Getting Away with the Stolen Vehicle: An Investigation of Journey-after-Crime*

Abstract

Analyses of criminals' travel patterns can provide significant suggestions to improve crime management. This study extends the investigation of criminals' travel behavior from journey-to-crime to journey-after-crime. Moreover, new methods are developed to examine the spatial patterns of location pairs when restricted by the underlying geographical process. The methods are employed to investigate criminals' journey-after-auto-theft in the city of Buffalo, New York. The analyses reveal that auto thieves' trips from vehicle-theft locations to the corresponding vehicle-recovery locations are local in nature. The travel distances are significantly shorter than the randomly simulated trips; the travel directions are biased from the random directions as well.     

Getting Away with the Stolen Vehicle: An Investigation of Journey‐after‐Crime*

Analyses of criminals' travel patterns can provide significant suggestions to improve crime management. This study extends the investigation of criminals' travel behavior from journey‐to‐crime to journey‐after‐crime. Moreover, new methods are developed to examine the spatial patterns of location pairs when restricted by the underlying geographical process. The methods are employed to investigate criminals' journey‐after‐auto‐theft in the city of Buffalo, New York. The analyses reveal that auto thieves' trips from vehicle‐theft locations to the corresponding vehicle‐recovery locations are local in nature. The travel distances are significantly shorter than the randomly simulated trips; the travel directions are biased from the random directions as well.     

AFV refueling stations and the complexity of freeway intersections: the scale dependency of network representation

As interest for alternative fuel vehicles (AFVs) in urban areas continues to build, there has been a corresponding focus on the development of methods that can locate initial refueling stations on regional transportation networks in an optimal manner. Recent studies suggest that the behavior of early adopters of AFVs is consistent with the objectives of flow-capturing station location models. One outstanding issue with the further use of these models to locate AFV stations is the relationship between the relatively coarse geographic representation of regional transportation networks used in flow-capturing models and the complexity of the sites they recommend, which are often nodes that represent freeway intersections. Since AFV refueling stations cannot be built directly at freeway intersections, a network GIS method entitled the freeway traffic capture metric (FTCM) is developed to identify locations on proximate local street networks that can effectively capture all traffic passing through a freeway intersection. The FTCM considers deviation from a shortest travel path specifically through a freeway intersection as its metric of convenience for all possible travel routes that pass through it, computing a score for each candidate site on the nearby local street network. The FTCM is tested on nearly 45,000 candidate sites within one mile of 72 freeway intersections in greater Los Angeles, California. Locations that can capture all traffic passing through the nearby freeway intersection are shown to generally be near the intersection’s center, but not necessarily next to freeway entrances or exits. In total, 6.7% of possible station locations near these 72 freeway intersections are convenient for all traffic passing through them, and 22 out of the 72 freeway intersections lack such a site altogether. This indicates that there is high likelihood of inconsistency between regional modeling results and station location effectiveness if this scale dependency between coarse representations of transportation networks and the complexity of local street networks near freeway intersections is not considered when building initial AFV stations near these locations.     

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.     

建成环境对北京市郊区居民工作日汽车出行的影响

郊区化导致的汽车出行增加及相关的城市环境与社会问题日益成为城市研究关注的焦点,但目前国内对建成环境与汽车出行行为的研究刚刚起步。基于GPS与活动日志相结合的居民一周活动与出行数据,利用GIS空间分析分别以居住地、工作地和活动空间作为地理背景,分析建成环境对于郊区居民汽车出行距离的影响因素。研究发现,建成环境对工作日汽车出行的影响因地理背景的选择而有不同。整日出行受到工作地和活动空间的影响,工作地与活动空间建设密度增高汽车出行减少,但是居住空间的影响不显著;通勤出行受到居住地、工作地和活动空间的影响,居住地商业密度提高和建设密度降低、工作地和活动空间建设密度提高,汽车出行减少;非工作活动出行也受到居住地、工作地和活动空间的影响,居住地、工作地和活动空间的公交密度低、工作地和活动空间建设密度高,汽车出行少。基于研究结果,本文对地理背景不确定性问题进行了探讨,提出出行行为的研究需要考虑居住地以外其他地理背景的影响,并对控制汽车使用的公共政策提出了建议。     

