NDLI: Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen

Content Provider	Springer Nature Link
Author	Lu, Xin Wrathall, David J. Sundsøy, Pål Roe Nadiruzzaman, Md. Wetter, Erik Iqbal, Asif Qureshi, Taimur Tatem, Andrew J. Canright, Geoffrey S. Engø Monsen, Kenth Bengtsson, Linus
Copyright Year	2016
Abstract	Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions of people in areas affected by climate stress. Using anonymized data on mobility and calling behavior from 5.1 million Grameenphone users in Barisal Division and Chittagong District, Bangladesh, we investigate the effect of Cyclone Mahasen, which struck Barisal and Chittagong in May 2013. We characterize spatiotemporal patterns and anomalies in calling frequency, mobile recharges, and population movements before, during and after the cyclone. While it was originally anticipated that the analysis might detect mass evacuations and displacement from coastal areas in the weeks following the storm, no evidence was found to suggest any permanent changes in population distributions. We detect anomalous patterns of mobility both around the time of early warning messages and the storm’s landfall, showing where and when mobility occurred as well as its characteristics. We find that anomalous patterns of mobility and calling frequency correlate with rainfall intensity (r = .75, p < 0.05) and use calling frequency to construct a spatiotemporal distribution of cyclone impact as the storm moves across the affected region. Likewise, from mobile recharge purchases we show the spatiotemporal patterns in people’s preparation for the storm in vulnerable areas. In addition to demonstrating how anomaly detection can be useful for modeling human adaptation to climate extremes, we also identify several promising avenues for future improvement of disaster planning and response activities.
Starting Page	505
Ending Page	519
Page Count	15
File Format	PDF
ISSN	01650009
Journal	Climatic Change
Volume Number	138
Issue Number	3-4
e-ISSN	15731480
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-08-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Climate change adaptation Migration Resilience Mobile network data Anomaly detection Disaster risk Atmospheric Sciences Climate Change/Climate Change Impacts
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Global and Planetary Change

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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