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Geoscience and Remote Sensing, IEEE Transactions on

Issue 11  Part 1 • Date Nov. 2003

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Displaying Results 1 - 25 of 25
  • Foreword special issue on analysis of multitemporal remote sensing images

    Publication Year: 2003 , Page(s): 2419 - 2422
    Cited by:  Papers (4)
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    Freely Available from IEEE
  • List of reviewers

    Publication Year: 2003 , Page(s): 2423
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    Freely Available from IEEE
  • Software wave receiver for the SS-520-2 rocket experiment

    Publication Year: 2003 , Page(s): 2638 - 2647
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1106 KB) |  | HTML iconHTML  

    A software wave receiver was aboard the SS-520-2 rocket as a part of the plasma wave analyzer and successfully accomplished waveform observations and spectral observations. In the present paper, we describe the specifications and roles of the software wave receiver on the SS-520-2 rocket experiment. This receiver consists of a waveform receiver using real-time data compression and a spectral receiver with high time and frequency resolution using a programmable down converter. We report here on the first flight test of the new plasma wave receiver to be used for future planet explorers and space observation missions. Every 0.5 s, spectra of a 3-MHz signal with 0.3-kHz resolution are obtained, and the data compression of waveforms with the bandwidth of 15 kHz are performed. Although the sweep time was occasionally affected if the data were not compressed enough, no data were lost during the flight. View full abstract»

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  • An application of tomographic reconstruction of atmospheric CO2 over a volcanic site based on open-path IR laser measurements

    Publication Year: 2003 , Page(s): 2629 - 2637
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1540 KB) |  | HTML iconHTML  

    The southern area of Italy is characterized by the presence of many active volcanic areas. In Pozzuoli (Naples, Italy), an urban area characterized by high volcanic risk, a gas emitting site is present. A high percentage of CO2 is emitted, whose atmospheric concentration measurement is an important task in many environmental and scientific applications. In this paper, we describe the utilization over that area of a mobile infrared (IR) laser system, able to measure the CO2 concentration along rectilinear atmospheric paths up to 1-km length, and the result of tomographic processing applied to retrieve a two-dimensional CO2 concentration field. The laser system computes the link averaged concentration by processing the received IR laser radiation propagated along an open-air rectilinear link connecting the transmitter/receiver laser unit and a passive retroreflector device. A one-day measurement campaign has been made and 15 different atmospheric propagation links were considered moving the transmitter/receiver unit and some retroreflectors. View full abstract»

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  • Forest fire scar detection in the boreal forest with multitemporal SPOT-VEGETATION data

    Publication Year: 2003 , Page(s): 2575 - 2585
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (739 KB) |  | HTML iconHTML  

    Disturbance events, such as fire, have a major impact on boreal forest dynamics, succession, and the global carbon cycle. Methods using satellite imagery are well established for detecting forest fires in real time and mapping the burned area (fire scars) within one year of the fire. This paper focuses on the detection of older fire disturbance-regeneration patterns in the boreal forests of Canada. Previous work found that shortwave-infrared image segmentation proved particularly good at creating uniform regions that were easy to associate with fire scars. Our findings suggest it is possible to detect fire scars up to ten years old using SPOT-VEGETATION data from a single year and that the use of a vegetation index based on near- and shortwave-infrared reflectance is critical to this success. We demonstrate how the use of short-term multitemporal imagery can enhance segmentation results and present a threshold-based procedure for a posteriori identification of fire scar segments. The resulting fire scar probability map showed a good correspondence with records of fire scars mapped by the Canadian Forest Service for 1980-1992 and "hot spots" from the FireM3 Information System for 1994-1998. View full abstract»

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  • Multitemporal evaluation of topographic normalization methods on deciduous forest TM data

    Publication Year: 2003 , Page(s): 2586 - 2590
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (687 KB) |  | HTML iconHTML  

