ICT数据中的空间信息是否可靠？
Is spatial information in ICT data reliable?
摘要：
越来越多的人类活动是利用个人的信通技术设备产生的数据进行研究的。特别是，当信通技术数据包含空间信息时，它们是分析城市动态的宝贵来源。然而，有相对较少的贡献，调查这类结果对数据特征波动的鲁棒性。在这里，我们提出了一个稳定性分析，从手机数据中提取的更高层次的信息被动产生在一整年的900万人在塞内加尔。我们专注于两个信息检索任务：（a）识别的土地利用在达喀尔地区的时间节奏的通信活动;（b）识别的家庭和工作地点的匿名个人，这使得构建通勤流的起源-目的地（OD）矩阵。我们的分析表明，结果的不确定性在很大程度上取决于样本大小，规模和收集数据的年份。然而，不同样本计算的土地利用的空间分布是非常强大的：平均而言，我们观察到超过75%的共享表面积之间的不同空间分区时，考虑到至少10万用户的活动，无论规模。OD矩阵不太稳定，并且取决于在考虑从100，000个用户的家庭工作位置构建的所有类型的流时，至少有75%的通勤者共享的规模。对于这两项任务，可以在更大的聚合级别或通过考虑更多的用户来获得更好的结果。这些结果证实，信通技术数据是城市系统空间分析的非常有用的来源，但其可靠性一般应更彻底地测试。
英文摘要：
An increasing number of human activities are studied using data produced by individuals' ICT devices. In particular, when ICT data contain spatial information, they represent an invaluable source for analyzing urban dynamics. However, there have been relatively few contributions investigating the robustness of this type of results against fluctuations of data characteristics. Here, we present a stability analysis of higher-level information extracted from mobile phone data passively produced during an entire year by 9 million individuals in Senegal. We focus on two information-retrieval tasks: (a) the identification of land use in the region of Dakar from the temporal rhythms of the communication activity; (b) the identification of home and work locations of anonymized individuals, which enable to construct Origin-Destination (OD) matrices of commuting flows. Our analysis reveal that the uncertainty of results highly depends on the sample size, the scale and the period of the year at which the data were gathered. Nevertheless, the spatial distributions of land use computed for different samples are remarkably robust: on average, we observe more than 75% of shared surface area between the different spatial partitions when considering activity of at least 100,000 users whatever the scale. The OD matrix is less stable and depends on the scale with a share of at least 75% of commuters in common when considering all types of flows constructed from the home-work locations of 100,000 users. For both tasks, better results can be obtained at larger levels of aggregation or by considering more users. These results confirm that ICT data are very useful sources for the spatial analysis of urban systems, but that their reliability should in general be tested more thoroughly.
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