Leonie Hodel
Leonie is a land system scientist and postdoctoral researcher at the Global Land Use and Environment Lab at the University of Wisconsin-Madison. With a background in bioinformatics, she recently earned her PhD from ETH Zurich in Switzerland. Her research is dedicated to understanding deforestation trends in tropical regions and evaluating the effects of both private and public conservation interventions. Leonie's work employs AI-driven large-scale geospatial analysis, complemented by qualitative methods, to explore and analyze complex land systems.
Sessions
This talk will uncover the power of AI in combating Amazon deforestation through an innovative cattle detection system. We present a cutting-edge approach to monitoring illegal ranching, a primary driver of deforestation, using very high-resolution satellite imagery and deep learning. We'll dive into the unique challenges of detecting cattle from space – from congested scenes with small, clustered targets to diverse and cluttered backgrounds – and how we overcame them with a two-step neural network approach. By combining classification and density estimation techniques, our model efficiently identifies potential cattle locations and estimates herd sizes across varied landscapes. Discover how this interdisciplinary project, developed in collaboration with Brazilian prosecutors, leverages data science to drive real-world impact in environmental conservation and sustainable land management. Join us to explore the intersection of computer vision, geospatial analysis, and environmental advocacy, and learn how AI can be a powerful tool in the fight against deforestation in the Amazon and beyond.