基于网页旅游攻略的旅行线路规划

为帮助旅行者规划旅行线路,以旅游攻略为数据源,针对旅行线路规划问题中可选景点的动态性问题,根据传统车辆路径问题求解方法中两阶段法的先分组再定路线的策略,重点研究并设计改进了一种基于攻略中景点出现频率的先分组再定路线的启发式旅行线路规划策略用于自动规划旅游行程。试验结果表明,使用本文所提出的方法生成的旅游线路,时间分配更加合理,游览的景点间路程更短,线路的游览时间与景点间距离的费效比更高,对于游客规划旅行线路有着很大的现实意义。     

A Network Model for Dispersion of Communicable Diseases

The spread of communicable diseases through a population is an intrinsic spatial and temporal process. This paper presents an individual‐based analytical framework for modeling the spatial and temporal heterogeneity in the disease transmission. The framework specifies a network model structure and six associated parameters. These parameters describe the properties of nodes, the properties of links, and the topology of the network. Through this model structure and associated parameters, this framework allows the representation of discrete individuals, individualized interactions, and interaction patterns in a network of human contact. The explicit representation of the spatial distribution and mobility of individuals in particular facilitates the modeling of spatial heterogeneity in the disease transmission.     

A hybrid approach to modeling territorial control in violent armed conflicts

Territorial control is central to the understanding of violent armed conflicts, yet reliable and valid measures of this concept do not exist. We argue that geospatial analysis provides an important perspective to measure the concept. In particular, measuring territorial control can be seen as an application of calculating service areas around points of control. The modeling challenge is acute for areas with limited road infrastructure, where no complete network is available to perform the analysis, and movements largely occur off road. We present a new geospatial approach that applies network analysis on a hybrid transportation network with both actual road data and hexagon‐fishnet‐based artificial road data representing on‐road and off‐road movements, respectively. Movement speed or restriction can be readily adjusted using various input data. Simulating off‐road movement with hexagon‐fishnet‐based artificial road data has a number of advantages including scalability to small or large study areas and flexibility to allow all‐directional travel. We apply this method to measuring territorial control of armed groups in Sub‐Saharan Africa where inferior transport infrastructure is the norm. Based on the Uppsala Conflict Data Program's (UCDP) Georeferenced Event Data (GED) as well as spatial data on terrain, population locations, and limited transportation networks, we enhance the delineation of the specific areas directly controlled by each warring party during civil wars within a given travel time.     

Exploring the spatiotemporal relationships between search flows and travel flows

Numerous studies attempted to associate search engine data with travel behaviors. However, most existing studies focus on the destinations of search and travel, while ignoring the origins, which embed critical information of where the search requests were initiated and where the travelers came from. In this study, we explore the relationships between two types of intercity origin–destination flow data, namely travel flows and search flows, which, respectively, record the number of travelers and search requests from one city towards another. By comparing the two flows during holiday and non-holiday, we examine their complex spatiotemporal relationships from multiple perspectives, including time-lag effect, distance decay effect, spatial autocorrelation, network community, cities' rankings, and important factors of search and travel activities. The findings can deepen our understanding of search and travel behaviors, hence they can help decision makers to develop targeted strategies to enhance city's attractiveness, improve transportation infrastructure, and promote tourism.     

Accessibility Futures

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility‐based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side‐by‐side. For roadway modeling, zone‐to‐zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person‐weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.     

Dynamic GIS Case Studies: Wildfire Evacuation and Volunteered Geographic Information

Incorporating the temporal element into traditional GIS is a challenge that has been researched for many years and has many proposed solutions. The implemented system "Extended Dynamic GIS" or EDGIS is based on the "geo-atom" and Space Time Point (STP). EDGIS provides a platform for spatiotemporal data representation, storage, and query in order to address the need for a dynamic GIS to manage complex geographic data types. The system has the capability of executing spatiotemporal object interaction queries (OIQs) such as crossing and coincidence of field-objects and object-fields. In this article existing dynamic GIS analysis techniques are further improved and enhanced through exploration of more in-depth case studies. Further examined here are applications to wildfire evacuation modeling and travel scenarios of urban environments with individuals providing volunteered geographic information (VGI). The EDGIS platform provides a means for interacting with a range of dynamic geographic phenomena. The areas of transportation, location based services (LBS), hazards, and geo-sensor networks provide challenges intertwined with the above applications as well as additional challenges pertinent to the ongoing GIScience research topic of spatiotemporal GIS. Using EDGIS to explore the described case studies of wildfire evacuation as well as VGI provides the advancements described above and demonstrates implemented uses for dynamic GIS.     

Multi‐temporal transport network models for accessibility studies

Vehicle tracking is a spatio‐temporal source of high‐granularity travel time information that can be used for transportation planning. However, it is still a challenge to combine data from heterogeneous sources into a dynamic transport network, while allowing for network modifications over time. This article uses conceptual modeling to develop multi‐temporal transport networks in geographic information systems (GIS) for accessibility studies. The proposed multi‐temporal network enables accessibility studies with different temporal granularities and from any location inside the city, resulting in a flexible tool for transport and urban planning. The implemented network is tested in two case studies that focus on socially excluded people in a large global city, São Paulo, Brazil, including accessibility analyses from slum areas. It explores variations within a day and differences between transport modes across time. Case study results indicate how the accessibility is heterogeneous in low‐income regions.     

