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Geoscience and Remote Sensing, IEEE Transactions on

Issue 1 • Date Jan. 2004

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

    Publication Year: 2004 , Page(s): 01
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensinig Publication Information

    Publication Year: 2004 , Page(s): 0_2
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  • Table of contents

    Publication Year: 2004 , Page(s): 1 - 2
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  • A new hybrid-beam data acquisition strategy to support ScanSAR radiometric calibration

    Publication Year: 2004 , Page(s): 3 - 13
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (744 KB) |  | HTML iconHTML  

    Wide-swath synthetic aperture radar (SAR) coverage is provided by RADARSAT using a multiple-beam scanning strategy called ScanSAR. Each beam covers a different range, and is allocated a fixed period of time in which to transmit and receive radar pulses. During SAR processing, the data from each beam must be "stitched" together to form a complete image of the scanned area. This data must be radiometrically calibrated to compensate for antenna beam patterns. However, incorrect measurements of the satellite roll angle cause errors in radiometric calibration, and can lead to visible artifacts in the image (e.g. banding). A new ScanSAR data acquisition technique is proposed that improves roll angle estimation through the use of radar pulses, transmitted by one beam and received by another. The new data are called "hybrid beam data" and can be utilized with modified versions of existing roll estimation algorithms. This paper shows how the hybrid beam data are collected, accommodating pulse repetition frequency, range gate delay, and other timing changes as beams are switched. View full abstract»

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  • Doppler centroid estimation for ScanSAR data

    Publication Year: 2004 , Page(s): 14 - 23
    Cited by:  Papers (7)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    We introduce a novel accurate technique to estimate the Doppler centroid (DC) in ScanSAR missions. The technique starts from the ambiguous DC measures in the subswaths and uses a method alternative to standard unwrapping to undo the jumps in estimates induced by modulo pulse repetition frequency (PRF) measures. The proposed alternative is less error prone than the usual unwrapping techniques. Doppler Ambiguity is then solved by implementing a maximum-likelihood estimate that exploits the different PRFs used in different subswaths. An azimuth pointing of the antenna that does not change with subswaths, or that changes in a known way, is assumed. However, if the PRF diversity is strong enough, unknown small changes in azimuth pointing are tolerated and accurately estimated. This estimator is much simpler and more efficient, than those in the literature. Results achieved with both RADARSAT 1 and ENVISAT ScanSAR data are reported. View full abstract»

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  • On neural network algorithms for retrieving forest biomass from SAR data

    Publication Year: 2004 , Page(s): 24 - 34
    Cited by:  Papers (21)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (744 KB) |  | HTML iconHTML  

    We discuss the application of neural network algorithms (NNAs) for retrieving forest biomass from multifrequency (L- and P-band) multipolarization (hh, vv, and vv) backscattering. After discussing the training and pruning procedures, we examine the performances of neural algorithms in inverting combinations of radar backscattering coefficients at different frequencies and polarization states. The analysis includes an evaluation of the expected sensitivity of the algorithm to measurement noise stemming both from speckle and from fluctuations of vegetation and soil parameters. The NNA accomplishments are compared with those of linear regressions for the same channel combinations. The application of NNAs to invert actual multifrequency multipolarization measurements reported in literature is then considered. The NNA retrieval accuracy is now compared with those yielded by linear and nonlinear regressions and by a model-based technique. A direct analysis of the information content of the radar measurements is finally carried out through an extended pruning procedure of the net. View full abstract»

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  • Wheat cycle monitoring using radar data and a neural network trained by a model

    Publication Year: 2004 , Page(s): 35 - 44
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB) |  | HTML iconHTML  

    This paper describes an algorithm aimed at monitoring the soil moisture and the growth cycle of wheat fields using radar data. The algorithm is based on neural networks trained by model simulations and multitemporal ground data measured on fields taken as a reference. The backscatter of wheat canopies is modeled by a discrete approach, based on the radiative transfer theory and including multiple scattering effects. European Remote Sensing satellite synthetic aperture radar signatures and detailed ground truth, collected over wheat fields at the Great Driffield (U.K.) site, are used to test the model and train the networks. Multitemporal, multifrequency data collected by the Radiometer-Scatterometer (RASAM) instrument at the Central Plain site are used to test the retrieval algorithm. View full abstract»

