The POPGRID Data Collaborative aims to bring together and expand the international community of data providers, users, and sponsors concerned with georeferenced data on population, human settlements and infrastructure. We seek to improve data access, timeliness, consistency, and utility; support data use and interpretation; identify and address pressing user needs; reduce duplication and user confusion; and encourage innovation and cross-disciplinary use.
Many of the Sustainable Development Goals’ (SDGs) indicators have a direct connection to total population count, and gridded population data are valuable for policymakers to measure population growth, monitor change, and plan interventions. Traditionally, population counts are derived from census data. However, infrequent intervals of data collection, inaccessibility to certain geographic locations, and other social constraints (e.g. language barriers between enumerators and indigenous communities) often leave many uncounted in the total population estimates. Over the past two decades, high resolution satellite imagery, advanced Geospatial Information Systems (GIS) and remote sensing capabilities have created the opportunity to produce gridded population datasets (using different modeling approaches to disaggregate population data using spatial data and imagery) that can complement census data and fill in the gaps. For instance, gridded population data easily integrates with remote sensing data, it allows population data to be aggregated to non-administrative geographies, and for certain data sets it allows users to compare units of the same shape and size. These benefits all work towards the goal of leaving no one behind.
We bring expertise and perspectives from diverse natural, social, health, and engineering science disciplines and sectors, and from government, academia, private industry, and nongovernmental organizations. We promote cooperation in producing and harmonizing high-quality data products and services needed by a range of scientific and applied users. This includes:
Improving accessibility and documentation of data sets and data services
Comparing and contrasting methods and implications of different data sources
Convening technical experts from the geospatial and demographic communities at events and conferences worldwide
Providing online tools and services to facilitate user visualization and intercomparison for specific regions and types of data of interest
Developing an intercomparison report that clarifies how different data sets