Case Study: University of Vermont Spatial Analysis Lab trains AI for invasive species monitoring with Wingtra

University of Vermont Spatial Analysis Lab trains AI with 119 Wingtra flights for invasive species monitoring

The University of Vermont Spatial Analysis Lab, in collaboration with Mississippi State University, faced the challenge of monitoring invasive aquatic plant species across expansive and inaccessible wetlands. Traditional survey methods were too costly and slow for effective management, and the team needed to gather extensive aerial data to train AI models, all while navigating a steep learning curve for new pilots and strict regulatory compliance requirements. They turned to the Wingta aerial survey platform to address these needs.

Using the versatile Wingtra drone with swappable RGB and multispectral payloads, the team efficiently captured high-resolution data across six sites. The platform's intuitive, automated operation and vertical take-off and landing capability made it possible to train ten people quickly and conduct 119 reliable flights, resulting in 163 datasets. This data successfully trained an AI model for species detection, providing a proof of concept for efficient, repeatable environmental monitoring. Wingtra's NDAA compliance also ensured the project met all regulatory standards.

University of Vermont Spatial Analysis Lab