Welcome to the British Columbia's Wildfire Predictive Service (wps) tutorials repository, a collaborative space dedicated to understanding and combating wildfires through the lens of data science. This repository hosts a growing collection of hands-on lab tutorials that bridge the gap between advanced technology and practical wildfire management.
Our mission is to increase awareness, collaboration, and education on the applications of remote sensing and machine learning to wildfire research.
By increasing exposure to the challenges of wildfires amongst the wider Data Science community, we strive to empower leaders with the tools to make optimal decisions which minimize the loss that communities and wildlife suffer.
Each tutorial in this repository is carefully crafted to build foundational knowledge while tackling real-world challenges, such as early fire detection, perimeter mapping, and burn severity assessment. Whether you're a data scientist looking to apply your skills to environmental challenges, or a wildfire researcher seeking to leverage machine learning, you'll find resources here to support your journey.
All government employees, public and members of the private sector are encouraged to contribute to the repository by forking and submitting a pull request. If you are new to GitHub, you may want to start with a basic tutorial and check out a more detailed guide to pull requests.
Pull requests will be evaluated by the repository guardians on a schedule and if deemed beneficial will be committed to the master or the main branch.
All contributors retain the original copyright to their stuff, but by contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under the terms of the license under which this project is distributed.