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Geoscience and Remote Sensing Letters, IEEE

Issue 4 • Date Oct. 2004

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

    Page(s): c1
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    Freely Available from IEEE
  • IEEE Geoscience and Remote Sensing Letters publication information

    Page(s): c2
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  • Table of contents

    Page(s): 233 - 234
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  • List of reviewers

    Page(s): 235 - 236
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  • Coregistration of multiangle fine spatial resolution SAR images

    Page(s): 237 - 241
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    Provides a first assessment of a coregistration technique suitable for multiangle fine spatial resolution synthetic aperture radar (SAR) images. The technique is based on crossroad and road junction extraction and matching and exploits recently introduced road extraction routines for SAR data. These features are matched using relational and geometrical analysis. Results are encouraging and show the possibility to exploit multiangle SAR available from future airborne and satellite missions. View full abstract»

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  • The depth of sunlight penetration in cloud fields for remote sensing

    Page(s): 242 - 245
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    Derives a simple approximate equation for the depth of sunlight penetration in a cloud field. This depth is defined as the cloud optical thickness, which corresponds to the reflection function equal to 90% of the reflection function for a semi-infinite cloudy layer. View full abstract»

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  • Knowledge discovery from multispectral satellite images

    Page(s): 246 - 250
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB) |  | HTML iconHTML  

    A new approach to extract knowledge from multispectral images is suggested. We describe a method to extract and optimize classification rules using fuzzy neural networks (FNNs). The FNNs consist of two stages. The first stage represents a fuzzifier block, and the second stage represents the inference engine. After training, classification rules are extracted by backtracking along the weighted paths through the FNN. The extracted rules are then optimized by use of a fuzzy associate memory bank. We use the algorithm to extract classification rules from a multispectral image obtained with a Landsat Thematic Mapper sensor. The scene represents the Mississippi River bottomland area. In order to verify the rule extraction method, measures such as the overall accuracy, producer's accuracy, user's accuracy, kappa coefficient, and fidelity are used. View full abstract»

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  • Azimuth resolution of spaceborne P, VHF-band SAR

    Page(s): 251 - 254
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB) |  | HTML iconHTML  

    A degradation of spatial resolution performance of spaceborne synthetic aperture radar (SAR) images, which is due to the atmospheric radio waves propagation effects, is considered in this letter. A special calculation procedure of spatial resolution performances, in particular of the SAR azimuth resolution, is offered. Herein, the analysis of a potential spatial resolution, resulting from the influence of the atmosphere, on SAR images is presented. View full abstract»

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  • Narrowband vegetation indexes and detection of disease damage in soybeans

    Page(s): 255 - 259
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB) |  | HTML iconHTML  

    A portable narrowband spectroradiometer was used to detect sclerotinia stem rot infection, caused by the fungus Sclerotinia sclerotiorum in soybeans. Increasing levels of fungal inoculum were used to cause a gradient of disease infection in the field. Canopy reflectance measured in narrowband R675-R685 and broadband R635-R685 could estimate 86% of the variation in soybean plants damage measured by a count of early dead plants. Plant damage was also associated with the chlorophyll absorption in reflectance and the normalized pigment chlorophyll vegetation indexes, showing a loss of chlorophyll pigment compared to healthy plants. A new field approach is suggested for the investigation of plant damage with narrowband spectroradiometry. View full abstract»

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  • Unambiguous SAR signal reconstruction from nonuniform displaced phase center sampling

    Page(s): 260 - 264
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    The displaced phase center (DPC) technique will enable a wide-swath synthetic aperture radar (SAR) with high azimuth resolution. In a classic DPC system, the pulse repetition frequency (PRF) has to be chosen such that the SAR carrier moves just one half of its antenna length between subsequent radar pulses. Any deviation from this PRF will result in a nonuniform sampling of the synthetic aperture. This letter derives an innovative reconstruction algorithm and shows that an unambiguous reconstruction of a SAR signal is possible for nonuniform sampling of the synthetic aperture. This algorithm will also have great potential for multistatic satellite constellations as well as the dual receive antenna mode in Radarsat 2 and TerraSAR-X. View full abstract»

