Abstract

This paper presents an analysis of transit accessibility to employment for 11 African cities. The use of identical methodologies and similar data sets allows for the creation of the first benchmark to compare accessibility across urban areas in Africa through different metrics and visuals. The study shows how the spatial pattern of land use and transport systems perform in connecting people to employment opportunities in these various settings. This first comparable benchmark is achieved by overcoming two significant data hurdles that are common in many developing country cities and in Africa in particular: (i) the scarcity of information on the distribution of employment and (ii) the lack of information on transit routes and travel times. These data gaps are filled through a novel methodology to estimate the distribution of employment in urban areas (Employment Opportunity Areas) as well as a comprehensive mapping of informal transit networks. The analysis developed here can be replicated in different cities in the future. The computation of these baseline accessibility studies also opens up the possibility to assess the impacts of future transport investments and/or land use changes, through the use of counterfactual scenarios, which could assist decision makers in these cities. Finally, this analysis can serve as a demonstration that the computation of accessibility metrics is achievable, including in data scarce environments, and should be considered as a progress indicator for Sustainable Development Goal 11.2, which focuses on safe and affordable transport for all, including public transport.

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The different versions of the original document can be found in:

http://hdl.handle.net/10986/32223 under the license cc-by
https://openknowledge.worldbank.org/handle/10986/32223,
https://documents.shihang.org/curated/zh/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark,
https://ideas.repec.org/p/wbk/wbrwps/8971.html,
https://academic.microsoft.com/#/detail/2967018335 under the license http://creativecommons.org/licenses/by/3.0/igo
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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.1596/1813-9450-8971
Licence: CC BY-NC-SA license

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