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Geoscience and Remote Sensing, IEEE Transactions on

Issue 12  Part 1 • Date Dec. 2003

 This issue contains several parts.Go to:  Part 2 

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Displaying Results 1 - 25 of 26
  • Satellite-based columnar water vapor retrieval with the multi-spectral thermal imager (MTI)

    Publication Year: 2003 , Page(s): 2767 - 2770
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (259 KB)  

    The Multi-spectral Thermal Imager (MTI) has three near-infrared bands (E, F, and G) within the 850-1050-nm spectral range that are used for the columnar water vapor (CWV) retrieval using the continuum interpolated band ratio (CIBR) and the atmospheric precorrected differential absorption (APDA) methods. The retrieved CWV amounts are compared with the aerosol robotic network (AERONET) measurements at the Oklahoma Atmospheric Radiation Measurement (ARM) program and the Stennis Space Center sites. We find no significant difference in the accuracy of the two tested methods. However, there is a considerable difference in the root mean square error (RMSE) for the CWV retrieval over the Oklahoma ARM and the Stennis Space Center sites. The overall RMSE of the MTI CWV retrieval is found to be 13% to 14%. The error is reduced to 11% to 12% for CWV amounts larger then 1 g/cm2. View full abstract»

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  • Maximum-likelihood estimation of specific differential phase and attenuation in rain

    Publication Year: 2003 , Page(s): 2771 - 2782
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (778 KB) |  | HTML iconHTML  

    Precise estimation of propagation parameters in precipitation media is of interest to improve the performance of communications systems and in remote sensing applications. In this paper, we present maximum-likelihood estimators of specific attenuation and specific differential phase in rain. The model used for obtaining the cited estimators assumes coherent propagation, reflection symmetry of the medium, and Gaussian statistics of the scattering matrix measurements. No assumptions about the microphysical properties of the medium are needed. The performance of the estimators is evaluated through simulated data. Results show negligible estimators bias and variances close to Cramer-Rao bounds. View full abstract»

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  • SOFM-MLP: a hybrid neural network for atmospheric temperature prediction

    Publication Year: 2003 , Page(s): 2783 - 2791
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (637 KB) |  | HTML iconHTML  

    Here, first we study the effectiveness of multilayer perceptron networks (MLPs) for prediction of the maximum and the minimum temperatures based on past observations on various atmospheric parameters. To capture the seasonality of atmospheric data, with a view to improving the prediction accuracy, we then propose a novel neural architecture that combines a self-organizing feature map (SOFM) and MLPs to realize a hybrid network named SOFM-MLP with better performance. We also demonstrate that the use of appropriate features such as temperature gradient can not only reduce the number of features drastically, but also can improve the prediction accuracy. These observations inspired us to use a feature selection MLP (FSMLP) instead of MLP, which can select good features online while learning the prediction task. FSMLP is used as a preprocessor to select good features. The combined use of FSMLP and SOFM-MLP results in a network system that uses only very few inputs but can produce good prediction. View full abstract»

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  • On the use of complex SAR image spectral analysis for target detection: assessment of polarimetry

    Publication Year: 2003 , Page(s): 2725 - 2734
    Cited by:  Papers (30)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (764 KB) |  | HTML iconHTML  

    The objective of this paper is to assess the joint use of the magnitude and the phase of a synthetic aperture radar (SAR) polarimetric image for point target detection and analysis. We first consider a single-look complex (SLC), single polarized radar image including point targets embedded in clutter. A series of sublooks are generated from this SLC image, both in azimuth and in range in order to analyze the inherent speckle effects. The two-looks internal Hermitian product (2L-IHP) is defined and is further shown to qualitatively increase the target/environment contrast. The processing of azimuth and range spectra preliminary to the 2L-IHP derivation (spectral whitening, generation and overlapping of sublooks) is described. A simulation tool is developed to model a point target behavior. Then, the polarimetric extension of the 2L-IHP is proposed, and the optimized polarimetric 2L-IHP is defined. The gain is twofold: in comparison with single polarization, polarimetry is shown to enhance detection capabilities, but also to provide additional information for target analysis. View full abstract»

