Understanding the bias of call detail records in human mobility research

ABSTRACT

In recent years, call detail records (CDRs) have been widely used in human mobility research. Although CDRs are originally collected for billing purposes, the vast amount of digital footprints generated by calling and texting activities provide useful insights into population movement. However, can we fully trust CDRs given the uneven distribution of people’s phone communication activities in space and time? In this article, we investigate this issue using a mobile phone location dataset collected from over one million subscribers in Shanghai, China. It includes CDRs (~27%) plus other cellphone-related logs (e.g., tower pings, cellular handovers) generated in a workday. We extract all CDRs into a separate dataset in order to compare human mobility patterns derived from CDRs vs. from the complete dataset. From an individual perspective, the effectiveness of CDRs in estimating three frequently used mobility indicators is evaluated. We find that CDRs tend to underestimate the total travel distance and the movement entropy, while they can provide a good estimate to the radius of gyration. In addition, we observe that the level of deviation is related to the ratio of CDRs in an individual’s trajectory. From a collective perspective, we compare the outcomes of these two datasets in terms of the distance decay effect and urban community detection. The major differences are closely related to the habit of mobile phone usage in space and time. We believe that the event-triggered nature of CDRs does introduce a certain degree of bias in human mobility research and we suggest that researchers use caution to interpret results derived from CDR data.     

A simple and direct method to analyse the influences of sampling fractions on modelling intra-city human mobility

Sampling fraction is crucial to sampling-related studies and applications, especially in the big data era when most data are neither originally designed nor controllable in the data collection process. A common concern among researchers is ‘what’s the modelling accuracy when using a sample?’. Taking intra-city human mobility as the study objective, this study utilizes a simple and direct method to analyse the influences of various sampling fractions on modelling accuracy. Five common intra-city human mobility indicators (travel distance, travel time, travel frequency, radius of gyration and movement entropy) are evaluated considering mean value, median and probability distribution. Experimental results demonstrate that the representativeness of each considered indicator converges to 1 in its own unique rate and variances. The minimum required sampling fractions to satisfy specific accuracies differ for various indicators and evaluation measures. To further investigate how related factors influence the modelling accuracy of sampling fractions, additional experiments are conducted considering multiple sampling methods, study scopes, and data sources. Several interesting general findings are observed. This study provides a reference for other sampling-based applications.     

老年人公交移动性的季节时空分异特征研究——以安徽省芜湖市为例

移动性是老年人生活质量的重要影响因素,提高老年人的移动性是延长老年人独立生活时间,从而减小社会养老成本的重要手段。公共交通是中国老年人较长距离出行的最主要交通方式,但已有研究对公交移动性的关注较少。论文从季节时空分异的角度出发,利用安徽省芜湖市智能公交卡数据,分析不同季节老年人公交移动性静态空间集聚特征以及季节变化条件下移动性变化值的空间集聚特征。结果表明：① 老年人公交移动性空间集聚明显,呈现圈层式分布的特征。不同季节、不同移动性指标在城市中心、城市中心外围和城市边缘的集聚现象存在较大差异。② 老年人公交移动性的时空分异现象是复合的,不同城市空间对季节变化的敏感程度存在差异,主要呈现出从城市中心向外递增的趋势。研究公交移动性的季节时空分异现象可以为老年友好型城市的规划建设提供更加适当的规划和灵活的政策建议。     

