Automated Cyclone Identification From Remote QuikSCAT Satellite Data

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.