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

• DOI: 10.1007/s10584-016-1753-7
• Publication Date: 2016-08-01T05:33:36Z
• Authors: Xin Lu; David J. Wrathall; Pål Roe Sundsøy; Md. Nadiruzzaman; Erik Wetter; Asif Iqbal; Taimur Qureshi; Andrew J. Tatem; Geoffrey S. Canright; Kenth Engø-Monsen; Linus Bengtsson
• Keywords: Landfall; Anomaly (physics)

Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions people in areas affected by climate stress. Using anonymized mobility and calling 5.1 million Grameenphone users Barisal Division Chittagong District, Bangladesh, we investigate effect Cyclone Mahasen, which struck May 2013. We characterize spatiotemporal patterns anomalies frequency, recharges, population movements before, during after cyclone. While it was originally anticipated that analysis might detect mass evacuations displacement coastal weeks following storm, no evidence found to suggest any permanent changes distributions. anomalous both around time early warning messages storm's landfall, showing where when occurred as well its characteristics. find frequency correlate with rainfall intensity (r = .75, p < 0.05) use construct a distribution cyclone impact storm moves across region. Likewise, recharge purchases show people's preparation for vulnerable areas. In addition demonstrating how anomaly detection can be useful modeling human adaptation extremes, also identify several promising avenues future improvement disaster planning response activities.