The University of Southampton
University of Southampton Institutional Repository

Modelling spatial patterns of urban growth in Africa

Modelling spatial patterns of urban growth in Africa
Modelling spatial patterns of urban growth in Africa
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.
Africa, urban growth, modelling, spatial pattern, boosted regression trees
0143-6228
23-32
Linard, Catherine
231a1de7-72c2-4dc1-bc4e-ea30ed444856
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Gilbert, Marius
c7b7a250-9ec8-47ea-8f08-3b847f0c576c
Linard, Catherine
231a1de7-72c2-4dc1-bc4e-ea30ed444856
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Gilbert, Marius
c7b7a250-9ec8-47ea-8f08-3b847f0c576c

Linard, Catherine, Tatem, Andrew J. and Gilbert, Marius (2013) Modelling spatial patterns of urban growth in Africa. Applied Geography, 44, 23-32. (doi:10.1016/j.apgeog.2013.07.009).

Record type: Article

Abstract

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.

This record has no associated files available for download.

More information

Published date: October 2013
Keywords: Africa, urban growth, modelling, spatial pattern, boosted regression trees
Organisations: Global Env Change & Earth Observation, WorldPop, PHEW – S (Spatial analysis and modelling), Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 355455
URI: http://eprints.soton.ac.uk/id/eprint/355455
ISSN: 0143-6228
PURE UUID: fd0f3fc1-0946-431b-bb07-c941970cb05c
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 28 Aug 2013 15:10
Last modified: 15 Mar 2024 03:43

Export record

Altmetrics

Contributors

Author: Catherine Linard
Author: Andrew J. Tatem ORCID iD
Author: Marius Gilbert

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

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.

×