globalchange  > 气候减缓与适应
DOI: 10.1007/s10584-016-1753-7
Scopus记录号: 2-s2.0-84982851928
论文题名:
Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
作者: Lu X.; Wrathall D.J.; Sundsøy P.R.; Nadiruzzaman M.; Wetter E.; Iqbal A.; Qureshi T.; Tatem A.J.; Canright G.S.; Engø-Monsen K.; Bengtsson L.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 138, 期:2018-03-04
起始页码: 505
结束页码: 519
语种: 英语
英文关键词: Anomaly detection ; Climate change adaptation ; Disaster risk ; Migration ; Mobile network data ; Resilience
Scopus关键词: Climate change ; Disaster prevention ; Disasters ; Mobile telecommunication systems ; Signal detection ; Telephone circuits ; Wireless networks ; Anomaly detection ; Climate change adaptation ; Digital infrastructures ; Migration ; Mobile phone networks ; Resilience ; Spatiotemporal distributions ; Spatiotemporal patterns ; Storms ; adaptive management ; anomaly ; calling behavior ; cyclone ; disaster management ; environmental management ; extreme event ; human behavior ; mobile communication ; precipitation intensity ; spatiotemporal analysis ; Bangladesh ; Barisal ; Chittagong [Bangladesh]
英文摘要: 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. © 2016, The Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84192
Appears in Collections:气候减缓与适应
气候变化事实与影响

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作者单位: Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden; Flowminder Foundation, Stockholm, Sweden; College of Information System and Management, National University of Defense Technology, Changsha, China; College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR, United States; Telenor Research, Oslo, Norway; Department of Geography, University of Exeter, Exeter, United Kingdom; International Centre for Climate Change and Development, Dhaka, Bangladesh; Stockholm School of Economics, Stockholm, Sweden; WorldPop, Department of Geography and Environment, University of Southampton, Southampton, United Kingdom

Recommended Citation:
Lu X.,Wrathall D.J.,Sundsøy P.R.,et al. Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen[J]. Climatic Change,2016-01-01,138(2018-03-04)
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