We discuss a fully automated remote cyclone identification and tracking approach using the QuikSCAT wind sensor data. Our approach consists of five main automated steps: QuikSCAT data retrieval, QuikSCAT feature extraction & data preprocessing, cyclone identification, motion/location prediction, and cyclone tracking. Ensemble learning based on a committee of support vector machines using features extracted from QuikSCAT wind sensor data are used for cyclone identification. Experimental results demonstrates the feasibility and usefulness of our automated approach.


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    Titel :

    Automated Cyclone Identification From Remote QuikSCAT Satellite Data


    Beteiligte:
    Ho, Shen-Shyang (Autor:in) / Talukder, Ashit (Autor:in)


    Erscheinungsdatum :

    01.03.2008


    Format / Umfang :

    1299153 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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