David Dao (ETH); Johannes Rausch (ETH Zurich); Ce Zhang (ETH)
Monitoring, Reporting and Verification (MRV) systems for land use play a key role in the decision-making of climate investors, policymakers and conservationists. Remote sensing is commonly used for MRV but practical solutions are constrained by a lack of labels to train machine learning-based downstream tasks. GeoLabels is an automated MRV system that can rapidly adapt to novel applications by leveraging existing geospatial information and domain expertise to quickly create training sets through data programming. Moreover, GeoLabels uses dimensionality reduction interfaces, allowing non-technical users to create visual labeling functions.