Gridded Population Datasets: Which One Is Fit For Purpose?
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CANBERRA — Access to timely and reliable data on population is critical to delivering global development programs and humanitarian assistance. It helps governments, donors, and implementing partners understand what services people have access to and the challenges they face both geographically and socially.
Gridded population datasets — spatial databases on global populations that can be analyzed within mapping software — enable this to be achieved. But awareness of them is low.
A new report, “Leaving No One Off the Map: A Guide for Gridded Population Data for Sustainable Development,” aims to help fill this gap by providing researchers and policymakers with guidance on how gridded population data can support critical decision-making, and what limitations exist.
“This report aims to bring attention to the importance of gridded population data in a clear and accessible way, particularly for individuals who may lack the time and technical expertise to understand differences among various products and assess their strengths and weaknesses for potential applications,” Maryam Rabiee, Sustainable Development Solutions Network TReNDS manager and report author, told Devex.
What population datasets are available?
Gridded population datasets are expansions — not a replacement — of data collected as part of national census collection rounds, modelling known growth between years to spatially represent the changing population.
“The survey revealed that nearly all of the countries surveyed were unfamiliar with the major gridded population datasets included in the report.”
Seven gridded population datasets are assessed in the report, each using different processes to model data that create different population results. But they each offer unique values that can support various areas of development work.
The Gridded Population of the World and WorldPop are two gridded datasets that both enable demographic characteristics, including age and sex, through a digital population database.
The High Resolution Settlement Layer — a dataset produced in a collaboration between Facebook, the World Bank, and the Center for International Earth Science Information Network — also enable age and sex breakdowns with a detailed understanding of settlements in urban and rural areas, although not distinguished between commercial and residential areas.
Through a separation of urban and rural estimates, the Global Rural-Urban Mapping Project dataset is considered to provide one of the better estimates of rural, coastal, and remote populations. LandScan, on the other hand, enables users to distinguish between night and day populations — especially important for areas that have high population movements for business.
The Global Human Settlement Layer is produced using a method that enables a globally consistent time series — making it more appropriate for analyses across time — while the World Population Estimate is considered useful for large-scale population analysis.
Continual improvements are being made in the data in terms of accuracy, timeliness, and coverage of additional variables beyond simply counting people. And it continues to be tested for accuracy and usefulness.
“With the range of different population datasets now available, it is critical that we test how accurate these data products actually are by comparing estimates against known conditions on the ground,” Raibee said. “Moreover, additional validation work will help detail other nuances to consider when choosing and evaluating datasets.”
Will 2020 census delays impact gridded population data?
As the gridded population data is built upon census information, delays in 2020 censuses — due to COVID-19 — will impact future development of the products. According to the United Nations Population Fund, more than 65 countries have confirmed possible delays to their censuses this year.
“There is still a lot of uncertainty, and many countries are still figuring out whether to proceed with, cancel, or postpone their censuses,” Rabiee said.
“As all of the global gridded datasets included in the report are built off the census data, and the reliability of the input population data is the most important factor in the overall accuracy of the resulting estimates, the delayed censuses are likely to impact the gridded population datasets moving forward.”
Data is one thing — but what other capabilities are needed?
“In terms of hardware or software, all that is needed is a Mac or PC and [software supporting] a geographic information system,” said Alex De Sherbinin, senior research scientist at CIESIN.
QGIS, a free, open-source geographic information system software package, is a tool De Sherbinin recommends to provide a cost-effective way of delving into gridded population data, with online training — including a training course CIESIN is releasing soon.
“Many government ministries — especially for health, environment or land and natural resources — in even the least developed countries have GIS capacity,” he said.
But simply knowing that these datasets exist and can be used is also an important capability to have.
As part of the research for this report, SDSN TReNDS partnered with the Global Partnership for Sustainable Development Data to survey capacity within their country partners including Paraguay, Nepal, Ghana, Tanzania. Rabiee said that the survey showed the importance of the report through the lack of awareness governments had on gridded population datasets.
“The survey revealed that nearly all of the countries surveyed were unfamiliar with the major gridded population datasets included in the report,” she said. “In particular, the results demonstrated that they lacked the knowledge and understanding of how to navigate the nuances of each of the datasets and where to apply them.”
Organizations such as Grid3, Raibee said, are performing in-country training with national statistics offices on how to produce and use these datasets to help fill the knowledge gap.
“But there is a lot more work to be done.”