    Five empirical and nonempirical parametric topographic normalization methods (the cosine, SCS, Minnaert, b correction, and c correction methods) were applied to multitemporal Landsat Thematic Mapper data (bands 1-5 and 7) collected in different periods of the growing season (April, June, and July) of a mixed deciduous forest area (340 ha) in the northern Apennines. The effectiveness of the models at removing topographic control, preserving internal data variability, and consistently normalizing radiance for flat pixels from band to band and image to image was evaluated. The entirely empirical b correction outperformed the other considered methods without relying on any photometric function. View full abstract»

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  • Coherence estimation from multilook incoherent SAR imagery

    Publication Year: 2003 , Page(s): 2531 - 2539
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1594 KB) |  | HTML iconHTML  

    This paper presents an unsupervised method capable to provide estimates of temporal coherence starting from a pair of multilook detected synthetic aperture radar (SAR) images of the same scene. The method relies on robust measurements of the temporal correlation of speckle patterns between the two pass dates. To this end, a nonlinear transformation aimed at decorrelating the data across time while retaining the multiplicative noise model is defined as the pixel geometric mean and ratio of the two overlapped images. The temporal correlation coefficient (TCC) of speckle is analytically derived from the noise variances, measured in the transformed pair of images as regression coefficients of local standard deviation to local mean, calculated on homogeneous, i.e., nontextured, pixels. Such pixels are identified based on the observation that homogeneous areas produce clustered scatter-points that are aligned along the regression line. Experiments were carried out on two pairs of multitemporal SAR observations, from the European Remote Sensing 1/2 (ERS-1/2) tandem mission and from the 1994 SIR-C mission. A good fit with the true coherence values was found, irrespective of the presence of textures; when the true coherence was unavailable, the estimated coherence results match the available ground truth data. View full abstract»

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  • Effect of band-to-band coregistration on fire property retrievals

    Publication Year: 2003 , Page(s): 2648 - 2661
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3724 KB)  

    The impact of satellite band-to-band coregistration errors on fire retrievals from biomass burning has not been well quantified. However, the retrieval of fire temperature and area using a two-channel algorithm can be extremely sensitive to coregistration between the channels because fire sizes are generally much smaller than the sensor pixel resolution. Simulations are used to determine the magnitude of these errors for a range of spatial response shapes, including one case that is representative of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Presented are results that show typical sensor band-to-band coregistration errors of 10% to 15% are a dominant source of error in the retrieved fire properties. For example, a MODIS-type instrument with a 1-km horizontal spatial resolution and a 10% coregistration error would generate retrieval errors on the order of 150 K and 210% for a single retrieved fire temperature and fractional fire area, respectively. The retrieval errors, which depend on the position of the fire in the pixel, are asymmetric in the direction of the misregistration, and it is noted that this characteristic could be utilized in validation studies to flag or correct for coregistration errors. View full abstract»

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  • Using temporal averaging to decouple annual and nonannual information in AVHRR NDVI time series

    Publication Year: 2003 , Page(s): 2590 - 2594
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (375 KB) |  | HTML iconHTML  

    As regularly spaced time series imagery becomes more prevalent in the remote sensing community, monitoring these data for temporal consistency will become an increasingly important problem. Long-term trends must be identified, and it must be determined if such trends correspond to true changes in reflectance characteristics of the study area (natural), or if their source is a signal collection and/or processing artifact that can be identified and corrected in the data (artificial). Spectrally invariant targets (SITs) are typically used for sensor calibration and data consistency checks. Unfortunately, such targets are not always available in study regions. The temporal averaging technique described in this research can be used to determine the presence of artificial interannual value drift in any region possessing multiyear regularly sampled time series remotely sensed imagery. Further, this approach is objective and does not require the prior identification of a SIT within the region of study. Using biweekly Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data from 1990 to 2001 covering the conterminous United States, an interannual trend present in the entire scene was identified using the proposed technique and found to correspond extremely well with interannual trends identified using two SITs within the region. View full abstract»

