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Geoscience and Remote Sensing Letters, IEEE

Issue 4 • Date Oct. 2009

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Displaying Results 1 - 25 of 64
  • [Front cover]

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

    Page(s): C2
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  • Table of contents

    Page(s): 621 - 880
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  • Introduction to the Special Issue on Airborne Field Campaigns for Soil Moisture

    Page(s): 623 - 624
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  • Improved Understanding of Soil Surface Roughness Parameterization for L-Band Passive Microwave Soil Moisture Retrieval

    Page(s): 625 - 629
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (372 KB) |  | HTML iconHTML  

    Surface roughness parameterization plays an important role in soil moisture retrieval from passive microwave observations. This letter investigates the parameterization of surface roughness in the retrieval algorithm adopted by the Soil Moisture and Ocean Salinity mission, making use of experimental airborne and ground data from the National Airborne Field Experiment held in Australia in 2005. The surface roughness parameter is retrieved from high-resolution (60 m) airborne data in different soil moisture conditions, using the ground soil moisture as input of the model. The effect of surface roughness on the emitted signal is found to change with the soil moisture conditions with a law different from that proposed in previous studies. The magnitude of this change is found to be related to soil textural properties: in clay soils, the effect of surface roughness is higher in intermediate wetness conditions (0.2-0.3 v/v) and decreases on both the dry and wet ends. Consequently, this letter calls for a rethink of surface roughness parameterization in microwave emission modeling. View full abstract»

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  • Parameterization of the Land Parameter Retrieval Model for L-Band Observations Using the NAFE'05 Data Set

    Page(s): 630 - 634
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (217 KB) |  | HTML iconHTML  

    The Land Parameter Retrieval Model (LPRM) has been successfully applied to retrieve soil moisture from space-borne passive microwave observations at C-, X-, or Ku-band and high incidence angles (50deg-55deg). However, LPRM had never been applied to lower angles or to L-band observations. This letter describes the parameterization and performance of LPRM using aircraft and ground data from the National Airborne Field Experiment 2005. This experiment was undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. It was found that model convergence could only be achieved with a temporally dynamic roughness. The roughness was parameterized according to incidence angle and soil moisture. These findings were integrated in LPRM, resulting in one uniform parameterization for all sites. The parameterized LPRM correlated well with field observations at 5-cm depth (r = 0.93 based on all sites) with a negligible bias and an accuracy of 0.06 m3middotm-3. These results demonstrate comparable retrieval accuracies as the official SMOS soil-moisture retrieval algorithm (L-MEB), but without the need for the ancillary data that are required by L-MEB. However, care should be taken when using the proposed dynamic roughness model as it is based on a limited data set, and a more thorough evaluation is necessary to test the validity of this new approach to a wider range of conditions. View full abstract»

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  • Assessing the SMOS Soil Moisture Retrieval Parameters With High-Resolution NAFE'06 Data

    Page(s): 635 - 639
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (387 KB) |  | HTML iconHTML  

    The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations, and then to interpret the differences between airborne and ground estimates in terms of land use, parameter variability, and sensing depth. For pastures (17 pixels) and nonirrigated crops (5 pixels), the root mean square error (rmse) was 0.03 volumetric (vol./vol.) soil moisture with a bias of 0.004 vol./vol. For pixels dominated by irrigated crops (5 pixels), the rmse was 0.10 vol./vol., and the bias was -0.09 vol./vol. The correlation coefficient between bias in irrigated areas and the 1-km field soil moisture variability was found to be 0.73, which suggests either 1) an increase of the soil dielectric roughness (up to about one) associated with small-scale heterogeneity of soil moisture or/and 2) a difference in sensing depth between an L-band radiometer and the in situ measurements, combined with a strong vertical gradient of soil moisture in the top 6 cm of the soil. View full abstract»

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  • An Assessment of QuikSCAT Ku-Band Scatterometer Data for Soil Moisture Sensitivity

    Page(s): 640 - 643
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (342 KB) |  | HTML iconHTML  

