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Geoscience and Remote Sensing, IEEE Transactions on

Issue 3  Part 2 • Date March 2010

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Displaying Results 1 - 25 of 35
  • [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): 1297 - 1298
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  • Automatic Spectral-Rule-Based Preliminary Classification of Radiometrically Calibrated SPOT-4/-5/IRS, AVHRR/MSG, AATSR, IKONOS/QuickBird/OrbView/GeoEye, and DMC/SPOT-1/-2 Imagery—Part I: System Design and Implementation

    Page(s): 1299 - 1325
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1469 KB) |  | HTML iconHTML  

    To date, the automatic or semiautomatic transformation of huge amounts of multisource multiresolution spaceborne imagery into information still remains far below reasonable expectations. The original contribution of this paper to existing knowledge on the development of operational automatic remote sensing image understanding systems (RS-IUSs) is fourfold. First, existing RS-IUS architectures are critically revised. In this review section, the two-stage stratified hierarchical RS-IUS model, originally proposed by Shackelford and Davis, is identified as a subclass of the parent class of multiagent hybrid systems for RS image understanding, which is potentially superior to the two-stage segment-based RS-IUS architecture that is currently considered the state-of-the-art in commercial RS image-processing software toolboxes. Second, this paper highlights the degree of novelty of an operational automatic near-real-time well-posed model-driven application-independent per-pixel Landsat-like spectral-rule-based decision-tree classifier (LSRC) recently presented in RS literature. Third, five original downscaled implementations of the LSRC system are proposed to be input with a multispectral image whose spectral resolution overlaps with, but is inferior to, Landsat's. These five downscaled LSRC implementations are identified as the Satellite Pour l'Observation de la Terre-like SRC, the Advanced Very High Resolution Radiometer-like SRC, the Advanced Along-Track Scanning Radiometer-like SRC, the IKONOS-like SRC, and the Disaster Monitoring Constellation-like SRC, respectively. LSRC, together with its five downscaled implementations, called the integrated SRC system of systems, is eligible for use as the automatic pixel-based preliminary classification first stage of a two-stage stratified hierarchical RS-IUS instantiation. Fourth, to sustain the feasibility of the new downscaled LSRC implementations, a novel vegetation spectral index is introduced and discussed. In Part II of - - this paper, experimental results are presented and discussed for the entire SRC family of classifiers. View full abstract»

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  • Automatic Spectral Rule-Based Preliminary Classification of Radiometrically Calibrated SPOT-4/-5/IRS, AVHRR/MSG, AATSR, IKONOS/QuickBird/OrbView/GeoEye, and DMC/SPOT-1/-2 Imagery—Part II: Classification Accuracy Assessment

    Page(s): 1326 - 1354
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3879 KB) |  | HTML iconHTML  

