We regret to inform you that the Gridsample tool and associated services are now closed.
Should you have any questions, please reach out to us at gridsample@flowminder.org. However, if you have knowledge of R, Python and basic Docker, you can run the code directly on your computer using the information available on our GitHub page.
GridSample is a tool to select clusters for household surveys using gridded population data.
This tool may be used when a gridded population dataset is more accurate than the census sample frame, the survey design calls for spatial oversampling to improve small area estimates, or when custom-sized clusters are needed
With the GridSample tool, you can design and implement household surveys from gridded population estimates in low- and middle-income countries.
It provides practitioners with timely, open-access gridded population sample frames and easy-to-use flexible sampling tools. For help, visit the Tutorial page or click on "guidance text" on each tab of the GridSample Tool.
GridSample was developed by the Flowminder Foundation.
Flowminder is an award-winning non-profit organisation whose mission is to enable decision makers to access the data they need to transform the lives of vulnerable people, at scale.
The tool is created with support from the WorldPop team at University of Southampton and the GRID3 programme, with funding from the Bill & Melinda Gates Foundation and the UK's FCDO.
Flowminder has pioneered the use of big data, including the use of mobile operator data, to tackle development and humanitarian challenges.
Flowminder partners with decision makers and key stakeholders in national and international data systems to produce high-quality data, strengthen capacity, develop new methods and tools, and leverage non-traditional and novel data sources to deliver projects that improve the lives of vulnerable populations in low- and middle-income countries.
Case studies
World Food Programme (WFP)
Kinshasa, Democratic Republic of the Congo (DRC)
