Identifying and Tracking Storms in Satellite Images

Both the correlation methods and cell-identification methods currently used to identify and track individual storms in remotely sensed weather images have drawbacks. A hybrid method is introduced wherein we use a segmentation-based approach to identify storms in images and arrange the identified storms heirarchially. A genetic-algorithm method of matching these segmented regions across frames is also introduced. We show how this method can easily handle splits and merges of storm cells. Since it deals with all scales, this method should, theoretically, overcome the drawbacks inherent in the cross-correlation and cell-tracking methods.