Geospatial Impact Evaluation in Practice

Foundations, Methods, and Applications
1. Auflage 2027
ISBN: 978-1-032-77715-3
Verlag: Taylor & Francis Ltd

Buch, Englisch, 944 Seiten, Format (B × H): 178 mm x 254 mm

Governments and institutions invest billions annually to reduce poverty and protect ecosystems, yet conventional evaluations rely on costly, limited surveys that provide only snapshots of change. This book introduces Geospatial Impact Evaluation (GIE), an interdisciplinary framework integrating Earth Observation (EO), remote sensing, GIS, and causal inference to generate spatially explicit, policy-relevant evidence. Enabled by satellite imagery, cloud computing, and AI, GIE expands impact evaluation across space and time, especially in data-scarce settings. This practice-oriented book bridges geospatial science, development economics, and impact evaluation through conceptual foundations, reproducible workflows, real-world datasets, and case studies—helping readers move beyond descriptive mapping toward causally credible evidence for better development decisions. No prior remote sensing or programming expertise required.

Features

- Combines satellite data, spatial analysis, and rigorous methods into a unified evaluation framework.

- Offers step-by-step workflows with real-world datasets using widely adopted software.

- Covers diverse sectors: agriculture, natural resources, climate adaptation, infrastructure, and public health.

- Examines how emerging technologies and geospatial foundation models are transforming evaluation practice

- Features hands-on exercises and adaptable tools for researchers, educators, and practitioners.

An essential resource for researchers, practitioners, policymakers, educators, and students, this book equips readers to generate spatially explicit, causally credible evidence that strengthens development decision-making and maximizes the impact of investments for people and the planet.

Zielgruppe

Postgraduate, Professional Practice & Development, and Undergraduate Advanced

Autoren/Hrsg.

Singh, Kunwar K.

Zanuso, Claire

BenYishay, Ariel

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung
• Geowissenschaften Geologie GIS, Geoinformatik

Inhaltsverzeichnis

Part I. Foundations of Geospatial Impact Evaluation.  1. Introduction to Geospatial Impact Evaluation in Practice.  2. Foundations of geospatial data and methods for impact evaluation.  3. Advanced geospatial analytics: from data to spatial inference.  4. Location data as the foundation for geospatial impact evaluation.  5. Choosing spatial units for geospatial impact evaluation.  6. Treatment geometry and causal identification with earth observation data.  7. Measuring reach and its impact with remote sensing.  8. Uses (and misuses) of earth observation data for weather and vegetation analysis.  9. Foundations of geospatial data engineering.  10. Geospatial foundation models for data generation and indicator production.  11. Geospatial artificial intelligence (GeoAI) in evaluation practice.  12. Integrating ethics into geospatial impact evaluation.  Part II. Methods for Spatial Causal Inference.  13. From ground observation to spatial causal inference.  14. Causal inference and counterfactuals in earth observation research.  15. Designing randomized controlled trials with remote sensing data.  16. Spatial difference-in-differences.  17. Sampling for spatial discontinuity designs.  18. Integrating geospatial impact evaluation into complex evaluations through a structured framework.  Part III. Applied Use Cases: GIE Across Sectors and Geographies.  Environment and Natural Resources. 19. Assessing climate resilience interventions in flood-prone landscapes.  20. Effect of support to protected areas on forest cover.  21. Rainwater harvesting (demi-lune) impacts in arid landscapes.  22. Offsetting forest loss from major infrastructure development.  23. Assessing impacts of landscape restoration interventions.  Agriculture and Food Systems.  24. Assessing impacts of irrigation and land rehabilitation programs.  25. Assessing impacts of small-scale irrigation programs.  26. Matching-based impact evaluations of climate-resilient pastures.  Health, Infrastructure, and Mobility.  27. Measuring typhoon impacts on economic activity.  28. Measuring impacts of the Mexico City policy on reproductive health access.  29. Impact of urban and national transport systems.  30. Estimating impacts of illegal gold mining on forest loss.  31. Women’s travel safety and economic impact.  Perspectives.  32. Beyond Impact: Integrating geospatial thinking across evaluation practice.

Über Autor(innen)

Kunwar K. Singh is a Geospatial Scientist at AidData, William & Mary, specializing in geospatial impact evaluation. His research integrates Earth observation, remote sensing, drones, and advanced geospatial analytics with causal inference to evaluate development interventions. He has led interdisciplinary research across Africa and South Asia on agriculture, water security, climate resilience, and natural resource management. He advances scalable, evidence-based approaches that bridge geospatial science, economics, and international development.

Claire Zanuso is head of the impact evaluation team at the French Development Agency, Paris, France as a development economist since 2016. She completed her Ph.D. in 2015 at Paris-Dauphine University on the impact of natural disasters on households’ vulnerability, coping strategies, and labor market behavior. Her research focuses on labor market issues, expectations of youth and impact evaluations of urban development interventions in developing countries.

Ariel BenYishay is a development economist using geospatial analysis, remote sensing, and randomized control trials to study the human and ecological impacts of development programs. His work focuses on slowing deforestation in tropical regions, as well as on harnessing social networks to promote sustainable agriculture and other practices. He serves as chief economist at AidData, a research lab based at William & Mary and leads geospatial analysis efforts to produce a variety of geospatial data.