Нейромережевий метод картографування повеней на основі супутникових зображень

Abstract

Floods are among the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the most important problems associated with flood monitoring is a flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a new method to the flood extent extraction from synthetic- aperture radar (SAR) images that is based on intelligent computations. In particular, we apply artificial neural networks, self-organizing Kohonen’s maps (SOMs), for SAR image segmentation and classification. We implemented our approach in a Grid system that was used to process data from three different satellite sensors: ERS-2/SAR, ENVISAT/ASAR WSM (Wide Swath Mode) and RADARSAT-1.