    In Part I of this paper, an operational fully automated Landsat-like image spectral rule-based decision-tree classifier (LSRC), suitable for mapping radiometrically calibrated seven-band Landsat-4/-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM+ (ETM+) spaceborne images [eventually synthesized from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (MODIS) imaging sensor] into a discrete and finite set of spectral categories, has been downscaled to properly deal with spaceborne multispectral imaging sensors whose spectral resolution overlaps with, but is inferior to Landsat's, namely: 1) Satellite Pour l'Observation de la Terre (SPOT)-4/-5, Indian Remote Sensing Satellite (IRS)-1C/-1D/-P6 Linear Imaging Self-Scanner (LISS)-III, and IRS-P6 Advanced Wide Field Sensor (AWiFS); 2) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and Meteosat Second Generation (MSG); 3) Environmental Satellite (ENVISAT) Advanced Along-Track Scanning Radiometer (AATSR); 4) GeoEye-1, IKONOS-2, QuickBird-2, OrbView-3, TopSat, KOrean MultiPurpose SATellite (KOMPSAT)-2, FORMOsa SATellite (FORMOSAT)-2, Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), RapidEye, WorldView-2, PLEIADES-1/-2, and SPOT-6/-7; and 5) Disaster Monitoring Constellation (DMC), IRS-P6 LISS-IV, and SPOT-1/-2. LSRC, together with its five downscaled versions, identified, respectively, as the four-band SPOT-like SRC (SSRC), the four-band AVHRR-like SRC (AVSRC), the five-band AATSR-like SRC (AASRC), the four-band IKONOS-like SRC (ISRC), and the three-band DMC-like SRC (DSRC), form the so-called integrated SRC system of systems. In this paper, first, the classification accuracy and robustness to changes in the input data set of SSRC, AVSRC, AASRC, ISRC, and DSRC are assessed, both qualitatively and quantitatively, in comparison with LSRC- - 's. Next, ongoing and future SRC applications are presented and discussed. They encompass: 1) the implementation of operational two-stage stratified hierarchical Remote Sensing (RS) image understanding systems discussed in Part I of this paper; 2) the integration of near real-time satellite mapping services with Internet map servers; and 3) the development of a new approach to semantic querying of large-scale multisensor image databases. These experimental results and application examples prove that the integrated SRC system of systems is operational, namely, it is effective, near real-time, automatic, and robust to changes in the input data set. Therefore, SRC appears eligible for use in operational satellite-based measurement systems such as those envisaged by the ongoing international Global Earth Observation System of Systems (GEOSS) Programme and the Global Monitoring for Environment and Security (GMES) system project. View full abstract»

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  • Simulated Multispectral Imagery for Tree Species Classification Using Support Vector Machines

    Page(s): 1355 - 1364
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (635 KB) |  | HTML iconHTML  

    The information content of remotely sensed data depends primarily on the spatial and spectral properties of the imaging device. This paper focuses on the classification performance of the different spectral features (hyper- and multispectral measurements) with respect to three tree species. The Support Vector Machine was chosen as the classification algorithm for these features. A simulated optical radiation model was constructed to evaluate the identification performance of the given multispectral system for the tree species, and the effects of spectral-band selection and data preprocessing were studied in this setting. Simulations were based on the reflectance measurements of the pine (Pinus sylvestris L.), spruce [ Picea abies (L.) H. Karst.], and birch trees (Betula pubescens Ehrh. and Betula pendula Roth). Leica ADS80 airborne sensor with four spectral bands (channels) was used as a fixed multispectral sensor system that leads to response values for the at-sensor radiance signal. Results suggest that this four-band system has inadequate classification performance for the three tree species. The simulations demonstrate on average a 5-15 percentage points improvement in classification performance when the Leica system is combined with one additional spectral band. It is also demonstrated for the Leica data that feature mapping through a Mahalanobis kernel leads to a 5-10 percentage points improvement in classification performance when compared with other kernels. View full abstract»

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  • HAMSTRAD-Tropo, A 183-GHz Radiometer Dedicated to Sound Tropospheric Water Vapor Over Concordia Station, Antarctica

    Page(s): 1365 - 1380
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    The H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers (HAMSTRAD) program aims to develop two ground-based microwave radiometers to sound tropospheric and stratospheric water vapor (H2O) above Dome C (Concordia Station), Antarctica (75??06' S, 123??21'E, 3233 m asml), an extremely cold and dry environment, over decades. By using state-of-the-art technology, the HAMSTRAD-Tropo radiometer uses spectral information in the domains 51-59 GHz (oxygen line) and 169-197 GHz (water vapor line) to derive accurate tropospheric profiles of temperature (with accuracy ranging from 1 to 2 K) and low absolute humidity (with accuracy ranging from 0.02 to 0.05 g ?? m-3), together with integrated water vapor (with accuracy of about 0.008 kg ?? m-2) and liquid water path. Prior to its installation at Dome C in January 2009, the fully automated radiometer has been deployed at the Pic du Midi (PdM, 42??56'N, 0??08'E, 2877 m asml, France) in February 2008 and was in operation for five months. Preliminary comparisons with radio soundings particularly launched in the vicinity of PdM in February 2008 and the outputs from the mesoscale MESO-NH model show a great consistency to within 0.2-0.3 g ?? m-3 between all absolute humidity data sets whatever the atmosphere considered (extremely dry or wet). View full abstract»