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  • Soil moisture retrieval using the passive/active L- and S-band radar/radiometer

    Publication Year: 2003 , Page(s): 2792 - 2801
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (519 KB) |  | HTML iconHTML  

    In the present study, remote sensing of soil moisture is carried out using the Passive and Active L- and S-band airborne sensor (PALS). The data in this paper were taken from five days of overflights near Chickasha, OK during the 1999 Southern Great Plains (SGP99) experiment. Presently, we analyze the collected data to understand the relationships between the observed signals (radiometer brightness temperature and radar backscatter) and surface parameters (surface soil moisture, temperature, vegetation water content, and roughness). In addition, a radiative transfer model and two radar backscatter models are used to simulate the PALS observations. An integration of observations, regression retrievals, and forward modeling is used to derive the best estimates of soil moisture under varying surface conditions. View full abstract»

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  • Faraday rotation effects on L-band spaceborne SAR data

    Publication Year: 2003 , Page(s): 2735 - 2744
    Cited by:  Papers (52)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (904 KB) |  | HTML iconHTML  

    Several proposed near-future spaceborne radar missions, such as the Advanced Land Observing Satellite (ALOS) and TerraSAR, will include an L-band instrument. At such low frequencies, the Faraday rotation in the ionosphere, which rotates the polarization plane of the radar signal, becomes an important consideration in instrument design. In this paper, both simple analytic approximations and numerical models are used to derive likely values of Faraday rotation and determine their impact on polarimetric imagery and derived products. One-way rotations exceeding 5° are likely to significantly reduce the accuracy of geophysical parameter recovery, such as forest biomass. On average, Faraday rotation can be neglected at solar minimum, but correction methods are needed at other times of the solar cycle and under disturbed conditions. Methods for implementing such corrections based on estimates of the Faraday rotation and prerotation of the transmitted signal are described. View full abstract»

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  • Electromagnetic detection of dielectric scatterers using phaseless synthetic and real data and the memetic algorithm

    Publication Year: 2003 , Page(s): 2745 - 2753
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (824 KB) |  | HTML iconHTML  

    Phaseless data are used to evaluate the application of an electromagnetic inverse-scattering-based procedure for the detection of cylindrical inhomogeneities, which are schematized as multilayer infinite dielectric cylinders with elliptic cross sections. The electromagnetic inverse problem is recast as a global optimization problem and iteratively solved by an efficient memetic algorithm, which combines deterministic and stochastic concepts. Moreover, a recursive analytical procedure is used for the forward-scattering computation. The possibility of localizing and reconstructing the scatterers by using phaseless input data, which would greatly simplify the design of the imaging apparatus, is evaluated both with reference to synthetically produced data and by means of experimental data obtained by a microwave tomograph. View full abstract»

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  • Application of the correlation theory of thermal regime and thermal radio emission for atmosphere

    Publication Year: 2003 , Page(s): 2754 - 2759
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (320 KB) |  | HTML iconHTML  

    The results obtained by application of the earlier developed stochastic theory of temperature distribution and thermal radio emission of medium (half-space) to atmosphere are presented. It was obtained that the exponential autocovariance function of the surface temperature is in good agreement with that determined from meteorological data (such covariance functions are inherent in random processes generated by the Poisson process). The theory offers a good qualitative explanation of the frequency and height dependencies of statistical parameters, and for some of these parameters there is a good quantitative agreement. The theoretically predicted effect of the time shift of the correlation functions maxima was discovered in the data. The theory was generalized for the spatial inhomogeneities of atmosphere, and the vertical correlation length of random atmosphere inhomogeneities was obtained as the geometric mean from the diffusion length and the horizontal correlation length of surface temperature. View full abstract»

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  • Target decomposition analysis of SIR-C imagery for characterization of scattering mechanisms and their dependence on observation parameters

    Publication Year: 2003 , Page(s): 2721 - 2724
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (719 KB) |  | HTML iconHTML  