    The QuikSCAT enhanced (2.225-km) backscattering product is investigated for sensitivity to changes in soil moisture and its potential for spatial disaggregation of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture. Specifically, an active-passive methodology based on temporal change detection is tested using data from the 2006 National Airborne Field Experiment data set. This campaign was carried out from October 29 to November 20, 2006 in a 60 km times 40 km area of the Murrumbidgee catchment, southeast Australia. Temporal change detection analysis and accuracy in terms of spatial pattern distribution throughout the domain were assessed using a passive microwave airborne product derived from the Polarimetric L-band Multibeam Radiometer at 1-km spatial resolution. QuikSCAT-AMSR-E intercomparisons indicated higher correlations when using C-band observations. The greatest sensitivity to soil moisture was observed when using V-polarized backscatter measurement. While backscattering data showed adequate temporal sensitivity to changes in soil moisture due to precipitation events, the spatial agreement was complicated by the presence of irrigation and standing water (rice fields). This resulted in low Cramer's Phi values (less than 0.06), which were used as a measure of spatial correspondence in terms of change in soil moisture and backscatter. In addition, the high QuikSCAT sensor frequency and existence of noise in the observed data contributed to the observed discrepancies. View full abstract»

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  • Combined Passive and Active Microwave Observations of Soil Moisture During CLASIC

    Page(s): 644 - 648
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (885 KB) |  | HTML iconHTML  

    An important research direction in advancing higher spatial resolution and better accuracy in soil moisture remote sensing is the integration of active and passive microwave observations. In an effort to address this objective, an airborne instrument, the passive/active L-band sensor (PALS), was flown over two watersheds as part of the cloud and land surface interaction campaign (CLASIC) conducted in Oklahoma in 2007. Eleven flights were conducted over each watershed during the field campaign. Extensive ground observations (soil moisture, soil temperature, and vegetation) were made concurrent with the PALS measurements. Extremely wet conditions were encountered. As expected from previous research, the radiometer-based retrievals were better than the radar retrievals. The standard error of estimates (SEEs) of the retrieved soil moisture using only the PALS radiometer data were 0.048 m3/m3 for Fort Cobb (FC) and 0.067 m3/m3 for the Little Washita (LW) watershed. These errors were higher than typically observed, which is likely the result of the unusually high soil moisture and standing water conditions. The radar-only-based retrieval SEEs were 0.092 m3/m3 for FC and 0.079 m3/ m3 for LW. Radar retrievals in the FC domain were particularly poor due to the high vegetation water content of the agricultural fields. These results indicate the potential for estimating soil moisture for low-vegetation water content domains from radar observations using a simple vegetation model. Results also showed the compatibility between passive and active microwave observations and the potential for combining the two approaches. View full abstract»

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  • Using Passive Microwave Response to Soil Moisture Change for Soil Mapping: A Case Study for the Livingstone Creek Catchment

    Page(s): 649 - 652
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (533 KB) |  | HTML iconHTML  

    The 46-km2 Livingstone Creek Catchment in southeastern Australia was flown with a passive microwave airborne remote sensor four times throughout the three-week National Airborne Field Experiment in 2006, with a spatial resolution of ~200 m. Both continuous and discrete measurements of soil moisture were taken to help with interpretation of results. The catchment was experiencing extreme drought conditions leading up to the experiment, and as a result, ground cover in the catchment was minimal with many paddocks consisting of sparse dry stubble and grass. During the experiment period of November 2006, 30 mm of rainfall occurred, with the catchment going from parched dry conditions to surface wet conditions and back to dry conditions again in a short period of time. Changes in moisture responses observed by the airborne passive microwave sensor were field verified to reflect the different geology, soil, and landform elements of the catchment. Consequently, this study suggests that passive microwave remote sensing has potential as a tool to assist with soil mapping, through detecting changes in soil moisture spatial and temporal patterns. View full abstract»

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  • Orbit Accuracy Requirement for ABYSS: The Space Station Radar Altimeter to Map Global Bathymetry

    Page(s): 653 - 657
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (414 KB) |  | HTML iconHTML  

