MD-WERP tactical project: Drone waterbirds monitoring and innovation sweep
Project Lead: The University of Adelaide
To help assess the success of water management initiatives in maintaining and improving bird breeding and recruitment, there is need to accurately and routinely monitor waterbird numbers and breeding events. An automated detection tool to count nesting waterbirds was developed using machine learning. This included guidelines for image characteristics and data collection requirements. Drone imagery of Straw-necked Ibis was collected and used to train, test and evaluate the model to demonstrate its potential.
The innovation sweep provides a summary of emerging conservation technologies and their potential applications for broad landscape monitoring. The technologies (sensors, data analysis and models) were selected based on their advanced development, innovation, and increasing uptake in the fields of conservation biology and natural resource management. These technologies can be applied at broad spatial and temporal scales within the Basin to increase the power of monitoring efforts and inform future management initiatives working towards improved water quality and environmental condition.