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  • Forecasting of onset of southwest monsoon over Kerala coast using satellite data

    Page(s): 265 - 267
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (144 KB) |  | HTML iconHTML  

    The Global Precipitation Climatology Project and in situ gauge data have been used in the present study of the Indian monsoon for the region bounded by 8° to 13°N; 70° to 95°E, from March 1 to May 31 for the years 1979 to 2001. The monsoon onset dates over Kerala, as declared by India Meteorological Department has been used in the present study as an indicator of the onset of this event. For each year, the midday of the pentad with the rainfall peak was located in the period from 1st April to 10th May and identified as the pre-monsoon rainfall peak (PMRP). The analysis showed that the PMRP exists about six pentads prior to the onset of the monsoon over the Kerala coast. A regression equation developed using the first 20 years of data (1979-1998) with a standard error estimate of four days was used for predicting the onset dates for the years 1999, 2000 and 2001, with encouraging results. Thus, we feel that the pre-monsoon rainfall estimate from the satellite data can be used for predicting the monsoon onset over Kerala coast. View full abstract»

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  • Identification and analysis of airborne laser swath mapping data in a novel feature space

    Page(s): 268 - 271
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB) |  | HTML iconHTML  

    Several novel features are examined to determine their effectiveness in separating buildings from trees in airborne laser swath mapping (ALSM) data. New one- and two-dimensional distance measures are created to quantify the separability of the classes using the different features. Several features involving the intensity of the laser returns were found to be highly effective at separating the classes. The new distance measure provides insight into what makes a good/bad feature when discriminating between classes. It also lays the groundwork for future classification of ALSM data by providing a systematic method of ranking features to be used for classification. View full abstract»

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  • Cross-sensor calibration between Ikonos and Landsat ETM+ for spectral mixture analysis

    Page(s): 272 - 276
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    Spectral mixture analysis is an algorithm that is developed to overcome the weakness in traditional land-use/land-cover (LULC) classification where each picture element (pixel) from remote sensing is assigned to one and only one LULC type. In reality, a remotely sensed signal from a pixel is often a spectral mixture from several LULC types. Spectral mixture analysis can derive subpixel proportions for the endmembers from remotely sensed data. However, one frequently faces the problem in determining the spectral signatures for the endmembers. This study provides a cross-sensor calibration algorithm that enables us to obtain the endmember signatures from an Ikonos multispectral image for spectral mixture analysis using Landsat ETM+ images. The calibration algorithm first converts the raw digital numbers from both sensors into at-satellite reflectance. Then, the Ikonos at-satellite reflectance image is degraded to match the spatial resolution of the Landsat ETM+ image. The histograms at the same spatial resolution from the two images are matched, and the signatures from the pure pixels in the Ikonos image are used as the endmember signatures. Validation of the spectral mixture analysis indicates that the simple algorithm works effectively. The algorithm is not limited to Ikonos and Landsat sensors. It is, in general, applicable to spectral mixture analysis where a high spatial resolution sensor and a low spatial resolution sensor with similar spectral resolutions are available as long as images collected by the two sensors are close in time over the same place. View full abstract»

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  • Soil moisture retrievals from biangular L-band passive microwave observations

    Page(s): 277 - 281
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    A simple approach for correcting the effect of vegetation in the estimation of soil moisture (wS) from L-band passive microwave observations is presented in this study. The approach is based on statistical relationships, calibrated from simulated datasets, which requires only two observations made at distinct incidence angles (θ12). A sensitivity study was carried out, and best retrieval remote sensing configurations, in terms of polarization and couple of incidence angles (θ12), were investigated. Best estimations of wS could be made at H polarization, for θ1 varying between 15° and 30°, and with a difference (θ21) larger than 30°. The method was tested against two experimental datasets acquired over crop fields (soybean and wheat). The average accuracy in the soil moisture retrievals during the whole crop cycle was found to be about 0.05 m3/m3 for both crops. View full abstract»

