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Geoscience and Remote Sensing, IEEE Transactions on

Issue 5 • Date May 2010

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Displaying Results 1 - 25 of 31
  • [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
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  • Table of contents

    Page(s): 2181 - 2182
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  • Potential of 229-GHz Channel for Ice-Cloud Screening

    Page(s): 2183 - 2188
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (394 KB) |  | HTML iconHTML  

    The purpose of this paper is to evaluate the potential of a 229-GHz channel as part of a humidity sounder to improve the sounder's cloud-screening capability. The humidity-sounding channels centered around the 183.31-GHz water-vapor line are affected by ice-cloud scattering. Usually, in the operational assimilation of humidity data, the problem of undetected clouds is overcome by setting high observation errors for humidity channels. However, high observation errors diminish the impact of good clear-sky data also, thus, leading to a smaller impact from humidity sounders in weather forecasts. It is expected that a channel at 229 GHz can offer a better cloud-detection capability due to its higher sensitivity to ice scattering compared with the existing channels. Here, a simple cloud-screening method is devised based on the difference between observed and background brightness temperatures. This method was tested for 229 GHz and for an existing channel at 166 GHz, and the results are compared. The new method using 229 GHz is also compared with an existing cloud-screening test, namely, the cirrus-cost test which uses the 183-GHz channels. The study demonstrates that a channel at 229 GHz has a better skill at detecting cirrus clouds which could be interpreted as an error in the background humidity profile. Therefore, addition of a 229-GHz channel can allow more weight to be given to the 183-GHz channels in data assimilation thus significantly increasing their impact on weather forecasting. View full abstract»

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  • Validation of Tropospheric Water Vapor as Measured by the 183-GHz HAMSTRAD Radiometer Over the Pyrenees Mountains, France

    Page(s): 2189 - 2203
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3883 KB) |  | HTML iconHTML  

    The H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers (HAMSTRAD) 183-GHz radiometer has been developed to measure vertical profiles of tropospheric water vapor above Dome C (Concordia station), Antarctica ( 75?06'S, 123?21'E, 3233 m asml), which is an extremely cold and dry environment, over decades. Prior to its installation at Dome C in January 2009, the instrument was deployed at the Pic du Midi (PdM) station ( 42?56'N, 0?08'E, 2877 m asml) in the Pyrenees Mountains, France, over the period covering February-June 2008. Vertical profiles of absolute humidity and integrated water vapor (IWV) as measured by HAMSTRAD were compared with measurements from radiosondes launched in three different sites: Lannemezan (43?07'N, 0?23'E, 610 m asml), France (~30 km northeast from PdM), Bordeaux-Me?rignac Airport (44?49'N, 0?42'W, 50 m asml), France ( ~ 220 km northwest from PdM), and Zaragoza (41?39'N, 0?53'W, 263 m asml), Spain ( ~170 km southwest from PdM). The validation process also used the vertical profiles of tropospheric H2O as measured by the nadir-viewing infrared atmospheric sounding interferometer (IASI) instrument aboard the MetOp-A space platform. The temporal evolution of the HAMSTRAD H2O measurements above the PdM station is very consistent with IASI, sonde, and in situ measurements, tracking the same atmosphere from a dry period in February to a wet period in June. HAMSTRAD showed unrealistic values in periods of well-established snow tempest. While the sensitivity of the HAMSTRAD measurements tends to be degraded 6 km above the altitude of the instrument, namely, above 8877 m asml, the HAMSTRAD measurements seem reasonable at the uppermost retrieval level (namely, 10 km, 12 877 m asml). In May, the wet periods are systematically showing a good agreement between sonde and HAMSTRAD IWV fields and H2O below 6777 m asml but a dry bias of IASI by more than 4-kg m-2 IWV, where- - as outside of these periods, the three data sets behave consistently. Since the best results (mean, standard deviation, bias, and correlation) are obtained when the HAMSTRAD radiometer operates in the very dry conditions of February, namely, in dryness conditions comparable to Dome C summertime values, we are very confident in the optimal use of the instrument when deployed in Antarctica. View full abstract»

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  • Toward SMOS L4 SSS Products: Improving L3 SSS With Auxiliary SSS Data

    Page(s): 2204 - 2214
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1835 KB) |  | HTML iconHTML  