广州市零售商业中心的居民消费时空行为及其机制

居民消费行为的空间选择及其影响因素是地理学的重点关注领域,已有研究对行为中时间选择、时空关系及内在机制的研究相对缺乏。为揭示居民消费时空行为形成的影响因素以及各因素内在相互作用机制,基于2016年广州城市居民消费行为调查数据,分析消费者到大型商业中心内消费的时空特征,构建结构方程模型,探讨消费时空行为影响因素和作用机制。研究表明：居民在商业中心的消费行为存在明显的时空差异。在影响路径方面,消费者社会经济属性通过影响消费偏好导致消费时空行为的差异,商业空间属性既可以直接影响消费时空行为,也可以通过影响消费偏好而间接对其施加影响,消费偏好既可以直接影响消费时空行为,又是消费者社会经济属性和商业空间属性影响消费时空行为的中间变量。在显著性因素方面,年龄、家庭结构、在广州居住时间、就业状况、家庭月收入等消费者社会经济属性变量会显著影响消费时空行为,各个商业空间属性变量都在不同程度上影响消费行为在时间和空间上的差异,仅有出行交通方式、出行花费时间2个消费偏好变量会显著影响消费者消费时空间行为。本文结论可以加深对商业中心内消费时空行为影响因素及其作用机制的理解,并为商业网点规划调整、商业中心转型升级提供建议。     

The benefits of a high-resolution analysis of transit accessibility

Accessibility is an important consideration in sustainable mobility policies, particularly for transit users. Measures suggested in the literature are based on coarse aggregate spatial resolution of traffic analysis zones that is sufficient for managing car travels only. To reflect a human door-to-door travel, transit accessibility demands an explicit view of the location of origin, transit stops and destination, as well as of the temporal fit between transit lines timetable and traveler’s needs. We thus estimate transit accessibility based on mode-specific travel times and corresponding paths, including walking and waiting, at the resolution of individual buildings and stops. Car accessibility is estimated at a high resolution too. A novel representation of transit network as a graph is proposed. This representation includes all modal components of a transit travel – walking, waiting at a stop, transit ride, transfers between lines, thus enabling unified view of a travel, regardless of mode. The use of modern high-performance graph database allows construction of high-resolution accessibility maps for an entire metropolitan area with its 100–200 K buildings. The application is tested and applied in a case study involving the evaluation of the 2011 bus line reform in the city of Tel Aviv. Specifically, we demonstrate that while the reform increased the average accessibility for the entire city the increase was not uniform with different areas of the city experiencing different absolute accessibility by transit and relative accessibility in comparison to car travel. The bus reform did in fact benefit travelers that experienced low relative accessibility, but the benefits are mainly accruing to longer trips. Our approach and computational methods can be employed for directly investigating the impacts of transportation infrastructure investments.     

Will you escort your child to school? The effect of spatial and temporal constraints of parental employment

Children's independent mobility in many urban areas in the United States has been in decline. This implies that children's out-of-home travel involves the company of adults more often than before. This need requires parents to seek ways to balance work-family life. This study examines the factors that influence a parent-child joint trip to school in dual-earner households, with special consideration given to parental work arrangements and location, which act as intra-household temporal and spatial constraints. The study is carried out in the five-county Los Angeles region, drawing from household travel diaries from the 2001 Southern California Association of Governments (SCAG) Post Census Regional Household Travel Survey. The results show that parental employment, especially the mother's, is a very important factor influencing the probability of a joint trip to school. In terms of temporal constraints, longer working hours will reduce the likelihood that a child will be escorted by its parents. However, the option of flexible work hours offsets the negative effect of long working hours by offering a higher degree of scheduling flexibility. In terms of spatial constraints, the closer the mother's workplace is to the school, the more likely it is that the child will be escorted by the parents. This research provides important evidence that a child's joint trip is heavily influenced by the parents' work schedule and location. The findings shed light on how the provision of certain employment policies and programs may affect joint trips to school.     