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  • Trend analysis of the Pathfinder AVHRR Land (PAL) NDVI data for the deserts of central Asia

    Page(s): 282 - 286
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB) |  | HTML iconHTML  

    We analyzed spatially averaged normalized difference vegetation index (NDVI) time series from the Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset of 11 desert and semidesert ecoregions in central Asia using standard statistical tests for discontinuities and trends. Results from the test for discontinuities reveal that seven ecoregions display significant differences in the data acquired by the AVHRRs on the National Oceanic and Atmospheric Administration satellite 11 (NOAA-11) versus the data acquired by AVHRR on other NOAA satellites (NOAA-7, NOAA-9, and NOAA-14). Across the more than 2×106 km2 of deserts and semideserts in the selected central Asian ecoregions, a significant upward trend in NDVI is evident during the tenure of NOAA-11 (1989-1994). This trend is not found during any other period. We argue that the data from the PAL NDVI dataset for NOAA-11 will pose problems for land surface change analyses, if these significant sensor-related artifacts are ignored. We do not find these artifacts in data from the other three satellites (NOAA-7, NOAA-9, and NOAA-14). We suggest that the comparison of data from any combination of these three AVHRRs can be used for land surface change analyses, but that the inclusion of NOAA-11 AVHRR NDVI data in trend analyses may result in the detection of spurious trends. View full abstract»

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  • Water quality classification of lakes using 250-m MODIS data

    Page(s): 287 - 291
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    The traditional method used in the water quality classification of Finnish lakes includes the collection of water samples from lakes and their analysis in laboratory conditions. The classification is based on statistical analysis of water quality parameter values and on expert opinion. It is possible to acquire similar information by using radiance values measured with the Earth Observing System Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). In this letter, the classification accuracy with MODIS data is about 80%. Only about 0.2% of the 20 391 pixels were misclassified by two or more classes, as a four-class classification system is used. View full abstract»

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  • Laser Doppler vibrometer-based acoustic landmine detection using the fast M-sequence transform

    Page(s): 292 - 294
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB) |  | HTML iconHTML  

    Acoustic landmine detection using a laser Doppler vibrometer (LDV) has demonstrated success in recent field tests. However, low detector signals and speckle noise are still challenging problems in the LDV-based acoustic-to-seismic detection of buried landmines. This letter describes the use of binary maximum-length sequences as the acoustic excitation for achieving high SNRs of scanning results. Some relevant issues associated with the detection system design and experimental field results are discussed. View full abstract»

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  • Synthetic aperture Radar oil spill segmentation by stochastic complexity minimization

    Page(s): 295 - 299
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2024 KB)  

    We present a new algorithm for oil spill segmentation in synthetic aperture radar (SAR) images, using the minimum description length (MDL) principle and a polygonal active grid. This algorithm is based on two steps: a first partitioning step into homogeneous regions and a second classification step with an automatic MDL thresholding. The obtained method allows one to segment the different candidate oil spills in an image automatically and in a few seconds. View full abstract»

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  • A polarimetric extension of the van Cittert-Zernike Theorem for use with microwave Interferometers

    Page(s): 300 - 303
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    The van Cittert-Zernike theorem describes the Fourier transform relationship between an extended source and its visibility function. Developments in classical optics texts use scalar field formulations for the theorem. Here, we develop a polarimetric extension to the van Cittert-Zernike theorem with applications to passive microwave earth remote sensing. The development provides insight into the mechanics of two-dimensional inteferometric imaging, particularly the effects of polarization basis differences between the scene and the observer. View full abstract»

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  • Polarization state conformation and its application to change detection in polarimetric SAR data

    Page(s): 304 - 308
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1672 KB)  