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  • An adaptive approach to reducing registration noise effects in unsupervised change detection

    Publication Year: 2003 , Page(s): 2455 - 2465
    Cited by:  Papers (26)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1003 KB) |  | HTML iconHTML  

    In this paper, an approach to reducing the effects of registration noise in unsupervised change detection is proposed. The approach is formulated in the framework of the change vector analysis (CVA) technique. It is composed of two main phases. The first phase aims at estimating in an adaptive way (given the specific pair of images considered) the registration-noise distribution in the magnitude-direction domain of the difference vectors. The second phase exploits the estimated distribution to define an effective decision strategy to be applied to the difference image. Such a strategy allows one to perform change detection by significantly reducing the effects of registration noise. Experimental results obtained on simulated and real multitemporal datasets confirm the effectiveness of the proposed approach. View full abstract»

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  • A Markov random field approach to spatio-temporal contextual image classification

    Publication Year: 2003 , Page(s): 2478 - 2487
    Cited by:  Papers (54)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (873 KB) |  | HTML iconHTML  

    Markov random fields (MRFs) provide a useful and theoretically well-established tool for integrating temporal contextual information into the classification process. In particular, when dealing with a sequence of temporal images, the usual MRF-based approach consists in adopting a "cascade" scheme, i.e., in propagating the temporal information from the current image to the next one of the sequence. The simplicity of the cascade scheme makes it attractive; on the other hand, it does not fully exploit the temporal information available in a sequence of temporal images. In this paper, a "mutual" MRF approach is proposed that aims at improving both the accuracy and the reliability of the classification process by means of a better exploitation of the temporal information. It involves carrying out a bidirectional exchange of the temporal information between the defined single-time MRF models of consecutive images. A difficult issue related to MRFs is the determination of the MRF model parameters that weight the energy terms related to the available information sources. To solve this problem, we propose a simple and fast method based on the concept of "minimum perturbation" and implemented with the pseudoinverse technique for the minimization of the sum of squared errors. Experimental results on a multitemporal dataset made up of two multisensor (Landsat Thematic Mapper and European Remote Sensing 1 synthetic aperture radar) images are reported. The results obtained by the proposed "mutual" approach show a clear improvement in terms of classification accuracy over those yielded by a reference MRF-based classifier. The presented method to automatically estimate the MRF parameters yielded significant results that make it an attractive alternative to the usual trial-and-error search procedure. View full abstract»

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  • A frame center matching technique for precise registration of multitemporal airborne frame imagery

    Publication Year: 2003 , Page(s): 2436 - 2444
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (803 KB) |  | HTML iconHTML  

    Accurate spatial registration between multitemporal imagery is necessary if pixel-level changes are to be detected. Registration of multitemporal airborne frame imagery is complicated by image distortions resulting from wide view angles and variable terrain. A novel technique for acquiring and precisely registering multitemporal airborne frame imagery is presented. This technique, referred to as frame center (FC) matching, may enable precise registration between a long series of multitemporal airborne imagery. Polynomial warping and orthorectification algorithms were tested for registering multitemporal imagery acquired with matched FCs. Registration results were compared to those derived using imagery not acquired with matched FC locations. The FC matching approach to image acquisition yielded substantially lower misregistration errors between all multitemporal image sets for each method evaluated. Special tools and protocols required for operationally replicating FCs in time sequential image acquisitions were evaluated. The effectiveness of these tools and protocols for frame-center matched acquisition and registration of multidate imagery is demonstrated. View full abstract»

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  • QuikSCAT wind retrievals for tropical cyclones

    Publication Year: 2003 , Page(s): 2616 - 2628
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1126 KB) |  | HTML iconHTML  

