Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
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利用孟加拉国的移动网络数据检测气候适应：飓风“马哈森”期间通信、移动和消费模式的异常
DOI：
10.1007/s10584-016-1753-7
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发表时间：
2016-08
期刊：
影响因子：
4.8
通讯作者：
Linus
中科院分区：
文献类型：
--
作者：
Eng？-Monsen;Kenth;Bengtsson;Linus
来自移动电话网络等数字基础设施的大规模数据为受气候压力影响地区的数百万人的行为提供了丰富的信息。利用孟加拉巴里萨尔地区和吉大港地区510万Grameenphone用户的移动和通话行为匿名数据，我们调查了2013年5月袭击巴里萨尔和吉大港的飓风Mahasen的影响。我们描述了气旋前、中和后的呼叫频率、流动补给和种群迁移的时空模式和异常。虽然最初预计分析可能会在风暴过后的几周内检测到沿海地区的大规模疏散和流离失所，但没有发现任何证据表明人口分布有任何永久性的变化。我们在预警信息和风暴登陆前后都检测到了流动性的异常模式，显示了流动性发生的地点和时间及其特征。我们发现移动和呼叫频率的异常模式与降雨强度相关(r=0.75，p<；0.05)，并使用呼叫频率来构建风暴在受影响地区移动时气旋影响的时空分布。同样，通过移动充值购买，我们展示了脆弱地区人们应对风暴的时空模式。除了展示异常检测如何有助于模拟人类对极端气候的适应，我们还确定了未来改进灾害规划和应对活动的几个有希望的途径。
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.
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DOI：
--
发表时间：
2010-03
期刊：
--
影响因子：
--
作者：
Ashish Kapoor;N. Eagle;E. Horvitz
通讯作者：
Ashish Kapoor;N. Eagle;E. Horvitz
DOI：
10.1073/pnas.1203882109
发表时间：
2012-07-17
影响因子：
11.1
作者：
Lu, Xin;Bengtsson, Linus;Holme, Petter
通讯作者：
Holme, Petter
影响因子：
5.4
作者：
Auffhammer, Maximilian;Hsiang, Solomon M.;Sobel, Adam
通讯作者：
Sobel, Adam
DOI：
--
发表时间：
2014
期刊：
--
影响因子：
--
作者：
C. Field;V. Barros;M. Mastrandrea;K. Mach;Abdrabo;W. Adger;Yury A. Anokhin;O. Anisimov;D. Arent-D
通讯作者：
C. Field;V. Barros;M. Mastrandrea;K. Mach;Abdrabo;W. Adger;Yury A. Anokhin;O. Anisimov;D. Arent-D
影响因子：
64.8
作者：
P. Palmer;Matthew J. Smith
通讯作者：
P. Palmer;Matthew J. Smith