    The Altimetric Bathymetry from Surface Slopes (ABYSS), which is the proposed science payload on the International Space Station (ISS), is a Johns Hopkins University Applied Physics Laboratory-developed flight-proved delay-Doppler phase-monopulse radar altimeter capable of measuring ocean surface slope in the 6-200-km half-wavelength frequency band range with an accuracy of 0.5 mu rad , with autonomous gimbal control to compensate for the ISS structural motions. This measurement allows an improved mapping of the global bathymetry, enabling a wide range of scientific research works and applications. The nonrepeat ISS orbital ground track is ideal for ABYSS. This letter describes a simulation study on the effects of the Earth's gravity field and other errors, including thermal bending of the ISS, on the orbit determination of the altimeter instrument antenna phase center location, fulfilling the science objectives of ABYSS. Our study concluded that the error due to mean gravity field is no longer limiting due primarily to the recent Gravity Recovery and Climate Experiment gravity modeling and that the ABYSS/ISS radial orbit slope error budget in the presence of various force and measurement model errors is estimated at the 0.2-mu rad root-sum-squared (RSS) level, which satisfies the ABYSS orbit accuracy science requirement to provide an improved mapping of global bathymetry. View full abstract»

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  • ISAR Imaging of a Ship Target Using Product High-Order Matched-Phase Transform

    Page(s): 658 - 661
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    Inverse synthetic aperture radar (ISAR) imaging of a ship target is very important compared with the plane target, and the imaging condition of the ship target is more complicated than that of the plane target due to the complexity of the ship's movement. In this letter, the received signal of a ship target is modeled as a multicomponent cubic phase signal, and the product high-order matched-phase transform is proposed to estimate the parameters of each component. Then, the instantaneous ISAR images can be obtained. Results of real data demonstrate the effectiveness of the new method proposed. View full abstract»

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  • Hypercomplex Quality Assessment of Multi/Hyperspectral Images

    Page(s): 662 - 665
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (259 KB) |  | HTML iconHTML  

    This letter presents a novel image quality index which extends the Universal Image Quality Index for monochrome images to multispectral and hyperspectral images through hypercomplex numbers. The proposed index is based on the computation of the hypercomplex correlation coefficient between the reference and tested images, which jointly measures spectral and spatial distortions. Experimental results, both from true and simulated images, are presented on spaceborne and airborne visible/infrared images. The results prove accurate measurements of inter- and intraband distortions even when anomalous pixel values are concentrated on few bands. View full abstract»

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  • A New Numerical Method for Calculating Extrema of Received Power for Polarimetric SAR

    Page(s): 666 - 670
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (370 KB) |  | HTML iconHTML  

    A numerical method called cross-step iteration is proposed to calculate the maximal/minimal received power for polarized imagery based on a target's Kennaugh matrix. This method is much more efficient than the systematic method, which searches for the extrema of received power by varying the polarization ellipse angles of receiving and transmitting polarizations. It is also more advantageous than the Schuler method, which has been adopted by the PolSARPro package, because the cross-step iteration method requires less computation time and can derive both the maximal and minimal received powers, whereas the Schuler method is designed to work out only the maximal received power. The analytical model of received-power optimization indicates that the first eigenvalue of the Kennaugh matrix is the supremum of the maximal received power. The difference between these two parameters reflects the depolarization effect of the target's backscattering, which might be useful for target discrimination. View full abstract»

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  • Reconstruction of One-Dimensional Dielectric Scatterers Using Differential Evolution and Particle Swarm Optimization

    Page(s): 671 - 675
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (193 KB) |  | HTML iconHTML  

    A comparison between differential evolution (DE) and particle swarm optimization (PSO) in solving 1-D small-scale inverse scattering problems is presented. In this comparison, the efficiency of both aforementioned optimization techniques is examined for permittivity and conductivity profile reconstruction problems. The comparison is carried out under the same conditions of initial population of candidate solutions and number of iterations. Numerical results indicate that both optimization methods are reliable tools for inverse scattering applications even when noisy measurements are considered. In the particular case of small-scale problems investigated in this letter, DE outperforms the PSO in terms of reconstruction accuracy. This is considered an indicative result and not generally applicable. View full abstract»

