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A trip to work: estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR

A trip to work: estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR
A trip to work: estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR

The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively.

Call detail records, CDR, Commuting, Non-supervised learning, Urban planning, Urbanisation
2352-7285
133-165
Zagatti, Guilherme Augusto
90869882-a121-46e2-b309-ebd576eb68be
Gonzalez, Miguel
e77dc324-ee8a-44a6-806f-23dbad2a3d36
Avner, Paolo
f76b97ef-c2c4-4b83-9458-86e472998292
Lozano-Gracia, Nancy
bc164de6-9227-4146-a051-29904d29ec08
Brooks, Christopher J.
5c504fef-0360-4b2a-b6c4-d88bbd6e5bac
Albert, Maximilian
a8049610-1e98-4cfb-b59a-177645a42b47
Gray, Jonathan
93c44ff0-29b8-48a1-be30-09be7d129ed1
Antos, Sarah Elizabeth
a290906f-4d45-4e9d-9f8f-abe659765b71
Burci, Priya
63312f6a-ab21-4f7b-be07-fc46e84c0ca1
zu Erbach-Schoenberg, Elisabeth
9a1f59b2-c661-42c9-ad94-96772c292add
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Wetter, Erik
dd9554f1-7107-4d5b-b19f-7198af551091
Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e
Zagatti, Guilherme Augusto
90869882-a121-46e2-b309-ebd576eb68be
Gonzalez, Miguel
e77dc324-ee8a-44a6-806f-23dbad2a3d36
Avner, Paolo
f76b97ef-c2c4-4b83-9458-86e472998292
Lozano-Gracia, Nancy
bc164de6-9227-4146-a051-29904d29ec08
Brooks, Christopher J.
5c504fef-0360-4b2a-b6c4-d88bbd6e5bac
Albert, Maximilian
a8049610-1e98-4cfb-b59a-177645a42b47
Gray, Jonathan
93c44ff0-29b8-48a1-be30-09be7d129ed1
Antos, Sarah Elizabeth
a290906f-4d45-4e9d-9f8f-abe659765b71
Burci, Priya
63312f6a-ab21-4f7b-be07-fc46e84c0ca1
zu Erbach-Schoenberg, Elisabeth
9a1f59b2-c661-42c9-ad94-96772c292add
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Wetter, Erik
dd9554f1-7107-4d5b-b19f-7198af551091
Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e

Zagatti, Guilherme Augusto, Gonzalez, Miguel, Avner, Paolo, Lozano-Gracia, Nancy, Brooks, Christopher J., Albert, Maximilian, Gray, Jonathan, Antos, Sarah Elizabeth, Burci, Priya, zu Erbach-Schoenberg, Elisabeth, Tatem, Andrew J., Wetter, Erik and Bengtsson, Linus (2018) A trip to work: estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR. Development Engineering, 3, 133-165. (doi:10.1016/j.deveng.2018.03.002).

Record type: Article

Abstract

The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively.

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Accepted/In Press date: 19 March 2018
e-pub ahead of print date: 21 March 2018
Keywords: Call detail records, CDR, Commuting, Non-supervised learning, Urban planning, Urbanisation

Identifiers

Local EPrints ID: 421769
URI: https://eprints.soton.ac.uk/id/eprint/421769
ISSN: 2352-7285
PURE UUID: 5f703fa4-7b6a-48b0-b0a1-a230e7edeb73
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 27 Jun 2018 16:30
Last modified: 14 Mar 2019 01:35

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Contributors

Author: Guilherme Augusto Zagatti
Author: Miguel Gonzalez
Author: Paolo Avner
Author: Nancy Lozano-Gracia
Author: Christopher J. Brooks
Author: Maximilian Albert
Author: Jonathan Gray
Author: Sarah Elizabeth Antos
Author: Priya Burci
Author: Elisabeth zu Erbach-Schoenberg
Author: Andrew J. Tatem ORCID iD
Author: Erik Wetter
Author: Linus Bengtsson

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