Preface

Population data at small area scales is a crucial foundation for informed decision-making across various sectors, from public health and disaster management to urban planning and environmental monitoring. The global demand for precise, high-resolution population estimates is growing, as governments, humanitarian organizations, and researchers increasingly rely on this information to address critical societal and environmental challenges. However, obtaining accurate, timely, and spatially disaggregated population data has been a longstanding challenge in many parts of the world, particularly in low- and middle-income countries where administrative data sources can be incomplete and the implementation of regular and high-quality censuses can face logistical and financial obstacles. Such factors can mean that small area population data are outdated, incomplete or lacking completely in many settings.

The WorldPop Book of Methods, Vol. I: Gridded Population Estimates represents an important step in addressing this gap by providing an accessible and comprehensive guide to WorldPop’s gridded population data sets and the methodologies behind them that can complement traditional census processes. As the first volume in this series, this book seeks to not only offer technical insight into the approaches and innovations developed by WorldPop, but also to serve as a valuable resource for the broader scientific and policy-making communities engaged in population-related research and applications.

The WorldPop Research Group, based in the University of Southampton’s School of Geography and Environmental Science, has been at the forefront of global population mapping efforts for over a decade. Our work draws on interdisciplinary expertise, spanning fields such as geography, demography, epidemiology, statistics, computer science, and remote sensing. WorldPop’s core mission is to undertake innovative research to empower decision-makers to harness the power of reliable, inclusive, and accurate spatial demographic data. This involves the production of high-resolution, open-access population data to support development, health, and emergency response activities, especially in regions where recent and reliable demographic data collected through traditional methods are scarce or outdated. Through novel modeling techniques and the integration of diverse data sources, we aim to produce population estimates that are reliable, transparent, and adaptable to different user needs.

This book details the cutting-edge methods used to generate WorldPop’s gridded population estimates, which combine satellite imagery, census data, surveys, and machine learning algorithms. Each chapter delves into specific methodological aspects, ranging from data collection and processing to spatial modelling and validation. Contributors to this volume include leading researchers and practitioners in the fields of spatial demography whose expertise has been instrumental in refining these techniques over time.

A significant aspect of WorldPop’s approach is its commitment to openness, collaboration and co-development with stakeholders. We make the data sets and methods described in this book freely available to the public, reflecting our belief that access to accurate population information is a global public good. We also acknowledge the crucial role of partnerships with international agencies, national statistical offices, and regional organizations in enabling the co-development and successful implementation of WorldPop’s models in diverse settings.

This volume acknowledges the invaluable contributions of our collaborators and funders, whose support has enabled the creation of WorldPop’s toolbox of methods and extensive population databases. By making these methods available in an open and transparent manner, we hope to inspire further innovation and improvement in population estimation methodologies.

We are thrilled to share this resource with you in the hopes that the ideas and techniques discussed here will aid in the creation of precise, timely, and useful population data that will enhance human well-being worldwide.

Prof. Andrew Tatem
Director
WorldPop
University of Southampton

Acknowledgements

This work is the culmination of the collective efforts of many individuals and organizations, to whom we owe our deepest gratitude. We are especially thankful to our esteemed colleagues at the WorldPop Research Group, whose unwavering support has been integral to the successful production of this book.

We extend our heartfelt thanks to Ortis Yankey for his invaluable assistance in converting the various chapters into RMarkdown scripts and for his meticulous work in compiling the book. We are equally grateful to Amy Bonnie, Somnath Chaudhuri, and Gianluca Boo for their thoughtful feedback and thorough review, which greatly enhanced the quality of this publication. We want to also thank Douglas Leasure for starting this Book of Method project and to Edith Darin for providing support to the project.

We also wish to acknowledge the generous financial support of our key funding partners, without whom this work would not have been possible: the Bill & Melinda Gates Foundation, the United Nations Population Fund (UNFPA), Geo-Referenced Infrastructure and Demographic Data for Development (GRID3), the Foreign, Commonwealth & Development Office (FCDO), and the World Bank, as well as other United Nations agencies. Their contributions have been instrumental in advancing the research and outputs shared in this book.