Leveraging similarity analysis to understand variability in movement behavior

The increasingly large volume of trajectories of moving entities obtained through GPS and cellphone tracking, telemetry, and other location-aware technologies motivates researchers to understand the implicit patterns hidden in movement trajectories and understand how movement is influenced by the environmental context. Trajectory similarity serves as an important tool in computational movement analysis and as the foundation of revealing those patterns. However, there are various trajectory similarity measures, each of which has its own strengths and weaknesses. In this article, we present a hierarchical clustering framework that integrates five commonly used similarity measures, including Fréchet distance, dynamic time warping, Hausdorff distance, longest common subsequence, and normalized weighted edit distance, a special kind of edit distance for movement analysis. The framework aims at clustering similar patterns and identifying variability in movement. The optimal number of clusters are first obtained. Then, the clusters are characterized by environmental variables to explore the associations between variability in movement and the environmental conditions. We evaluate the proposed framework using 15 years of tracking data of turkey vultures, tracked at 1- to 3-h sampling intervals, during their fall and spring migration seasons. The results suggest that, at 5% significance level, turkey vultures select their movement paths intentionally and those selections appear to be related to certain environmental context variables, including thermal uplift, vegetation state (observed indirectly through Normalized Difference Vegetation Index), temperature, precipitation, tailwind, and crosswind. And interestingly, there exist preferential differences among individuals. Although the preference of the same turkey vulture is not strictly consistent over different years, each individual tends to preserve a more similar preference over different years, compared with the preferences of other turkey vultures.     

Nonthermal radio emission from hot star winds

Nonthermal radio emission has been observed from some of the most luminous hot star winds. It is understood to be synchrotron radiation of the relativistic electrons in the winds. To understand how the electrons are accelerated to such high energies and to correctly explain the observed radio flux and spectra require an exhaustive investigation of all the relevant physical processes involved and possibly point to a complex wind structure. In this paper we discuss the logical path toward a comprehensive model of the nonthermal radio emission from hot star winds. Based on the available observational data and fundamental theoretical considerations, we found that the only physically viable and self-consistent scenario is:the nonthermal radio emission is synchrotron radiation of relativistic electrons the electrons are accelerated by shocks via the first-order Fermi mechanism the acceleration has to be in situ in the radio emitting region the shocks formed at the base of the winds have to propagate to beyond the radio photosphere).     

The hypermedia data model based on the infinity image

This paper presents the hypermedia data model based on the infinity RS image information system we have developed. The hypermedia data model consists of different semantic units called nodes, and the associations between nodes are called links. This paper proposes three kinds of nodes (interior node, physical node and complex node) and two kinds of links (plane network structure link, hyper-cube network structure links). The hypermedia information system, based on the model and the basic data layer (the infiniy RS image), represents a digital globe. An approach to the “Getting Lost in the Hyper-space” problem is presented. The approach using the hypermedia data model is an efficient way of handling a large number of RS images in various geographical information systems.     

Spatial and Temporal Dynamics of Urban Heat Island and Their Relationship with Land Cover Changes in Urbanization Process: A Case Study in Suzhou, China

One of the significant environmental consequences of urbanization is the urban heat island (UHI). In this paper, Landsat TM images of 1986 and 2004 were utilized to study the spatial and temporal variations of heat island and their relationships with land cover changes in Suzhou, a Chinese city which experienced rapid urbanization in past decades. Land cover classifications were derived to quantify urban expansions and brightness temperatures were computed from the TM thermal data to express the urban thermal environment. The spatial distributions of surface temperature indicated that heat islands had been largely broadened and showed good agreements with urban expansion. Temperature statistics of main land cover types showed that built-up and bare land had higher surface temperatures than natural land covers, implying the warming effect caused by the urbanization with natural landscape being replaced by urban areas. In addition, the spatial detail distributions of surface temperature were compared with the distribution of land cover by means of GIS buffer analysis. Results show remarkable show good correspondence between heat island variations with urban area expansions.     

Classifying Human Activity Patterns from Smartphone Collected GPS data: A Fuzzy Classification and Aggregation Approach

Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone‐measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone‐collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g. up to 96% in activity identification) using of this method. Two examples are provided in the Appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.     

中原城市群与产业群耦合发展研究

依托空间偏离-份额模型建立了产业群与城市群耦合发展的基本分析框架,并对中原城市群进行了定量诊断。研究结果表明:2001—2013年间,首位城市郑州的产业实力和集聚扩散能力显著提升,产业群与城市群的耦合在地理空间呈圈层式扩展态势,然而城市群尚未形成功能等级与分工协作明确的区域综合经济体。继续实施中心城市带动战略、发挥成员城市比较优势促进城际产业链接、完善城市群综合交通运输网络是促进产业群与城市群耦合、提高群域经济发展水平和增强城市竞争力的有效手段。     

孔兹岩系——山西吕梁地区界河口群的年代学和地球化学

吕梁地区界河口群主要由变泥砂质岩石和一定数量的大理岩及少量斜长角闪岩等类岩石组成。7个变泥砂质岩石样品分析,ΣREE=152～322μg/g,Eu/Eu