Rapid Damage Assessment from High Resolution Imagery

Abstract

Disaster impact modeling and analysis uses huge volumes of image data that are produced immediately following a natural or an anthropogenic disaster event. Rapid damage assessment is the key to time critical decision support in disaster management to better utilize available response resources and accelerate recovery and relief efforts. But exploiting huge volumes of high resolution image data for identifying damaged areas with robust consistency in near real time is a challenging task. In this paper, we present an automated image analysis technique to identify areas of structural damage from high resolution optical satellite data using features based on image content.