Abstract
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.
| Original language | English (US) |
|---|---|
| Title of host publication | 2008 IEEE Aerospace Conference, AC |
| DOIs | |
| State | Published - Aug 19 2008 |
| Externally published | Yes |
| Event | 2008 IEEE Aerospace Conference, AC - Big Sky, MT, United States Duration: Mar 1 2008 → Mar 8 2008 |
Publication series
| Name | IEEE Aerospace Conference Proceedings |
|---|---|
| ISSN (Print) | 1095-323X |
Other
| Other | 2008 IEEE Aerospace Conference, AC |
|---|---|
| Country | United States |
| City | Big Sky, MT |
| Period | 3/1/08 → 3/8/08 |
All Science Journal Classification (ASJC) codes
- Aerospace Engineering
- Space and Planetary Science
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Cite this
Ho, S. S., & Talukder, A. (2008). Automated cyclone identification from remote QuikSCAT satellite data. In 2008 IEEE Aerospace Conference, AC [4526521] (IEEE Aerospace Conference Proceedings). https://doi.org/10.1109/AERO.2008.4526521