University of Zurich – Partner’s Feature Presentation
UZH – University of Zurich
EcoVision Lab,
Department of Mathematical Modeling and Machine Learning (DM3L),
University of Zurich
The EcoVision Lab in the Department of Mathematical Modeling and Machine Learning (DM3L) at University of Zurich does research at the frontier of machine learning, computer vision, and remote sensing to solve scientific questions in the environmental sciences and geosciences. Its objective is to invent original, data-driven methods that analyze environmental data at large scale automatically. We innovate on a very technical level and closely collaborate with our colleagues from, for example, ecology to jointly find new ways to protect our environment at global scale. Scientific projects include global mapping of vegetation parameters like canopy top height and carbon stocks at very high spatial and temporal resolution, monitoring of agricultural land, water-level prediction under flooding scenarios, or establishing a rapid-alert system that detects forest degradation. On the technical side, we investigate exciting topics like uncertainty quantification in deep learning, explainable and causal AI, graph neural networks, or time-series analysis with transformers. We believe that interdisciplinary research is key to scientific breakthroughs and always aim at putting our research into practice by collaborating with NGOs, company’s or public administration.
What is your organization’s role in the project? What unique contribution does it bring to the team?
The EcoVision Lab will contribute to the use case of global above ground biomass mapping from satellite imagery and NASA GEDI data. It brings long-standing experience in computer vision, machine learning, and remote sensing to the project consortium.
Why is this project important for your organization?
The embed2scale project provides a unique opportunity to combine research on the very technical, cutting-edge topic like data compression, foundation models, and unsupervised learning with use cases that contribute to the benefit of society and the planet. This perfectly fits with the core mission of the EcoVision Lab.