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Geoscience and Remote Sensing, IEEE Transactions on

Issue 4  Part 2 • Date April 2003

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Displaying Results 1 - 9 of 9
  • Editorial

    Page(s): 894
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    Freely Available from IEEE
  • An algorithm for mapping burnt areas in Australia using SPOT-VEGETATION data

    Page(s): 907 - 909
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (354 KB) |  | HTML iconHTML  

    An algorithm has been developed to map burnt areas over the Australian continent using SPOT-VEGETATION (VGT) S1 satellite images. The algorithm is composed of a set of thresholds applied to each pixel's value of the VGT spectral channels, two spectral indices and their temporal difference. The threshold values have been derived by means of a supervised classification methodology based on the classification and regression trees algorithm. A procedure has also been developed specifically for preprocessing the daily S1 images for burnt area mapping purposes. The final product is composed of ten-day and monthly burnt area maps over Australia for the full year 2000. View full abstract»

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  • Identification of systematic bias in the cross-platform (SMMR and SSM/I) EASE-Grid brightness temperature time series

    Page(s): 910 - 915
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (639 KB) |  | HTML iconHTML  

    Vertically polarized 18-, 19-, and 37-GHz brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) are examined for the August 2-20, 1987 period when data from both sensors are available in the Equal-Area Scalable Earth Grid (EASE-Grid) projection. Colocated measurements over terrestrial surfaces of central North America are compared because of a previously observed inconsistency in derived winter season snow water equivalent across the cross-platform passive microwave time series. The results of this comparison show that SSM/I brightness temperatures systematically exceed SMMR measurements, with the magnitude of this difference dependant on overpass time and brightness temperature magnitude. Regression relationships are determined for adjusting EASE-Grid SMMR data to an SSM/I F8 baseline and are compared to the results of a previous study that examined daily averaged data for the polar regions. These results suggest that adjustment factors are not globally applicable; rather the region and application must be considered. View full abstract»

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  • Comparative analysis of ocean color measurements of IRS-P4 OCM and SeaWiFS in the Arabian Sea

    Page(s): 922 - 926
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (664 KB) |  | HTML iconHTML  

    The Indian Remote Sensing P4 (IRS-P4) satellite has carried an Ocean Color Monitor (OCM) sensor for investigations on ocean color parameters in open and coastal seas. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) sensor of the National Aeronautics and Space Administration is also an ocean color instrument, which is in concurrent operation with IRS-P4 OCM. Results of an intercomparison analysis are described for ocean color data from OCM and SeaWiFS, using a consistent methodology for atmospheric correction and bio-optical algorithms. Near synchronous data of OCM and SeaWiFS sensors was obtained on March 22, 2000 over parts of the Arabian Sea. The OCM and SeaWiFS image data were processed to estimate normalized water-leaving radiance (nLw) in 443-, 490-, 510-, and 555-nm spectral bands. A comparison was made for 10×10 colocated pixels of OCM and SeaWiFS images. Differences were observed in the estimated values of nLw [443] and nLw [490], respectively, obtained by OCM, when compared to SeaWiFS. However, OCM estimated nLw [510] and nLw [555] were comparable to that of SeaWiFS. An intercalibration approach for OCM was adopted using SeaWiFS calibration as "standard". An intercomparison of the top-of-the-atmosphere radiance measured by OCM and SeaWiFS sensor was performed for colocated pixels having similar viewing geometry. Individual OCM bands were vicariously recalibrated, and a gain coefficient for each OCM band was derived through this procedure. The OCM data for March 22, 2000 were reprocessed using derived gain coefficients, and new gain coefficients were further tested on an independent dataset of March 18, 2000. Results obtained for the recalibrated OCM data showed a better match up with the ocean color estimation obtained by SeaWiFS. View full abstract»

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  • Multisource remote sensing data classification based on consensus and pruning

    Page(s): 932 - 936
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (279 KB) |  | HTML iconHTML  