UK-based terrorists' antecedent behavior: A spatial and temporal analysis

Background and purposeTerrorism is a real and present danger. The build-up to an attack includes planning, travel, and reconnaissance which necessarily require the offender to move through their environment. Whilst research has examined patterns of terrorist attack locations, with a few exceptions (e.g. Rossmo & Harries, 2011), it has not examined the spatial behavior of the terrorists themselves. In this paper, we investigate whether the spatial mobility patterns of terrorists resemble those of criminals (and the wider population) and if these change in the run up to their attacks.MethodUsing mobile phone data records for the ringleaders of four different UK-based terrorist plots in the months leading up to their attacks, we examine the frequency with which terrorists visit different locations, how far they travel from key anchor points such as their home, the distance between sequential cell-site hits and how their range of movement varies as the planned time to attack approaches.ConclusionsLike the wider population (and criminals), the sample of terrorists examined exhibited predictable patterns of spatial behavior. Most movements were close to their home location or safe house, and they visited a relatively small number of locations most of the time. Disaggregating these patterns over time provided mixed evidence regarding the way in which their spatial activity changed as the time to the planned attack approached. The findings are interpreted in terms of how they inform criminological understanding of the spatial behavior of terrorists, and the implications for law enforcement.     

A proportional odds model of human mobility and migration patterns

The modelling of human mobility and migration patterns has received much attention due to its substantial importance. Despite long-term efforts, we still lack a modelling framework that captures mobility patterns and further obtains a prospective view of movement trends with regards to diverse impacting factors. Here, we propose a proportional odds model of human mobility and migration (POM-HM) that takes a probabilistic approach to model human movements. Our model is based on the migration probability with a log-logistic distribution under the proportional odds assumption. Explanatory variables are introduced into the model by re-parameterizing the probability distribution function. The two resultant functions, namely, the migration strength and cumulative hazard, are used to estimate regional differences among travel fluxes and their tendencies. The performance of the POM-HM in terms of its validity and accuracy is examined and compared with the gravity model and the radiation model. The probability-based modelling framework enables us to investigate regional variations in migrant fluxes consequently further predict potential future patterns. In short, our modelling approach captures the probabilistic nature of human mobility and migration and furthers our understanding of both the spatiotemporal patterns of population movements and the impacts of various driving forces.     

Estimating Stable Measured Values and Detecting Anomalies in Groundwater Geochemistry Time Series Data Across the Athabasca Oil Sands Area,Canada

Regional groundwater monitoring in the Athabasca region of Alberta, Canada, provides information on groundwater quality and geochemical changes over time, including data useful for evaluating potential impacts of industrial activity such as oil sands mining and in situ operations. Data collected from over 5000 wells from the 1950s to 2014, including 161 wells from government’s monitoring network, were used to develop and apply bootstrap techniques for the detection of changes in groundwater geochemistry over time and at specific points in time. Increasing temporal anomalies were identified in Cl, TDS, B, and naphthenic acids in the McMurray formation across 2003 and 2008, while decreasing anomalies were found for SO₄. Temporal variance for 15 indicators was quantified for a smooth bootstrap approach to arrive at stable values representative of the most recent samples taken from wells in the study area. Stable values revealed sampling bias in the Devonian, Grand Rapids, Empress, Channel Beverly, and Muriel Lake formations suggesting expansion of sampling may be necessary. Although temporal anomalies were found in the McMurray formation, sampling bias was not identified. The entropy and relative magnitude of time series were evaluated to identify candidate wells for continued observations, which consist of wells with low measurements and low entropy that are near active industry lease boundaries. Temporal anomalies, stable values, and entropy were combined into type-well information to provide plots for visual inspection and interpretation. Stable values are useful for regional mapping, for detecting future changes and trends, and for identifying areas of interest warranting further investigation.

