The University of Southampton
×
Filter your search:
University of Southampton Institutional Repository

Census-based gridded population estimates for Bukina Faso (2019), version 1.0

Census-based gridded population estimates for Bukina Faso (2019), version 1.0
Census-based gridded population estimates for Bukina Faso (2019), version 1.0
This repository includes census-disaggregated population gridded estimates for Burkina Faso, using a top-down approach based on Random Forest modelling. A breakdown by age and sex groups is joined to the gridded population count. A technical report explains the methodology, the validation procedures, the input data used and the limitations of the modelling. The data used for modelling are also attached.
Human population, Sub-national, Spatial dataset
University of Southampton
WorldPop,
e0dc4f20-2c0d-494b-8adf-11cb57608ab8
Institut National de la Statistique et de la Démographie,
aca8f0c0-d9d6-4d4b-aa03-53182fba58f2
Bondarenko, Maksym
1cbea387-2a42-4061-9713-bbfdf4d11226
WorldPop,
e0dc4f20-2c0d-494b-8adf-11cb57608ab8
Institut National de la Statistique et de la Démographie,
aca8f0c0-d9d6-4d4b-aa03-53182fba58f2
Bondarenko, Maksym
1cbea387-2a42-4061-9713-bbfdf4d11226

WorldPop, and Institut National de la Statistique et de la Démographie, (2021) Census-based gridded population estimates for Bukina Faso (2019), version 1.0. University of Southampton doi:10.5258/SOTON/WP00687 [Dataset]

Record type: Dataset

Abstract

This repository includes census-disaggregated population gridded estimates for Burkina Faso, using a top-down approach based on Random Forest modelling. A breakdown by age and sex groups is joined to the gridded population count. A technical report explains the methodology, the validation procedures, the input data used and the limitations of the modelling. The data used for modelling are also attached.

This record has no associated files available for download.

More information

Published date: 11 January 2021
Related URLs:
Keywords: Human population, Sub-national, Spatial dataset

Identifiers

Local EPrints ID: 445879
URI: http://eprints.soton.ac.uk/id/eprint/445879
DOI: doi:10.5258/SOTON/WP00687
PURE UUID: 94a8d95f-7b3e-4f9b-933f-1f892ef386e1
ORCID for Maksym Bondarenko: ORCID iD orcid.org/0000-0003-4958-6551

Catalogue record

Date deposited: 13 Jan 2021 17:30
Last modified: 06 May 2023 01:43

Export record

Altmetrics

Contributors

Creator: WorldPop
Creator: Institut National de la Statistique et de la Démographie
Data Manager: Maksym Bondarenko ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Library staff additional information
Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×