    The use of QuikSCAT data for wind retrievals of tropical cyclones is described. The evidence of QuikSCAT σ0 dependence on wind direction for >30-m/s wind speeds is presented. The QuikSCAT σ0s show a peak-to-peak wind direction modulation of ∼1 dB at 35-m/s wind speed, and the amplitude of modulation decreases with increasing wind speed. The decreasing directional sensitivity to wind speed agrees well with the trend of QSCAT1 model function at near 20 m/s. A correction of the QSCAT1 model function for above 23-m/s wind speed is proposed. We explored two microwave radiative transfer models to correct the attenuation and scattering effects of rain for wind retrievals. One is derived from the collocated QuikSCAT and Special Sensor Microwave/Imager (SSM/I) dataset, and the other one is a published parametric model developed for rain radars. These two radiative transfer models account for the effects of volume scattering, scattering from rain-roughened surfaces and rain attenuation. The models suggest that the σ0s of wind-roughened sea surfaces for 40-50-m/s winds are comparable to the σ0s of rain contributions for up to about 10-15 mm/h. Both radiative transfer models have been used to retrieve the ocean wind vectors from the collocated QuikSCAT and SSM/I rain rate data for several tropical cyclones. The resulting wind speed estimates of these tropical cyclones show improved agreement with the wind fields derived from the best track analysis and Holland's model for up to about 15-mm/h SSM/I rain rate. A comparative analysis of maximum wind speed estimates suggests that other rain parameters likely have to be considered for further improvements. View full abstract»

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  • Accuracy of ground-based microwave radiometer and balloon-borne measurements during the WVIOP2000 field experiment

    Publication Year: 2003 , Page(s): 2605 - 2615
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (982 KB) |  | HTML iconHTML  

    We discuss the performances of a set of four microwave water vapor radiometers operating in the 20-30-GHz band during a field experiment, with an emphasis on calibration and achievable accuracy. The field experiment was conducted at the Department of Energy's Atmospheric Radiation Measurement Program's field site in north central Oklahoma, and was focused on clear-sky water vapor measurements by both radiometers and radiosondes. A comparison between two published radiometric tip curve calibration procedures is presented, and these procedures are applied to measurements from two nearly identical instruments placed a few meters apart. Using the instantaneous tip cal method of the Environmental Technology Laboratory, the brightness temperature measurements for the two identical instruments differed by less than 0.2 K over a 24-h period. Results from reference load cryogenic tests and brightness temperature cross comparisons have shown differences within 0.7 K. In addition, we compare radiometric measurements with calculations of brightness temperature based on the Rosenkranz absorption model and radiosonde observations. During the experiment, both Vaisala-type RS80 and RS90 humidity sensors were used. Our comparisons demonstrate the improvements achieved by the new Vaisala RS90 sensors in atmospheric humidity profiling, which reduce or eliminate the "dry bias" problem. View full abstract»

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  • Monitoring forest succession with multitemporal Landsat images: factors of uncertainty

    Publication Year: 2003 , Page(s): 2557 - 2567
    Cited by:  Papers (38)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (460 KB) |  | HTML iconHTML  

    This study evaluates uncertainty factors in using multitemporal Landsat images for subtle change detection, including atmosphere, topography, phenology, and sun and view angles. The study is based on monitoring forest succession with a set of multiple Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images spanning 15 years over the H.J. Andrews Experimental Forest in the Western Cascades of Oregon. The algorithms for removing atmospheric effects from remotely sensed images evaluated include a new version of the dark object subtraction (DOS3) method, the dense dark vegetation (DDV) method, the path radiance (PARA) approach, and the 6S radiative transfer codes. We found that the DOS3 approach undercorrects the image, and the recently developed DDV and PARA approaches can produce surface reflectance values closely matching those produced by 6S using in situ measurements of atmospheric aerosol optical depth. Atmospheric effects reduce normalized difference vegetation index (NDVI) and greenness, and increase brightness and wetness. Topography modifies brightness and greenness, but has minimal effects on NDVI and wetness, and it interacts with sun angle. Forest stands at late successional stages are more sensitive to topography than younger stands. Though the study areas are covered predominantly by evergreen needleleaf forests, phenological effect is significant. Sun angle effects are confounded with phenology, and reflectance values for stands at different successional stages are related to sun angles nonlinearly. Though Landsat has a small field of view angle, the view angle effects from overlapping Landsat scenes for a mountainous forested landscape may not be ignored when monitoring forest succession with multitemporal images. View full abstract»

