Disaster monitoring by extracting geophysical parameters from SAR data

The fractal geometry proved to be the most appropriate mathematical instrument in describing natural scenes, by means of few effective and reliable geophysical parameters. In this paper we use fractal concepts to model and to identify geometrical changes occurred in areas hit by disasters. We present an overall framework employing fractal based models, algorithms and tools to support identification of natural area changes due to natural or man-made disasters. The proposed framework includes a SAR raw signal simulator, which is of key importance to improve the comprehension of the mechanisms underlying SAR image formation. In addition, we consider, as a case study, the simulation and detection of lava flows in a volcanic scenario. The potentialities of our technique for the discrimination between different types of lava are presented and discussed.