    Multitemporal Shuttle Imaging Radar C (SIR-C) images taken over the Sarobetsu test site were analyzed using target decomposition to characterize the scattering mechanisms and relate them with the target conditions. Analysis results indicate a change in the dominant scattering mechanism with a change in the observation parameters, which is reasonably related with the surface conditions estimated from aerial photographs. View full abstract»

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  • Measurements of ocean surface waves and currents using L- and C-band along-track interferometric SAR

    Publication Year: 2003 , Page(s): 2821 - 2832
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2706 KB)  

    Along-track interferometric synthetic aperture radar (ATI-SAR) is an active coherent imaging system, utilizing two antennas separated along the platform flight direction. The phase information of ATI-SAR from the Doppler shift of the backscattered signal represents the line-of-sight velocity of the water scatterers. While the advent of ATI-SAR provided us with a potentially powerful technique for ocean surface current and wave mapping, the surface current has not been measured exactly from the ATI-SAR velocity because the Doppler shift is not simply proportional to the component of the mean surface current. It also includes other types of contributions associated with the phase velocity of the Bragg waves and orbital motions of all ocean waves that are longer than Bragg waves. In this paper, we review how the phase difference measured by ATI-SAR is related to the mean Doppler frequency, and we develop a new and practically useful method to extract the surface current component utilizing simultaneously measured L- and C-band ATI-SAR data. Since the measured ATI-SAR velocity shows a different value at a different radar-frequency, we investigate the influence of Bragg-resonant waves and long ocean wave motions on the ATI-SAR velocity according to the radar frequency. The Bragg-wave phase velocity component, which is a significant source of error for extracting the surface current, can be effectively eliminated by using L- and C-band ATI-SAR. The method is applied to L- and C-band ATI-SAR measurements acquired at the Ulsan coast in the southeastern part of the Korean peninsula. The resulting ocean surface current vectors are compared with in situ measurements collected by recording current meter. We furthermore extract ocean surface wave information from the ATI-SAR phase image using a quasi-linear transform. View full abstract»

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  • A cognitive pyramid for contextual classification of remote sensing images

    Publication Year: 2003 , Page(s): 2906 - 2922
    Cited by:  Papers (20)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2720 KB) |  | HTML iconHTML  

    Many cases of remote sensing classification present complicated patterns that cannot be identified on the basis of spectral data alone, but require contextual methods that base class discrimination on the spatial relationships between the individual pixel and local and global configurations of neighboring pixels. However, the use of contextual classification is still limited by critical issues, such as complexity and problem dependency. We propose here a contextual classification strategy for object recognition in remote sensing images in an attempt to solve recognition tasks operatively. The salient characteristics of the strategy are the definition of a multiresolution feature extraction procedure exploiting human perception and the use of soft neural classification based on the multilayer perceptron model. Three experiments were conducted to evaluate the performance of the methodology, one in an easily controlled domain using synthetic images, the other two in real domains involving builtup pattern recognition in panchromatic aerial photographs and high-resolution satellite images. View full abstract»

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  • Application of machine-learning techniques toward the creation of a consistent and calibrated global chlorophyll concentration baseline dataset using remotely sensed ocean color data

    Publication Year: 2003 , Page(s): 2844 - 2860
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (889 KB) |  | HTML iconHTML  

    This paper introduces a machine-learning approach to satellite ocean color sensor cross calibration. The cross-calibration objective is to eliminate incompatibilities among sensor data from different missions and produce merged daily global ocean color coverage. The approach is designed and investigated using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard of the Terra satellite and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Data from these two sensors show apparent discrepancies originating from differences in sensor design, calibration, processing algorithms, and from the rate of change in the atmosphere and ocean within 1(1/2) h between sensor imaging of the same regions on the ground. The discrepancies have complex, noisy, and often contradictory time and space variabilities. Support vector machines are used to bring MODIS data to the SeaWiFS representation where SeaWiFS data are considered to exemplify a consistent ocean color baseline. Support vector machines are effective in learning and resolving convoluted data relationships between the two sensors given a variety of bio-optical, atmospheric, viewing geometry, and ancillary information. The method works accurately in low chlorophyll waters and shows a potential to eliminate sensor problems, such as scan angle dependencies and seasonal and spatial trends in data. The results illustrate that MODIS and SeaWiFS differences are noisy and highly variable, which makes it difficult to extrapolate the cross-calibration knowledge onto new time and space domains and to define representative global ocean color datasets for support vector machine training. View full abstract»