出租车轨迹数据的南京人群出行模式挖掘

针对现有出租车轨迹数据挖掘中时间序列邻近度量方法存在的问题,提出一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,进而研究城市人群出行行为的时空差异。以南京市为例,结合电子地图对出行模式的空间分布特征进行分析,证明了本文所提出的方法的有效性。实验结果表明:在空间分布上,工作日出租车出行模式按照平均出行频次由高到低排序,从城市中心向四周扩散,呈中心环状分布,出行模式区域界限较为明显,同类出行模式分布区域对应相似的功能。提出了一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,有效地分析城市人群出行行为的时空差异。     

Rethinking the regularity in mobility patterns of personal vehicle drivers: A multi-city comparison using a feature engineering approach

Large-scale trajectory data offer a finer lens into the regularity in individual mobility choices. Previous studies have exerted efforts to measure the regularity in people's location visiting patterns. However, the complexity of travel behavior at different spatial and temporal scales has not been adequately considered. To capture regularity in a more comprehensive manner, we construct human mobility profiles with interpretable features at three levels, that is, location, motif, and route, on personal vehicle drivers. A feature engineering approach is designed to analyze the extent to which individuals exhibit multi-level regularity. The analysis pipeline includes feature selection, user segmentation and profiling, and feature importance evaluation. Our empirical study analyzed over 4 million trips of 3743 personal vehicle drivers collected over a month in six metropolitan areas in the United States. The weak correlations between features confirm the validity of quantifying regularity from different aspects. We discovered five clusters of drivers (i.e., gig drivers, homebodies, movers, typical drivers, and work-focused commuters) that differ in their regularity to commute to the workplace and the inclination to participate in non-work activities. A similar driver segmentation and profiling pattern is found in all of the studied metro areas. The minor differences are interpreted from the distribution of mobility features and urban features. The proposed method using multi-level feature engineering provides a generic framework to study regularity and can be readily adapted to other mobility data sources by customizing the features. The improved understanding of mobility patterns within the built environment is valuable for innovating urban transportation solutions.     

Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?

Despite their increasing popularity in human mobility studies, few studies have investigated the geo‐spatial quality of GPS‐enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter “active mobile phone data”). We focus on two key issues in active mobile phone data—systematic gaps in tracking records and positioning uncertainty—and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants’ online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals’ frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies.     

Spatial Approaches to Modeling Dispersion of Communicable Diseases – A Review

The dispersion of communicable diseases in a population is intrinsically spatial. In the last several decades, a range of spatial approaches has been devised to model epidemiological processes; and they differ significantly from each other. A review of spatially oriented epidemiological models is necessary to assess advances in spatial approaches to modeling disease dispersion and to help identify those most appropriate for specific research goals. The most notable difference in the design of these spatially oriented models is the scale and mobility of the modeling unit. Using two criteria, this review identifies six types of spatially oriented models. These include: (1) population‐based wave models, (2) sub‐population models, (3) individual‐based cellular automata models, (4) mobile sub‐population models, (5) individual‐based spatially implicit models, and (6) individual‐based mobile models. Each model type is evaluated in terms of its design principles, assumptions, and intended applications. For the evaluation of design, four aspects of design principles are discussed: the modeling unit, the interaction between the modeling units, the spatial process, and the temporal process utilized in a design. Insights gained from this review can be useful for devising much‐needed spatially and temporally oriented strategies to forecast, prevent, and control communicable diseases.     

A multilevel path analysis of contact frequency between social network members

Recently, there has been an increasing interest in the role of social networks in spatial-choice and travel behavior. It has been acknowledged that social activities and the travel for these activities can emerge from individuals’ social networks and that social activities are responsible for an important portion of travel demand. The influence of information and communication technologies (ICT’s) is also important in this respect. The purpose of the paper is to examine the effects of characteristics of egos and ego-alter relationships on the frequency of social interaction by different communication modes, using multilevel path analysis. The analyses are based on social network data collected in 2008 in the Eindhoven region in the Netherlands among 116 respondents. The results indicate a complementary relationship between contact frequencies by different modes. The contact frequencies of the different modes, especially face-to-face and telephone, can also be largely explained by the ego’s personal characteristics and the type of relationship and the distance between ego and alter.     

Estimating traffic speed and speeding using passively collected big mobility data and a distributed computing framework

With the increasing availability of location-aware devices, passively collected big GPS trajectory data offer new opportunities for analyzing human mobility. Processing big GPS trajectory data, especially extracting information from billions of trajectory points and assigning information to corresponding road segments in road networks, is a challenging but necessary task for researchers to take full advantage of big data. In this research, we propose an Apache Spark and Sedona-based computing framework that is capable of estimating traffic speeds for statewide road networks from GPS trajectory data. Taking advantage of spatial resilient distributed datasets supported by Sedona, the framework provides high computing efficiency while using affordable computing resources for map matching and waypoint gap filling. Using a mobility dataset of 126 million trajectory points collected in California, and a road network inclusive of all road types, we computed hourly speed estimates for approximately 600,000 segments across the state. Comparing speed estimates for freeway segments with speed limits, our speed estimates showed that speeding on freeways occurred mostly during the nighttime, while analysis of travel on residential roads showed that speeds were relatively stable over the 24-h period.     

