? We address the problem in a simplified setup in which the data are related to (the slope of) the original scene through a zero-memory mapping. A mathematical framework is presented in which the above questions can be answered in the asymptotic regime of infinite data size. The effect of the finite sample size is also investigated. The mathematical model is also validated by real data, which are collected by a synthetic aperture radar that is mounted onboard of ERS-1/2 satellites. View full abstract»

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  • Global Analysis of Envisat RA-2 Burst Mode Echo Sequences

    Page(s): 2869 - 2874
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (890 KB) |  | HTML iconHTML  

    The Envisat RA-2 burst echoes are being gathered throughout the mission; however, these data are only now being made generally available by the European space agency. Considerable work has been necessary to turn these engineering-level data into a useable altimeter product. This paper documents the processing steps undertaken to generate usable data and presents the first extensive analysis of this unique dataset, using over 75 000 burst sequences with a global distribution. The results show that the burst echo data from Envisat are of extremely low noise, which is particularly evident over non-ocean surfaces, and contain a wealth of detailed information from both land and ocean surfaces. Examples illustrate the complexity of surface response from targets such as inland water and rough terrain. These unique data clearly have the potential to inform future instrument design as well as to improve the understanding of existing altimeter datasets. View full abstract»

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  • MODIS Polarization-Sensitivity Analysis

    Page(s): 2875 - 2885
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB) |  | HTML iconHTML  

    The moderate resolution imaging spectroradiometer (MODIS) is one of the primary instruments in the Earth Observing System (EOS). Currently, MODIS instruments are onboard the NASA EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. The MODIS reflective solar bands (RSBs) are sensitive to the polarization of incident light, particularly for the visible bands. To derive accurate top-of-the-atmosphere radiances, it is essential to know the polarization sensitivity, characterized by a polarization factor and phase angle, of the instruments. From prelaunch polarization sensitivity measurements, the polarization factors and phase angles for all visible and near-infrared bands of both instruments are derived, analyzed, and compared. The polarization factors are wavelength, angle of incidence on the MODIS scan mirror, and detector-dependent. For Terra MODIS, they are also mirrorside-dependent. The 412-nm band has the largest polarization factor, which is about 0.04 for both instruments. The polarization factors of all other bands are either smaller than or close to 0.02, which is the polarization requirement for the MODIS RSB whose wavelengths are longer than 412 nm. The unexpected one-, three-, and four-cycle anomalies observed in the measurements are analyzed. These anomalies are shown to be likely due to the nonuniformity of the light source and the retro-reflected light from the MODIS optical system. Their impacts on the derived polarization parameters are estimated and discussed. View full abstract»

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  • Differences Between Collection 4 and 5 MODIS Ice Cloud Optical/Microphysical Products and Their Impact on Radiative Forcing Simulations

    Page(s): 2886 - 2899
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2313 KB) |  | HTML iconHTML  

    This paper reports on the comparison of two latest versions (collections 4 and 5) of ice cloud products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. The differences between the bulk optical properties of ice clouds used in collections 4 and 5 and the relevant impact on simulating the correlation of the bidirectional reflection functions at two MODIS bands centered at 0.65 (or 0.86) and 2.13 mum are investigated. The level-3 MODIS ice cloud properties (specifically, ice cloud fraction, optical thickness, and effective particle size in this paper) from the collection 4 and 5 datasets are compared for a tropical belt of 30deg S-30deg N. Furthermore, the impact of the differences between the MODIS collection 4 and 5 ice cloud products on the simulation of the radiative forcing of these clouds is investigated. Over the tropics, the averaged ice cloud fraction from collection 5 is 1.1% more than the collection 4 counterpart, the averaged optical thickness from collection 5 is 1.2 larger than the collection 4 counterpart, and the averaged effective particle radius from collection 5 is 1.8 mum smaller than the collection 4 counterpart. Moreover, the magnitude of the differences between collection 5 and 4 ice cloud properties also depends on the surface characteristics, i.e., over land or over ocean. The differences of these two datasets (collections 4 and 5) of cloud properties can have a significant impact on the simulation of the radiative forcing of ice clouds. In terms of total (longwave plus shortwave) cloud radiative forcing, the differences between the collection 5 and 4 results are distributed primarily between -60 and 20 W ldr m-2 but peak at 0 W ldr m-2. View full abstract»

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  • An Extended 3-D Radiosity–Graphics Combined Model for Studying Thermal-Emission Directionality of Crop Canopy

    Page(s): 2900 - 2918
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3099 KB) |  | HTML iconHTML  

    Radiosity-graphics combined model (RGM) has been proposed to calculate the radiation regime and bidirectional reflectance distribution function of complex 3D scene, which is limited in visible and near-infrared wavelength (0.3-3 mum) region. In this paper, RGM is extended to thermal region (named as TRGM) based on thermal-radiosity theory and thermal-emission directionality of vegetation canopy. The TRGM has been implemented on Microsoft Windows platform, and a parameterization scheme for crop canopies is introduced in this paper. It is then evaluated by comparing with two row-crop directional thermal emission models and one thermal radiative-transfer model. Field experiment data has been used to validate the TRGM for row structural wheat and maize canopies. The root mean square error of directional brightness temperature (DBT) is smaller than 1.0degC for the wheat canopy and 0.5degC for the maize canopy while the canopy DBTs vary more than 4degC. Model sensitivity analyses have also been conducted to illustrate influences of component temperature distribution, component emissivity, incident atmospheric radiation, and canopy structure on the crop canopy DBT. View full abstract»