     

移动定位大数据视角下的人群移动模式及城市空间结构研究进展

了解城市人群移动行为和空间结构对城市规划、交通管理、应急响应等具有重要的意义。近年来,随着信息技术(ICT)的快速发展,采集大规模、长时间序列的人群移动定位大数据变得容易,为人群移动行为研究带来了新的机遇和挑战。本文首先介绍了目前用于城市人群移动行为和空间结构研究的主要数据源及其特征,并分别从人群移动行为、城市空间结构2个方面对近3年国内外相关研究进行归纳总结。目前的研究主要从移动定位大数据中挖掘人群移动模式,理解人群移动时空规律,进一步透视城市的空间结构特征;而对城市空间结构与人群移动行为影响的研究较少。未来可通过融合多源时空数据,综合研究人群移动行为与城市空间结构之间的相互作用,发展大规模群体移动行为时空分析理论和模型,进一步深入理解人群移动行为与城市空间结构的耦合关系。     

Analyzing the distribution of human activity space from mobile phone usage: an individual and urban-oriented study

Travel activities are embodied as people’s needs to be physically present at certain locations. The development of Information and Communication Technologies (ICTs, such as mobile phones) has introduced new data sources for modeling human activities. Based on the scattered spatiotemporal points provided in mobile phone datasets, it is feasible to study the patterns (e.g., the scale, shape, and regularity) of human activities. In this paper, we propose methods for analyzing the distribution of human activity space from both individual and urban perspectives based on mobile phone data. The Weibull distribution is utilized to model three predefined measurements of activity space (radius, shape index, and entropy). The correlation between demographic factors (age and gender) and the usage of urban space is also tested to reveal underlying patterns. The results of this research will enhance the understanding of human activities in different urban systems and demographic groups, as well as providing novel methods to expand the important and widely applicable area of geographic knowledge discovery in the age of instant access.     

基于居民行为周期特征的城市空间研究

伴随着中国经济社会进入“新常态”的发展阶段,对城市存量空间的研究提出了更加精细化的要求,基于居民行为活动的周期规律对城市空间进行研究,进而提升城市空间的品质日益重要。随着信息通信技术的快速发展,使许多大数据的获取成为可能,并由于其低成本、即时、大样本等优势,在城市空间研究方面具有巨大的价值。以上海市中心城区为例,利用手机信令数据,探究居民活动的空间周期变化特征,并基于空间的周期特征曲线,采用相似性传播聚类算法进行空间分类。研究表明,居民活动有平日一日周期和平日加周末二日周期,与人的作息规律相符合。市核心区、城市副中心及主要就业中心,昼夜波动和平日周末活动强度的差异都较为明显。空间分类结果显示,城市活动空间的组织既体现出个体充分的空间能动性,也反映出对土地使用类型以及设施建设、投入程度的耦合性。上海市内环内核心区混合多样的用地模式使得活动区内居民活动内容丰富,周期特征功能区边界模糊。研究成果可为未来的城市空间规划提供指导,为城市空间结构、功能布置、设施布局等优化提供决策支撑和科学依据。     

The Moderating Effect of the Ski Resort Environment on the Skier’s Travel Radius under the Restriction of Skill Consumption

Starting from the skill characteristics of ski tourism, this paper discusses the impact of consumer skill on travel decisions, and the moderating effect of the ski resort’s comprehensive leisure environment (including the ski resort sports environment and the regional cultural tourism environment), in order to both understand their impacts on the travel distance characteristics of skiers and attempt to provide necessary research support for the development of China’s ski industry and the construction of destinations. Based on the data from multi-period visitor surveys, this paper constructs the consumption skill-travel radius decision-making influence model under the moderating effect of the ski resort comprehensive leisure environment. The results show three main characteristics. (1) The travel radius obviously differs among skiers with different skill levels. The skill level of skiers has a significant positive effect on the larger travel radius, and a significant negative effect on the smaller travel radius. That is, skiers with a higher skill level are more inclined to undertake long-distance skiing travel, while skiers with a lower skill level are more inclined to undertake short-distance skiing travel. (2) The comprehensive leisure environment has a significant moderating effect on the skiers’ travel radius, with a significant positive impact on enlarging the travel radius, while the influences on high-skill and low-skill skiers are significantly higher than on middle-skill skiers. (3) In the comprehensive leisure environment, there are differences in the moderating effect of the ski resort sports environment and the regional cultural tourism environment on the skiers travel radius, and the positive moderating effect of the ski resort sports environment on the high-skill skiers’ travel radius is more obvious. While the regional cultural tourism environment has a more obvious positive moderating effect on the travel radius of non-skiers and junior skiers, it is more conducive to promoting domestic travel. In general, the skier skill level in China was generally lower, and the ski resort comprehensive leisure environment optimization is conducive to overcoming the limitation of the travel radius caused by the disadvantageous skill level of consumers. However, to promote the development of China’s ski industry in the long run, it is necessary to focus on improving the consumer’s ski skill level, but prevent the risk of losing high-skill consumers overseas. In the course of improving the level of domestic ski sports facilities, we should also focus on the domestic leisure cultural tourism environment to better enhance the attractiveness of domestic ski destinations.     