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  • Temperature and Humidity Profiling in the Arctic Using Ground-Based Millimeter-Wave Radiometry and 1DVAR

    Page(s): 1381 - 1388
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    A 1-D variational (1DVAR) retrieval technique has been developed for obtaining temperature and humidity profiles from observations of the Ground-Based Scanning Radiometer (GSR) operating at millimeter-wavelengths. The GSR was deployed in two Arctic experiments held at the Atmospheric Radiation Measurement Program in Barrow, Alaska. Temperature and humidity profiles retrieved with the 1DVAR technique are compared with simultaneous radiosonde observations (RAOBs) during the Radiative Heating in Underexplored Bands Campaign (February-March 2007). Examples and statistical results are presented and discussed to demonstrate the achieved retrieval accuracy and vertical resolution. The 1DVAR retrievals based on GSR observations improve the NWP background up to 5 km, particularly in the lower 3 km. The present implementation achieved an root-mean-square (rms) error with respect to RAOB within 1.5 K for temperature and 0.10 g/kg for humidity profiles of up to 5 km in height, with 2.9 and 2.0 degrees of freedom for signal, respectively. Using the interlevel covariance definition of the vertical resolution, the 1DVAR retrievals showed a < 1-km vertical resolution of up to 5 km for both temperature and humidity profiles. The integrated water vapor obtained from the retrieved humidity profiles showed an rms accuracy within 0.10 kg/m2 , with small bias (< 0.01 kg/m2) and excellent correlation (0.96). View full abstract»

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  • Prelaunch Estimation of Radiometric Resolution and Stability of SMOS Zero-Baseline Radiometer in Anechoic Chamber

    Page(s): 1389 - 1397
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1604 KB) |  | HTML iconHTML  

    The purpose of the Soil Moisture and Ocean Salinity (SMOS) mission is to measure soil moisture and sea surface salinity (SSS). The measurement of SSS using microwave radiometry requires a very sensitive instrument. In SMOS, the image is formed using the interferometric technique complemented by the average brightness temperature, or zero baseline, to set the absolute level of the image. Therefore, the measurement of the zero baseline is very critical for the success of the mission. In this paper, the radiometric resolution and stability of the radiometers dedicated to the measurement of zero baseline on SMOS are estimated. The results of a measurement campaign carried out in an anechoic electromagnetic compatibility chamber are used. The results show that the zero-baseline radiometers have the potential for relative accuracy better than 20 mK, depending on the integration scenario, satisfying the mission requirement for SSS retrieval. View full abstract»

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  • L-Band RFI as Experienced During Airborne Campaigns in Preparation for SMOS

    Page(s): 1398 - 1407
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1487 KB) |  | HTML iconHTML  

    In support of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission, a number of soil moisture and sea salinity campaigns, including airborne L-band radiometer measurements, have been carried out. The radiometer used in this context is fully polarimetric and has built-in radio-frequency-interference (RFI)-detection capabilities. Thus, the instrument, in addition to supplying L-band data to the geophysicists, also gave valuable information about the RFI environment. Campaigns were carried out in Australia and in a variety of European locations, resulting in the largest and most comprehensive data set available for assessing RFI at L-band. This paper introduces the radiometer system and how it detects RFI using the kurtosis method, reports on the percentage of data that are typically flagged as being corrupted by RFI, and gives a hint about geographical distribution. Also, examples of polarimetric signatures are given, and the possibility of detecting RFI using such data is discussed. View full abstract»

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  • UWB Through-Wall Imaging Based on Compressive Sensing

    Page(s): 1408 - 1415
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    To achieve high-resolution 2-D images, through-wall imaging (TWI) radar with ultra-wideband and long antenna arrays faces considerable technical challenges such as a prolonged data collection time, a huge amount of data, and a high hardware complexity. This paper presents a novel data acquisition scheme and an imaging algorithm for TWI radar based on compressive sensing (CS), which states that a signal having a sparse representation can be reconstructed from a small number of nonadaptive randomized projections by solving a tractable convex program. Instead of measuring all spatial-frequency data, a few samples, by employing an overcomplete dictionary, are sufficient to obtain reliable target space images even at high noise levels. Preliminary simulated and experimental results show that the proposed algorithm outperforms the conventional delay-and-sum beamforming method even though many fewer CS measurements are used. View full abstract»