    The Soil Moisture and Ocean Salinity (SMOS) mission will provide for the first time satellite observations of sea-surface salinity (SSS). At level 3 (L3) of the SMOS processing chain, a large amount of SSS data obtained by the satellite will be summarized in gridded products with the aim of synthesizing the information and reducing the error of individual SSS observations. A further improvement of SSS maps could come from the combination of L3 products with auxiliary SSS data from Argo buoys, ships of opportunity, or moored oceanographic stations. In this paper, we investigate the benefits of combining SMOS data with different auxiliary data sets. We show that the greatest error reductions come from the increase in the spatial-data coverage, even if the temporal coverage is scarce. Conversely, redundant information (i.e., many observations close to each other) or very localized measurements, even if they have a high temporal resolution, do not provide a significant improvement of the SSS products. We show that the most useful auxiliary data in terms of improving the analysis accuracy are those obtained in areas where SMOS data are noisier or, as a second choice, where the SSS field has a large variance. We also show that for areas with the same error in the L3 product (whatever the source of those errors is), it is more advisable to place the auxiliary observations in areas with longer correlation length scales. View full abstract»

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  • Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques

    Page(s): 2215 - 2223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (574 KB) |  | HTML iconHTML  

    Vertical profiles of the leaf area density (LAD) of a Japanese zelkova canopy were estimated by combining airborne and portable ground-based light detection and ranging (lidar) data and using a voxel-based canopy profiling method. The profiles obtained by the two types of lidars complemented each other, eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. In the combined results, the mean absolute errors (MAEs) of LAD ranged from 0.20 to 0.42 m2 m-3, and the mean absolute percentage errors (MAPEs) of the leaf area index (LAI) ranged from 22.3% to 27.2%, for ground areas from 4 to 32 m2, respectively. A laser beam coverage index ?? incorporating the lidar's beam settings and a beam attenuation factor was proposed. This index showed general applicability to explain the LAD estimation error for LAD measurements using different types of lidars and with different beam settings. Parts of the LAD profiles that were underestimated even when data from both lidars were combined were interpolated by using a Gaussian function. The interpolation yielded improved results for ground areas of 16 and 32 m2; the respective MAEs of LAD were 0.17 and 0.11 m2 m-3, and the respective MAPEs of LAI were 8.0% and 9.4%. The proposed method improves lidar-derived LAD estimation and is adapted to broadleaved canopies. The index ?? was tested against an actual canopy scenario and could be used to determine appropriate lidar measurement settings when data from different sources of lidar data are combined to estimate LAD profiles. View full abstract»

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  • WindSat Global Soil Moisture Retrieval and Validation

    Page(s): 2224 - 2241
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2185 KB) |  | HTML iconHTML  

    A physically based six-channel land algorithm is developed to simultaneously retrieve global soil moisture (SM), vegetation water content (VWC), and land surface temperature. The algorithm is based on maximum-likelihood estimation and uses dual-polarization WindSat passive microwave data at 10, 18.7, and 37 GHz. The global retrievals are validated at multispatial and multitemporal scales against SM climatologies, in situ network data, precipitation patterns, and Advanced Very High Resolution Radiometer (AVHRR) vegetation data. In situ SM observations from the U.S., France, and Mongolia for diverse land/vegetation cover were used to validate the results. The performance of the estimated volumetric SM was within the requirements for most science and operational applications (standard error of 0.04 m3/m3, bias of 0.004 m3/m3, and correlation coefficient of 0.89). The retrieved SM and VWC distributions are very consistent with global climatology and mesoscale precipitation patterns. The comparisons between the WindSat vegetation retrievals and the AVHRR Green Vegetation Fraction data also reveal the consistency of these two independent data sets in terms of spatial and temporal variations. View full abstract»

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  • Coseismic Horizontal Offsets and Fault-Trace Mapping Using Phase Correlation of IRS Satellite Images: The 1999 Izmit (Turkey) Earthquake

