DRI-EDIA-F4A: Advancing Equity in Forestry: Digital Research Infrastructure and Deep Learning for All
News • About • Team • Workshops • Tutorials
News
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🔥 Mar. 31, 2025: we uploaded the recording, slides, and code for our second workshop!
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🎉 Mar. 04, 2025: we uploaded the recording, slides, unsupervised learning code, run distributed code on cluster for our second workshop!
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🎉 Feb. 10, 2025: we uploaded the recording and slides in our first workshop 🌟 Workshop 1: Earth Observation (EO) Data Management and Open Science Practices 🌟!
Tutorials
Workshops
Workshop 1 - Earth Observation (EO) Data Management and Open Science Practices
Workshop 2 - Machine Learning in Forest Modelling
Workshop 3 - Advanced Computing and Deep Learning in Forestry
Team
- Members: Yuwei Cao & Brianne Boufford & Harry Seely & Jing Jiang & Sarah Smith-Tripp & Tommaso Trotto
- Roles & Responsibilities: Team Directory outlines roles, responsibilities and their ways of working.
Vision
Forestry professionals, environmental researchers, and policy makers are working together to advance digital research infrastructure and deep learning for all, and have gained significant skills to strengthen and disseminate their work in forestry research and applications through advanced computing and open science principles.
🎯 Roadmap & Milestones
🤝 Credits & Acknowledgement
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Acknowledgment: Thanks Alejandro Coca-Castro for mentoring this project and his valuable suggestions!
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These Contributing Guidelines have been adapted from the Contributing Guidelines of STEMM Role Models App! (License: MIT)
Contributors ✨
Thanks goes to these wonderful people (emoji key):
 gingerlolipop 🎨 📖 |  Tommaso Trotto 🎨 📖 |  Harry Seely 🎨 📖 |  Brianne Boufford 🎨 📖 |  Sarah Smith-Tripp 🎨 📖 |  Yuwei 🎨 📖 |
This project follows the all-contributors specification. Contributions of any kind welcome!
♻️ License
This work is licensed under the MIT license. You are free to share and adapt the material for any purpose, even commercially, as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use and with no additional restrictions.