Susrik M.
Computer science
Hometown: Tempe, Arizona, United States
Graduation date: Spring 2026
FURI | Spring 2026
Machine Learning enabled Future Wildfire Spread Prediction using a Unified Spatiotemporal Dataset
This project develops a unified geospatial dataset and machine learning framework for next-day wildfire spread prediction across the contiguous United States. Using Google Earth Engine, the dataset integrates wildfire boundaries, terrain, land cover, meteorological variables, and MODIS active-fire observations into spatially aligned 96 × 96 km samples with five days of historical inputs and next-day target masks. These data support the development of deep learning models for forecasting fire growth patterns. This work advances data-driven wildfire forecasting for improved monitoring, early warning, and fire-response decision-making.
Mentor: Hua Wei
It’s hip to be square.
Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future.
Right click the image to save it to your computer.