Gridded disaggregated population estimates for Mozambique, version 2.0.
Gridded disaggregated population estimates for Mozambique, version 2.0.
These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund (UNICEF) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Mozambique Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Amy Bonnie supported the covariates processing work. In-country engagement were done by Katia Quinhas, Sandra Baptista, Maria Muniz. The National Bureau of Statistics of Mozambique (INE) released the updated yearly census-based total population projection and projection by age-groups, and sex (female and male) using the results of the 2017 national census. In addition, the District-level administrative boundaries were shared by INE. Attila N Lazar and Edith Darin advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem.
population, Mozambique, Demographic, gridded datasets
University of Southampton
Gadiaga, Assane
eada3464-b0a2-4aaa-b594-eff8182c2aee
Bonnie, Amy
2f08b4e7-768a-4aa0-8c4c-4d23f0b01311
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Darin, Édith
868fa688-2567-4dbd-aa12-3dcc91f2aa8d
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Gadiaga, Assane
eada3464-b0a2-4aaa-b594-eff8182c2aee
Bonnie, Amy
2f08b4e7-768a-4aa0-8c4c-4d23f0b01311
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Darin, Édith
868fa688-2567-4dbd-aa12-3dcc91f2aa8d
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Gadiaga, Assane, Bonnie, Amy, Lazar, Attila, Darin, Édith and Tatem, Andrew
(2024)
Gridded disaggregated population estimates for Mozambique, version 2.0.
University of Southampton
doi:10.5258/SOTON/WP00764
[Dataset]
Abstract
These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund (UNICEF) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Mozambique Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Amy Bonnie supported the covariates processing work. In-country engagement were done by Katia Quinhas, Sandra Baptista, Maria Muniz. The National Bureau of Statistics of Mozambique (INE) released the updated yearly census-based total population projection and projection by age-groups, and sex (female and male) using the results of the 2017 national census. In addition, the District-level administrative boundaries were shared by INE. Attila N Lazar and Edith Darin advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem.
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More information
Published date: 1 March 2024
Keywords:
population, Mozambique, Demographic, gridded datasets
Identifiers
Local EPrints ID: 487796
URI: http://eprints.soton.ac.uk/id/eprint/487796
PURE UUID: 1fc20b03-f13f-459a-bf62-2bb57b2b4670
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Date deposited: 05 Mar 2024 18:16
Last modified: 06 Mar 2024 03:08
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Contributors
Creator:
Assane Gadiaga
Creator:
Amy Bonnie
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