Using AI and satellite imagery for disaster insights

What this post added

Introduced a framework for using convolutional neural networks (CNNs) on satellite imagery to identify disaster-affected areas. This method trains models on general road and building datasets, then computes relative changes between pre- and post-disaster imagery to pinpoint areas of maximum change. A new metric, the Disaster Impact Index (DII), was proposed to quantify detected changes.