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  • A Single-Pixel Imaging System for Remote Sensing by Two-Step Iterative Curvelet Thresholding

    Page(s): 676 - 680
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (390 KB) |  | HTML iconHTML  

    Recently, a new framework named compressed sensing (CS) for the simultaneous sampling and compression of signals has been applied for panoramic-view imaging in aerospace remote sensing. By CS, it is possible for us to take superresolution photographs using only one or a few pixels rather than a million pixels by conventional digital cameras. However, the most popular approach of satellite/airborne remote sensing is line-scan imaging instead of panoramic-view imaging. In this letter, we propose a single-pixel imaging system for line-scan onboard cameras by applying compressive-scanning matrices in a sensing step and a two-step iterative curvelet thresholding method in an offline decoding step, which converges faster than previous single-step iterative thresholding methods. Numerical experiments show good performance of the proposed method for remote sensing. Results indicate the need to design practical single-pixel remote sensing instruments involving less storage space, less power consumption, and smaller size than the currently used charged-coupled-device cameras. View full abstract»

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  • An Accurate Strategy for 3-D Ground-Based SAR Imaging

    Page(s): 681 - 685
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    In this letter, an analytical description of the 2-D and 3-D imaging of ground-based synthetic aperture radar data is given. The ability of the 3-D imaging to separate targets along the elevation direction will also be shown, thus allowing their complete localization in space. The validation of the proposed method is done by exploiting simulated data. View full abstract»

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  • On the Use of the Adaptive Integral Method in the Presence of Perfectly Conducting Perpendicular Planes

    Page(s): 686 - 688
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (386 KB) |  | HTML iconHTML  

    The adaptive integral method (AIM) is widely used to solve electromagnetic scattering and radiation problems involving large objects in free space. In the presence of one or more perfectly conducting perpendicular planes, the AIM formulation can be applied by exploiting the principle of images at the cost of increasing the number of fast Fourier transforms evaluated in the method. In this letter, we show how to obtain an efficient scheme with respect to a plain application of the principle of images. View full abstract»

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  • Superresolution Reconstruction of Multispectral Data for Improved Image Classification

    Page(s): 689 - 693
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (489 KB) |  | HTML iconHTML  

    In this letter, the application of superresolution (SR) techniques to multispectral image clustering and classification is investigated and tested using satellite data. A set of multispectral images with better spatial resolution is obtained after an SR technique is applied to several data sets recorded within a short period over a study area. Improved clustering and classification performance is demonstrated visually and quantitatively by comparison with the original low-resolution data or enlarged images using a conventional interpolation method. This letter illustrates the possibility and feasibility of the use of SR reconstruction for the classification of remote sensing data, which is encouraging as a means of breaking through current satellite detectors' resolution limits. View full abstract»

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  • Machine Learning and Bias Correction of MODIS Aerosol Optical Depth

    Page(s): 694 - 698
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (662 KB) |  | HTML iconHTML  

    Machine-learning approaches (neural networks and support vector machines) are used to explore the reasons for a persistent bias between aerosol optical depth (AOD) retrieved from the MODerate resolution Imaging Spectroradiometer (MODIS) and the accurate ground-based Aerosol Robotic Network. While this bias falls within the expected uncertainty of the MODIS algorithms, there is room for algorithm improvement. The results of the machine-learning approaches suggest a link between the MODIS AOD biases and surface type. MODIS-derived AOD may be showing dependence on the surface type either because of the link between surface type and surface reflectance or because of the covariance between aerosol properties and surface type. View full abstract»

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  • An Optimization Procedure of the Lagrange Multiplier Method for Polarimetric Power Optimization

    Page(s): 699 - 702
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (247 KB) |  | HTML iconHTML  

