The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use
The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use
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.
Leyk, Stefan
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Gaughan, Andrea E.
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Adamo, Susana B.
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de Sherbinin, Alex
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Balk, Deborah
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Freire, Sergio
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Rose, Amy
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Stevens, Forrest R.
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Blankespoor, Brian
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Frye, Charlie
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Comenetz, Joshua
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Sorichetta, Alessandro
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MacManus, Kytt
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Pistolesi, Linda
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Levy, Marc
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Tatem, Andrew
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Pesaresi, Martino
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11 September 2019
Leyk, Stefan
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Gaughan, Andrea E.
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Adamo, Susana B.
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de Sherbinin, Alex
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Balk, Deborah
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Freire, Sergio
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Rose, Amy
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Stevens, Forrest R.
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Blankespoor, Brian
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Frye, Charlie
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Comenetz, Joshua
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Sorichetta, Alessandro
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MacManus, Kytt
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Pistolesi, Linda
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Levy, Marc
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Tatem, Andrew
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Pesaresi, Martino
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Leyk, Stefan, Gaughan, Andrea E., Adamo, Susana B., de Sherbinin, Alex, Balk, Deborah, Freire, Sergio, Rose, Amy, Stevens, Forrest R., Blankespoor, Brian, Frye, Charlie, Comenetz, Joshua, Sorichetta, Alessandro, MacManus, Kytt, Pistolesi, Linda, Levy, Marc, Tatem, Andrew and Pesaresi, Martino
(2019)
The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use.
Earth System Science Data, 11 (3).
(doi:10.5194/essd-11-1385-2019).
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.
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The spatial allocation of population
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Submitted date: 21 March 2019
Accepted/In Press date: 25 July 2019
Published date: 11 September 2019
Identifiers
Local EPrints ID: 434156
URI: http://eprints.soton.ac.uk/id/eprint/434156
ISSN: 1866-3516
PURE UUID: b38c8a89-28b5-40df-bb5b-5d8979277def
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Date deposited: 13 Sep 2019 16:30
Last modified: 16 Mar 2024 04:11
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Contributors
Author:
Stefan Leyk
Author:
Andrea E. Gaughan
Author:
Susana B. Adamo
Author:
Alex de Sherbinin
Author:
Deborah Balk
Author:
Sergio Freire
Author:
Amy Rose
Author:
Forrest R. Stevens
Author:
Brian Blankespoor
Author:
Charlie Frye
Author:
Joshua Comenetz
Author:
Kytt MacManus
Author:
Linda Pistolesi
Author:
Marc Levy
Author:
Martino Pesaresi
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