David Dao gave an invited talk "Scaling Natural Climate Solutions with Machine Learning" at Applied Machine Learning Days at EPFL

David Dao gave the following talk at the Applied Mashine Learning Days at EPFL. 

Scaling Natural Climate Solutions with Machine Learning


Nature-based Solutions (NbS) such as forests have the potential to deliver up to a third of the emission reduction required to achieve the Paris Agreement and limit climate change to safe levels. Yet, deforestation rates in Brazil are reaching its highest in decades and it is estimated that humanity has already cut down half of the world's forests. To date NbS receive less than 3% of available climate funding. In this talk we introduce Komorebi, a joint research project between ETH Zurich and the Government of Chile, that aims to protect, restore and fund NbS using machine learning systems. We leverage unsupervised learning and data programming on satellite and drone imagery to improve deforestation warning alerts and increase the efficiency of results-based payments for ecosystem services.