Automated Infrastructure & Dependency Detection via Satellite Imagery and Dependency Profiles

Computer vision, a broad set of techniques for training statistical models and neural networks to process images, has advanced substantially in recent years. Applying these capabilities to satellite imagery can improve critical infrastructure analysis and interdependency data build-outs. Combining advanced computer vision techniques, a functional taxonomic approach to critical infrastructure, and the unique geo-spatial and dependency datasets the research team developed can produce innovative and state- of-the-art image processing results that advance abilities to secure and defend national critical infrastructure.