
Shamak G. 2025 | BASIS Independent Fremont
- Project Title: Using Image Recognition to Assess Forest Areas Prone to Wildfires
- BASIS Independent Advisor: Ms. Shahin
While the South Atlantic suffers from hurricanes, wildfires define the West Coast. They have been the most occurring natural disaster in California in the last two decades–made clear by the fires currently raging in LA. It’s an all too familiar problem for Bay Area residents, one that Has no clear solution. While traditional methods of fire mitigation focus on reactive measures like early detection and fire suppression, my project shifts the focus to preemptive prevention by using image recognition to identify fire-prone areas. Through this virtual project, I’ll design a model that analyzes factors such as vegetation dryness, density, and other fire-risk indicators using satellite and drone imagery–as well as relevant quantitative data. This project is a proof of concept, with the final product showcasing a website where users can select certain Northern California forest areas to determine forest fire proneness. By combining high-resolution data from drones with large-scale satellite imagery, my aim is to demonstrate the possibility of an accessible, modular system that can be integrated seamlessly with commercial drones. I hope to enable local communities, park rangers, and environmental agencies to better assess and manage wildfire risks.