UAVs and Machine Learning Team Up to Combat Invasive Species in WV and PA
Researchers at the West Virginia University Davis College of Agriculture, Natural Resources, and Design have secured a $175,000 grant from the Richard King Mellon Foundation to tackle the issue of invasive plant species using unmanned aerial vehicles (UAVs) and machine learning technology. Their primary focus is on combating multiflora rose, an invasive shrub that poses a threat to native plants in several states, including West Virginia and Pennsylvania.
The project’s goal is to equip UAVs with advanced sensors that can collect environmental data within a designated area in southwestern Pennsylvania over multiple seasons. By combining this data with machine learning algorithms, the research team aims to develop software capable of identifying multiflora rose. Furthermore, this technology can be used to identify and combat other invasive species in the future. The software’s end goal is to enable targeted delivery of herbicides through UAVs.
To facilitate the project, the West Virginia University is collaborating with two partners. First is CNX, a natural gas company headquartered in Canonsburg, Pennsylvania, which has generously offered the use of reclaimed mine land for the research. The second partner is Resource Environmental Solutions, an ecological restoration company providing technical assistance for herbicide selection and deployment.
This project builds upon existing UAV-based research conducted by the National Resource Analysis Center (NRAC) in conjunction with the U.S. Office of Surface Mine Reclamation and Enforcement. The ongoing research focuses on autumn olive, one of the most prevalent invasive brush species in West Virginia. While most data collection and analysis targeted at multiflora rose is scheduled to begin in the spring of 2024, the NRAC research team is currently using autumn olive data to explore the potential for gathering information about multiflora rose.
This collaborative effort aims to utilize cutting-edge technology to combat the spread of invasive species, ultimately protecting the natural biodiversity of the region. By combining UAVs, environmental data collection, machine learning, and herbicide delivery, researchers hope to make significant progress in the identification and control of multiflora rose and other invasive species. The practical application of this technology could pave the way for more effective and targeted efforts in invasive species management, benefitting not only West Virginia and Pennsylvania but also other affected regions.
The innovative nature of this project brings attention to the capabilities of UAVs and machine learning in addressing complex environmental challenges. With further research and development, these technologies could revolutionize invasive species management and contribute to the preservation of ecosystems worldwide.
