Data Infrastructure for Development (DID) Summit 2026: Linking Geodata to Decision-Making in Africa and Beyond

Low- and middle-income countries increasingly see georeferenced and integrated data systems as essential for delivering responsive and equitable public services. Yet despite rapid progress in satellite data, earth observation (EO), and AI-driven analytics, the institutional and technical foundations for using these tools remain uneven.

DID 2026 convened African and global leaders to highlight how GIS, remote sensing, mobile data, and emerging computational methods can transform decision-making across sectors—from agriculture and disaster response to energy, social protection, and urban planning.

The one-day event featured research talks, panels, hands-on workshops, and lightning presentations showcasing practical geodata innovations and the systems that enable them.

Learn more about DID 2026 in the Togo Data Lab recap video. 

Full AGENDA | DID 2026

Program

View selected presentations below.

Using MOSAIKS to Model Agricultural Outcomes in Togo | Gnouyaro Sogoyou, Togo Data Lab, Ministry of Public Service Efficiency and Digital Transformation, Republic of Togo; Enam Labike, Directorate of Planning, Statistics, and Monitoring Evaluation, Ministry of Agriculture, Fisheries, Animal Resources, and Food Sovereignty

Research Session I: Detecting Economic Activities at Scale Using Remote Sensing

Using Satellite Imagery to Map Rural Marketplaces and Monitor their Activity at High Frequency | Tillmann von Carnap, University of Oslo

Estimating the Footprint of Artisanal Mining in Africa | Cullen Molitor, Center for Effective Global Action

AI-Driven Detection of Large-Scale Agricultural Investments (LSAIs) in Senegal | Mouhamed Rassoul Sy, Wageningen University

Keynote Presentation

The Promise of Satellite Imagery and Machine Learning for Measuring Human and Environmental Wellbeing | Tamma Carleton, UC Berkeley

Lightning Talks

Navigating the Trust Gap: A Framework for Ethical Geodata Governance in African Development | Solomon Onyango, Onamika Strategic Capital Limited

PredictFlood | Abla Ruth Agbofoati, AgriTechPlus

EcoDrips | Kossi Elom Hervé Djoguenou

From Geodata to Decisions: A Reproducible, Privacy-Aware Pipeline for Public Service Targeting in LMICs | Joel Christoph, Harvard Kennedy School

Research Session II: Understanding Environmental Stress

Mountain Buffer Zones as Potential Refugia for At-risk Banana Crops | Sally Musungu

Climatic Suitability Analysis for AI Data Center Development in Kenya | Monalisa Mbilinyi, ATOM AI

Influence of Land Use on Urban Heat Islands in Greater Lomé, Togo | Essi Farida Geraldo, University of Lomé

Research Session III: Frontiers in Multimodal Geospatial Machine Learning

Mapping on a Budget: Optimizing Spatial Data Collection for ML| Livia Betti, University of Colorado, Boulder

A High Resolution Look at Long Run Development: Evidence from 1.3 Million Historical Aerial Photographs| Joel Ferguson, University of Wisconsin – Madison

Contextualized poverty targeting with multimodal spatial data and machine learning in Brazzaville, Congo | Woojin Jung, Rutgers University

Workshops

Cropland Map Accuracy and Area Estimation with Remote Sensing and Unbiased Estimators of Area | Josef Wagner, University of Strasbourg – NASA Harvest

GEMS: From Field Data to Decision-Making – Integrating Mobile Georeferenced Data Collection and Business Intelligence for Evidence-Based Public Service Management in Togo | Louis Boffan, World Bank