From COVID-19 to unprecedented wildfires, the events of 2020 affirm that knowing where people live, work, and travel, and how vulnerable they are, is essential to public health interventions, humanitarian action, and disaster risk reduction. To this end, geo-referenced population and infrastructure data derived from Earth observations are increasingly being integrated with environmental data and models to aid decision makers. However, many end-users are unaware of best practices when integrating and applying geo-referenced population and infrastructure data.

This session showcases progress in fitness-for-use guidelines, validation and inter-comparison, case studies, and novel applications, including crowdsourcing and machine learning. Focal areas highlight anticipatory humanitarian actions, risk reduction and financing, disease modeling, climate services, food security, and early warning systems, especially in the context of climate change. The session provides a venue for both researchers and end-users to learn about developments in geo-referenced population and infrastructure data across public and private sectors.