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  • High-sensitivity radiometry of air-water interface fast temperature and heat flux variances

    Publication Year: 2003 , Page(s): 2760 - 2766
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (388 KB) |  | HTML iconHTML  

    Fast variances of temperature profile and heat flux through the water-air interface caused by atmospheric turbulence in weak wind conditions have been determined on the basis of measurements of radio brightness evolution of water at the frequencies of 60 and 131 GHz. Two components of the heat flux related to evaporation and to thermal conductivity have been obtained, which enabled us to determine evaporation rate and viscous sublayer depth variances. Statistical parameters of water surface temperature variations have been calculated. View full abstract»

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  • A new polarimetric classification approach evaluated for agricultural crops

    Publication Year: 2003 , Page(s): 2881 - 2889
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1024 KB) |  | HTML iconHTML  

    Statistical properties of the polarimetric backscatter behavior for a single homogeneous area with constant radar reflectivity are described by the Wishart distribution or its marginal distributions. These distributions do not necessarily well describe the statistics for a collection of homogeneous areas of the same class because of variation in, for example, biophysical parameters. Using Kolmogorov-Smirnov (KS) tests of fit, it is shown that, for example, the Beta distribution is a better descriptor for the polarimetric correlation, and the log-normal distribution for the backscatter level. An evaluation is given for a number of agricultural crop classes, grasslands, and fruit tree plantations at the Flevoland test site, using an AirSAR (C-, L- and P-band polarimetric) image from July 3, 1991. A new reversible transform of the covariance matrix into backscatter intensities will be introduced in order to describe the full polarimetric target properties in a mathematically alternative way, allowing for the development of simple, versatile, and robust classifiers. Moreover, it allows for polarimetric image segmentation using conventional approaches. The effect of azimuthally asymmetric backscatter behavior on the classification results is discussed. Several models are proposed, and results are compared with results from the literature for the same test site. It can be concluded that the introduced classifiers perform very well, with levels of accuracy for this test site, with 14 cover types, of 90.4% for C-band, 88.7% for L-band, and 96.3% for the combination of C- and L-band. View full abstract»

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  • Use of the novelty detection technique to identify the range of applicability of empirical ocean color algorithms

    Publication Year: 2003 , Page(s): 2833 - 2843
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (725 KB) |  | HTML iconHTML  

    Novelty detection is used to identify the range of applicability of empirical ocean color algorithms. This method is based on the assumption that the level of accuracy of the algorithm output depends on the representativeness of inputs in the training dataset. The effectiveness of the novelty detection method is assessed using two datasets: one representative of the northern Adriatic Sea coastal waters and the other representative of open sea waters. The two datasets are independently used to develop neural network algorithms for the retrieval of chlorophyll-a concentration (Chl-a). The range of applicability of the individual algorithms is presented using remote sensing data derived from the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) for three selected regions: the central Mediterranean Sea, the North Sea, and the Baltic Sea. An extension of the novelty detection technique is also proposed to blend the individual algorithms and to avoid discontinuities in the resulting Chl-a maps. View full abstract»

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  • Noise Radar for range/Doppler processing and digital beamforming using low-bit ADC

    Publication Year: 2003 , Page(s): 2703 - 2720
    Cited by:  Papers (31)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1616 KB) |  | HTML iconHTML  

