Session summary
GeoField 2026 opened with a plenary welcome and keynote framing geospatial impact evaluation as both a methodological opportunity and a practical necessity. The session introduced the convening’s central theme: Earth observation can expand what evaluators are able to measure, but only when paired with strong research design, field data, program knowledge, and local context.
Session 1: Plenary Welcome + Keynote
David Laborde, Karen Macours, and Ariel BenYishay opened the convening by reflecting on the growing need for rigorous, cost-effective evidence in climate-sensitive agriculture and related development sectors. Ariel BenYishay welcomed participants on behalf of AidData and described GeoField as the culmination of a multi-year effort to integrate Earth observation into impact evaluations of real-world development programs. David Laborde emphasized the importance of sustaining high-quality evidence generation in settings where ground surveys are costly, difficult, or unsafe. Karen Macours discussed the promise and limits of Earth observation for impact evaluation, noting that satellite data can help address challenges such as limited follow-up periods, noisy self-reported outcomes, restricted geographic coverage, and inaccessible field sites.
Textbook and Field-Building Updates
Kunwar Singh and Claire Zanuso also previewed the forthcoming open-access textbook, Geospatial Impact Evaluation in Practice. The textbook was presented as a collaborative resource for researchers, practitioners, students, and decision-makers, with 32 chapters, 80 contributors, and applied use cases across agriculture, environment, natural resources, health, infrastructure, and mobility. The speakers also discussed related efforts to broaden access, including possible translation and online learning resources.
Together, the opening session set the agenda for the convening. GeoField is not about replacing surveys with satellites. It is about building an interdisciplinary community that can combine remote sensing, field data, program knowledge, and causal inference to evaluate development and climate interventions more rigorously, more quickly, and at greater scale.