人类移动性与健康研究中的时间问题

随着地理信息科学的发展,地理学围绕着社会热点问题不断向其他学科交叉渗透,同时学科的交叉也为地理学研究本身注入了热量。空间一直是地理学研究中的基本问题,而时间与空间密不可分,从时间维度研究人类移动性及其丰富内涵具有重要意义。本文在总结人类移动性热点问题的基础上,重点从时间维度探讨了可达性、出行体验与幸福感、人类健康与疾病等问题的研究内容和方法,并从低收入者社区医疗保健可达性研究和阿帕拉契亚乡村地区吸烟者影响因素研究等案例进行详细阐释,最后对人类移动性与健康研究的发展方向进行了展望。     

Constraints of Housing Age and Migration on Residential Mobility

This paper investigates the role of housing age in constraining residential mobility, measured as the percent of households that have moved into their homes in the past 15 months. The leading explanation for why mobility rates differ so much among regions of the United States has been the overall level of growth. The present analysis shows that the growth effect operates through both the newness of population (migration) and the newness of housing available for occupancy by all local residents. The posited explanation for this housing age effect is that progressively older units contain increasingly settled occupants, yielding fewer opportunities for in-movers in areas with older housing. It is empirically demonstrated that households in older housing have lower likelihood of recent mobility even after controlling for age, tenure, migration status, and state location of residence. The analysis reveals the temporal interdependency of mobility, migration, person age, and housing age.     

Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns

Understanding the stability of urban flows is critical for urban transportation, urban planning and public health. However, few studies have measured the stability of aggregate human convergence or divergence patterns. We propose a spatiotemporal model for assessing the stability of human convergence and divergence patterns. A mobile phone location data set obtained from Shenzhen, China, was used to assess the stability of daily human convergence and divergence patterns at three different spatial scales, i.e. points (cell phone towers), lines (bus lines) and areas (traffic analysis zones [TAZs]). Our analysis results demonstrated that the proposed model can identify points and bus lines with time-dependent variations in stability, which is useful for delineating TAZs for transportation planning, or adjusting bus timetables and routes to meet the needs of bus riders. Comparisons of the results obtained from the proposed model and the widely used entropy measure indicated that the proposed model is suitable for assessing the differences in stability for various types of spatial analysis units, e.g. cell phone towers. Therefore, the proposed model is a useful alternative approach of measuring spatiotemporal stability of aggregate human convergence and divergence patterns, which can be derived from the space–time trajectories of moving objects.     

A framework for identifying activity groups from individual space-time profiles

ABSTRACT

Datasets collecting the ever-changing position of moving individuals are usually big and possess high spatial and temporal resolution to reveal activity patterns of individuals in greater detail. Information about human mobility, such as ‘when, where and why people travel’, is contained in these datasets and is necessary for urban planning and public policy making. Nevertheless, how to segregate the users into groups with different movement and behaviours and generalise the patterns of groups are still challenging. To address this, this article develops a theoretical framework for uncovering space-time activity patterns from individual’s movement trajectory data and segregating users into subgroups according to these patterns. In this framework, individuals’ activities are modelled as their visits to spatio-temporal region of interests (ST-ROIs) by incorporating both the time and places the activities take place. An individual’s behaviour is defined as his/her profile of time allocation on the ST-ROIs she/he visited. A hierarchical approach is adopted to segregate individuals into subgroups based upon the similarity of these individuals’ profiles. The proposed framework is tested in the analysis of the behaviours of London foot patrol police officers based on their GPS trajectories provided by the Metropolitan Police.     

