Machine Learning and Forests: Deforestation, Afforestation, and Forest Management

Presented on Agriculture, Forestry, and Other Land Use Day (April 28) at the virtual workshop “Tackling Climate Change with Machine Learning,” held as part of the International Conference on Learning Representations (ICLR) 2020. More info at: https://www.climatechange.ai/ICLR2020... Session description: Deforestation and forest degradation are key influences on climate change, accounting for 17% of anthropogenic greenhouse gas emissions. In this session, we will learn about what drives unsustainable forest management and how machine learning can enable us to better protect, manage, and restore our world’s forests. Speakers: Max Nova (SilviaTerra) Simeon Max (ETH Zürich) Janina Grabs and Sam Levy (ETH Zürich)