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Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh

Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh
Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh
Climate change is likely to drive migration from environmentally stressed areas. However quantifying short and long-term movements across large areas is challenging due to difficulties in the collection of highly spatially and temporally resolved human mobility data. In this study we use two datasets of individual mobility trajectories from six million de-identified mobile phone users in Bangladesh over three months and two years respectively. Using data collected during Cyclone Mahasen, which struck Bangladesh in May 2013, we show first how analyses based on mobile network data can describe important short-term features (hours–weeks) of human mobility during and after extreme weather events, which are extremely hard to quantify using standard survey based research. We then demonstrate how mobile data for the first time allow us to study the relationship between fundamental parameters of migration patterns on a national scale. We concurrently quantify incidence, direction, duration and seasonality of migration episodes in Bangladesh. While we show that changes in the incidence of migration episodes are highly correlated with changes in the duration of migration episodes, the correlation between in- and out-migration between areas is unexpectedly weak. The methodological framework described here provides an important addition to current methods in studies of human migration and climate change.
climate change, adaptation, disaster, mobile data, migration, bangladesh
0959-3780
1-7
Lu, Xin
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Wrathall, David J.
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Sundsøy, Pål Roe
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Nadiruzzaman, Md.
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Wetter, Erik
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Iqbal, Asif
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Qureshi, Taimur
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Tatem, Andrew
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Canright, Geoffrey
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Engø-Monsen, Kenth
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Bengtsson, Linus
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Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d
Wrathall, David J.
ecd694c6-838c-4e24-b1cf-0005c700fcce
Sundsøy, Pål Roe
84d88a87-2120-4fb6-a48e-cc7176e3b5a8
Nadiruzzaman, Md.
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Wetter, Erik
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Iqbal, Asif
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Qureshi, Taimur
c4da8b5a-aa68-4e66-9e64-ec36dfb35cde
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Canright, Geoffrey
9b68d117-594d-437c-a8d7-817b0f84ad42
Engø-Monsen, Kenth
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Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e

Lu, Xin, Wrathall, David J., Sundsøy, Pål Roe, Nadiruzzaman, Md., Wetter, Erik, Iqbal, Asif, Qureshi, Taimur, Tatem, Andrew, Canright, Geoffrey, Engø-Monsen, Kenth and Bengtsson, Linus (2016) Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh. Global Environmental Change, 38, 1-7. (doi:10.1016/j.gloenvcha.2016.02.002).

Record type: Article

Abstract

Climate change is likely to drive migration from environmentally stressed areas. However quantifying short and long-term movements across large areas is challenging due to difficulties in the collection of highly spatially and temporally resolved human mobility data. In this study we use two datasets of individual mobility trajectories from six million de-identified mobile phone users in Bangladesh over three months and two years respectively. Using data collected during Cyclone Mahasen, which struck Bangladesh in May 2013, we show first how analyses based on mobile network data can describe important short-term features (hours–weeks) of human mobility during and after extreme weather events, which are extremely hard to quantify using standard survey based research. We then demonstrate how mobile data for the first time allow us to study the relationship between fundamental parameters of migration patterns on a national scale. We concurrently quantify incidence, direction, duration and seasonality of migration episodes in Bangladesh. While we show that changes in the incidence of migration episodes are highly correlated with changes in the duration of migration episodes, the correlation between in- and out-migration between areas is unexpectedly weak. The methodological framework described here provides an important addition to current methods in studies of human migration and climate change.

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More information

Accepted/In Press date: 8 February 2016
e-pub ahead of print date: 22 February 2016
Published date: May 2016
Keywords: climate change, adaptation, disaster, mobile data, migration, bangladesh
Organisations: Global Env Change & Earth Observation, WorldPop, Geography & Environment, Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 388532
URI: https://eprints.soton.ac.uk/id/eprint/388532
ISSN: 0959-3780
PURE UUID: acd76503-ee22-4fc6-94df-cb56b113812e
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 29 Feb 2016 10:30
Last modified: 15 Aug 2019 00:36

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Contributors

Author: Xin Lu
Author: David J. Wrathall
Author: Pål Roe Sundsøy
Author: Md. Nadiruzzaman
Author: Erik Wetter
Author: Asif Iqbal
Author: Taimur Qureshi
Author: Andrew Tatem ORCID iD
Author: Geoffrey Canright
Author: Kenth Engø-Monsen
Author: Linus Bengtsson

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