By Topic

Geoscience and Remote Sensing, IEEE Transactions on

Issue 5  Part 2 • Date Sep 2000

Filter Results

Displaying Results 1 - 10 of 10
  • Snow crystal orientation effects on the scattering of passive microwave radiation

    Page(s): 2430 - 2434
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (148 KB)  

    For this study, consideration is given to the role crystal orientation plays in scattering and absorbing microwave radiation. A discrete dipole scattering model is used to measure the passive microwave radiation at two polarizations (horizontal and vertical), scattered by snow crystals oriented in random and nonrandom positions and having various sizes (ranging from 1 μm to 10000 μm in radius) and shapes (including spheres, cylinders, hexagons). The model results demonstrate that for the crystal sizes typically found in a snowpack, crystal orientation is insignificant compared to crystal size in terms of scattering microwave energy in the 8100 μm (37 GHz) region of the spectrum. Therefore, the assumption used in radiative transfer approaches, where snow crystals are modeled as randomly oriented spheres, is adequate to account for the transfer of microwave en energy emanating from the ground and passing through a snowpack View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Estimates of Faraday rotation with passive microwave polarimetry for microwave remote sensing of Earth surfaces

    Page(s): 2434 - 2438
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (128 KB)  

    A technique based on microwave passive polarimetry for the estimates of ionospheric Faraday rotation for microwave remote sensing of Earth surfaces is described. Under the assumption of azimuth symmetry for the surfaces under investigation, it is possible to estimate the ionospheric Faraday rotation from the third Stokes parameter of microwave radiation. An error analysis shows that the Faraday rotation can be estimated with an accuracy of better than 1° with a space-based L-band system, and the residual correction errors of linearly polarized brightness temperatures can be less than 0.1 K. It is suggested that the estimated Faraday rotation angle can be further utilized to derive the ionospheric total electron content (TEC) with an accuracy of about 1 TECU=1016 electrons-m-2 which will yield 1 mm accuracy for the estimate of an ionospheric differential delay at the Ku-band. Therefore, this technique can potentially provide accurate estimates of ionospheric Faraday rotation, TEC and differential path delay for applications including microwave radiometry and scatterometry of ocean salinity and soil moisture as well as satellite altimetry at sea surface height. A conceptual design applicable to real aperture and aperture synthesis radiometers is described for the measurements of the third Stokes parameter View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data

    Page(s): 2387 - 2401
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (700 KB)  

    This paper describes results from prototyping of the moderate resolution imaging spectroradiometer (MODIS) radiative transfer-based synergistic algorithm for the estimation of global leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) absorbed by vegetation using land surface reflectances (LASUR) and Landsat data. The algorithm uses multispectral surface reflectances and a land cover classification map as input data to retrieve global LAI and FPAR fields. The authors' objectives are to evaluate its performance as a function of spatial resolution and uncertainties in surface reflectances and the land cover map. They analyzed reasons the algorithm can or cannot retrieve a value of LAI/FPAR from the reflectance data and justified the use of more complex algorithms, instead of NDVI-based methods. The algorithm was tested to investigate the effects of vegetation misclassification on LAI/FPAR retrievals. Misclassification between distinct biomes can fatally impact the quality of the retrieval, while the impact of misclassification between spectrally similar biomes is negligible. Comparisons of results from the coarse and fine resolution retrievals show that the algorithm is dependent on the spatial resolution of the data. By evaluating the data density distribution function, they can adjust the algorithm for data resolution and utilize the algorithm with data from other sensors View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spatial resolution improvement of remotely sensed images by a fully interconnected neural network approach

    Page(s): 2426 - 2430
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    In previous works, backpropagation neural networks (BPNN) had been applied successfully in the spatial resolution improvement of remotely sensed, low-resolution images using data fusion techniques. However, the time required in the learning stage is long. In the present paper, a fully interconnected neural network (NN) model, valid from the mathematical and neurobiological points of view, is developed. With this model, the global minimum error is reached considerably faster than with any other method without regarding the initial settings of the network parameters View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Linear spectral mixture models and support vector machines for remote sensing

    Page(s): 2346 - 2360
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB)  

    Mixture modeling is becoming an increasingly important tool in the remote sensing community as researchers attempt to resolve subpixel, area information. This paper compares a well-established technique, linear spectral mixture models (LSMM), with a much newer idea based on data selection, support vector machines (SVM). It is shown that the constrained least squares LSMM is equivalent to the linear SVM, which relies on proving that the LSMM algorithm possesses the “maximum margin” property. This in turn shows that the LSMM algorithm can be derived from the same optimality conditions as the linear SVM, which provides important insights about the role of the bias term and rank deficiency in the pure pixel matrix within the LSMM algorithm. It also highlights one of the main advantages for using the linear SVM algorithm in that it performs automatic “pure pixel” selection from a much larger database. In addition, extensions to the basic SVM algorithm allow the technique to be applied to data sets that exhibit spectral confusion (overlapping sets of pure pixels) and to data sets that have nonlinear mixture regions. Several illustrative examples, based on an area-labeled Landsat dataset, are used to demonstrate the potential of this approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The correlation of visibility noise and its impact on the radiometric resolution of an aperture synthesis radiometer

