Institute: Connecticut
Year Established: 2023 Start Date: 2023-09-01 End Date: 2024-08-30
Total Federal Funds: $23,994 Total Non-Federal Funds: $23,994
Principal Investigators: Chandi Witharana
Project Summary: Simple Language Summary: We propose to develop a novel framework - Continuous Aquatic Plant Tracking And Imaging Network (CAPTAIN) - that seamlessly integrates remote sensing observations and in-situ measurements. The CAPTAIN centers on machine learning and artificial intelligence algorithms to fuse multi-sensor data, such as satellites, drones, proximal sensing, and sonar to model and predict distribution of aquatic plants. Our approach is modular. In the first phase of the project, we will use hydrilla (Hydrilla verticillata) as a model IAP species to test and validate CAPTAIN. In later phases, we will integrate other IAPs to expand the tracking capabilities. Once fully developed, the CAPTAIN will serve as an operational tool to track invasive aquatic plant dynamics at multiple spatial scales. Impacts and benefits of the proposed research are manyfold. Our research will close existing knowledge and technological gaps pertaining to the adaptation of satellites and drones in Connecticut’s aquatic plant monitoring and management applications. The CAPTAIN will help multiple stakeholders to identify where invasive plants occur, track their change over time, and predict future trends. The proposed study will identify opportunities of drones as alternative and complimentary data acquisition mode to conventional IAP surveys and will establish best practices and standards for aquatic plant surveying applications.