Forecasting Blazing Wildfires with XGBoost ML Algorithm

Overview

I chose this project because wildfires are becoming a bigger problem in Canada. they can affect forests, wildlife, air quality, and nearby communities. I wanted to see if a machine learning could help people understand fire risk before a fire starts. To do this, I created a wildfire prediction program for Canada. It works by looking at real information such as past fires, weather, land and soil conditions, snow, roads, and nearby population, then using those patterns to predict how likely a fire is to happen, how large it could become, and how severe it might be. This project matters because it shows how computers can help us study complex natural problems and better prepare for wildfire danger.

Awards (2)

• Silver Medal
• Selected for CWSF 2026

Competition history

• CWSF 2026 Digital Technology

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