Anchor uncertainty and space-time prisms on road networks

Space-time prisms capture all possible locations of a moving person or object between two known locations and times given the maximum travel velocities in the environment. These known locations or ‘anchor points’ can represent observed locations or mandatory locations because of scheduling constraints. The classic space-time prism as well as more recent analytical and computational versions in planar space and networks assume that these anchor points are perfectly known or fixed. In reality, observations of anchor points can have error, or the scheduling constraints may have some degree of pliability. This article generalizes the concept of anchor points to anchor regions: these are bounded, possibly disconnected, subsets of space-time containing all possible locations for the anchor points, with each location labelled with an anchor probability. We develop two algorithms for calculating network-based space-time prisms based on these probabilistic anchor regions. The first algorithm calculates the envelope of all space-time prisms having an anchor point within a particular anchor region. The second algorithm calculates, for any space-time point, the probability that a space-time prism with given anchor regions contains that particular point. Both algorithms are implemented in Mathematica to visualize travel possibilities in case the anchor points of a space-time prism are uncertain. We also discuss the complexity of the procedures, their use in analysing uncertainty or flexibility in network-based prisms and future research directions.     

Map-matching algorithm for large-scale low-frequency floating car data

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.     

Incorporating behavior into animal movement modeling: a constrained agent-based model for estimating visit probabilities in space-time prisms

ABSTRACT

Animal movement is a dynamic spatio-temporal process. While trajectory data reflect the instantaneous animal position in space and time, other factors influence movement decisions between these observed positions. While some methods incorporate environmental (habitat) context into their understanding of the animal movement process, it is often captured in terms of simple parameters or weights influencing model results; primary behavioral data are not used directly to inform these models. Here, a new space-time constrained agent-based model is introduced, capable of producing ordered, behaviorally informed animal potential paths between observed space-time anchors. Potential paths generated by this approach incorporate both observed animal behavior and classical space-time constraints, and are used to construct associated visit probability distributions. Additionally, the notion of a behavioral space-time path is introduced, a variant of the space-time path based on the results of behaviorally aware animal movement simulation. The results of this approach demonstrate a means to better understand the varied movement opportunities within space-time prisms from an animal behavior perspective. From a spatial ecology perspective, not only is the environmental context considered, but the animal’s choice of transition and movement magnitude between contexts is modeled. This approach provides insight into the complex sequence of behaviorally informed actions driving animal movement decision-making.     

商人流迁与市场系统的时空组织模式

本文分别讨论了流动商在地方性交换系统、区域间贸易系统及流动性零售系统中的作用及其市场系统的时空分布特征,并分析了网上空间市场的崛起对商人流迁影响。     

中国区域创新的时空动态分析

基于探索性空间数据分析和验证性空间面板模型,本文探讨了2000年以来中国区域创新的时空动态。结果表明：① 自创新战略实施以来,中国各省区创新产出的年均增长率几乎都经历了一个剧烈的加速过程,说明区域创新能力的总体提升,但是,东部沿海地区仍然在创新产出中居于压倒性地位,导致“沿海—内陆”分化加剧和区域鸿沟的进一步突出,省区创新可能会陷入“强者愈强,弱者愈弱”的“马太效应”;② 中国区域创新产出与创新投入的空间集聚随时间推移不断强化,通过识别不同时期各变量“热点”,表明创新产出“热点”地区与创新投入“热点”具有高度的时空耦合特征;③ 人均GDP、研发投入、研发人员及在校大学生数对省区创新产出有显著的直接影响。省区间创新活动存在明显的空间溢出效应,其知识溢出的地理区域跨越了省区边界。空间依赖性的存在导致省区间创新活动具有反馈效应,相邻省区的知识溢出对该省区的创新活动具有实质性影响。     

基于手机基站数据的城市交通流量模拟

基于移动定位数据的城市内社会经济活动特征分析是人类移动性的重要研究内容,而交通流量更是这些特征的基本反映。为还原城市道路网络的使用情况并分析其分布特征,本文从产生交通流量的个体出发,对包含基站位置的手机话单数据进行系统抽样,利用蒙特卡洛方法产生个体的出行起止点,并结合当地道路交通网络求得最短路径,最后估算出一天内道路交通网络上的流量分布。通过分析发现：城市内大部分道路的流量小,使用率低,大部分交通流量集中在小部分主干道路;进一步统计分析可知,当地道路交通流量符合20/80规律,即大约20%的道路承担着80%的交通流量;而对不同类型的道路,流量分布也反映出其在城市道路网络中的地位和作用。此研究对于历史交通流量分布的重现、城市道路交通模式的研究以及基于此的道路网络规划情景模拟都有着重要意义。     

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。     

福建省年均温空间分布模拟研究

收集、整理和分析了福建省71个气象观测站点30年(1961～1990)年均温的资料,建立了数据库;以福建省1∶100000的数字等高线图为基础底图,在ArcGIS支持下,生成福建省数字高程模型(DEM),在此基础上,生成福建省经、纬度及海拔宏观地理因素数据库;采用趋势面分析与克里金(Kriging)插值相结合的混合插值模型,进行气温空间分布模拟,为快速模拟福建省年均温空间分布提供了一种行之有效的方法,对福建省气温资源的专题应用具有重要的意义.     

福建省年均温空间分布模拟研究

收集、整理和分析了福建省71个气象观测站点30年(1961～1990)年均温的资料,建立了数据库;以福建省1∶100 000的数字等高线图为基础底图,在ArcGIS支持下,生成福建省数字高程模型(DEM),在此基础上,生成福建省经、纬度及海拔宏观地理因素数据库;采用趋势面分析与克里金(Kriging)插值相结合的混合插值模型,进行气温空间分布模拟,为快速模拟福建省年均温空间分布提供了一种行之有效的方法,对福建省气温资源的专题应用具有重要的意义.     

Agent-based modeling within a cyberinfrastructure environment: a service-oriented computing approach

Agent-based models (ABM) allow for the bottom-up simulation of dynamics in complex adaptive spatial systems through the explicit representation of pattern–process interactions. This bottom-up simulation, however, has been identified as both data- and computing-intensive. While cyberinfrastrucutre provides such support for intensive computation, the appropriate management and use of cyberinfrastructure (CI)-enabled computing resources for ABM raise a challenging and intriguing issue. To gain insight into this issue, in this article we present a service-oriented simulation framework that supports spatially explicit agent-based modeling within a CI environment. This framework is designed at three levels: intermodel, intrasimulation, and individual. Functionalities at these levels are encapsulated into services, each of which is an assembly of new or existing services. Services at the intermodel and intrasimulation levels are suitable for generic ABM; individual-level services are designed specifically for modeling intelligent agents. The service-oriented simulation framework enables the integration of domain-specific functionalities for ABM and allows access to high-performance and distributed computing resources to perform simulation tasks that are often computationally intensive. We used a case study to investigate the utility of the framework in enabling agent-based modeling within a CI environment. We conducted experiments using supercomputing resources on the TeraGrid – a key element of the US CI. It is indicated that the service-oriented framework facilitates the leverage of CI-enabled resources for computationally intensive agent-based modeling.     

区域经济增长时空分异模拟方法——以京津冀都市圈为例

区域经济增长是有着丰富时空内涵的动态变化过程,认识和定量分析这种动态变化过程一直受到广泛关注。借助农业区位论、增长极理论和梯度推移理论的学术思想、概念和术语,在量化定义区域经济增长空间概念的基础上,提出了基于GIS技术的区域经济增长时空分异模拟方法,进而以京津冀都市圈为例进行实证研究和专业分析。研究结果表明:京津冀都市圈由城市增长极中心向外围,随着距离的增大,经济增长呈现出了显著的衰减特征,不同城市之间存在着明显的经济低谷地带。1993~2003年期间,都市圈的经济增长时空分异尤以京、津两市的极化增长最为显著;京、津两大增长极除对唐山方向有拉动效应外,对其它地市的带动辐射力度尚较小;都市圈内部的城市等级还未完全展开,尚未形成合理的梯度推移和梯级演化结构。     

Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin,Paris, and Tallinn

This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of temporal events referenced as ‘midnight’, ‘morning start’, ‘midday’, and ‘duration of day’, which represent the mobile telephone usage of residents (what we call social time) rather than solar or standard time. Density maps by time quartiles were also utilized to test the versatility of this methodology and to analyze the spatial differences in cities. The methodology was tested with data from cities of Harbin (China), Paris (France), and Tallinn (Estonia). Results show that the developed methods have potential for measuring the distribution of temporal activities in cities and monitoring urban changes with georeferenced mobile phone data.     