    Page(s): 2242 - 2250
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    On August 17, 1999, a strong earthquake (Mw ?? 7.4) occurred along the western sector of the North Anatolian Fault system in Turkey. The epicenter was located near the city of Izmit, 50 km east of Istanbul. Previous works determined the coseismic surface displacements by satellite synthetic aperture radar (SAR) interferometry (InSAR) and satellite optical-image correlation. In 1999, the highest spatial resolution orbiting camera was the panchromatic sensor (PAN), a 5.8-m pixel sensor (SPOT 2 was a 10-m pixel sensor) onboard the Indian Remote Sensing (IRS) satellite. We propose to apply a new phase-correlation method to PAN images to study the coseismic rupture due to the Izmit earthquake. The phase-correlation method does not need phase unwrapping and was proved to be robust under a wide variety of circumstances. Image correlometry deals with the quantification of the subpixel offsets over the whole image, allowing displacement measurement with an accuracy that is proportional to the pixel size. We measured the near-field deformations exploiting two geometrically corrected IRS images with similar look angles. A quality check of the derived offset map was performed by comparison with GPS benchmarks and SPOT offsets. The results show that IRS PAN images can be correlated to derive coseismic slip offsets due to a large earthquake (and to map its fault trace). View full abstract»

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  • Soil Moisture Effect on Thermal Infrared (8–13-μm) Emissivity

    Page(s): 2251 - 2260
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (730 KB) |  | HTML iconHTML  

    Thermal infrared (TIR) emissivities of soils with different textures were measured for several soil moisture (SM) contents under controlled conditions using the Box method and a high-precision multichannel TIR radiometer. The results showed a common increase of emissivity with SM at water contents lower than the field capacity. However, this dependence is negligible for higher water contents. The highest emissivity variations were observed in sandy soils, particularly in the 8-9-μm range due to water adhering to soil grains and decreasing the reflectance in the 8-9-μm quartz doublet region. Thus, in order to model the emissivity dependence on soil water content, different approaches were studied according to the a priori soil information. Soil-specific relationships were provided for each soil texture and different spectral bands between 8 and 13 μm, with determination coefficients up to 0.99, and standard estimation errors in emissivity lower than ± 0.014. When considering a general relationship for all soil types, standard estimation errors up to ±0.03 were obtained. However, if other soil properties (i.e., organic matter, quartz, and carbonate contents) were considered, along with soil water content, the general relationship predicted TIR emissivities with a standard estimation error of less than ±0.008. Furthermore, the study showed the possibility of retrieving SM from TIR emissivities with a standard estimation error of about ±0.08 m3 . m-3. View full abstract»

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  • Hyperspectral Texture Synthesis Using Histogram and Power Spectral Density Matching

    Page(s): 2261 - 2270
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1340 KB) |  | HTML iconHTML  

    Image synthesis tools provide a means for generating hyperspectral image data without the expense of data collection. An important use of these tools is to provide data for the assessment of image exploitation algorithms. However, the detailed spectral/spatial structure of synthetic images is typically not sufficiently realistic to support the prediction of algorithm performance on real data. In this paper, we develop a new method for hyperspectral texture synthesis that accurately simulates the spectral/spatial structure of real hyperspectral image data. The method uses the multiband histogram to model spectral properties and a 3-D Fourier representation to model within-band and cross-band spatial properties. Since multiband histogram equalization does not have a unique solution, we employ a sorting-based method for equalizing multiband distributions that is efficient and produces an exact histogram match. Spatial properties are matched by equalizing the power spectral density (psd) derived from the 3-D Fourier representation. An iterative scheme is used to equalize the histogram and psd for an input and synthesized image. Experiments show that the iteration tends to converge after a small number of steps. A subspace correction method is used to further refine the spectral accuracy of the synthesized image. We demonstrate the utility of the new technique by presenting real and synthesized images and by analyzing spectral angle deviation from the mean functions that describe spectral properties. View full abstract»

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  • Semisupervised Neural Networks for Efficient Hyperspectral Image Classification

    Page(s): 2271 - 2282
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    A framework for semisupervised remote sensing image classification based on neural networks is presented. The methodology consists of adding a flexible embedding regularizer to the loss function used for training neural networks. Training is done using stochastic gradient descent with additional balancing constraints to avoid falling into local minima. The method constitutes a generalization of both supervised and unsupervised methods and can handle millions of unlabeled samples. Therefore, the proposed approach gives rise to an operational classifier, as opposed to previously presented transductive or Laplacian support vector machines (TSVM or LapSVM, respectively). The proposed methodology constitutes a general framework for building computationally efficient semisupervised methods. The method is compared with LapSVM and TSVM in semisupervised scenarios, to SVM in supervised settings, and to online and batch k-means for unsupervised learning. Results demonstrate the improved classification accuracy and scalability of this approach on several hyperspectral image classification problems. View full abstract»

