Our research focuses on innovative techniques in fire management and remote sensing. We explore active fire clustering and spatiotemporal dynamics to improve forest fire management. Additionally, we compare various perimeter delineation methods for remote sensing fire spot data, aiming to enhance near-real-time applications. These studies contribute to more effective and timely wildfire responses.

Related Studies:

1. Active Fire Clustering and Spatiotemporal Dynamic Models for Forest Fire Management
2. Comparison of perimeter delineation methods for remote sensing fire spot data in near/ultra-real-time applications
3. Utilizing MODIS Remote Sensing and Integrated Data for Forest Fire Spread Modeling in the Southwest Region of Canada