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  • Directional borehole radar with dipole antenna array using optical modulators

    Publication Year: 2004 , Page(s): 45 - 58
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (872 KB) |  | HTML iconHTML  

    In this paper, we describe a directional borehole radar comprising a dipole antenna array with an optical modulator capable of determining the position of targets in three dimensions (3-D). Optical modulators using a Mach-Zehnder interferometer are used to transform electrical signals into optical signals at the feeding points of the dipole antennas. The advantages of using these modulators are that we can easily arrange the dipole antennas in a borehole, and that we can expect a good agreement between the experimental data and a theoretical model representing the array. We have made a prototype borehole radar system with five dipole antennas for the reception. In order to model the antennas, we used the method of moment (MoM), utilizing a modified Green's function for dipole antennas in multiple cylindrical layers. The Green's function is evaluated analytically by numerical integration. Cross-hole and single-hole measurements were carried out in granite at the Kamaishi mine (Iwate, Japan), and we obtained good agreement between the experimental data and the MoM results. After applying superresolution techniques to the data received by the array, we estimated the 3-D scattering position of a geological interface in granite. The results were in fairly good agreement with borehole scanner images. View full abstract»

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  • A study of scattering from an object below a rough surface

    Publication Year: 2004 , Page(s): 59 - 66
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (432 KB) |  | HTML iconHTML  

    A numerical model is applied in a Monte Carlo study of scattering from a three dimensional penetrable object below a lossy dielectric rough interface. Both time and frequency domain results are investigated to illustrate the relative importance of coherent and incoherent scattering effects in the sample problem considered. Results show that introducing a reduced transmission coefficient is reasonable for object coherent scattering predictions in this example, and that incoherent object/surface interaction effects approximately follow a simple scaling behavior as surface roughness is increased. View full abstract»

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  • Polarimetric scattering from two-layered two-dimensional random rough surfaces with and without buried objects

    Publication Year: 2004 , Page(s): 67 - 76
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB) |  | HTML iconHTML  

    A three-dimensional polarimetric analysis of the two-layered rough ground with and without buried objects is investigated here. A rigorous electromagnetic surface integral-equation-based model is used in this analysis. The statistical average of the polarimetric scattering matrix elements is computed based on the Monte Carlo simulations for both the vertically and horizontally polarized incident waves. The results show a significant impact on the scattered intensities due to the two-layer nature of the ground. However, these intensities show almost no difference between the ground signature with or without the object. On the other hand, the statistical average of the covariance matrix elements shows a distinct difference between these two signatures despite the small size of the buried object. View full abstract»

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  • Scattering from natural soils modeled by dielectric fractal profiles: the forward-backward approach

    Publication Year: 2004 , Page(s): 77 - 85
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB) |  | HTML iconHTML  

    The forward-backward (FB) method is an efficient technique for numerical evaluation of electromagnetic scattering from rough surfaces. In its usual formulation, this technique can be only applied to perfectly or highly conducting surfaces. In addition, up to now FB has been employed to compute scattering from surfaces modeled by Gaussian stochastic processes with Gaussian or Pierson-Moscowitz spectra. Accordingly, this technique can be fruitfully used for numerical simulations of scattering from sea surfaces. However, in order to properly deal with natural soil surfaces, extension to the dielectric interface case and to fractal surface models is needed. Extension of the FB method to the dielectric interface case has been recently presented, whereas application to fractal surface models is presented here. Original contribution of the present paper is twofold. First of all, the FB method for dielectric profiles is framed within the theory of iterative methods for the solution of linear systems. In addition, application of the FB method to dielectric band-limited fractional Brownian motion fractal one-dimensional surfaces is explored. Numerical experiments show that, for most of realistic values of dielectric constant and fractal parameters actually encountered for natural soil profiles, the FB method is very rapidly convergent, and its results are in perfect agreement with "exact" ones (i.e. with results of method of moments solved via a direct method). View full abstract»

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  • Exploration of factors limiting biomass estimation by polarimetric radar in tropical forests