    The Lagrange multiplier method is one of the basic optimization procedures to find the optimum polarizations for the incoherent scattering case. This letter proves for the first time that a fixed relationship exists between the optimum polarization and the Lagrange multiplier. Then, an optimization procedure is proposed to simplify the computational complexity of the Lagrange multiplier method. To speed up the convergence of the proposed procedure, the minimum search intervals are discussed and given theoretically. A numerical example is shown to demonstrate the effectiveness of the proposed procedure. View full abstract»

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  • Multi ^{3} Scat—A Helicopter-Based Scatterometer for Snow-Cover and Sea-Ice Investigations

    Page(s): 703 - 707
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB) |  | HTML iconHTML  

    A helicopter-based Doppler scatterometer (Multi3Scat) is described. It allows simultaneous measurements of the surface radar backscatter at five different frequencies at co- and cross-polarization at incidence angles of 20deg -65deg from an altitude of 30-300 m. Video and infrared (IR) cameras simultaneously sense the surface in the scatterometers' footprint. The Multi 3Scat is calibrated using measurements carried out over corner reflectors. The stability of the Multi3Scat's signal is found to be, on average, better than 0.5 dB. Typical signal-to-noise-ratio values for sigma-0 range between 10 and 20 dB for cross-polarization and between 15 and 25 dB for copolarization over snow and ice surfaces. The potential of the Multi3Scat to acquire multifrequency multipolarization radar backscatter data and coincident video and IR temperature observations at different incidence angles over remote terrain such as the Arctic Ocean or the Alps is demonstrated. View full abstract»

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  • Evaluation of the Surface Temperature Variation With Surface Settings on the Urban Heat Island in Seoul, Korea, Using Landsat-7 ETM+ and SPOT

    Page(s): 708 - 712
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (955 KB) |  | HTML iconHTML  

    Spectral satellite imagery has been frequently used to identify surface features of the Earth. The moderate-resolution images of Landsat are typically useful to extract land cover and land use classification and surface temperature for large areas. High-resolution images such as from the Satellite Pour l'Observation de la Terre (SPOT) also provide highly detailed surface cover for regional and local scale studies. These features of satellite images were used to understand the surface temperature causing the urban heat island (UHI) in Seoul, Korea, according to the land cover settings. The surface temperature of the urbanized area had a close relationship with the surface structures, for example, density, rooftop materials, and shadow of buildings and resulted into the UHI effect in Seoul. These parameters playing an important role in controlling the surface temperature were investigated using the remote sensing approach employing both Landsat-7 and SPOT images. View full abstract»

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  • Segmented Principal Component Analysis for Parallel Compression of Hyperspectral Imagery

    Page(s): 713 - 717
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (277 KB) |  | HTML iconHTML  

    Principal component analysis (PCA) is widely used for spectral decorrelation in the JPEG2000 compression of hyperspectral imagery. However, due to the data-dependent nature of principal components, the principal component transform matrix is stored in the JPEG2000 bitstream, constituting an overhead that is often negligible if the spatial size of the image is large. However, in parallel compression in which the data set is partitioned to multiple independent processing nodes, the overhead may no longer remain negligible. It is shown that a segmented approach to PCA can greatly mitigate the detrimental effects of transform-matrix overhead and can outperform wavelet-based decorrelation which entails no such overhead. View full abstract»

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  • Nondestructive Sensor Using Microwaves From Laser Plasma by Subnanosecond Laser Pulses

    Page(s): 718 - 722
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (838 KB) |  | HTML iconHTML  

    Conventional ground-penetrating radar (GPR) requires large-aperture antennas or long-span measurements to survey a remote location precisely. We propose a laser-driven GPR (LGPR) as a new detection method. LGPR uses microwaves from laser-produced plasmas as remote transmitters and can survey a remote location using a compact instrument. We performed numerical simulations to investigate the radiation mechanism of microwaves from laser plasmas and confirmed the pulsewidth of the laser suitable for LGPR. Experiments with subnanosecond pulse lasers clarified the feasibility and detection performance of LGPR. View full abstract»

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Aims & Scope

IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts.

 

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Meet Our Editors

Editor-in-Chief
Alejandro C. Frery
Universidade Federal de Alagoas