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  • Multipolarization Microwave Scattering Model for Sahelian Grassland

    Page(s): 1416 - 1432
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1825 KB) |  | HTML iconHTML  

    A coherent scattering formulation is developed for radar remote sensing of Sahelian grassland. This African vegetation is mainly composed of annual grass and shrubs. In the proposed procedure, first, a temporal model for generation of grass and shrub structures, which includes important realistic botanical information, is implemented. Because we develop a coherent scattering model, preserving the relative position of plant elements in a statistical manner as accurately as possible is very important. Shrubs are reproduced using cylindrical elements which represent trunks, branches, and thin green stems that function as leaves for these shrubs. Their crown shape is highly irregular, but for the most part can be encompassed in an ellipsoidal or cylindrical volume; on the other hand, the grass is represented as a set of cylindrical stalks and blade leaves. The scattered power from each grass element is added because multiple scattering among adjacent elements can be neglected at microwave frequencies. We calculate the soil scattering using the Integral Equation Method and neglect the soil volume scattering which may become significant for dry soil condition at high incidence angles. Backscatter statistics are acquired via a Monte Carlo simulation over a large number of realizations. The accuracy of the model is verified using measured data acquired by the C-band environmental satellite advanced synthetic aperture radar instrument at different incident angles. View full abstract»

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  • F k Filter Designs to Suppress Direct Waves for Bistatic Ground Penetrating Radar

    Page(s): 1433 - 1444
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    Two design methods of a filter in a frequency-spatial frequency (f-k) domain have been developed for bistatic ground penetrating radar. The proposed methods suppress the direct wave, which causes significant artifacts in radar images, and are evaluated by laboratory measurements. Because the geometric positions of a transmitting antenna and a receiving antenna are not fixed, the suppression of a direct wave is an important issue. Then, we propose an f-k filtering approach for the solution, and present two methods to design the f-k filter. Both methods use a difference of an apparent horizontal velocity between a direct wave and a reflection from a target, and work automatically from position information of a transmitting antenna and a receiving antenna. One method is to mask an f-k spectrum in a region where a spectrum of the direct wave is distributed. The region is defined from the maximum and the minimum apparent horizontal velocity of the direct wave, which are calculated from the location of the transmitting antenna and the scanning area of the receiver. As for the other method, the most essential point is applying a time shift to eliminate a difference of an arrival time of a direct wave, where the time shift is calculated beforehand from the location of the transmitting antenna and the receiving antenna. Then, an apparent horizontal velocity of the direct wave becomes infinitely large due to the time shift. Thus, the f-k spectrum of the direct wave concentrates around a frequency axis because its slope is infinitely large. Then, a filter to reject the dc component in the spatial frequency direction is applied. Both methods are applied to an experimental data set which is acquired by a bistatic radar measurement to detect a buried landmine model with a depth of 10 cm. In addition, it is confirmed that they can suppress the undesired fluctuation of the images nearly one-tenth and help the rel- - iable detection of a buried object. View full abstract»

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  • Ray-Tracing Simulation Techniques for Understanding High-Resolution SAR Images

    Page(s): 1445 - 1456
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1610 KB) |  | HTML iconHTML  

    In this paper, a simulation concept is presented for creating synthetic aperture radar (SAR) reflectivity maps based on ray tracing. Three-dimensional models of man-made objects are illuminated by a virtual SAR sensor whose signal is approximated by rays sent through the model space. To this end, open-source software tools are adapted and extended to derive output data in SAR geometry followed by creating the reflectivity map. Rays can be followed for multiple reflections within the object scene. Signals having different multiple reflection levels are stored in separate image layers. For evaluating the potentials and limits of the simulation approach, simulated reflectivity maps and distribution maps are compared with real TerraSAR-X images for various complex man-made objects like a skyscraper in Tokyo, the Wynn Hotel in Las Vegas, and the Eiffel Tower in Paris. The results show that the simulation can provide very valuable information to interpret complex SAR images or to predict the reflectivity of planned SAR image acquisitions. View full abstract»

