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== Abstract ==
 
== 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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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.
  
 
Document type: Book
 
Document type: Book
  
 
== Full document ==
 
== Full document ==
<pdf>Media:Draft_Content_115870944-beopen764-5591-document.pdf</pdf>
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<pdf>Media:Peralta-Quiros_et_al_2019a-beopen415-4438-document.pdf</pdf>
  
  
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The different versions of the original document can be found in:
 
The different versions of the original document can be found in:
  
* [http://documents.worldbank.org/curated/en/514081565267887937/pdf/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark.pdf http://documents.worldbank.org/curated/en/514081565267887937/pdf/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark.pdf]
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* [http://dx.doi.org/10.1596/1813-9450-8971 http://dx.doi.org/10.1596/1813-9450-8971] under the license https://creativecommons.org/licenses/by
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* [https://openknowledge.worldbank.org/bitstream/10986/32223/4/WPS8971.pdf https://openknowledge.worldbank.org/bitstream/10986/32223/4/WPS8971.pdf]
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* [http://documents.worldbank.org/curated/en/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark http://documents.worldbank.org/curated/en/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark],
 +
: [http://hdl.handle.net/10986/32223 http://hdl.handle.net/10986/32223] under the license cc-by
 +
 
 +
* [https://documents.worldbank.org/curated/en/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark https://documents.worldbank.org/curated/en/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark],
 +
: [https://openknowledge.worldbank.org/handle/10986/32223 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://documents.shihang.org/curated/zh/514081565267887937/Exploring-Accessibility-to-Employment-Opportunities-in-African-Cities-A-First-Benchmark],
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: [https://ideas.repec.org/p/wbk/wbrwps/8971.html https://ideas.repec.org/p/wbk/wbrwps/8971.html],
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: [https://academic.microsoft.com/#/detail/2967018335 https://academic.microsoft.com/#/detail/2967018335] under the license http://creativecommons.org/licenses/by/3.0/igo

Latest revision as of 14:28, 21 January 2021

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.

Document type: Book

Full document

The URL or file path given does not exist.


Original document

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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