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    Cloud Classification of AVHRR Imagery in Maritime Regions Using a Probabilistic Neural Network 

    Source: Journal of Applied Meteorology:;1994:;volume( 033 ):;issue: 008:;page 909
    Author(s): Bankert, Richard L.
    Publisher: American Meteorological Society
    Abstract: Using Advanced Very High Resolution Radiometer data, 16 pixel ? 16 pixel sample areas are classified into one of ten output classes using a probabilistic neural network (PNN). The ten classes are cirrus, cirrocumulus, ...
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    Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms 

    Source: Weather and Forecasting:;2007:;volume( 022 ):;issue: 005:;page 1123
    Author(s): Bankert, Richard L.; Hadjimichael, Michael
    Publisher: American Meteorological Society
    Abstract: Accurate cloud-ceiling-height forecasts derived from numerical weather prediction (NWP) model data are useful for aviation and other interests where low cloud ceilings have an impact on operations. A demonstration of the ...
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    Optimization of an Instance-Based GOES Cloud Classification Algorithm 

    Source: Journal of Applied Meteorology and Climatology:;2007:;volume( 046 ):;issue: 001:;page 36
    Author(s): Bankert, Richard L.; Wade, Robert H.
    Publisher: American Meteorological Society
    Abstract: An instance-based nearest-neighbor algorithm was developed for a Geostationary Operational Environmental Satellite (GOES) cloud classifier. Expert-labeled samples serve as the training sets for the various GOES image ...
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    Cluster Analysis of A-Train Data: Approximating the Vertical Cloud Structure of Oceanic Cloud Regimes 

    Source: Journal of Applied Meteorology and Climatology:;2015:;volume( 054 ):;issue: 005:;page 996
    Author(s): Bankert, Richard L.; Solbrig, Jeremy E.
    Publisher: American Meteorological Society
    Abstract: oderate Resolution Imaging Spectroradiometer (MODIS) data continue to provide a wealth of two-dimensional, cloud-top information and derived environmental products. In addition, the A-Train constellation of satellites ...
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    Improvement to a Neural Network Cloud Classifier 

    Source: Journal of Applied Meteorology:;1996:;volume( 035 ):;issue: 011:;page 2036
    Author(s): Bankert, Richard L.; Aha, David W.
    Publisher: American Meteorological Society
    Abstract: Examination of various feature selection algorithms has led to an improvement in the performance of a probabilistic neural network (PNN) cloud classifier. Thee algorithms reduce the number of network inputs by eliminating ...
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    An Automated Method to Estimate Tropical Cyclone Intensity Using SSM/I Imagery 

    Source: Journal of Applied Meteorology:;2002:;volume( 041 ):;issue: 005:;page 461
    Author(s): Bankert, Richard L.; Tag, Paul M.
    Publisher: American Meteorological Society
    Abstract: An automated method to estimate tropical cyclone intensity using Special Sensor Microwave Imager (SSM/I) data is developed and tested. SSM/I images (512 km ? 512 km) centered on a given tropical cyclone (TC), with a known ...
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    Meteorological Education and Training Using A-Train Profilers 

    Source: Bulletin of the American Meteorological Society:;2011:;volume( 093 ):;issue: 005:;page 687
    Author(s): Lee, Thomas F.; Bankert, Richard L.; Mitrescu, Cristian
    Publisher: American Meteorological Society
    Abstract: ain vertical profilers provide detailed observations of atmospheric features not seen in traditional imagery from other weather satellite data. CloudSat and Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observations ...
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    An AVHRR Multiple Cloud-Type Classification Package 

    Source: Journal of Applied Meteorology:;2000:;volume( 039 ):;issue: 002:;page 125
    Author(s): Tag, Paul M.; Bankert, Richard L.; Brody, L. Robin
    Publisher: American Meteorological Society
    Abstract: Using imagery from NOAA?s Advanced Very High Resolution Radiometer (AVHRR) orbiting sensor, one of the authors (RLB) earlier developed a probabilistic neural network cloud classifier valid over the world?s maritime regions. ...
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    Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics 

    Source: Journal of Applied Meteorology and Climatology:;2009:;volume( 048 ):;issue: 007:;page 1411
    Author(s): Bankert, Richard L.; Mitrescu, Cristian; Miller, Steven D.; Wade, Robert H.
    Publisher: American Meteorological Society
    Abstract: Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described ...
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    Automated Lightning Flash Detection in Nighttime Visible Satellite Data 

    Source: Weather and Forecasting:;2011:;volume( 026 ):;issue: 003:;page 399
    Author(s): Bankert, Richard L.; Solbrig, Jeremy E.; Lee, Thomas F.; Miller, Steven D.
    Publisher: American Meteorological Society
    Abstract: he Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) nighttime visible channel was designed to detect earth?atmosphere features under conditions of low illumination (e.g., near the solar ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian