A method for discovery and analysis of temporal patterns in complex event data

Pattern analysis techniques currently common within geography tend to focus either on characterizing patterns of spatial and/or temporal recurrence of a single event type (e.g., incidence of flu cases) or on comparing sequences of a limited number of event types where relationships between events are already represented in the data (e.g., movement patterns). The availability of large amounts of multivariate spatiotemporal data, however, requires new methods for pattern analysis. Here, we present a technique for finding associations among many different event types where the associations among these varying event types are not explicitly represented in the data or known in advance. This pattern discovery method, known as T-pattern analysis, was first developed within the field of psychology for the purpose of finding patterns in personal interactions. We have adapted and extended the T-pattern method to take the unique characteristics of geographic data into account and implemented it within a geovisualization toolkit for an integrated computational-geovisual environment we call STempo. To demonstrate how T-pattern analysis can be employed in geographic research for discovering patterns in complex spatiotemporal data, we describe a case study featuring events from news reports about Yemen during the Arab Spring of 2011–2012. Using supplementary data from the Global Database of Events, Language, and Tone, we briefly summarize and reference a separate validation study, then evaluate the scalability of the T-pattern approach. We conclude with ideas for further extensions of the T-pattern technique to increase its utility for spatiotemporal analysis.     

芜湖市城市公园体系等级结构及其时空分布格局

近年来,随着城市化进程的加快,建设城市公园以满足生活需要成了备受关注的热点问题。本文尝试构建城市公园综合吸引力模型,并运用分形、聚类等方法,建立芜湖市城市公园等级体系,并分析其时空分布特征。研究表明：芜湖市城市公园在Z.ipf分布模型中呈现出双分形结构,可分为两个大类六个等级。城市公园体系具有等级层次性不强、高等级公园中心性明显等特征;高等级公园具有极强的老城区指向性、人口稠密区指向性和经济实力强区指向性,低等级公园散布在人口稠密区、数量多、分布范围广;总体上呈现出中心集聚、外围松散,分布不均衡的空间格局。自然条件是公园形成的基础条件,近年来为满足城市发展和城市居民需求,政府规划和企业行为是城市公园形成的决定性因素,各因素相互作用,共同影响着城市公园体系的形成和发展。     

和田绿洲景观破碎化特征及驱动因素

景观破碎化改变着区域景观结构的完整性和系统的连通性,对景观的稳定性和可持续发展具有重要影响.选取新疆和田绿洲为研究区,以1970年新疆考察数据与MSS影像,1990、2000、2013、2018年4期Landsat TM/ETM+同月相数据为主要数据源,采用景观指数法、移动窗口法、梯度分析及归因分析等方法开展绿洲景观破...     

时空轨迹聚类方法研究进展

时空轨迹(Trajectory)是移动对象的位置和时间的记录序列.作为一种重要的时空对象数据类型和信息源,时空轨迹的应用范围涵盖了人类行为、交通物流、应急疏散管理、动物习性和市场营销等诸多方面.通过对各种时空轨迹数据进行聚类分析,可以提取时空轨迹数据中的相似性与异常特征,并有助于发现其中有意义的模式.本文根据时空轨迹数...     

The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data

Mobile phone location data have been extensively used to understand human mobility patterns through the employment of mobility indicators. The temporal sampling interval (TSI), which is measured by the temporal interval between consecutive records, determines how well such data can describe human activities and influence the values of human mobility indicators. However, systematic investigations of how the TSI affects human mobility indicators remain scarce, and characterizing those relationships is a fundamental research question for many related studies. This study uses a mobile phone location dataset containing 19,370 intensively sampled individual trajectories (TSI < 5 minutes) to systematically assess the impacts of the TSI on four typical mobility indicators that describe human mobility patterns from different aspects, which are movement entropy, radius of gyration, eccentricity, and daily travel frequency. We find that different TSIs have complex impacts on the values of different mobility indicators. Specifically, (1) coarser TSIs tend to underestimate the values of the four selected indicators with different degrees; (2) the degrees of underestimation vary significantly among users for eccentricity and daily travel frequency but exhibit high inter-user consistency for radius of gyration and movement entropy. The above findings can help better understand the variations among human mobility studies.     

Sensitivity of disease cluster detection to spatial scales: an analysis with the spatial scan statistic method

ABSTRACT

The spatial scan statistic method has been widely used for detecting disease clusters. Its results may be affected by scales, including the aggregation level of the input data and the population threshold used in the detection. Previous studies offered inconsistent findings, and few had considered both types of scales at the same time. Using 24 simulated datasets and two real disease datasets, we investigated the method’s sensitivity to the two types of scales. We aggregated the individual-level data into areal units of three levels, including county, town, and a 900 m grid. We detected clusters with three population thresholds, including 10%, 25%, and 50%. We used two measurements, distance between cluster centres and the Jaccard index, to quantify the consistency of clusters detected with different scale settings. We find: (1) the method is not greatly sensitive to the data aggregation level when the cluster is strong and in a place with high population density; (2) the method’s sensitivity to the population threshold is determined by the actual size of the true cluster; and (3) a regular grid with fine resolution is advantageous over the subjectively defined areal units. The process and findings may have broader meanings to similar spatial analyses.     

