Integrating Artificial Intelligence and Thermal Imagery to Streamline Wildlife Monitoring
Research Location: Implemented: Grand Island, NE, USA
Conservation Partners: U.S. Fish and Wildlife Service
Student Researchers
Andrew Lee '25, Major: Data Science (2024)
Emilio Luz-Ricca ‘23, Major: Data Science; Minor: Economics (2021-2023)
Faculty Mentors
Dr. Robert Rose and Dr. Gregory HuntProject Description
Streamlining and automating systems for monitoring wildlife populations is critical for informing and evaluating conservation management and policy. Given the rapid changes in climate, land development, and wildlife habitat, there is a need to streamline wildlife population monitoring to guide and monitor conservation action and management. The combination of very high-resolution aerial remote sensing and deep learning techniques has the potential to provide an automated, efficient means to achieve these survey goals.
作为
Project ID - Format
21-012-21- CRP Year
21-012-23 - CRP Semester
21-012-24 - CRP Year