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  • Multifeature texture analysis for the classification of clouds in satellite imagery

    Publication Year: 2003 , Page(s): 2662 - 2668
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (485 KB) |  | HTML iconHTML  

    The aim of this work was to develop a system based on multifeature texture analysis and modular neural networks that will facilitate the automated interpretation of satellite cloud images. Such a system will provide a standardized and efficient way for classifying cloud types that can be used as an operational tool in weather analysis. A series of 98 infrared satellite images from the geostationary satellite METEOSAT7 were employed, and 366 cloud segments were labeled into six cloud types after combined agreed observations from ground and satellite. From the segmented cloud images, nine different texture feature sets (a total of 55 features) were extracted, using the following algorithms: statistical features, spatial gray-level dependence matrices, gray-level difference statistics, neighborhood gray tone difference matrix, statistical feature matrix, Laws' texture energy measures, fractals, and Fourier power spectrum. The neural network self-organizing feature map (SOFM) classifier and the statistical K-nearest neighbor (KNN) classifier were used for the classification of the cloud images. Furthermore, the classification results of the nine different feature sets were combined, improving the classification yield for the six classes, for the SOFM classifier to 61% and for the KNN classifier to 64%. View full abstract»

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  • Statistical and operational performance assessment of multitemporal SAR image filtering

    Publication Year: 2003 , Page(s): 2519 - 2530
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2552 KB) |  | HTML iconHTML  

    Multitemporal synthetic aperture radar (SAR) image filtering is a useful preprocessing step for many applications that require speckle reduction. Several multitemporal filters are now available with very different characteristics. In this paper, the performance of three multitemporal filters is assessed with respect to statistical and operational criteria. Statistical criteria include measures of bias, noise reduction, and preservation of both spatial and temporal information. Operational criteria evaluate the accuracy of manual detection of geographical features such as points, lines, and surfaces. This study was carried out with the help of ten photointerpreters. It uses a set of seven multitemporal SAR images from the European Remote Sensing 1 (ERS-1) satellite. It provides guidelines to select multitemporal filters according to the application and the subsequent processing. View full abstract»

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  • Performance of mutual information similarity measure for registration of multitemporal remote sensing images

    Publication Year: 2003 , Page(s): 2445 - 2454
    Cited by:  Papers (39)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1295 KB) |  | HTML iconHTML  

    Accurate registration of multitemporal remote sensing images is essential for various change detection applications. Mutual information has recently been used as a similarity measure for registration of medical images because of its generality and high accuracy. Its application in remote sensing is relatively new. There are a number of algorithms for the estimation of joint histograms to compute mutual information, but they may suffer from interpolation-induced artifacts under certain conditions. In this paper, we investigate the use of a new joint histogram estimation algorithm called generalized partial volume estimation (GPVE) for computing mutual information to register multitemporal remote sensing images. The experimental results show that higher order GPVE algorithms have the ability to significantly reduce interpolation-induced artifacts. In addition, mutual-information-based image registration performed using the GPVE algorithm produces better registration consistency than the other two popular similarity measures, namely, mean squared difference (MSD) and normalized cross correlation (NCC), used for the registration of multitemporal remote sensing images. View full abstract»

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  • Spatial surface prior information reflectance estimation (SPIRE) algorithms

    Publication Year: 2003 , Page(s): 2424 - 2435
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (767 KB) |  | HTML iconHTML  