    Publication Year: 2004 , Page(s): 86 - 104
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1592 KB) |  | HTML iconHTML  

    Direct inversion of radar return signals for forest biomass estimation is limited by signal saturation at medium biomass levels (roughly 150 ton/ha for P-band). Disturbing factors such as forest structural differences - and, notably, at low biomass levels, terrain roughness, and soil moisture variation - cause further complications. A new and indirect inversion approach is proposed that may circumvent such problems. Using multifrequency polarimetric radar the forest structure can be assessed accurately. Ecological relationships link these structures with biomass levels, even for high biomass levels. The LIFEFORM model is introduced as a new approach to transform field observations of the complex tropical forest into input files for the theoretical UTARTCAN polarimetric backscatter model. The validity of UTARTCAN for a wide range of forest structures is shown. Backscatter simulations for a wide range of forest structures, terrain roughness, and soil moisture clearly show the limitations of the direct approach and the validity of the proposed indirect approach up to very high levels of biomass. View full abstract»

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  • Ionospheric effects for L-band 2-D interferometric radiometry

    Publication Year: 2004 , Page(s): 105 - 118
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (928 KB) |  | HTML iconHTML  

    Ionospheric effects are a potential error source for the estimation of surface quantities such as sea surface salinity, using L-band radiometry. This study is carried out in the context of the SMOS future space mission, which uses an interferometric radiometer. We first describe the way the Faraday rotation angle due to electron content along the observing path varies across the two-dimensional field of view. Over open ocean surfaces, we show that it is possible to retrieve the total electron content (TEC) at nadir from radiometric data considered over the bulk of the field of view, with an accuracy better than 0.5 TEC units, compatible with requirements for surface salinity observations. Using a full-polarimetric design improves the accuracy on the estimated TEC value. The random uncertainty on retrieved salinity is decreased by about 15% with respect to results obtained when using only data for the first Stokes parameter, which is immune to Faraday rotation. Similarly, TEC values over land surfaces may be retrieved with the accuracy required in the context of soil moisture measurements. Finally, direct TEC estimation provides information which should allow to correct for ionospheric attenuation as well. View full abstract»

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  • Galactic noise and passive microwave remote sensing from space at L-band

    Publication Year: 2004 , Page(s): 119 - 129
    Cited by:  Papers (37)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    The spectral window at L-band (1.413 GHz) is important for passive remote sensing of soil moisture and ocean salinity from space, parameters that are needed to understand the hydrological cycle and ocean circulation. At this frequency, radiation from celestial (mostly Galactic) sources is strong and, unlike the constant cosmic background, this radiation is spatially variable. This paper presents a modern radiometric map of the celestial sky at L-band and a solution for the problem of determining what portion of the sky is seen by a down-looking radiometer in orbit. The data for the radiometric map are derived from recent radio astronomy surveys and are presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Near the Galactic plane, the contribution can exceed several kelvin. View full abstract»

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  • Sensitivity analyses of satellite rainfall retrieval and sampling error on flood prediction uncertainty

    Publication Year: 2004 , Page(s): 130 - 139
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB) |  | HTML iconHTML  

    The Global Precipitation Measurement mission planned jointly by the United States, Japanese, and European space agencies envisions providing global rainfall products from a constellation of passive microwave (PM) satellite sensors at time scales ranging from 3-6 h. In this paper, a sensitivity analysis was carried out to understand the implication of satellite PM rainfall retrieval and sampling errors on flood prediction uncertainty for medium-sized (∼100 km2) watersheds. The 3-h rainfall sampling gave comparable flood prediction uncertainties with respect to the hourly sampling, typically used in runoff modeling, for a major flood event in Northern Italy. The runoff prediction error, though, was magnified up to a factor of 3 when rainfall estimates were derived from 6-h PM sampling intervals. The systematic and random error components in PM retrieval are shown to interact with PM sampling introducing added uncertainty in runoff simulation. The temporal correlation in the PM retrieval error was found to have a negligible effect in runoff prediction. It is shown that merging rain retrievals from hourly infrared (IR) and PM observations generally reduces flood prediction uncertainty. The error reduction varied between 50% (0%) and 80% (50%) for the 6-h (3-h) PM sampling scenarios, depending on the relative magnitudes of PM and IR retrieval errors. Findings from this paper are potentially useful for the design, planning, and application assessment of satellite remote sensing in flood and flash flood forecasting. View full abstract»