Simulating Movement-Related Resource Dynamics to Improve Species Distribution Models: A Case Study with Oilbirds in Northern South America

A better understanding of the current and future distributions of organisms is a critical facet of biodiversity conservation, and species distribution models (SDMs) are an important framework for achieving this. Despite the potential of SDMs to address an array of biogeography questions, they are subject to a number of conceptual and methodological uncertainties, such as the role of animal movement processes in determining geographic ranges. Movement processes have only recently been incorporated in SDMs, predominantly conceptualized as broad-scale movement processes (e.g., dispersal), while finer scale ambulatory movements of mobile animals (e.g., foraging) have been omitted. This research addresses this gap by developing a model that simulates the dynamic relationship between movement and biotic resources (e.g., food sources) for oilbirds (Steatornis caripensis) in Venezuela. This simulation represented the sustainability of an oilbird’s neighborhood, based on the connectivity, accessibility, and viability of its biotic resources. These dynamic variables improved the accuracy and ecological realism of the SDM projection compared to other commonly applied SDM scenarios. Integration of a Lagrangian (individual-level) form of movement in SDM with step-selection functions to parameterize biased-correlated random walks provides a new empirical framework for applying geographic context to simulation.     

简单、复杂与地理分布模型的选择

地理分布的数学建模是空间分析的基本途径之一,但空间维度建模素为科学研究的难题。由于数学新方法的发展和复杂性研究的兴起,地理空间建模的一些传统困难有望解决。本文通过两类地理分布的对比分析,论述地理建模的关键在于简单分布的特征尺度和复杂分布的标度。地理分布包括空间分布和规模分布,其本质均为概率分布和广义的数学空间分布,而概率分布可以分为简单分布和复杂分布。简单分布具有特征尺度,平均值有效,概率结构清楚;复杂分布没有特征尺度,平均值无效,概率结构不明确。对于简单分布,应该采用有尺度分布函数开展尺度分析;对于复杂分布,理当采用无尺度分布函数开展标度分析。分形几何学、异速生长理论和无尺度网络理论都是复杂系统分析的定量方法,这些方法的综合集成,可望为地理分布建模和地理系统的空间分析提供有效的数理工具。     

Analyzing space-time evolution of rural transition in a rapidly urbanizing region: A case study of Suzhou,China

Journal of Geographical Sciences - Influenced by globalization, rural transition in developed Western countries has experienced processes of productivism, post-productivism, and multifunctional...     

网络关联、空间溢出效应与中国区域经济增长——基于腾讯位置大数据的研究

以腾讯公司根据手机位置得到的中国地级及以上城市之间人口流动数据为基础,考察人口流动网络下地级市经济增长的空间关联模式及其演变,结合网络分析方法,测度地级市间经济增长的空间溢出效应。主要结论有：① 符合现实的空间权重矩阵应该是非对称的,且随着互动关系的改变而发生变化。② 人口流动网络等反应地级市之间互动的因素在经济增长空间溢出中发挥了重要作用。③ 基于网络的空间溢出效应是地级市经济增长的重要因素。     

人口密度的空间降尺度分析与模拟——以贵州猫跳河流域为例

人口调查统计以行政区划为基本单元,数据精度不能满足较高分辨率的空间结构分析,也难以在地理综合研究中与自然地理要素数据相匹配.因此,人口密度空间化成为地理学的重要研究方向之一.本文基于贵州省猫跳河流域的乡镇人口数据,采用GIS空间分析技术与统计学方法,分析了人口密度与空间因子的关系;并采用多元回归的方法建立了人口密度数据...     

Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014

The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis (SFA) in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt (YREB) and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of additional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a “bar-like” distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran’s I within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association (LISA) statistic has enabled us to quantify characteristics of “small agglomeration and large dispersion”. Thus, “high- high” (H-H) agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by “low-low” (L-L) patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.