    Pulse compression radar is used in a great number of radar applications. Excellent range resolution and high resistance to electronic countermeasures (ECM) can be achieved by long wideband modulated pulses, which spread out the transmitted energy in frequency and time. By using random noise as the waveform, the range ambiguity can be suppressed as well. In this paper, noise radar for Doppler/range indication and digital beamforming is described. Main factors influencing the resolution and sidelobe level in range and Doppler are surveyed. In particular, the possible use of binary or low-bit analog-to-digital converters (ADCs) in noise radar is analyzed, which highly improves the signal-processing rate and reduces the costs. The very significant improvement of sidelobe suppression, when an extra noise signal is added before ADC, is explained theoretically and confirmed by simulation results. Mostly, the random signal is transmitted directly from a noise generating high-frequency source. A sine wave, which is phase or frequency modulated by random noise, is an alternative, giving lower range sidelobes, and higher transmitted mean power when peak-limited transmitters are applied. The dynamic requirements and the bandwidth of the modulating signal can be reduced as well. View full abstract»

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  • Information mining in remote sensing image archives: system concepts

    Publication Year: 2003 , Page(s): 2923 - 2936
    Cited by:  Papers (79)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1806 KB) |  | HTML iconHTML  

    In this paper, we demonstrate the concepts of a prototype of a knowledge-driven content-based information mining system produced to manage and explore large volumes of remote sensing image data. The system consists of a computationally intensive offline part and an online interface. The offline part aims at the extraction of primitive image features, their compression, and data reduction, the generation of a completely unsupervised image content-index, and the ingestion of the catalogue entry in the database management system. Then, the user's interests-semantic interpretations of the image content-are linked with Bayesian networks to the content-index. Since this calculation is only based on a few training samples, the link can be computed online, and the complete image archive can be searched for images that contain the defined cover type. Practical applications exemplified with different remote sensing datasets show the potential of the system. View full abstract»

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  • Calibrating the Quikscat/SeaWinds Radar for measuring rainrate over the oceans

    Publication Year: 2003 , Page(s): 2814 - 2820
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (807 KB) |  | HTML iconHTML  

    This effort continues a study of the effects of rain, over the oceans, on the signal retrieved by the SeaWinds scatterometer. It is determined that the backscatter radar cross section can be used to estimate the volumetric rain rate, averaged horizontally, across the surface resolution cells of the scatterometer. The dual polarization of the radar has a key role in developing this capability. The relative magnitudes of the radar backscatter depends on the volumetric rain rate, the rain column height and surface wind velocity, the viewing angle, as well as the polarization (due to the oblateness of raindrops at the higher rain rates). The approach to calibrating the SeaWinds normalized radar cross section (NRCS) is to collect National Weather Service Next Generation Weather Radar (NEXRAD) radar-derived rain rate measurements (4-km spatial resolution and 6-min rotating cycles) colocated in space (offshore) and time with scatterometer observations. These calibration functions lead to a Z-R relationship, which is then used at mid-ocean locations to estimate the rain rate in 0.25° or larger resolution cells, which are compared with Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) rain estimates. Experimental results to date are in general agreement with simplified theoretical models of backscatter from rain, for this frequency, 14 GHz. These comparisons show very good agreement on a cell-by-cell basis with the TMI estimates for both wide areas (1000 km) and smaller area rain events. View full abstract»

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  • DInSAR measurement of soil moisture

    Publication Year: 2003 , Page(s): 2802 - 2813
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2420 KB) |  | HTML iconHTML  

    Differential interferometric sythetic aperture radar (DInSAR) measurements using the European Remote Sensing 2 (ERS-2) satellite in a high-plains region of Colorado show intriguing spatial variations in millimeter-scale path-length change that may correspond to variations in soil moisture of a few percent by volume, in both farm fields and uncultivated terrain. The observed signal is hypothesized to result from both changes in penetration depth and the swelling of clay-rich soils, both due to changes in soil moisture. Comparisons with our field measurements of soil moisture cannot conclusively verify this, but strong support is found from prior and complementary research as well as the visual correlation with hydrological features such as stream channels and watershed boundaries on a 50-m scale. Detection of these subtle signals was facilitated using a digital elevation model with high vertical accuracy. If our interpretations are correct, C-band DInSAR is a promising new tool for the remote sensing of soil moisture in a variety of terrain. View full abstract»

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  • Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework

    Publication Year: 2003 , Page(s): 2900 - 2905
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (982 KB) |  | HTML iconHTML  