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  • Comparative evaluation of seasonal patterns in long time series of satellite image data and simulations of a global vegetation model

    Publication Year: 2004 , Page(s): 140 - 153
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2648 KB) |  | HTML iconHTML  

    A method has been developed and tested for comparing the complex spatio-temporal patterns present in two long time series of data of the seasonal cycles of vegetation for a large part of the global land surface. These two datasets are derived from global satellite observations (Advanced Very High Resolution Radiometer time series) and from a leading biogeochemical process model of global vegetation [Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM)], respectively. The datasets are completely independent of each other. The parameter compared is the fraction of photosynthetically active radiation. The comparison yields comparative parameters that quantify the differences between the two datasets. These comparative parameter images provide sufficient compression that they can be used for visual analysis so as to better understand the compatibility of, and the discrepancies between, the two datasets. The analysis shows that the LPJ model generally produces good correspondence with natural vegetation where the latter is primarily dependent upon climate. The correspondence was not as good where altitude, geomorphology, or hydrology of an area are the primary determinants of vegetation status. Due to a lack of representation of agriculture in the model, the correspondence with actual vegetative status was also poor where there is significant agricultural activity in an area. View full abstract»

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  • The effect of solar illumination angle and sensor view angle on observed patterns of spatial structure in tallgrass prairie

    Publication Year: 2004 , Page(s): 154 - 165
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB) |  | HTML iconHTML  

    While it has long been recognized that the anisotropic reflectance properties of a natural surface affect the intensity and spectral distribution of radiance received by a remote sensing instrument, the effects of canopy reflectance geometry on the observed spatial structure of canopy reflectance have not adequately been evaluated. In this paper, near-surface spectrometers were used as part of two experiments to evaluate the systematic variations in the sun-target-sensor geometry on semivariogram metrics (range, sill+nugget variance) summarizing the spatial structure observed in a tallgrass prairie canopy. In the first experiment, reflectance measurements and normalized difference vegetation index (NDVI) values were collected at five sensor viewing angles (-50°, -25°, 0°, 25°, and 50°) from six measurement grids representing three burn treatments and two slope/aspect situations. In the second experiment, data were collected at 2-h intervals, beginning at ≈0800 LST from the same grids with the radiometer at nadir, allowing the spatial structure of reflectance and NDVI to be observed under naturally changing illumination. Results of the geostatistical analysis show that both the range and sill+nugget variance values change with viewing angle. These effects were consistent across all treatments and slope/aspect combinations. However, when viewed from nadir, the sill+nugget variance values of the canopy changed with solar illumination angle and the range values remained nearly constant. These relationships were also observed across all treatments and slope/aspect combinations. The results suggest that sill+nugget values for the same surface may not be directly comparable if not acquired under very similar view angle and illumination conditions. Range values are comparable if the nadir view is used, but not under off-nadir viewing conditions. The implications of these findings point to the need for caution in interpreting spatial structure derived from close-range radiometry or from satellite/aircraft instruments with cross-track or off-nadir pointing capabilities, and in the comparison of images acquired under varying illumination conditions. View full abstract»

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  • Vegetation isoline equations for an atmosphere-canopy-soil system

    Publication Year: 2004 , Page(s): 166 - 175
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    The relationship between the reflectances at two different wavelengths over a three-layer system comprising atmosphere, canopy, and soil layers is derived. This work is an extension of the isoline equation previously derived in a red and near-infrared (NIR) reflectance space for a canopy-soil system. As a result of retaining only the zeroth and first-order interaction terms between the layers, the relationship has a linear form in which the slope and offset are functions of the optical properties of each layer. Numerical examples of isolines based on the derived expressions are obtained under various conditions and are shown to demonstrate some of the known behaviors of isolines. Since the derived expression relates a pair of reflectances, it is expected to be useful for the analysis of satellite data products involving algebraic manipulations of spectral reflectances, such as spectral vegetation indexes. View full abstract»

