Dynamic Monitoring to Analyze Grid Vulnerability to Fire

Holly Eagleston Factsheet

Project Overview:

This project will investigate autonomously digesting multi-spectral satellite imagery and applying machine learning algorithms to identify wildfire risk across a landscape. Grid simulation methods will be integrated into the analysis to determine the impact of component damage. As an outcome, we will offer data-driven response strategies that increase the grid’s resilience to fire risk.

Project Partners: University of New Mexico, Pacific Northwest National Laboratories, Los Alamos National Laboratories