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  • An Estimation Method for InSAR Interferometric Phase Based on MMSE Criterion

    Page(s): 1457 - 1469
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3484 KB) |  | HTML iconHTML  

    In this paper, we propose a method based on minimum mean squared error (mmse) criterion to estimate synthetic aperture radar interferometry (InSAR) interferometric phase. In this method, the cross-correlation coefficient vector with large coregistration error is given first, and then, the cost function under the mmse criterion is used to estimate the InSAR interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide an accurate estimate of the terrain interferometric phase (interferogram) even when the coregistration error reaches 1 pixel. View full abstract»

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  • APC Trajectory Design for “One-Active” Linear-Array Three-Dimensional Imaging SAR

    Page(s): 1470 - 1486
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2451 KB) |  | HTML iconHTML  

    This paper discusses the antenna phase center trajectory (APCT) design for the "one-active" linear-array 3D imaging SAR (LASAR). First, we discuss the principle of the one-active LASAR and demonstrate its feasibility by experiment. To describe the 3D spatial resolution of the one-active LASAR, the relationship between the 3D ambiguity function (AF) of the one-active LASAR and the system parameters is discussed in detail. Based on the analysis, we divide the APCT design into three topics: the direction of the linear array, the length of the linear array, and the switching mode of the active element [named as antenna phase center function (APCF)]. On the first topic, we conclude that, when the range, along-track, and cross-track directions are orthogonal to each other, the ambiguity region of the one-active LASAR attains minimum, and the 3D spatial resolution can be separated into the range, along-track, and cross-track resolutions. On the second topic, we find that the cross-track resolution is determined by the length of the linear array and the frequency of the carrier. To ensure that the length of the linear array is acceptable, the carrier should be W-band wave or millimeter wave. On the third topic, the effect of APCF is researched, and we find that both the periodic APCF and the pseudorandom APCF can produce 3D resolution, except for the periodic rectangle APCF. For the pseudorandom APCF and the periodic APCF with short period, the cross-range 2D AF is or can be approximated as the product of two 1D AFs in the along- and cross-track directions. Finally, the distribution of the pseudorandom APCF is optimized by the Lagrange multiplier method under the minimum variance criterion, and we find that, when the pseudorandom APCF obeys the parabolic distribution, the cross-range 2D AF is optimal. View full abstract»

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  • Building Height Retrieval From VHR SAR Imagery Based on an Iterative Simulation and Matching Technique

    Page(s): 1487 - 1504
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1693 KB) |  | HTML iconHTML  

    Experimental airborne synthetic aperture radar (SAR) systems achieve spatial resolutions of approximately 10 cm, whereas the new spaceborne very high spatial resolution (VHR) SAR sensors onboard the TerraSAR-X and COSMO-SkyMed satellites achieve spatial resolutions down to 1 m. In VHR SAR data, features from individual urban structures (i.e., buildings) can be identified by their characteristic settings in urban settlement patterns. In this paper, we present a novel concept for the height estimation of generic man-made structures from single detected SAR data. The proposed approach is based on the definition of a hypothesis on the height of the building and on the simulation of a SAR image for testing that hypothesis. A matching procedure is applied between the estimated and the actual SAR image in order to test the height hypothesis. The process is iterated for different height assumptions until the matching function is optimized, and thus, the building height is estimated. The efficiency of the proposed method is demonstrated on a set of 40 flat- and gable-roof buildings using two submeter VHR airborne and two 1-m resolution TerraSAR-X SAR scenes all acquired from the same residential area in Dorsten, Germany. The results show that, in the absence of string disturbing effects, the method is able to estimate the height of flat- and gable-roof buildings in the submeter data to the order of a meter, while the accuracy for the meter resolution spaceborne data is lower but still sufficient to estimate the number of floors of a building. View full abstract»