    A new set of algorithms has been developed to estimate spectral reflectance in remote sensing imagery. These algorithms are called surface prior information reflectance estimation (SPIRE) algorithms and estimate surface spectral reflectance using prior spatial and spectral information about the surface reflectance. This paper describes SPIRE algorithms that employ spatial processing of single-channel data to estimate local changes in spectral reflectance under spatially and spectrally varying multiplicative and additive noise caused by variations in illumination and atmospheric effects. Rather than modeling the physics of the atmosphere and illumination (using a physics-based code such as the Atmospheric Removal (ATREM) program), or using ground truth spectra at known locations to compensate for these effects [using the empirical line method (ELM)], prior information about the low spatial frequency content of the scene in each spectral channel is used instead. HYDICE visible near-infrared shortwave infrared (VNIR-SWIR) hyperspectral data were used to compare the performance of SPIRE, ATREM, and ELM atmospheric compensation algorithms. The spatial SPIRE algorithm performance was found to be nearly identical to the ELM ground-truth-based results, while spatial SPIRE performed better than ATREM overall and significantly better under high clouds and haze. View full abstract»

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  • A shape-based approach to change detection of lakes using time series remote sensing images

    Publication Year: 2003 , Page(s): 2466 - 2477
    Cited by:  Papers (16)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1224 KB) |  | HTML iconHTML  

    Shape analysis has not been considered in remote sensing as extensively as in other pattern recognition applications. However, shapes such as those of geometric patterns in agriculture and irregular boundaries of lakes can be extracted from the remotely sensed imagery even at relatively coarse spatial resolutions. This paper presents a procedure for efficiently retrieving and representing shapes of interesting features in remotely sensed imagery using supervised classification, object recognition, parametric contour tracing, and proposed piecewise linear polygonal approximation techniques. In addition, shape similarity can be measured by means of a computationally efficient metric. The study was conducted on a time series of radiometric and geometric rectified Landsat Multispectral Scanner (MSS) images and Thematic Mapper (TM) images, covering the scenes containing lakes in the Nebraska Sand Hills region. The results validate the effectiveness of the proposed processing chain in change detection of lake shapes and show that shape similarity is an important parameter in quantitatively measuring the spatial variations of objects. View full abstract»

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  • Measurement of glacier geophysical properties from InSAR wrapped phase

    Publication Year: 2003 , Page(s): 2595 - 2604
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1165 KB) |  | HTML iconHTML  

    A method is presented for calculating longitudinal glacier strain rates directly from the wrapped phase of an interferometric synthetic aperture radar (InSAR) interferogram assuming the ice flow path is known. This technique enables strain rates to be calculated for scenes lacking any velocity control points or areas within a scene where the phase is not continuously unwrappable from a velocity control point. The contributions to the error in the estimate of the strain rate are evaluated, and recommendations for appropriate SAR and InSAR parameters are presented. An example using Radarsat-1 InSAR data of an East Antarctic ice stream demonstrates the technique for calculating longitudinal strain rate profiles and estimating tensile strength of ice (186-215 kPa) from locations of crevasse initiation. The strain rate error was found to be 17% corresponding to a tensile strength of ice error of 5.3%. View full abstract»

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  • Linear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information

    Publication Year: 2003 , Page(s): 2540 - 2556
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3158 KB) |  | HTML iconHTML  

    This paper presents an almost unsupervised fusion algorithm on linear features (LF) extraction in synthetic aperture radar (SAR) interferometric data, in particular for mangroves/shorelines and thin internal channels. The spatial information on LFs is first extracted in the coherence image, where they are wider and more visible: water regions (in particular thin internal channels) are dark areas (low coherence) due to the temporal decorrelation of backscattering signals in these and surrounding regions, whereas conventional vegetation regions are brighter areas (high coherence). These approximate locations of LFs are further refined by using the edge map coming from a semantic fuzzy fusion of the coefficient of variation (CV) and the ratio of local means (RLM) measured in the amplitude image. The final detection of LFs is then performed by merging the two fuzzy inputs: the spatial information and the edge location map. The membership degree statistics of CV and RLM semantic fusion measures are introduced in order to illustrate the location detection ability. The originality of this method in comparison with conventional approaches is in the fusion scheme that follows the interpreter behavior by using first the coherence image for a fuzzy detection where thin LFs are more visible, but have low location accuracy, and then the amplitude image where they are poorly visible, but with higher location accuracy, to obtain improved results. A quantitative performance evaluation is also presented. The method has been applied on real interferometric SAR images from European Remote Sensing satellites over the western part of Cameroon. View full abstract»

