Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) – Phase 2
Project leads: Andy Tatem, Attila Lazar
Team: Sarchil Qader, Maksym Bondarenko, Heather Chamberlain, Tom Abbott, Chris Nnanatu, Assane Gadiaga, Duygu Cihan, Edith Darin, Chris Jochem, Ortis Yankey, Pat Jones, Ollie Pannel, Graeme Hornby, David Kerr, Gianluca Boo, Doug Leasure, Claire Dooley, Donna Clarke, Tim O’Riordan, Alexandra Frosch
Funding: Bill and Melinda Gates Foundation/Center for International Earth Science Information Network (CIESIN)
Start: Jan 2020
Completion: Dec 2022
The GRID3 initiative facilitates the production, collection, use, and dissemination of high-resolution population, infrastructure and other reference data. The overall aims are to support decision-making in low- and middle-income countries, and United Nations’ Sustainable Development Goals (SDGs). The GRID3 partners, CIESIN, UNFPA, Flowminder Foundation and ourselves work closely with governments and local stakeholders in Sub-Saharan Africa.
Our core activity within this initiative was in method development and implementation of high-resolution population mapping. This involved bespoke modelling methods for estimation of population numbers in the absence of national census using machine learning and Bayesian statistical approaches. High resolution geo-spatial covariate production was included in this process, as well as microcensus sampling design and questionnaire development, model development, data visualization and user interface development that enabled the easy and timely uptake of outputs by stakeholders.
We also provided assistance to national census authorities to improve their use of geospatial data collection technologies, incorporating remote sensing data, use of GIS, and related activities into census planning and operations.
We developed training materials and a curriculum on GIS, geospatial analysis, hybrid census, population estimation, and ‘R’ programming and delivered these through in-person and remote capacity strengthening workshops and during regional workshops organised by UNFPA. We also developed tools enable easier data utilisation and survey design:
- population data repository and user interface – wopr and woprVision,
- automated simple population estimation tool,
- pre-Enumeration Area delineation (Qader et al., 2021), and
- sample design for surveys – GridEZ
Webinars
- GRID3 videos
- DHIS2 Webinar on Micro-planning
- Gridded population data for decision making
- Mapping subnational boundaries
- Mapping settlements
Publications
- High-resolution population estimation using household survey data and building footprints
- Tools for mapping multi-scale settlement patterns of building footprints: An introduction to the R package foot
- Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings
- National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty
- Classifying settlement types from multi-scale spatial patterns of building footprints
- A grid-based sample design framework for household surveys
White papers
- Generating and Evaluating Digitised Census Enumeration Areas
- Mapping and Classifying Settlement Locations
- Harmonising Subnational Boundaries
Blog posts
- Population estimates in the Democratic Republic of the Congo draw on one of the largest survey efforts in almost 40 years
- South Sudan’s microcensus marks an important first step in campaign to leave no one behind
- Physical distancing datasets can help control COVID-19 spread in sub-Saharan Africa’s urban areas
- High-resolution population estimates improve understanding of displacement in South Sudan
- Modelled population estimates for census under-coverage make Burkina Faso’s population visible in times of conflict news story
- Tackling COVID-19 in Nigeria: using population data to model virus spread post-lockdown
- Mapping Subnational Boundaries
- GRID3 tests semi-automatic mapping of pre-Enumeration Areas to support census cartography in the Democratic Republic of the Congo
Countries
- Rwanda
- Kenya
- Mozambique
- Zambia
- Uganda
- Nigeria
- Democratic Republic of the Congo
- Senegal
- Niger
- Burkino Faso
- Zimbabwe
- Mali
- Guinea
- Cameroon
- Mozambique
- South Sudan
- Benin
- Sierra Leone
Related WorldPop projects
About Us
The WorldPop research programme, based in the School of Geography and Environmental Sciences at the University of Southampton, is a multi-sectoral team of researchers, technicians and project specialists that produces data on population distributions and characteristics at high spatial resolution.
Initiated in October 2013 to combine The AfriPop Project, AsiaPop and AmeriPop projects, we have a diverse portfolio of projects, including large multi-million-pound collaborative projects with partner organisations, commercial data providers and international development organisations.