Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone

In recent years, researchers have demonstrated that digital footprints from mobile phones can be exploited to generate data that are useful for transport planning, disaster response, and other development activities—thanks mainly to the high penetr...

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Main Authors:	Matekenya, Dunstan, Espinet Alegre, Xavier, Arroyo Arroyo, Fatima, Gonzalez, Marta
Format:	Working Paper
Language:	English
Published:	World Bank, Washington, DC 2021
Subjects:	URBAN TRANSPORT RESILIENT TRANSPORT MOBILE DATE BIG DATA CDRs DISASTER RESPONSE URBAN PLANNING POVERTY MOBILITY
Online Access:	http://documents.worldbank.org/curated/en/224761611175801192/Using-Mobile-Data-to-Understand-Urban-Mobility-Patterns-in-Freetown-Sierra-Leone http://hdl.handle.net/10986/35033

id	okr-10986-35033
recordtype	oai_dc
spelling	okr-10986-350332022-09-20T00:09:47Z Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone Matekenya, Dunstan Espinet Alegre, Xavier Arroyo Arroyo, Fatima Gonzalez, Marta URBAN TRANSPORT RESILIENT TRANSPORT MOBILE DATE BIG DATA CDRs DISASTER RESPONSE URBAN PLANNING POVERTY MOBILITY In recent years, researchers have demonstrated that digital footprints from mobile phones can be exploited to generate data that are useful for transport planning, disaster response, and other development activities—thanks mainly to the high penetration rate of mobile phones even in low-income regions. Most recently, in the effort to mitigate the spread of COVID-19, these data can be used and explored to track mobility patterns and monitor the results of lockdown measures. However, as rightly noted by other scholars, most of the work has been limited to proofs of concept or academic work: it is hard to point to any real-world use cases. In contrast, this paper uses mobile data to obtain insight on urban mobility patterns, such as number of trips, average trip length, and relation between poverty, mobility, and areas of Freetown, the capital of Sierra Leone. These data were used in preparation of an urban mobility lending operation. Additionally, the paper describes good practices in the following areas: accessing mobile data from telecom operators, frameworks for generating origin and destination matrices, and validation of results. 2021-01-21T17:24:34Z 2021-01-21T17:24:34Z 2021-01 Working Paper http://documents.worldbank.org/curated/en/224761611175801192/Using-Mobile-Data-to-Understand-Urban-Mobility-Patterns-in-Freetown-Sierra-Leone http://hdl.handle.net/10986/35033 English Policy Research Working Paper;No. 9519 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa Africa Western and Central (AFW) Sierra Leone
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English
topic	URBAN TRANSPORT RESILIENT TRANSPORT MOBILE DATE BIG DATA CDRs DISASTER RESPONSE URBAN PLANNING POVERTY MOBILITY
spellingShingle	URBAN TRANSPORT RESILIENT TRANSPORT MOBILE DATE BIG DATA CDRs DISASTER RESPONSE URBAN PLANNING POVERTY MOBILITY Matekenya, Dunstan Espinet Alegre, Xavier Arroyo Arroyo, Fatima Gonzalez, Marta Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
geographic_facet	Africa Africa Western and Central (AFW) Sierra Leone
relation	Policy Research Working Paper;No. 9519
description	In recent years, researchers have demonstrated that digital footprints from mobile phones can be exploited to generate data that are useful for transport planning, disaster response, and other development activities—thanks mainly to the high penetration rate of mobile phones even in low-income regions. Most recently, in the effort to mitigate the spread of COVID-19, these data can be used and explored to track mobility patterns and monitor the results of lockdown measures. However, as rightly noted by other scholars, most of the work has been limited to proofs of concept or academic work: it is hard to point to any real-world use cases. In contrast, this paper uses mobile data to obtain insight on urban mobility patterns, such as number of trips, average trip length, and relation between poverty, mobility, and areas of Freetown, the capital of Sierra Leone. These data were used in preparation of an urban mobility lending operation. Additionally, the paper describes good practices in the following areas: accessing mobile data from telecom operators, frameworks for generating origin and destination matrices, and validation of results.
format	Working Paper
author	Matekenya, Dunstan Espinet Alegre, Xavier Arroyo Arroyo, Fatima Gonzalez, Marta
author_facet	Matekenya, Dunstan Espinet Alegre, Xavier Arroyo Arroyo, Fatima Gonzalez, Marta
author_sort	Matekenya, Dunstan
title	Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
title_short	Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
title_full	Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
title_fullStr	Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
title_full_unstemmed	Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone
title_sort	using mobile data to understand urban mobility patterns in freetown, sierra leone
publisher	World Bank, Washington, DC
publishDate	2021
url	http://documents.worldbank.org/curated/en/224761611175801192/Using-Mobile-Data-to-Understand-Urban-Mobility-Patterns-in-Freetown-Sierra-Leone http://hdl.handle.net/10986/35033
_version_	1764482179908239360

Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone

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