Constraints of Housing Age and Migration on Residential Mobility

This paper investigates the role of housing age in constraining residential mobility, measured as the percent of households that have moved into their homes in the past 15 months. The leading explanation for why mobility rates differ so much among regions of the United States has been the overall level of growth. The present analysis shows that the growth effect operates through both the newness of population (migration) and the newness of housing available for occupancy by all local residents. The posited explanation for this housing age effect is that progressively older units contain increasingly settled occupants, yielding fewer opportunities for in-movers in areas with older housing. It is empirically demonstrated that households in older housing have lower likelihood of recent mobility even after controlling for age, tenure, migration status, and state location of residence. The analysis reveals the temporal interdependency of mobility, migration, person age, and housing age.     

基于网络游记的青岛市国内旅游客源市场结构与旅游流时空特征分析

随着“互联网+”的普及和自由行的广泛参与,以网络游记为代表的旅游信息逐渐增多,为旅游客源市场结构与旅游流时空特征研究提供了可靠数据源和新的视角。从携程旅行网与马蜂窝网站采集2016年1月1日至2018年12月31日共3 a的青岛市网络游记并清洗、归纳,共得1 891篇有效样本,涉及全国28个省区市共131个城市,结合统计分析及ArcGIS空间分析方法,以地级市为研究单元深入探索青岛市国内客源市场结构与旅游流时空特征。结果表明:① 青岛市国内客源市场可按客源城市游记样本数量指标划分为核心层、次核心层、中间层、次边缘层、边缘层5个层级,“胡焕庸线”两侧差异显著。② 客源吸引半径达590.68 km,覆盖京津冀、长三角、辽、豫、皖部分地区;引力主场集中在1 500 km范围内,在接近500 km处出现客源最高峰。③ 旅游流年内变化季节差异显著,存在节假日及“峰-谷”循环的周末效应;沿海区市与内陆区市的旅游流空间分布密度极不均衡,4个季度差异显著;旅游流轨迹集中于胶州湾东西两岸,尚未形成串联各景区景点的闭合式旅游环线。     

Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation

Novel digital data sources allow us to attain enhanced knowledge about locations and mobilities of people in space and time. Already a fast-growing body of literature demonstrates the applicability and feasibility of mobile phone-based data in social sciences for considering mobile devices as proxies for people. However, the implementation of such data imposes many theoretical and methodological challenges. One major issue is the uneven spatial resolution of mobile phone data due to the spatial configuration of mobile network base stations and its spatial interpolation. To date, different interpolation techniques are applied to transform mobile phone data into other spatial divisions. However, these do not consider the temporality and societal context that shapes the human presence and mobility in space and time. The paper aims, first, to contribute to mobile phone-based research by addressing the need to give more attention to the spatial interpolation of given data, and further by proposing a dasymetric interpolation approach to enhance the spatial accuracy of mobile phone data. Second, it contributes to population modelling research by combining spatial, temporal and volumetric dasymetric mapping and integrating it with mobile phone data. In doing so, the paper presents a generic conceptual framework of a multi-temporal function-based dasymetric (MFD) interpolation method for mobile phone data. Empirical results demonstrate how the proposed interpolation method can improve the spatial accuracy of both night-time and daytime population distributions derived from different mobile phone data sets by taking advantage of ancillary data sources. The proposed interpolation method can be applied for both location- and person-based research, and is a fruitful starting point for improving the spatial interpolation methods for mobile phone data. We share the implementation of our method in GitHub as open access Python code.