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  • Coherent MapDrift Technique

    Page(s): 1505 - 1517
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (802 KB) |  | HTML iconHTML  

    A new parametric autofocus technique with a high accuracy of flight-parameter estimation dedicated to strip-mode synthetic aperture radar (SAR) systems is presented. Most of the known autofocus techniques require high-reflectivity targets (man-made targets) to obtain a properly focused SAR image. The technique proposed in this paper allows flight parameters to be estimated effectively, even for a low-contrast scene (e.g., forests, fields, small paths, etc.). The autofocus technique is based on well-known MapDrift (MD) principles. The presented technique is a coherent one, which allows flight parameters to be estimated more precisely than in the other well-known parametric technique referred to as classical MD. The presented technique allows flight parameters to be estimated with accuracy that is independent of the initial velocity error. It can be used for real-time processing for both Earth imaging and moving-target indication. View full abstract»

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  • ISAR Imaging of Maneuvering Target Based on the L-Class of Fourth-Order Complex-Lag PWVD

    Page(s): 1518 - 1527
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (992 KB) |  | HTML iconHTML  

    In inverse synthetic aperture radar (ISAR) imaging of a maneuvering target, the received signal in a range bin can be characterized as a multicomponent polynomial phase signal (PPS) after motion compensation. The traditional discrete Fourier transform algorithm is not appropriate in analyzing the PPS. In this paper, the L-class of a fourth-order complex-lag polynomial Wigner-Ville distribution (PWVD) is presented to generate a high-resolution time-frequency distribution (TFD) for the multicomponent PPS. For a signal with polynomial phase up to order four (this is accurate enough in ISAR imaging), the cross-terms between different components can be reduced by the convolution in the frequency domain of the L-class of the fourth-order complex-lag PWVD. The new TFD is used in the ISAR imaging of the maneuvering target, and high-quality instantaneous ISAR images are obtained. Results of simulated and real data demonstrate the effectiveness of the method above. View full abstract»

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  • Forest Modeling For Height Inversion Using Single-Baseline InSAR/Pol-InSAR Data

    Page(s): 1528 - 1539
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    The Random Volume over Ground (RVoG) model has been extensively applied to polarimetric synthetic aperture radar interferometry (Pol-InSAR) data for forest height inversion. The model assumes forest as a homogeneous volume of randomly oriented particles characterized by a constant extinction but does not take into account the forest vertical heterogeneity, to which interferometric coherence is sensitive. In order to integrate vertical heterogeneity in forest models, two complementary models, which take into consideration the forest natural structure, are investigated through analysis of volume interferometric coherence. The first model assumes a vertically varying extinction in the volume layer, and the second model considers predominant contributions localized in a finite height interval, modeled as a Gaussian-distributed backscatter. The two forest models are compared with constant extinction RVoG in the coherence and interferometric phase aspects. Finally, the contribution of these new models for forest height inversion using the Pol-InSAR technique is discussed in the context of a two-layer ground + canopy medium. View full abstract»

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  • A Bistatic SAR Raw Data Simulator Based on Inverse  \omega {-}k Algorithm

    Page(s): 1540 - 1547
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    A synthetic aperture radar (SAR) raw data simulator is an important tool for testing the system parameters and the imaging algorithms. In this paper, a scene raw data simulator based on an inverse ω-k algorithm for bistatic SAR of a translational invariant case is proposed. The differences between simulations of monostatic and bistatic SAR are also described. The algorithm proposed has high precision and can be used in long-baseline configuration and for single-pass interferometry. Implementation details are described, and plenty of simulation results are provided to validate the algorithm. View full abstract»

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  • Bistatic Scattering of GPS Signals Off Arctic Sea Ice

    Page(s): 1548 - 1553
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (669 KB) |  | HTML iconHTML  