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  • Evaluation of radiative transfer simulations over bright desert calibration sites

    Publication Year: 2004 , Page(s): 176 - 187
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (832 KB) |  | HTML iconHTML  

    The Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Meteosat Second Generation main radiometer, measures the reflected solar radiation within three spectral bands centered at 0.6, 0.8, and 1.6 μm, and within a broadband. This broadband is similar to the solar channel of the radiometer onboard the first generation of METEOSAT satellites. The operational absolute calibration of these channels relies on modeled radiances over bright desert sites, as no in-flight calibration device is available. These simulated radiances represent, therefore, the "reference" against which SEVIRI is calibrated. The present study describes the radiative properties of these targets and evaluates the uncertainties associated with the characterization of this "reference", i.e. the modeled radiances. To this end, top-of-atmosphere simulated radiances are compared with several thousands of calibrated observations acquired by the European Remote Sensing 2/Along-Track Scanning Radiometer 2 (ERS2/ATSR-2), SeaStar/Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Syste`me Pour l'Observation de la Terre 4 (SPOT-4/VEGETATION), and the Environmental Research Satellite/Medium Resolution Imaging Spectrometer (ENVISAT/MERIS) instruments over the SEVIRI desert calibration sites. Results show that the mean relative bias between observation and simulation does not exceed 3% in the red and near-infrared spectral bands with respect to the first two instruments. View full abstract»

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  • Bayesian-based subpixel brightness temperature estimation from multichannel infrared GOES radiometer data

    Publication Year: 2004 , Page(s): 188 - 201
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    In this paper, a new image reconstruction scheme is devised for estimating a high-resolution temperature map of the top of the Earth's atmosphere using the Geostationary Operational Environmental Satellite (GOES) imager infrared channels 4 and 5. By simultaneously interpolating the image while estimating temperature, the proposed algorithm achieves a more accurate estimate of the subpixel temperatures than could be obtained by performing these operations independently of one another. The proposed algorithm differs from other Bayesian-based image interpolation schemes in that it estimates brightness temperature as opposed to image intensity and incorporates a detailed optical model of the GOES multichannel imaging system. In order to test the effectiveness of the proposed technique, high-resolution estimates of cloudtop temperatures using GOES channels 4 and 5 are compared to temperature estimates obtained from the Advanced Very High Resolution Radiometer (AVHRR). This test is achieved by examining sets of infrared data taken simultaneously by the GOES and AVHRR systems over the same geographic area. The AVHRR system collects longwave infrared data with a spatial resolution of 1 km, which is higher than the 4-km spatial resolution the GOES system achieves. In some cases, The estimated temperature differences between these systems are as high as 11.5 K. It is shown in this paper that the proposed algorithm improves the consistency between the cloudtop temperatures estimated with the GOES and AVHRR systems by allowing the GOES system to achieve substantially higher spatial resolution. View full abstract»

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  • Spin motion and orientation of LAGEOS-2 from photometric observation

    Publication Year: 2004 , Page(s): 202 - 208
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    The spin rate and spin axis orientation of the Laser Geodynamics Satellite 2 (LAGEOS-2) satellite were determined by analysis of photometric observation data. A photometer system developed at the Space Geodesy Facility at Herstmonceux, U.K., was used to time solar glints from the rotating satellite. It was found that the spin rate of LAGEOS-2 slowed by 38% per year between March 2000 and November 2002 and that the spin axis undergoes a slow, complex precession with respect to the Earth's rotation axis. Moreover, the analysis revealed that the direction of the spin was the reverse of that of the Earth's rotation and that the optical alignment of a reflector surface on LAGEOS-2 can deviate from its position vector by up to 15 arcmin. View full abstract»

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  • Geometric accuracy of Ikonos: zoom in

    Publication Year: 2004 , Page(s): 209 - 214
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB) |  | HTML iconHTML  

