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  • Journals
  • Other Sources  (221)
  • EARTH RESOURCES AND REMOTE SENSING  (220)
  • Meteorology and Climatology
  • 1985-1989  (221)
  • 1989  (221)
  • 1
    Publication Date: 2011-08-19
    Description: The Multispectral Atmospheric Mapping Sensor (MAMS) is an airborne scanner which collects imagery in eight visible and three IR bands, with ground resolution of 100 m at a nominal aircraft altitude of 20 km. The visible channels provide continuous spectral coverage from 0.42 to 1.05 microns, and the IR channels measure upwelling and reflected radiation at combinations of 3.7, 6.5, 11.1, and 12.5 microns. These include channels nearly identical to the Landsat TM channels 1-4, and similar to those on the VISSR Atmospheric Sounder (VAS) and AVHRR instruments. The high spatial resolution permits investigation of surface thermal and atmospheric water vapor structure at scales not available from current stabilities. Significant modifications have been made since engineering flights in 1985 to improve the radiometric performance. The increased data quality and recent multidisciplinary applications of this data are presented.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 2
    Publication Date: 2011-08-19
    Description: In summer 1988 an intensive field experiment was conducted in the vicinity of the Pisgah lava flow in the Mojave Desert. Physical properties such as microtopography, composition, soil moisture, and dielectric constant were measured at five sites representing surfaces with rms heights varying from less than one centimeter to tens of centimeters. In addition, polarimetric radar images at P-band, L-band, and C-band were acquired at three different incidence angles with the NASA/JPL airborne imaging radar polarimeter. Using trihedral corner reflectors deployed in the area prior to imaging, the L- and C-band images were calibrated to provide sigma0 values for each resolution element in the scene. The results of inferring geophysical parameters such as rms surface height and correlation length of the measured surfaces by fitting the observed signatures with those predicted by the small-perturbation model are presented: for smoother surfaces, the rms height values inferred are in good agreement with in situ measurements.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 3
    Publication Date: 2011-08-19
    Description: Radar modeling of mangal forest stands in the Sundarbans area of southern Bangladesh is discussed. The modeling uses radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water content (including slightly conductive water) in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed; the models are required to explain the contributions of various combinations of forest species in the attenuation and scattering of mangal-vegetated nonflooded or flooded surfaces. Statistical data of simulated images have been compared with those of SIR-B images both to refine the modeling procedures and to characterize the model output appropriately. The possibility of delineation of flooded or nonflooded boundaries is discussed.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 4
    Publication Date: 2011-08-19
    Description: Surface-air temperature differences are commonly used in a bulk resistance equation for estimating sensible heat flux (H), which is inserted in the one-dimensional energy balance equation to solve for the latent heat flux (LE) as a residual. Serious discrepancies between estimated and measured LE have been observed for partial-canopy-cover conditions, which are mainly attributed to inappropriate estimates of H. To improve the estimates of H over sparse canopies, one- and two-layer resistance models that account for some of the factors causing poor agreement are developed. The utility of the two models is tested with remotely sensed and micrometeorological data for a furrowed cotton field with 20 percent cover and a dry soil surface. It is found that the one-layer model performs better than the two-layer model when a theoretical bluff-body correction for heat transfer is used instead of an empirical adjustment; otherwise, the two-layer model is better.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 5
    Publication Date: 2011-08-19
    Description: Experimental treatments in a Douglas-fir forest in NE New Mexico were carried out to determine whether differences in forest canopy chemistry could be detected using data from the Airborne Imaging Spectrometer (AIS-2). Experimental treatments consisted of nitrogen fertilizer additions, sawdust additions, and control plots. After AIS-2 data were collected, the digital number of a given pixel was extracted from each channel, yielding 128 values that were used to form a spectrum. Four spectra were extracted from each treatment plot. Multiple stepwise linear regressions between first and second difference transformations of AIS-2 spectra and the canopy characteristics of biomass, nitrogen concentration, and nitrogen content were performed. The results showed a coefficient of multiple determination of 0.71 between first-difference AIS-2 spectra and measured nitrogen concentration in foliage, indicating that it may be possible to predict nitrogen concentration in Douglas fir using AIS-2 spectra.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 6
    Publication Date: 2011-08-19
    Description: The information content in polarimetric SAR images is examined, and the polarimetric image variables containing the information that is important to the classification of terrain features in the images are determined. It is concluded that accurate classification can be done when just over half of the image variables are retained. A reduction in image data dimensionality gives storage savings, and can lead to the improvement of classifier performance. In addition, it is shown that a simplified radar system with only phase-calibrated CO-POL or SINGLE TX channels can give classification performance which approaches that of a fully polarimetric radar.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 7
    Publication Date: 2011-08-19
    Description: The spatial and phenological distribution of vegetation was examined in a remote sensing geobotanical study of the East Africa Rift region. Six normalized difference vegetation index (NDVI) AVHRR (advanced very high resolution radiometer) scenes (February, June, and September of both 1984 and 1987) were used as a measure of vegetation presence. NOAA ETOPO-5 elevation and geographic coordinate data were coregistered with the multitemporal NDVI images. Univariate and multivariate statistics indicate that the NDVI values are significantly associated with elevation, latitude, and longitude. This supports the concept of quantifiable, regional gradients that affect large-scale geobotanical studies. A quadratic regression line was fitted to the NDVI, elevation, latitude, and longitudinal data. In this way a regional trend, as affected by elevation, was determined. The deviation of the actual data from this regional trend was displayed as an image, and shows the local climatic and geological influences.
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  • 8
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    Publication Date: 2011-08-19
    Description: The statistical characteristics of image speckle are reviewed. Existing segmentation techniques that have been used for speckle filtering, edge detection, and texture extraction are sumamrized. The relative effectiveness of each technique is briefly discussed.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 9
    Publication Date: 2011-08-19
    Description: Theory and experiments have shown that passive microwave radiometers can be used to measure soil moisture. However, the presence of a vegetative cover alters the measurement that might be obtained under bare conditions. Deterministically accounting for the effect of vegetation and developing algorithms for extracting soil moisture from observations of a vegetable-soil complex present significant obstacles to the practical use of this approach. The presence of a vegetation canopy reduces the sensitivity of passive microwave instruments to soil moisture variations. The reduction in sensitivity, as compared to a bare-soil relationship, increases as microwave frequency increases, implying that the longest wavelength sensors should provide the most information. Sensitivity also decreases as the amount of vegetative wet biomass increases for a given type of vegetation.
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  • 10
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    Publication Date: 2011-08-19
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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