Dynamic population mapping using mobile phone data
Dynamic population mapping using mobile phone data
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DOI：
10.1073/pnas.1408439111
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发表时间：
2014-11-11
影响因子：
11.1
通讯作者：
Tatem, Andrew J.
中科院分区：
文献类型：
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作者：
Deville, Pierre;Linard, Catherine;Tatem, Andrew J.
在过去的几十年里，遥感、地理信息系统和全球定位系统等技术已经改变了研究人口分布的方式，并在空间和时间上进行了建模。然而，人口绘图工作仍然受到人口普查和调查后勤工作的制约。因此，在需要及时信息的情况下，如灾害、冲突或流行病，很难评估按天、周或月甚至按年划分的空间详细变化，并限制了人口地图的应用。移动的电话（MP）现在在地球仪上具有极高的渗透率，并且分析地理定位到塔水平的MP呼叫的时空分布可以克服基于人口普查的方法的许多限制，只要适当地评估和校准MP数据的使用。使用来自葡萄牙和法国的超过10亿MP通话记录的数据集，我们展示了如何在国家尺度上对人口密度进行空间和时间上的明确估计，以及这些估计与使用其他人口映射方法产生的输出进行比较。我们还演示了如何在多个时间尺度上生成人口变化的地图，同时保持MP用户的匿名性。由于世界各地的MP网络提供商每天都在收集类似的数据，因此能够在相对较短的时间间隔内绘制当代和不断变化的人口分布图的前景是存在的，这为新的应用和对人文地理模式和过程的近实时理解铺平了道路。
During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.