    The present paper describes a feature extraction method based on M-band wavelet packet frames for segmenting remotely sensed images. These wavelet features are then evaluated and selected using an efficient neurofuzzy algorithm. Both the feature extraction and neurofuzzy feature evaluation methods are unsupervised, and they do not require the knowledge of the number and distribution of classes corresponding to various land covers in remotely sensed images. The effectiveness of the methodology is demonstrated on two four-band Indian Remote Sensing 1A satellite (IRS-1A) images containing five to six overlapping classes and a three-band SPOT image containing seven overlapping classes. View full abstract»

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  • Fast SAR image restoration, segmentation, and detection of high-reflectance regions

    Publication Year: 2003 , Page(s): 2890 - 2899
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1320 KB) |  | HTML iconHTML  

    An iterative filter that can be used for speckle reduction and restoration of synthetic aperture radar (SAR) images is presented here. This method can be considered as a first step in the extraction of other important information. The second step is the detection of high-reflectance regions and continues with the segmentation of the total image. We have worked in three-look simulated and real European Remote Sensing 1 satellite amplitude images. The iterative filter is based on a membrane model Markov random field approximation optimized by a synchronous local iterative method. The final form of restoration gives a total sum-preserving regularization for the pixel values of our image. The high-reflectance regions are defined as the brightest regions of the restored image. After the separation of this extreme class, we give a fast segmentation method using the histogram of the restored image. View full abstract»

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  • Automatic satellite image georeferencing using a contour-matching approach

    Publication Year: 2003 , Page(s): 2869 - 2880
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1341 KB) |  | HTML iconHTML  

    Multitemporal and multisatellite studies or comparisons between satellite data and local ground measurements require nowadays precise and automatic geometric correction of satellite images. This paper presents a fully automatic geometric correction system capable of georeferencing satellite images with high accuracy. An orbital prediction model, which provides initial earth locations, is combined with the proposed automatic contour-matching technique. This combination allows correcting the low-frequency error component, mainly due to timing and orbital model errors, as well as the high-frequency error component, due to variations in the spacecraft's attitude. The approach aims at exploiting the maximum reliable information in the image to guide the matching algorithm. The contour-matching process has three main steps: 1) estimation of the gradient energy map (edges) and detection of the cloudless (reliable) areas; 2) initialization of the contours positions; 3) estimation of the transformation parameters (affine model) using a contour optimization approach. Three different robust and automatic algorithms are proposed for optimization, and their main features are discussed. Finally, the performance of the three proposed algorithms is assessed using a new error estimation technique applied to Advanced Very High Resolution Radiometer (AVHRR), Sea-viewing Wide Field of view Sensor (SeaWiFS), and multisensor AVHRR-SeaWiFS imagery. View full abstract»

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  • Phytoplankton determination in an optically complex coastal region using a multilayer perceptron neural network

    Publication Year: 2003 , Page(s): 2861 - 2868
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1094 KB) |  | HTML iconHTML  

    The determination of phytoplankton in seawater, quantified as chlorophyll-a concentration (Chl-a) or absorption of pigmented matter (aph), is a major objective of optical remote sensing. The accuracy of multilayer perceptron (MLP) neural network algorithms in determining Chl-a and aph at 443 nm as a function of the multispectral remote sensing reflectance (Rrs) was investigated for optically complex waters. The implementation of the MLP algorithms was carried out relying on an experimental dataset collected in a coastal region of the northern Adriatic Sea. The performance of the algorithms was assessed on both separate and combined Case 1 and Case 2 water types. The proposed MLP algorithms showed a better accuracy both with respect to other algorithms developed on the basis of the same dataset as well as with respect to independent algorithms operationally used for the processing of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data. The study also showed a high accuracy in determining aph(443) and, thus, further confirmed the possibility of computing the inherent optical properties of seawater significant components from the Rrs spectra. View full abstract»

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  • List of reviewers

    Publication Year: 2003 , Page(s): 2699 - 2702
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    Freely Available from IEEE
  • Author index

    Publication Year: 2003 , Page(s): 2937 - 2949
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    Freely Available from IEEE

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