    This paper evaluates the potential of a global positioning system (GPS) bistatic radar for the retrieval of information concerning the presence and condition of sea ice cover. For this purpose, the permittivity and roughness of a ground scattering target at L-band are extracted from reflected GPS waveforms collected from an airborne platform using the Kirchhoff approximation for the surface cross section. The retrieved GPS estimates are then evaluated against collocated measurements of surface roughness obtained from a lidar profiler and a reference classification of sea ice types inferred from a multisensor data set that includes polarimetric microwave emissions, RADARSAT backscatter, and Moderate Resolution Imaging Spectroradiometer infrared/visible imagery. View full abstract»

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  • Segmentation and Reconstruction of Polyhedral Building Roofs From Aerial Lidar Point Clouds

    Page(s): 1554 - 1567
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2232 KB) |  | HTML iconHTML  

    This paper presents a solution framework for the segmentation and reconstruction of polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The eigenanalysis is first carried out for each roof point of a building within its Voronoi neighborhood. Such analysis not only yields the surface normal for each lidar point but also separates the lidar points into planar and nonplanar ones. In the second step, the surface normals of all planar points are clustered with the fuzzy k-means method. To optimize this clustering process, a potential-based approach is used to estimate the number of clusters, while considering both geometry and topology for the cluster similarity. The final step of segmentation separates the parallel and coplanar segments based on their distances and connectivity, respectively. Building reconstruction starts with forming an adjacency matrix that represents the connectivity of the segmented planar segments. A roof interior vertex is determined by intersecting all planar segments that meet at one point, whereas constraints in the form of vertical walls or boundary are applied to determine the vertices on the building outline. Finally, an extended boundary regularization approach is developed based on multiple parallel and perpendicular line pairs to achieve topologically consistent and geometrically correct building models. This paper describes the detail principles and implementation steps for the aforementioned solution framework. Results of a number of buildings with diverse roof complexities are presented and evaluated. View full abstract»

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  • Terrain Modeling From Lidar Range Data in Natural Landscapes: A Predictive and Bayesian Framework

    Page(s): 1568 - 1578
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2644 KB) |  | HTML iconHTML  

    The Earth's topography, including vegetation and human-made features, reduced to a virtual 3-D representation is a key geographic layer for any extended development or risk management project. Processed from multiple aerial images or from airborne lidar systems, the 3-D topography is first represented as a point cloud. This paper deals with the generation of digital terrain models (DTMs) in natural landscapes. We present a global methodology for estimating the terrain height by deriving a predictive filter paradigm. Under the assumption that the terrain topography (elevation and slope) is regular in a neighboring system, a predictive filter combines linearly the predicted topographic values and the effective measured values. In this paper, such a filter is applied to 3-D lidar data which are known to be of high elevation accuracy. The algorithm generates an adaptive local geometry wherein the elevation distribution of the point cloud is analyzed. Since local terrain elevations depend on the local slope, a predictive filter is first applied on the slopes and then on the terrain elevations. The algorithm propagates through the point cloud following specific rules in order to optimize the probability of computing areas containing terrain points. Considered as an initial surface, the previous DTM is finally regularized in a Bayesian framework. Our approach is based on the definition of an energy function that manages the evolution of a terrain surface. The energy is designed as a compromise between a data attraction term and a regularization term. The minimum of this energy corresponds to the final terrain surface. The methodology is discussed, and some conclusive results are presented on vegetated mountainous areas. View full abstract»

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  • Bayesian Estimation of Optical Properties of Nearshore Estuarine Waters: A Gibbs Sampling Approach

    Page(s): 1579 - 1587
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (680 KB) |  | HTML iconHTML  

    A novel approach is developed for the retrieval of inherent optical properties of coastal water, from which water-quality constituent concentrations can be obtained. The technique combines an analytical bio-optical model with statistical modeling for the formulation of posterior probability distributions of phytoplankton absorption, backscattering, and colored dissolved organic matter absorption; a Gibbs Sampler is employed for optimization. In contrast to other methods that typically provide point estimates of the unknown parameters, the proposed method estimates posterior distributions of the parameters, quantifying the uncertainty present in the problem and revealing correlation patterns. The method is tested successfully on synthetic reflectance data and real data measured in situ in the Hudson/Raritan Estuary of New York-New Jersey. View full abstract»

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Aims & Scope

 

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

 

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Meet Our Editors

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