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.