Recent Advances towards a Robust, Automated Hurricane Damage Assessment from High-Resolution Images

Abstract

Techniques in post-disaster assessment from remote sensing imagery have been studied by different research communities in the past decade. Such an assessment benefits everybody from government organizations and insurance agencies to individual home owners. The key objects of interest in such images are buildings, as their destruction directly impacts lives. This work attempts at building a system capable of fine-grained damage analysis by comparing before and after storm images. While much of the assessment is still done manually, we present an automated system for Hurricane damage analysis. We propose and evaluate techniques for image registration, color balancing, building extraction, and damage classification; each of which requires little or no manual supervision.