    Pioneering in the world, the high-resolution satellite Ikonos imagery has revolutionary changed the market - users now have the unique opportunity to get satellite images with spatial resolution comparable to middle-scale aerial photos. In our study, we tried to find an answer why such images, having submetre spatial resolution, still contain planimetric errors measured in dozens and even hundreds of metres. This paper is aimed at to not only show to potential users of high-resolution satellite images the main sources of image geometric distortions, but to uncover the errors, hardly to be corrected without possessing precise information about particular conditions on the spot at the moment of image acquisition, and evaluate sensibility of the corresponding image correction models for variations of such data. View full abstract»

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  • Comparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery

    Publication Year: 2004 , Page(s): 215 - 228
    Cited by:  Papers (53)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2608 KB) |  | HTML iconHTML  

    This paper compares the discrimination ability of two texture analysis methods: Markov random fields (MRFs) and gray-level cooccurrence probabilities (GLCPs). There exists limited published research comparing different texture methods, especially with regard to segmenting remotely sensed imagery. The role of window size in texture feature consistency and separability as well as the role in handling of multiple textures within a window are investigated. Necessary testing is performed on samples of synthetic (MRF generated), Brodatz, and synthetic aperture radar (SAR) sea ice imagery. GLCPs are demonstrated to have improved discrimination ability relative to MRFs with decreasing window size, which is important when performing image segmentation. On the other hand, GLCPs are more sensitive to texture boundary confusion than MRFs given their respective segmentation procedures. View full abstract»

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  • ARKTOS: an intelligent system for SAR sea ice image classification

    Publication Year: 2004 , Page(s): 229 - 248
    Cited by:  Papers (31)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1648 KB)  

    We present an intelligent system for satellite sea ice image analysis named Advanced Reasoning using Knowledge for Typing Of Sea ice (ARKTOS). ARKTOS performs fully automated analysis of synthetic aperture radar (SAR) sea ice images by mimicking the reasoning process of sea ice experts. ARKTOS automatically segments a SAR image of sea ice, generates descriptors for the segments of the image, and then uses expert system rules to classify these sea ice features. ARKTOS also utilizes multisource data fusion to improve classification and performs belief handling using Dempster-Shafer. As a software package, ARKTOS comprises components in image processing, rule-based classification, multisource data fusion, and graphical user interface-based knowledge engineering and modification. As a research project over the past ten years, ARKTOS has undergone phases such as knowledge acquisition, prototyping, refinement, evaluation, deployment, and operationalization at the U.S. National Ice Center. In this paper, we focus on the methodology, evaluations, and classification results of ARKTOS. View full abstract»

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  • Discrimination mode processing for EMI and GPR sensors for hand-held land mine detection

    Publication Year: 2004 , Page(s): 249 - 263
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    Signal processing algorithms for hand-held mine detection sensors are described. The goals of the algorithms are to provide alarms to a human operator indicating the likelihood of the presence of a buried mine. Two modes of operations are considered: search mode and discrimination mode. Search mode generates an initial detection at a suspected location and discrimination mode confirms that the suspected location contains a land mine. Search mode requires that the signal processing algorithm generate a detection confidence value immediately at the current sample location and no delay in producing an alarm confidence is tolerable. Search mode detection has a high false-alarm rate. Discrimination mode allows the operator to interrogate the entire suspected location to eliminate false alarms. It does not require that the signal processing algorithm produce an alarm confidence immediately for the current sample location, but rather allows the system to process all the data acquired over the region before producing an alarm. This paper proposes discrimination mode processing algorithms for metal detectors (MDs), or electromagnetic induction sensors (EMIs), ground-penetrating radars (GPRs), and their fusion. The MD discrimination mode algorithm employs a model-based approach and uses the target model parameters to discriminate between mines and clutter objects. The GPR discrimination mode algorithm uses the consistency of detection as well as the shape of the detection peaks over several sweeps to improve the discrimination accuracy. The performances of the proposed algorithms were examined on a dataset collected at a government test site, and performance was compared with baseline techniques. Experimental results showed that the proposed method can reduce the probability of false alarm by as much as 70% at a 100% correct detection rate and performed comparable to the best human operator on a blind test with data collected at approximately 1000 locations. View full abstract»

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Aims & Scope

 

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

 

Full Aims & Scope

Meet Our Editors

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