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  • Large-Scale Building Reconstruction Through Information Fusion and 3-D Priors

    Page(s): 2283 - 2296
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1636 KB) |  | HTML iconHTML  

    In this paper, a novel variational framework is introduced toward automatic 3-D building reconstruction from remote-sensing data. We consider a subset of building models that involve the footprint, their elevation, and the roof type. These models, under a certain hierarchical representation, describe the space of solutions and, under a fruitful synergy with an inferential procedure, recover the observed scene's geometry. Such an integrated approach is defined in a variational context, solves segmentation both in optical images and digital elevation maps, and allows multiple competing priors to determine their pose and 3-D geometry from the observed data. The very promising experimental results and the performed quantitative evaluation demonstrate the potentials of our approach. View full abstract»

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  • Feature Selection for Classification of Hyperspectral Data by SVM

    Page(s): 2297 - 2307
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB) |  | HTML iconHTML  

    Support vector machines (SVM) are attractive for the classification of remotely sensed data with some claims that the method is insensitive to the dimensionality of the data and, therefore, does not require a dimensionality-reduction analysis in preprocessing. Here, a series of classification analyses with two hyperspectral sensor data sets reveals that the accuracy of a classification by an SVM does vary as a function of the number of features used. Critically, it is shown that the accuracy of a classification may decline significantly (at 0.05 level of statistical significance) with the addition of features, particularly if a small training sample is used. This highlights a dependence of the accuracy of classification by an SVM on the dimensionality of the data and, therefore, the potential value of undertaking a feature-selection analysis prior to classification. Additionally, it is demonstrated that, even when a large training sample is available, feature selection may still be useful. For example, the accuracy derived from the use of a small number of features may be noninferior (at 0.05 level of significance) to that derived from the use of a larger feature set providing potential advantages in relation to issues such as data storage and computational processing costs. Feature selection may, therefore, be a valuable analysis to include in preprocessing operations for classification by an SVM. View full abstract»

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  • Visualization of Hyperspectral Images Using Bilateral Filtering

    Page(s): 2308 - 2316
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (769 KB) |  | HTML iconHTML  

    This paper presents a new approach for hyperspectral image visualization. A bilateral filtering-based approach is presented for hyperspectral image fusion to generate an appropriate resultant image. The proposed approach retains even the minor details that exist in individual image bands, by exploiting the edge-preserving characteristics of a bilateral filter. It does not introduce visible artifacts in the fused image. A hierarchical fusion scheme has also been proposed for implementation purposes to accommodate a large number of hyperspectral image bands. The proposed scheme provides computational and storage efficiency without affecting the quality and performance of the fusion. It also facilitates the midband visualization of a subset of the hyperspectral image cube. Quantitative performance results are presented to indicate the effectiveness of the proposed method. View full abstract»

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  • Method for Crater Detection From Martian Digital Topography Data Using Gradient Value/Orientation, Morphometry, Vote Analysis, Slip Tuning, and Calibration

    Page(s): 2317 - 2329
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    Recently, all the craters from the major currently available manually assembled catalogs have been merged into the catalog with 57 633 known Martian impact craters. This paper presents a new crater detection algorithm (CDA) for the search of still uncataloged impact craters. The CDA is based on fuzzy edge detectors and Radon/Hough transform and utilizes digital topography data instead of image data. The critical parts of the method providing increased accuracy are as follows: (1) gradient-value/orientation-based techniques; (2) automated morphometry measurements of depth/diameter ratio, circularity, topographic cross-profile, rim, central peak, and radial range where the crater is preserved; (3) circularity analysis of votes in parameter space; (4) slip tuning of detected craters' parameters; and (5) calibration which partially compensates differences in morphology between small and large craters. Using the framework for the evaluation of CDAs, in comparison with prior work, the proposed detector shows the following: (1) significantly larger area under the free-response receiver operating characteristics (AUROC) and (2) significantly larger number of correct detections. Using the Mars Orbiter Laser Altimeter data as input, the CDA proposed numerous candidates for GT-57633 catalog extension. After the manual survey of all proposed craters and rejection of false detections, 57 592 impact craters were confirmed as correct detections. The accompanying result to the CDA is a new GT-115225 catalog. View full abstract»

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  • Multiple-Shape Reconstruction by Means of Multiregion Level Sets

    Page(s): 2330 - 2342
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1993 KB) |  | HTML iconHTML  