    For polarimetric SAR (POLSAR) images, it is ideal that scattering geometries of the same target should display resemblance between multidate images, which are used in change detection applications, since the scattering mechanisms may change due to the data acquisition geometry. However, sometimes it is difficult to achieve these conditions. An attempt is made to maximize the resemblance between the scattering geometries in multidate images for a specific target. An algorithm is developed based on the polarimetric basis transformation along with the polarization signatures. As a result, the resemblance between the scattering mechanisms of the same target in both images is maximized. The effects predicted by the theory are confirmed by the change detection analysis of POLSAR data acquired by the Jet Propulsion Laboratory Spaceborne Imaging Radar-C mission. View full abstract»

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  • A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery

    Page(s): 309 - 312
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1240 KB) |  | HTML iconHTML  

    Among various image fusion methods, intensity-hue-saturation (IHS) technique is capable of quickly merging the massive volumes of data. For IKONOS imagery, IHS can yield satisfactory "spatial" enhancement but may introduce "spectral" distortion, appearing as a change in colors between compositions of resampled and fused multispectral bands. To solve this problem, a fast IHS fusion technique with spectral adjustment is presented. The experimental results demonstrate that the proposed approach can provide better performance than the original IHS method, both in processing speed and image quality. View full abstract»

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  • A global quality measurement of pan-sharpened multispectral imagery

    Page(s): 313 - 317
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    This letter focuses on quality assessment of fusion of multispectral (MS) images with high-resolution panchromatic (Pan) observations. A new quality index suitable for MS imagery having four spectral bands is defined from the theory of hypercomplex numbers, or quaternions. Both spectral and radiometric distortion measurements are encapsulated in a unique measurement, simultaneously accounting for local mean bias, changes in contrast, and loss of correlation of individual bands, together with spectral distortion. Results are presented and discussed on very high-resolution QuickBird data, through comparisons between state-of-the-art and advanced MS+Pan merge algorithms. View full abstract»

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  • Neuralizing target superresolution algorithms

    Page(s): 318 - 321
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    Tatem et al. (2001) have designed a Hopfield network-based algorithm for superresolving discrete targets that are larger than the sample spacing of an image. The algorithm iteratively minimizes a criterion function that contains a sigmoidal activation term. We have altered their algorithm to bring it in line with Hopfield's original network by reducing the pseudotemperature of the sigmoid. We found that smaller values of the pseudotemperature lead to faster convergence to a solution and resulting solutions that are more accurate. View full abstract»

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  • Exploiting spectral and spatial information in hyperspectral urban data with high resolution

    Page(s): 322 - 326
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (672 KB) |  | HTML iconHTML  

    Very high resolution hyperspectral data should be very useful to provide detailed maps of urban land cover. In order to provide such maps, both accurate and precise classification tools need, however, to be developed. In this letter, new methods for classification of hyperspectral remote sensing data are investigated, with the primary focus on multiple classifications and spatial analysis to improve mapping accuracy in urban areas. In particular, we compare spatial reclassification and mathematical morphology approaches. We show results for classification of DAIS data over the town of Pavia, in northern Italy. Classification maps of two test areas are given, and the overall and individual class accuracies are analyzed with respect to the parameters of the proposed classification procedures. View full abstract»

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  • New tools and series for forward and inverse scattering problems in lossy media

    Page(s): 327 - 331
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    A convenient rewriting of the pertinent integral equation is exploited to introduce a new model for two-dimensional electromagnetic scattering by dielectric objects in lossy media. Exploiting this latter, a new series expansion is introduced to solve the forward problem accurately and effectively. The first term of such a series coincides, in particular situations, with the well-known extended Born approximation. Theoretical tools and results are given on the range of applicability and rate of convergence of the series, which favorably compares with the traditional Born one. These tools allow noticing that the new model exhibits a lower "degree of nonlinearity" with respect to parameters embedding dielectric characteristics as compared to the traditional model, thus suggesting its exploitation in the solution of the inverse problem. Numerical examples assessing effectiveness and convenience of the proposed models, tools and inversion methods are presented. View full abstract»

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Aims & Scope

IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts.

 

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Editor-in-Chief
Alejandro C. Frery
Universidade Federal de Alagoas