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Proceedings Paper

Comparison of a geometric-based and an evolutionary technique for tracking storm systems
Author(s): Jo Ann Parikh; John S. DaPonte; Joseph N. Vitale; George Tselioudis
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Paper Abstract

The objective of this study is to compare geometric-based and evolutionary techniques for tracking storm systems from sequences of satellite images. Analysis was applied to the International Satellite Cloud Climatology Project low resolution D1 database for selected storm systems during the month of September, 1988. During this time period there were two exceptionally long tracks of major hurricane systems, Hurricanes Gilbert and Helene. Cloud top pressure and cloud optical thickness were used to identify storm systems. The ability of the geometric-based and evolutionary techniques to generate tracks through storm regions was assessed. Differences in final tracking results between the two techniques resulted not only from the differences in methodology but also form differences in the type of preprocessed input used by each of the techniques. Tracking results were compared to results disseminated by the Colorado State/Tropical Prediction Center and maintained by the National Hurricane Center in Miami, Florida. For the hurricanes investigated in this study, both techniques were able to generate tracks which followed either most or some of the portions of the hurricanes. The evolutionary algorithm was in general able to maintain good continuity along the tracks but, with no knowledge of overall region movement, was unable to discern which of two possible directions would be best to pursue in cases where there were tow or more equally close storm systems components. The geometric method was able to maintain a smooth track close to the course of the hurricane except for confusion primarily at the beginning and/or end of tracks.

Paper Details

Date Published: 30 March 2000
PDF: 10 pages
Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380571
Show Author Affiliations
Jo Ann Parikh, Southern Connecticut State Univ. (United States)
John S. DaPonte, Southern Connecticut State Univ. (United States)
Joseph N. Vitale, Southern Connecticut State Univ. (United States)
George Tselioudis, NASA Goddard Institute for Space Studies (United States)


Published in SPIE Proceedings Vol. 4055:
Applications and Science of Computational Intelligence III
Kevin L. Priddy; Paul E. Keller; David B. Fogel, Editor(s)

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