A new model for cloud tracking and analysis on satellite images
The study of convective clouds is an important issue in weather analysis. Previous methods are based on shape matching and level set. In this paper, a method based on snake model is used for cloud tracking. Snakes are known to be more efficient than level set for contour detection however they do not handle topological changes. Therefore, geometrical criteria are introduced to characterize topological transformations. Geometrical techniques are then combined and inserted in the tracking algorithm to perform morphological operations. By applying this method, a history of the positions of the clouds is obtained. In a second stage, a data model is presented for cloud interrogation. Physical information is introduced and data are organized so that spatiotemporal queries can be performed. Results obtained with the tracking method on a real data set are presented and some query examples are given.
cloud tracking snakes topological transformation spatiotemporal data model