Summary Report of the POPGRID workshop on Gridded Population Data in the Context of the Sustainable Development Goals
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, changes in reporting units’ boundaries, 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 Geographical Information Systems (GIS) and remote sensing capabilities have created the opportunity to produce gridded population datasets (based on different modeling approaches to disaggregate population data using spatial ancillary data and imagery) that can complement census data and fill in existing data gaps. For instance, gridded population data can easily be integrated with remote sensing data, aggregated to non-administrative, and alternative geographies. These benefits all work towards the goal of leaving no one behind.
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