    In the framework of inverse scattering techniques for microwave imaging, this paper proposes an approach based on the integration between a multiscaling procedure and the level-set-based optimization in order to properly deal with the shape reconstruction of multiple and disconnected homogeneous scatterers. The effectiveness and robustness of the proposed approach is assessed against both synthetic and experimental data. A selected set of results concerned with complex shapes is presented and discussed. View full abstract»

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  • Dry–Wet Bedrock Interface Detection by Radio Echo Sounding Measurements

    Page(s): 2343 - 2348
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (874 KB) |  | HTML iconHTML  

    In this paper, a method to distinguish a wet or dry bedrock-ice interface is proposed. It is based on the analysis of radio echo sounding (RES) measurements, a widely employed method for determining bedrock topography in Antarctica. In particular, the RES system has played an important role in subglacial lake exploration and hydrogeological studies at the bedrock-ice interface. Recently, bedrock characterization has been improved through the analysis of the power of radar echoes. Signal power depends on bedrock reflectivity and its specific physical condition. In this paper, a linear model describing the loss term (internal ice absorption) is proposed. This model, together with other known quantities, contributes toward an assessment of power variation of bedrock reflectivity in order to determinate wet and dry bedrock interfaces in the Dome C region in Antarctica. View full abstract»

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  • Physical Meaning of Bistatic Polarimetric Parameters

    Page(s): 2349 - 2356
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (873 KB) |  | HTML iconHTML  

    A generalization of the polarization theory to bistatic scattering had shown that coherent scattering mechanisms are characterized by six bistatic fork parameters. The purpose of this paper is to try again to assign physical properties to these parameters as it was done in the monostatic case by Huynen. Our conclusions are validated with COSMO (Coherent Scattering Model) model and BABI (Base BIstatique) measurements. View full abstract»

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  • A Polarimetric Target Detector Using the Huynen Fork

    Page(s): 2357 - 2366
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (940 KB) |  | HTML iconHTML  

    The contribution of synthetic aperture radar polarimetry in target detection is described and found to add valuable information. A new target detection methodology that makes novel use of the polarization fork of the target is described. The detector is based on a correlation procedure in the target space, and other target representations (e.g., Huynen parameters or ?? angle) can be employed. The mathematical formulation is general and can be applied to any kind of single target; however, in this paper, the detection is optimized for the odd and even bounces (the first two elements of the Pauli scattering vector) and for the oriented dipoles. Validation against real data shows significant agreement with the expected results based on the theoretical description. View full abstract»

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  • Numerical Backscattering Analysis for Rough Surfaces Including a Cloddy Structure

    Page(s): 2367 - 2374
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (513 KB) |  | HTML iconHTML  

    In recent years, the presence of a new type of agricultural-surface tillage used for the sowing of wheat and corn has been observed with increasing frequency. It illustrates less roughly ploughed soils, with a greater quantity of small clods distributed over the soil surface. In this paper, a new description of such rough agricultural surfaces is proposed. It is based on a composite model, including a classical surface represented by an exponential correlation function, together with a random cloddy structure. This description enables volumetric structures to be introduced over the soil's surface. A numerical moment-modeling method, based on integral equations, is used to evaluate the contribution of clods to the radar backscattering behavior of agricultural surfaces. It is found that the presence of clods explains the very small correlation lengths which are often found in cloddy agricultural fields. The classical approach, in which the surface is described by a correlation function only based on two statistical parameters, rms height and correlation length, overestimates the backscattering coefficients when compared with an approach that includes the clods. This overestimation is often observed with real radar data for such fields. View full abstract»

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  • Single and Multipolarimetric SAR Tomography of Forested Areas: A Parametric Approach

    Page(s): 2375 - 2387
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1667 KB) |  | HTML iconHTML  

    In this paper, a technique is described for the tomographic characterization of forested areas through multiple synthetic aperture radar (SAR) observations, based on either single or multipolarimetric acquisitions. This technique is based on the idea of characterizing the Fourier spectrum of the multibaseline data as being constituted by two effective scattering centers displaced along the vertical direction, plus the associated decorrelation terms. As a result, SAR tomography will be formulated as the problem of detecting the number of scattering centers within the resolution cell, estimating the parameters that describe their spatial structure, and evaluating the associated backscattered powers. Parameter estimation is carried out through the covariance matching estimation technique, which provides an asymptotically optimal solution. The results of an experiment performed on a real P-band multibaseline fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported. View full abstract»