基于居民出行活动特征的个体经济水平推断方法

提出了一种基于居民出行活动特征的个体经济水平推断方法。从出行轨迹的移动性指标、基于居住地的出行特征和出行活动链模式3个方面提取13维出行活动特征,以广州市居民出行日志调查数据为训练和测试数据,利用随机森林方法进行个体经济收入水平的推断与检验。结果表明,该方法能够获得最高80%的个体收入水平推断精度。基于家的出行特征（如工作时间（9:00-18:00）离家距离众数等、出行链模式）以及与出行范围有关的移动性指标（如最大距离、回旋半径）在推断个体经济水平上的重要性较高,而衡量出行地点空间异质性的指标（如空间多样性等）重要性相对较低。     

利用网络游记分析不同类型游客的旅游流网络特征差异——以云南省为例

旅游流网络分析对理解游客的目的地选择以及目的地在旅游流网络中承担的角色有重要意义。以中国云南省为例,基于网络游记数据挖掘游客的多维度偏好,并以此对游客聚类,进而划分出不同类型的游客群体。针对各类游客游记中的旅游目的地序列建立旅游流网络,并从多个角度分析各类游客旅游流网络的结构特征和各目的地节点的角色特征。结果表明,不同类别游客的旅游流网络在整体结构上各有特点,反映出旅游目的地不同的空间交互模式和网络中心化程度。此外,部分旅游目的地在不同类别旅游流网络中承担截然相反的角色。上述分析有助于优化旅游流网络中各节点的协作机制,辅助旅游目的地制定差异化的旅游产品。     

Obstacle‐limited service coverage: A new geospatial approach

Service coverage is a crucial component of spatial decision‐making involving facility siting. Determining coverage requires knowledge about travel behavior and accessibility across a region, as well as supporting methods of measurement and derivation when actual travel cannot necessarily be observed. When service is provided using vehicles that move freely without the restriction posed by roads (e.g., airplanes, helicopters, unmanned aerial vehicles/drones, boats, ships, and submarines), straight‐line travel is regularly assumed. However, this common assumption is often violated by geographical obstructions, resulting in overestimated service coverage. To date, no methods have been developed capable of accounting for obstacle‐limited service coverage. Existing methods either completely ignore obstructions or crudely estimate impacts on travel. In this research, we develop a novel method, ESP‐Cover, capable of deriving accurate obstacle‐limited coverage without introducing representation errors. A location siting problem involving drone‐based package delivery is presented to highlight the necessity of explicitly accounting for obstacles in system design. The assessment results demonstrate the importance of accurate derivation of the obstacle‐limited coverage for spatial decision‐making and the accuracy of the ESP‐Cover method in coverage derivation.     

A high-precision heuristic model to detect home and work locations from smart card data

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.     

'Situating' Simulation to Model Human Spatio-Temporal Interactions: An Example Using Crime Events

Many social phenomena have a spatio‐temporal dimension and involve dynamic decisions made by individuals. In the past, researchers have often turned to geographic information systems (GIS) to model these interactions. Although GIS provide a powerful tool for examining the spatial aspects of these interactions, they are unable to model the dynamic, individual‐level interactions across time and space. In an attempt to address these issues, some researchers have begun to use simulation models. But these models rely on artificial landscapes that do not take into account the environment in which humans move and interact. This research presents the methodology for ‘situating’ simulation through the use of a new modeling tool, Agent Analyst, which integrates agent‐based modeling (ABM) and GIS. Three versions of a model of street robbery are presented to illustrate the importance of using ‘real’ data to inform agent activity spaces and movement. The successful implementation of this model demonstrates that: (1) agents can move along existing street networks; (2) land use patterns can be used to realistically distribute agent's homes and activities across a city; and (3) the incidence and pattern of street robberies is significantly different when ‘real’ data are used.     

基于时间序列相似度的城市功能区识别研究

随着城市化的快速发展,城市空间结构愈发复杂,城市功能区的快速有效识别对资源的有效配置和城市规划具有重要意义.传统的功能区识别缺乏对居民这一城市空间活动主体的动态表征,而长时间序列的出租车数据能动态表征居民出行行为,进而反映城市空间结构.动态时间扭曲(DTW)距离比传统的欧氏距离更能有效挖掘高维数据,泛化后的LB_Keo...     

A Hybrid Link‐Node Approach for Finding Shortest Paths in Road Networks with Turn Restrictions

Turn restrictions, such as ‘no left turn’ or ‘no U‐turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link‐node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node‐based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link‐based Dijkstra's algorithm, while having a similar computational performance to the classical node‐based Dijkstra's algorithm.