Automated Monitoring to Evaluate and Inform Conservation Actions

We develop an automated approach to biodiversity monitoring that combines UAVs, camera traps, and automated species identification to generate scalable, standardized, and cost-effective biodiversity data. 

Three objectives guide the work: 

1. mapping vegetation structure, microclimate, and plant species composition in urban green spaces; 
2. monitoring butterfly and moth abundance and diversity through autonomous camera traps; and 
3. analyzing biodiversity patterns and drivers across partner cities. 

By mapping species distributions at high resolution, we bridge an information gap between field observations and nationwide remote-sensing products, while our time-series of lepidopteran diversity can assess the effectiveness of conservation actions.