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  • Capon- and APES-Based SAR Processing: Performance and Practical Considerations

    Page(s): 2388 - 2402
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2119 KB) |  | HTML iconHTML  

    This paper discusses the use of Capon's minimum-variance method (MVM) and Amplitude and Phase EStimation (APES) spectral-estimation algorithms to synthetic aperture radar range-azimuth focusing. The rationale of the algorithms is discussed. An implementation of a Capon or APES processing chain is explained, and processing parameters such as chip-image size, resampling factor, and diagonal loading are discussed. For multichannel cases, a joint-processing approach is presented. A set of Monte Carlo simulations are described and used to benchmark Capon- and APES-based processing against conventional matched-filter-based approaches. Both methods improve the resolution and reduce sidelobes. APES yields generally better estimates of amplitude and phase than Capon but with worse resolution. Results with RADARSAT-2 quad-polarization data over Barcelona are used to qualitatively study the real-life performance of these algorithms. View full abstract»

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  • Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery

    Page(s): 2403 - 2420
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2443 KB) |  | HTML iconHTML  

    Rapid damage assessment after natural disasters (e.g., earthquakes) and violent conflicts (e.g., war-related destruction) is crucial for initiating effective emergency response actions. Remote-sensing satellites equipped with very high spatial resolution (VHR) multispectral and synthetic aperture radar (SAR) imaging sensors can provide vital information due to their ability to map the affected areas with high geometric precision and in an uncensored manner. In this paper, we present a novel method that detects buildings destroyed in an earthquake using pre-event VHR optical and post-event detected VHR SAR imagery. The method operates at the level of individual buildings and assumes that they have a rectangular footprint and are isolated. First, the 3-D parameters of a building are estimated from the pre-event optical imagery. Second, the building information and the acquisition parameters of the VHR SAR scene are used to predict the expected signature of the building in the post-event SAR scene assuming that it is not affected by the event. Third, the similarity between the predicted image and the actual SAR image is analyzed. If the similarity is high, the building is likely to be still intact, whereas a low similarity indicates that the building is destroyed. A similarity threshold is used to classify the buildings. We demonstrate the feasibility and the effectiveness of the method for a subset of the town of Yingxiu, China, which was heavily damaged in the Sichuan earthquake of May 12, 2008. For the experiment, we use QuickBird and WorldView-1 optical imagery, and TerraSAR-X and COSMO-SkyMed SAR data. View full abstract»

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  • The Importance of Soil Moisture and Soil Structure for InSAR Phase and Backscatter, as Determined by FDTD Modeling

    Page(s): 2421 - 2429
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (794 KB) |  | HTML iconHTML  

    In this paper, we introduce a finite-difference time-domain simulator that accurately models the interaction of microwaves with realistic soils, specifically from spaceborne interferometric synthetic aperture radar (InSAR). The modeled soils are characterized by surface roughness, correlation length, bulk moisture content, vertical moisture gradient, and small air-filled-void content. Simulation results include both backscatter and interferometric phase, and we are particularly interested in assessing the potential of the latter as a proxy for soil moisture. We find that differences in homogeneous bulk moisture result in only small phase differences (< 5?). In contrast, combinations of vertical moisture gradients and small air-filled voids, which may typically exist in more realistic soils, can produce phase changes > 30? for HH and > 50? for VV when the soil moisture is varied from 3% to 30% in the uppermost 2 cm of the soil. Phase changes of this magnitude are easily detectable by spaceborne InSAR techniques. While a strong phase response to a change in mean bulk moisture is common to vertical moisture gradient and small air-filled-void cases, their corresponding backscatter responses are very different. A vertical moisture gradient makes the backscatter response dramatically flatter compared with the case of uniform moisture; in contrast, the introduction of air-filled voids barely alters the backscatter. Thus, it may be possible to infer near-surface soil-structure parameters such as vertical gradients or fractions of voids and inhomogeneities from combined SAR phase and backscatter data. Future SAR sensors could be optimized for this purpose. Prior theoretical work based on the assumption of vertically uniform soil-moisture distributions may need to be adjusted, and the lack of a theory that accommodates more complex soil structures may explain why backscatter inversions have yet to result in a viable operational system. View full abstract»

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

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Meet Our Editors

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