北极大气波导时空分布研究

在北极地区,有接通北美洲、欧洲北部和亚洲北部国家之间距离最短的直线路线,所以北极地区的战略位置日益重要。大气波导是重要的电波环境,利用大气波导可实现超短波、微波频段的超视距探测和通信应用。因此,研究北极大气波导有重要的意义。本文利用2007年1月—2016年12月十年的气象探空数据,统计分析了北极16个站点大气波导的时空分布,给出了大气波导出现概率与其波导层厚度、强度特征量的统计特征,并从天气和气候学角度初步探讨了其成因。统计结果显示:1.北极地区大气波导平均出现概率低于50%,且表面波导出现概率高于悬空波导; 2.表面波导层厚度、强度分别在30 m以下和10 M以下,悬空波导层厚度在40—80 m,强度小于10 M; 3.北欧海区和格陵兰岛为北极波导高发区,欧亚大陆的北部边缘为无波导区; 4.表面波导高发区在北欧海区和格陵兰岛,北大西洋暖流、格陵兰冷高压及极夜期的辐射逆温是表面波导形成的可能原因; 5.悬空波导高发区在北欧海区和白令海峡东北部区域,且在7—8月份的暖季极昼期间为其高发季,北欧海区暖季海雾、白令海峡东北部区域暖季受北极锋影响是悬空波导形成的可能原因。     

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。     

基于大数据的极端暴雨事件下城市道路交通及人群活动时空响应

随着全球气候变化加剧,极端降雨增多,暴雨内涝灾害频发,严重威胁城市的可持续发展。快速掌握暴雨给城市交通及人群的影响,有助于提高灾害应急管理水平和事件响应能力。利用实时动态的交通路况信息和手机定位请求数据,通过一种融合STL时序分解技术与极端学生化偏差统计检验的时间序列异常探测方法,监测和分析暴雨内涝灾害事件中,城市道路交通和人群活动的时空响应特征,并以2018年7月16日发生在北京的极端暴雨事件为例开展实证研究。研究结果显示,在降雨集中的早、晚高峰两个时段（8—9时、18—19时）,市区的拥堵道路数量超出往常水平最高可达150%,异常检测分析显示拥堵道路数量和交通拥堵指数均达到异常甚至极端水平。人群活动的异常响应分析结果显示,暴雨事件引起定位请求量异常升高、异常点增多,且异常点的空间分布与1 h前的降雨量分布存在较高相关性。以上结果不仅证明了大数据及异常检测方法对于快速洞察暴雨事件对城市交通及人群影响的有效性,也为城市暴雨内涝灾害的应急响应与管理提供了新的技术手段。     

1979~2005年青藏高原位势高度场变化趋势的时空特征

利用NCEP/NCAR位势高度再分析资料分析了1979~2005年青藏高原及其邻近地区30hPa、100hPa、300hPa和500hPa位势高度场变化趋势的时空特征。研究表明:(1)1979~2005年青藏高原区域平均位势高度场在对流层中层存在上升趋势,且主要发生在冷半年;随着等压面的升高,高度场上升趋势减弱;到平流层高度场呈显著降低趋势,且主要发生在暖半年。(2)从空间上看,平流层位势高度场年平均变化整体呈显著降低趋势,大致呈纬向分布,南部降低趋势强于北部,特别是高原东南、孟加拉湾北部降低趋势最强;对流层中层位势高度场变化趋势以上升为主,高原东北部上升趋势尤其显著。(3)尽管与高原各层位势高度值本身相比,变化趋势是一个小量,但国内外不同区域及不同空间尺度的研究都发现有类似现象,故对此应给予重视。今后应进一步加强青藏高原位势高度场时空变化趋势的驱动机制、影响及其对全球变暖的区域响应研究。(4)1979年以来NCEP/NCAR位势高度再分析资料用于青藏高原及其邻近地区的气候变化研究是有效的。     

基于互联网房产数据的住宅容积率多尺度时空特征——以广州市为例

基于网络爬虫技术获取房产时空数据,结合时间序列和空间自相关分析方法,在“小区—街道—区级”多尺度上探索广州市住宅容积率时空模式与演化规律。结果表明：① 近三十年广州市居住空间呈现中心城区集聚开发—向南、北方向近郊区拓展—往南、北、东方向远郊区外扩的演变过程,容积率呈现波动式增长态势。② 随着房地产的快速发展,住宅容积率逐渐呈现显著的空间自相关特征,体现了住宅开发与规划有序性的提高。③ 区级尺度上容积率呈现较强的自相关性,越秀区与天河区为HH集聚区,从化区为LL集聚区。街道尺度上容积率呈现出显著的空间不均衡性,区位交通条件较好的街道成为容积率HH集聚区,而LL集聚区主要分布于生态旅游重镇。     

Measures of transport mode segmentation of trajectories

ABSTRACT

Rooted in the philosophy of point- and segment-based approaches for transportation mode segmentation of trajectories, the measures that researchers have adopted to evaluate the quality of the results (1) are incomparable across approaches, hence slowing the progress in the field and (2) do not provide insight about the quality of the continuous transportation mode segmentation. To address these problems, this paper proposes new error measures that can be applied to measure how well a continuous transportation mode segmentation model performs. The error measures introduced are based on aligning multiple inferred continuous intervals to ground truth intervals, and measure the cardinality of the alignment and the spatial and temporal discrepancy between the corresponding aligned segments. The utility of this new way of computing errors is shown by evaluating the segmentation of three generic transportation mode segmentation approaches (implicit, explicit–holistic, and explicit–consensus-based transport mode segmentation), which can be implemented in a thick client architecture. Empirical evaluations on a large real-word data set reveal the superiority of explicit–consensus-based transport mode segmentation, which can be attributed to the explicit modeling of segments and transitions, which allows for a meaningful decomposition of the complex learning task.     

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.     

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