    Multisource classification methods based on neural networks, statistical modeling, genetic algorithms, and fuzzy methods are considered. For most of these methods, the individual data sources are at first treated separately and classified by either statistical or neural methods. Then, several decision fusion schemes are applied to combine information from the individual data sources. These schemes include weighted consensus theory where the weights of the individual data sources control the influence of the sources in the combined classification. Using all the data sources individually in consensus-theoretic classification can lead to a redundancy in the classification process. Therefore, a special focus in this letter is on neural networks based on pruning and regularization for combination and classification. The considered methods are applied in classification of a multisource dataset. View full abstract»

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  • Reflectivity estimation for SAR image compression

    Page(s): 901 - 906
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (661 KB) |  | HTML iconHTML  

    Synthetic aperture radar (SAR) images suffer from speckle noise that degrades image quality. Also, speckle removal is needed for lossy image compression as such noise increases image entropy. Nevertheless, most lossy compression schemes act as lowpass filters that might not suit multiplicative noise reduction. In order to build a compression scheme that takes into consideration statistics of SAR images, a well-known reflectivity estimator is integrated into an JPEG 2000-like image compression strategy, so that image compression artifacts may be viewed as an adaptive despeckle filter instead of a simple lowpass filter. It yields a compression algorithm that acts in a similar way to the Lee (or Kuan) filter. View full abstract»

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  • Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index

    Page(s): 916 - 921
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (306 KB) |  | HTML iconHTML  

    A correlation analysis was conducted between forest leaf area index (LAI) and two red edge parameters: red edge position (REP) and red well position (RWP), extracted from reflectance image retrieved from Hyperion data. Field spectrometer data and LAI measurements were collected within two days after the Earth Observing One satellite passed over the study site in the Patagonia region of Argentina. The two red edge parameters were extracted with four approaches: four-point interpolation, polynomial fitting, Lagrangian technique, and inverted-Gaussian (IG) modeling. Experimental results indicate that the four-point approach is the most practical and suitable method for extracting the two red edge parameters from Hyperion data because only four bands and a simple interpolation computation are needed. The polynomial fitting approach is a direct method and has its practical value if hyperspectral data are available. However, it requires more computation time. The Lagrangian method is applicable only if the first derivative spectra are available; thus, it is not suitable to multispectral remote sensing. The IG approach needs further testing and refinement for Hyperion data. View full abstract»

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  • An innovative real-time technique for buried object detection

    Page(s): 927 - 931
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    A new online inverse scattering methodology is proposed. The original problem is recast into a regression estimation and successively solved by means of a support vector machine (SVM). Although the approach can be applied to various inverse scattering applications, it is very suitable for dealing with buried object detection. The application of SVMs to the solution of such problems is firstly illustrated. Then some examples, concerning the localization of a given object from scattered field data acquired at a number of measurement points, are presented. The effectiveness of the SVM method is evaluated in comparison with classical neural network based approaches. View full abstract»

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  • Measurements of water vapor and high clouds over the Tibetan Plateau with the Terra MODIS instrument

    Page(s): 895 - 900
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (432 KB)  

    The seasonal variations of water vapor and cirrus clouds over the Tibetan Plateau are investigated using the recently available Level 3 monthly-mean atmospheric data products with a 1° × 1° latitude-longitude grid. The data products are derived from the multichannel imaging data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra Spacecraft. It is shown that the water vapor concentration over the Tibetan Plateau is normally low, whereas high clouds (mainly cirrus clouds) over the Plateau occur quite frequently. On an annual scale, the water vapor concentration reaches its maximum in July and its minimum in January. During the summer season, the southeastern part of Tibetan Plateau, which can be affected by moistures originating from the Bay of Bengal and southeastern Asia, is slightly moister than the other parts of the Plateau. This observation is in agreement with the previous surface meteorological measurements by Chinese scientists from the 1950s to mid-1970s. The mean high-cloud reflectance over the Plateau reaches its maximum in April and minimum in November. This feature of high clouds over the Plateau has not been reported previously. The special channel centered at 1.375-μm on the MODIS instrument has allowed the observation. We present a plausible mechanism to explain the seasonal variations of high clouds over the Plateau. We expect that the water vapor and high-cloud measurements with MODIS can be used to improve the model initialization and validation for climate models involving the Tibetan Plateau and the nearby regions in Asia. 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