Data Driven Natural Resources Management

Data Driven Natural Resources Management

Collaborators

NG Nelson, E Fidan, B Reich, A Huseth, S Hall, W Hunt, K Grieger (all at NC State)

Timeline

2020-2022

Project Goal

There are two main goals of this project. The first goal is to identify stakeholder (i.e., natural resources managers) priorities, knowledge gaps, and barriers to implementing machine learning for natural resources management (e.g., agriculture, aquaculture, forestry, water resources, etc.). The second is to develop educational materials based on the findings of the first goal to empower use of machine learning and other data-driven decision support tools for natural resources management.

Project Links

Please come back soon for more information on educational materials associated with this project.

Acknowledgements

Thanks to support from the United States Department of Agricultural Food and Agriculture Cyberinformatics and Tools (FACT) program for funding this research.

Publications

. Transitioning machine learning from theory to practice in natural resources management. Ecological Modelling (and preprint via EarthArxiv), 2020.

Preprint PDF Project