    Page(s): 2423 - 2426
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (148 KB)  

    The correlation between the visibility samples' noise of an aperture synthesis radiometer are required for the computation of the recovered temperature noise of a given pixel and of the improvement introduced by baseline redundance. A general expression for this correlation and noise examples for a linear array are presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Frequency and angular variations of land surface microwave emissivities: can we estimate SSM/T and AMSU emissivities from SSM/I emissivities?

    Page(s): 2373 - 2386
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (908 KB)  

    To retrieve temperature and humidity profiles from special sensor microwave/temperature (SSM/T) and advanced microwave sounding units (AMSU), it is important to quantify the contribution of the Earth surface emission. So far, no global estimates of the land surface emissivities are available at SSM/T and AMSU frequencies and scanning conditions. The land surface emissivities have been previously calculated for the globe from the SSM/I conical scanner between 19 and 85 GHz. To analyze the feasibility of deriving SSM/T and AMSU land surface emissivities from SSM/I emissivities, the spectral and angular variations of the emissivities are studied, with the help of ground-based measurements, models, and satellite estimates. Up to 100 GHz, for snow and ice free areas, the SSM/T and AMSU emissivities can be derived with useful accuracy from the SSM/I emissivities. The emissivities can be linearly interpolated in frequency. Based on ground-based emissivity measurements of various surface types, a simple model is proposed to estimate SSM/T and AMSU emissivities for all zenith angles knowing only the emissivities for the vertical and horizontal polarizations at 53° zenith angle. The method is tested on the SSM/T-2 91.655 GHz channels. The mean difference between the SSM/T-2 and SSM/I-derived emissivities is ⩽0.01 for all zenith angles with a root mean squared (RMS) difference of ≈0.02. Above 100 GHz, preliminary results are presented at 150 GHz based on SSM/T-2 observations and are compared with the very few estimations, available in the literature View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Seabottom characterization using multibeam echosounder angular backscatter: an application of the composite roughness theory

    Page(s): 2419 - 2422
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB)  

    Composite roughness theory is used to characterize Southern Ocean bottom backscatter (multibeam) data. Spectral parameters based on Helmholtz-Kirchhoff's theory, D. R. Jackson et al. (1986), are determined from measured near-normal incidence values. A splicing technique using Rayleigh-Rice theory, E.Y. Kuo (1964), is employed beyond 20° incidence angles. Estimated roughness parameters for six deep ocean areas correlate with geology View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Prototyping of MISR LAI and FPAR algorithm with POLDER data over Africa

    Page(s): 2402 - 2418
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB)  

    The multi-angle imaging spectroradiometer (MISR) instrument is designed to provide global imagery at nine discrete viewing angles and four visible/near-infrared spectral bands. The MISR standard products include vegetation canopy green leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). These products are produced using a peer-reviewed algorithm documented in the EOS-AM1 (Terra) special issue of the Journal of Geophysical Research. This paper presents results on spatial distributions of LAI and FPAR of vegetated land surfaces derived from the MISR LAI/FPAR algorithm with bidirectional reflectance data from the polarization and directionality of the Earth's reflectance (POLDER) instrument over Africa. The results indicate that the proposed algorithm reflects the physical relationships between surface reflectances and biophysical parameters and demonstrates the advantages of using multiangle data instead of single-angle data. A new method for evaluating bihemispherical reflectance (BHR) from multi-angle measurements of hemispherical directional reflectance factor (HDRF) was developed to prototype the algorithm with POLDER data. The accuracy of BHR evaluation and LAI/FPAR estimation is also presented. To authors demonstrate the advantages of using multi-angle data over single-angle data of surface reflectance View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Effect of antenna mast motion on X-SAR/SRTM performance

    Page(s): 2361 - 2372
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB)  

    A prelaunch study on performances of the X-SAR/SRTM mission in case of outboard antenna mast bending is presented. The paper provides the assessment of SAR products, raw data complex images, and interferograms. Theoretical analysis shows the influence of mast oscillation parameters on each SAR product. Employing a SAR raw data simulator, a numerical study on canonical as well as actual scenes is also presented. Numerical results confirm theoretical analysis and quantitatively show SAR products degradation View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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