Advanced spatial analytics for policy support: Use cases from One CGIAR

The CGIAR Science Program on Policy Innovations (“Policy Program”) is committed to driving transformation across Food, Land, and Water (FLW) systems. Identifying viable policies and investment options through Foresight and Prioritization exercises (Area of Work 1) is key to reaching this goal. However, prioritizing interventions that are relevant to local needs and conditions, while addressing global drivers and megatrends that affect FLW systems across different scales remains a challenge. This report seeks to address this challenge. It demonstrates how spatial analytics, a fast-evolving field that sits at the intersection of economics, public policy, geography, and data science, can provide actionable policy insights. It also aims to equip policymakers and partners with advanced and accessible spatial analytical tools to design and implement tailored policies, investments and programs. The report starts by providing a unified framework that brings together diverse spatial analytics approaches to support policy. It reviews the evolution of spatial analytics, spanning geographic information systems (GIS), spatial economics, and economic models with spatially explicit inputs and outputs. It also introduces a taxonomy of building blocks to illustrate how different spatial tools and methods can address various policy questions. This report draws on 11 use cases from across CGIAR centers in which spatial analytics have been applied to inform policies across Africa, Asia, and Latin America. It demonstrates how spatial analytics can identify priority intervention areas and appropriate actions at the local level while accounting for global drivers. Key challenges in scaling spatial analytics for policy application are also identified, including data gaps, methodological complexities, and computational constraints. The report concludes by outlining future directions to fully leverage spatial analytics for policy support. This report aims to advance the integration of spatial analytics across disciplines and scales, enabling the translation of local spatial patterns into regional and global policy frameworks. The curated use cases show that spatial analytics is no longer a niche technical exercise, but an operational tool that facilitates FLW systems transformation towards desirable futures. By systematically linking spatial heterogeneity to multi-scale policy needs, spatial analytics can generate actionable and scalable insights for policy development and implementation.

Song, C.; Cenacchi, N.; Chamberlin, J.; Diao, X.; Gebrekidan, B.; Ghosh, A.; Gonzalez, C.; Gotor, E.; Guo, Z.; Lenaerts, B.; Mbabazi, G.; Mishra, A.; Mkondiwa, M.; Mwungu, C.; Otieno, F.; Pede, V.; Petsakos, A.; Robertson, R.; Thomas, T.; Wanjau, A.; Yego, F.; You, L.; Zhou, S.