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  • A new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images

    Publication Year: 2003 , Page(s): 2500 - 2518
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2147 KB) |  | HTML iconHTML  

    In this paper, we devise a new technique for the fusion of a sequence of multitemporal single-channel synthetic aperture radar (SAR) images of a given area with a single multiband optical image. Unlike for SAR, the availability of optical images is largely affected by atmospheric conditions, so that this is a case of practical interest. First, a statistical model for the joint distribution of SAR and optical data is provided. Then, a split-merge test based on this model is derived, and its performance is evaluated both analytically and using a Monte Carlo simulation. A new segmentation technique is introduced (OPT MUM), based on the test and on a region-growing scheme. The effectiveness of the proposed technique for the fusion of multitemporal SAR and multiband optical images is tested on synthetic and real images. Results show that the proposed scheme allows to both 1) discriminate characteristics that would be impossible to distinguish using only a single sensor and 2) increase the overall discrimination performance, even when each sensor has its own discrimination capability. View full abstract»

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  • Comparison of single-year and multiyear NDVI time series principal components in cold temperate biomes

    Publication Year: 2003 , Page(s): 2568 - 2574
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (638 KB) |  | HTML iconHTML  

    Standardized principal components analysis (SPCA) is performed on normalized difference vegetation index (NDVI) time series of a 10° latitude by 10° longitude area of western Canada including grassland, parkland, and forest ecosystems. When used with input from a single growing season (April-October), early components correspond closely to ecoregional mapping based on long-term vegetation composition. Later components isolate areas showing agricultural practice or climatic stress particular to the year. When three years' growing seasons are input together into a multiyear SPCA, similar patterns occur in the first component. However, components occur early in the series that discriminate areas having different seasonality patterns associated with plant phenology. Deciduous-dominated areas are well distinguished from grasslands. Multiyear SPCA includes an early component apparently related to latitudinal variation in day length, which does not appear in single-year component series. An early component unrelated to any known geographical or climatological pattern or event appears, which may relate to sensor degradation. Both single-year and multiyear SPCA isolate NDVI variability in higher numbered components that is limited in space and/or in time. This allows interpretation of transient or localized events using detailed local data, separating them from regional trends that occur in earlier (lower numbered) components of the series. These results demonstrate the possibility of refining ecoregion mapping based on selected early components to incorporate actual interannual variability for selected time periods as well as the long-term stable elements of biogeoclimatic regions. Longer time series could potentially quantify observed unidirectional trends resulting from climate change. View full abstract»

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  • A credit assignment approach to fusing classifiers of multiseason hyperspectral imagery

    Publication Year: 2003 , Page(s): 2488 - 2499
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (857 KB) |  | HTML iconHTML  

    A credit assignment approach to decision-based classifier fusion is developed and applied to the problem of land-cover classification from multiseason airborne hyperspectral imagery. For each input sample, the new method uses a smoothed estimated reliability measure (SERM) in the output domain of the classifiers. SERM requires no additional training beyond that needed to optimize the constituent classifiers in the pool, and its generalization (test) accuracy exceeds that of a number of other extant methods for classifier fusion. Hyperspectral imagery from HyMAP and PROBE2 acquired at three points in the growing season over Smith Island, VA, a barrier island in the Nature Conservancy's Virginia Coast Reserve, serves as the basis for comparing SERM with other approaches. 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