HAI Policy Briefs
Using Satellite Imagery to Understand and Promote Sustainable Development
The number of non-military satellites in orbit is rapidly growing and each of these satellites offers unprecedented access to imagery to help measure sustainable development outcomes. AI-powered tools can help extract and assess important information from satellite imagery—such as agricultural productivity, urban population density, and rural economic activity, making them an intriguing and valuable addition to the sustainable development toolkit. This brief discusses how AI models can map satellite image inputs to sustainable development outcomes, their potential and future applications, as well as the limitations of such an approach and ways to respond.
➜ The data needed to inform policymaking for sustainable development is often lacking or inaccurate.
➜ Machine learning analysis of satellite imagery could help estimate sustainable development outcomes—broadening the availability of existing high-quality development data.
➜ Currently, there is relatively limited adoption of satellite imagery analysis in many sustainable development domains, with the primary exceptions being population and agricultural measurement.
➜ Policymakers and researchers should explore using synthetic data and pursue more work on model explainability and scalability to ensure ML models can be appropriately trained for satellite images.
Marshall Burke - Stanford University
Anne Driscoll - Stanford University
David Lobell - Stanford University
Stefano Ermon - Stanford University