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  • A MODIS Sea Surface Temperature Composite for Regional Applications

    Page(s): 2919 - 2927
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1213 KB) |  | HTML iconHTML  

    Sea surface temperature (SST) is an important input for regional and global weather modeling, but timely high- resolution SST data from either in situ or satellite sources are limited. A regional near-real-time aqua moderate resolution imaging spectroradiometer (MODIS) 1-km-resolution SST composite has been developed by the NASA Short-term Prediction and Research Transition (SPoRT) program to provide continuous high-resolution SST fields twice daily for regional weather applications. The SPoRT Aqua MODIS SST composite is inter- compared to both half-degree-resolution real-time global (RTG) SST analysis and a 6-km-resolution geostationary operational environmental satellite 12 (GOES) Imager SST analysis and validated against buoy data for the month of May 2004. The SPoRT MODIS composite provides more accurate and detailed spatial information than the RTG-SST or GOES products during this period. Compared to limited buoy data, the daytime MODIS composites for May 2004 were found to have an average cool bias of -0.09degC, and the nighttime composites an average cool bias of -0.29degC, with both day and night composites having correlation values of approximately 0.90. A comparison of the MODIS SST composite to the more recent and higher resolution 12th-degree RTG-SST analysis and the 20th-degree resolution operational sea surface temperature and sea ice analysis indicated that the SPoRT MODIS composite provides additional spatial and diurnal cycle information on a regional scale. View full abstract»

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  • Surface Reflectance Estimation Using Prior Spatial and Spectral Information

    Page(s): 2928 - 2939
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (952 KB) |  | HTML iconHTML  

    Surface prior-information reflectance estimation (SPIRE) algorithms estimate changes in spectral reflectance using imperfect prior spatial and spectral information. This paper combines spectral and spatial processing to estimate local changes in spectral reflectance between pairs of spectral images under spatially and spectrally varying multiplicative and additive noise, which arise from variations in illumination and atmospheric effects. This approach extends the spatial SPIRE algorithms that were described earlier and utilizes only a prior reflectance image cube and ensembles of typical multiplicative and additive illumination noise spectral vectors that are deduced from images cubes of similar scenes. The method minimizes the impact of environmental noise by replacing with their prior equivalents low-spatial-frequency content and low-order principal components that are known to be noisy based on prior noise spectra. This filtering and substitution process occurs in log space when minimizing the effects of multiplicative noise. Tests on Hyperspectral Digital Imagery Collection Experiment visible near-infrared-shortwave infrared data demonstrated the algorithm's superior ability to estimate absolute reflectance changes under varying illumination conditions. SPIRE performance was nearly identical to the empirical line method (ELM) ground-truth-based atmospheric compensation results and was better than the physics-based Atmospheric removal (ATREM) code overall, particularly, under high clouds and haze. A ldquoSelective SPIRErdquo technique that chooses between combined-spatial/spectral and spectral-only SPIRE reflectance estimates was developed; it maximizes estimation performance on both changed and unchanged pixels. Minimum-distance classification experiments demonstrated Selective SPIRE's superior performance relative to both ATREM and ELM in cross-image supervised classification applications. View full abstract»

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  • An Innovative Neural-Net Method to Detect Temporal Changes in High-Resolution Optical Satellite Imagery

    Page(s): 2940 - 2952
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3169 KB) |  | HTML iconHTML  

    The advent of new high spatial resolution optical satellite imagery has greatly increased our ability to monitor land cover changes from space. Satellite observations are carried out regularly and continuously, and provide a great deal of insight into the temporal changes of land cover use. High spatial resolution imagery better resolves the details of these changes and makes it possible to overcome the "mixed-pixel" problem that is inherent with more moderate resolution satellite sensors. At the same time, high-resolution imagery presents a new challenge over other satellite systems, in that a relatively large amount of data must be analyzed and corrected for registration and classification errors to identify the land cover changes. To obtain the accuracies that are required by many applications to large areas, very extensive manual work is commonly required to remove the classification errors that are introduced by most methods. To improve on this situation, we have developed a new method for land surface change detection that greatly reduces the human effort that is needed to remove the errors that occur with many classification methods that are applied to high-resolution imagery. This change detection algorithm is based on neural networks, and it is able to exploit in parallel both the multiband and the multitemporal data to discriminate between real changes and false alarms. In general, the classification errors are reduced by a factor of 2-3 using our new method over a simple postclassification comparison based on a neural-network classification of the same images. View full abstract»

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  • Consensual and Hierarchical Classification of Remotely Sensed Multispectral Images

    Page(s): 2953 - 2963
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (955 KB) |  | HTML iconHTML  

    Consensual and hierarchical approaches are developed for the classification of remotely sensed multispectral images. The proposed method consists of preprocessing of input patterns, generating multiple classification results by hierarchical neural networks, and a combining scheme to generate a consensus of multiple classification results. Transformations of input patterns by random matrices and nonlinear filtering are used for preprocessing. By varying the input patterns, the multiple classification results are generated with sufficiently independent errors by using a single type of classifier. This helps to improve classification performance when the multiple classification results are combined. Hierarchical neural networks involve the use of successive classifiers which are tuned to reduce the remaining errors to increase the classification performance. This structure includes detection schemes to decide whether successive classifiers are utilized for each input. Consensual and hierarchical approaches generate more reliable and accurate results based on group decision. 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.

 

Full Aims & Scope

Meet Our Editors

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