Year-end Sale % OFF 
Abstract
Abstract. Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.
Highlights
The distribution and density of human population continues to be a critical component to measuring, mapping and understanding human–environment interrelationships; identifying populations at risk of infectious diseases or disasters; and informing management and policy decisions from local- to global-level initiatives (e.g., Wesolowski et al, 2014; Simarro et al, 2011; McDonald et al, 2011; Jones et al, 2008; McGranahan et al, 2007; Doocy et al, 2007)
The traditional form of collecting population data is through a census or registry, and those population counts can be spatially linked to boundary datasets representing enumeration areas or administrative units in a Geographic Information System (GIS)
The combination of access, increased computing power and greater spatial accuracy in ancillary datasets has provided the basis for methodological advances to redistribute censusenumerated population counts to grid cells at continental and global scales with high accuracy (e.g., Freire et al, 2018) and to create time series of population estimates that can be used to fill in data gaps between national census surveys that are commonly taken at decadal intervals (e.g., WorldPop and Center for International Earth Science Information Network (CIESIN), 2018)
Summary
The distribution and density of human population continues to be a critical component to measuring, mapping and understanding human–environment interrelationships; identifying populations at risk of infectious diseases or disasters; and informing management and policy decisions from local- to global-level initiatives (e.g., Wesolowski et al, 2014; Simarro et al, 2011; McDonald et al, 2011; Jones et al, 2008; McGranahan et al, 2007; Doocy et al, 2007). The combination of access, increased computing power and greater spatial accuracy in ancillary datasets has provided the basis for methodological advances to redistribute censusenumerated population counts to grid cells at continental and global scales with high accuracy (e.g., Freire et al, 2018) and to create time series of population estimates that can be used to fill in data gaps between national census surveys that are commonly taken at decadal intervals (e.g., WorldPop and CIESIN, 2018). “Fitness for use” is a concept that has often been used to assess the appropriateness of a given spatial dataset for an intended purpose (Agumya and Hunter, 1999; de Bruin et al, 2001; Devillers et al, 2007) This concept will be applied to guide a growing user community in making informed decisions regarding the most appropriate dataset(s) for their intended use by better understanding the characteristics of the available different data products that include the modeling assumptions behind them.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
