Human mobility across national borders is a key phenomenon of our time. At the global scale, however, we still know relatively little about the structure and nature of such transnational movements. This study uses a large dataset on monthly air passenger traffic between 239 countries worldwide from 2010 to 2018 to gain new insights into (a) mobility trends over time and (b) types of mobility. A time series decomposition is used to extract a trend and a seasonal component. The trend component permits—at a higher level of granularity than previous sources—to examine the development of mobility between countries and to test how it is affected by policy and infrastructural changes, economic developments, and violent conflict. The seasonal component allows, by measuring the lag between initial and return motion, to discern different types of mobility, from tourism to seasonal work migration. Moreover, the exact shape of seasonal mobility patterns is extracted, allowing to identify regular mobility peaks and nadirs throughout the year. The result is a unique classification of trends and types of mobility for a global set of country pairs. A range of implications and possible applications are discussed.

中文翻译：

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剖析全球空中交通数据，以识别跨国人员流动的不同类型和趋势

跨越国界的人员流动是我们这个时代的关键现象。但是，在全球范围内，我们对这种跨国运动的结构和性质仍然知之甚少。这项研究使用了一个庞大的数据集，从2010年到2018年，全球239个国家/地区之间的每月航空客运量获得了以下新见解：（a）随时间推移的交通趋势和（b）交通类型。时间序列分解用于提取趋势和季节成分。趋势成分允许以比以前更高的粒度级别检查国家之间流动性的发展，并测试其如何受到政策和基础设施变更，经济发展以及暴力冲突的影响。通过测量初始运动和返回运动之间的时滞，季节性因素可以识别出不同类型的机动性，从旅游业到季节性工作移民。此外，还提取了季节性出行方式的确切形状，从而可以确定全年的定期出行高峰和最低点。结果是对全球一组国家/地区的趋势和流动性类型进行了独特的分类。讨论了一系列含义和可能的应用。