Assessing National Progress through Sustainable Development Goal Indicators: The Impact of Alternative Population Grids

In 2015, the international community agreed on 17 Sustainable Development Goals (SDGs) to be achieved by the year 2030. More than 220 SDG indicators were then adopted to measure progress towards these goals at the national level. Many of these indicators are designed to characterize the conditions under which people live, e.g., with respect to access to resources and services, exposure to pollution or hazards, and housing and settlement characteristics. Therefore, understanding where people live in relationship to environmental, infrastructure, and land use/cover data is critical. To facilitate such spatial analysis, various groups have developed gridded population data sets that can be more easily integrated with other spatial data to estimate indicator values. These data sets model population distribution utilizing different algorithms and covariates, leading to variations in indicator estimates depending on the country, indicator, and population data set. We have developed national estimates of selected SDG indicators related to access to roads, open space, and public transport, and land consumption, using several different global georeferenced population data sets, and compared the results. Utilizing the same population data set across both indicators and countries increases consistency between indicators and countries, but may lead to quite different results from indicators estimated using local sources of data, if available. Use of georeferenced population data products, together with continually updated data sources like OpenStreetMap, offers the opportunity to more quickly update SDG indicators as the year 2030 approaches. In addition, subnational estimates of SDG indicators may be valuable in developing and implementing policies and interventions to achieve specific SDGs--and also to leave no one behind.