Implications for Tracking SDG Indicator Metrics with Gridded Population Data
Creators: name: Tuholske, Cascade
name: Gaughan, Andrea E.
name: Sorichetta, Alessandro
name: de Sherbinin, Alex
name: Bucherie, Agathe
name: Hultquist, Carolynne
name: Stevens, Forrest
name: Kruczkiewicz, Andrew
name: Huyck, Charles
name: Yetman, Greg
Publisher: name: GEO Knowledge Hub
Year: 2022
Subjects: subject: Sustainable Development Goals
subject: SDG
subject: sdgs
subject: Hazards
subject: Earth Observation
subject: EO
subject: Remote Sensing
subject: RS
subject: Demography
subject: FOS: Sociology
subject: Urbanization
subject: Gridded Population
subject: Management, Monitoring, Policy and Law
subject: Renewable Energy, Sustainability and the Environment
subject: Geography, Planning and Development
subject: Resolution: 1KM+
subject: Data Source: Landsat
subject: Data Source: MODIS
subject: Format: Raster
subject: Data Type: Float
subject: Level: Global

description: Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial scales needed to monitor SDG progress. While the increasing abundance of Earth observation-derived gridded population products provides analysis-ready population estimates, end users lack clear use criteria to track SDGs indicators. In fact, recent comparisons of gridded population products identify wide variation across gridded population products. Here we present three case studies to illuminate how gridded population datasets compare in measuring and monitoring SDGs to advance the "fitness for use" guidance. Our focus is on SDG 11.5, which aims to reduce the number of people impacted by disasters. We use five gridded population datasets to measure and map hazard exposure for three case studies: the 2015 earthquake in Nepal; Cyclone Idai in Mozambique, Malawi, and Zimbabwe (MMZ) in 2019; and flash flood susceptibility in Ecuador. First, we map and quantify geographic patterns of agreement/disagreement across gridded population products for Nepal, MMZ, and Ecuador, including delineating urban and rural populations estimates. Second, we quantify the populations exposed to each hazard. Across hazards and geographic contexts, there were marked differences in population estimates across the gridded population datasets. As such, it is key that researchers, practitioners, and end users utilize multiple gridded population datasets—an ensemble approach—to capture uncertainty and/or provide range estimates when using gridded population products to track SDG indicators. To this end, we made available code and globally comprehensive datasets that allows for the intercomparison of gridded population products.
Article
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Related materials
This resource is associated with the Earth Observations Toolkit for Sustainable Cities and Human Settlements. If you want to learn more about it, please, check the EO Toolkit portal (https://eotoolkit.unhabitat.org/), a place where you will find use cases, learning material, and many other tools and resources related to the Sustainable Development Goal 11 and New Urban Agenda.