Travel times of Pn -waves in the Aegean and surrounding area

Summary. Based on accurately located 23 very shallow earthquakes ( h = 1–14 km) in northern and central Greece by portable networks of seismic stations and by the joint epicentre method, the travel times of the P_n -waves from the foci of these earthquakes to the sites of 54 permanent stations in the Balkan region have been determined. The travel times of P_n -waves in the central and eastern part of the area (eastern Greece, south-eastern Yugoslavia, the Aegean Sea, Bulgaria, southern Romania, western Turkey) fit a straight line very well with the P_n velocity equal to 7.9 ± 0.1 km s^-1. On the contrary, the travel times of P_n -waves to stations in the western part of the area (Albania, western Greece) do not fit this curve because the P_n -waves travelling to these stations are delayed by more than 1 s due to the thicker crust under the Dinarides–Hellenides mountain range. Time delays for P_n -waves have been calculated for each permanent station in the Balkan area with respect to the mean travel-time curve of these waves in the central and eastern part of the area. Corrections of the travel times for these delays contribute very much to the improvement of the accuracy in the location of the shallow earthquakes in the Aegean and surrounding area.     

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.     

竞争型公共设施区位决策——概念、选址原则及模型构建

竞争型公共设施竞争性、公益性并存,其区位决策相对更加复杂。首先提出了“竞争型公共设施”的概念,指出“兼顾效率与公平的空间均衡”是其选址的基本原则,并概括出具体选址要求：遵循供需双方的空间相互作用模式、限制至邻近设施的最大出行成本、追求总出行成本最小化、约束设施规模门槛、与低层级设施在出行成本上相区分等。其次构建了基于概率分配规则的重力P中值模型,通过纳入设施规模因子实现区位和规模同步求解,并对邻近设施最大出行成本和设施最小规模进行约束,以实现空间公平-效率、服务质量公平与规模效率等多重目标。最后经过实证检验,优化后的设施布局更为均衡合理。     

Race,Gender, and Constrained Work Trips in Buffalo,NY, 1990

This study investigates whether women's short commutes should be interpreted as constrained or convenient work trips by examining how race, gender, travel mode, occupation, residential location, workplace location, and Inc.ome affect commuting time. The analysis is restricted to a sample of European American and African American male and female workers residing in Buffalo, New York, and the surrounding county using data drawn from the Public Use Microdata Samples of the 1990 U.S. census. Given the pervasive gender wage gap, women unsurprisingly have more compromised (short commutes to low-Inc.ome jobs) work trips than do men. Multivariate analysis reveals that among those who reverse commute to suburban locations, African American women have the longest work trips.     

THE DETERMINANTS OF DAILY TRAVEL-ACTIVITY PATTERNS: RELATIVE LOCATION AND SOCIODEMOGRAPHIC FACTORS

In an effort to explore the determinants of urban travel behavior, this paper examines the effects of two sets of variables on different aspects of individuals' complex travel-activity patterns: (1) sociodemographic variables (attributes of the individual and household) and (2) spatial variables (the location of the individual relative to potential destinations). The paper reviews earlier work that has investigated the relationships between these factors and travel and finds that (1) studi,es investigating the impact of sociodemographics on travel have generally not controlled for variation in spatial constraints and (2) few empirical studies have examined the relationship between travel and spatial constraints. Using the Uppsala travel-diary data, this study assesses the role of spatial and sociodemographic factors in explaining each of a number of different aspects of travel (e.g., frequency of travel, dispersion of destinations visited). The significance of the regression coefficients in stepwise regression establishes which independent variables are important in explaining each travel measure. The results indicate that the operative variables differ as a function of the particular aspect of travet in question. Spatial constraints are important to several travel measures, and sociodemographics remain significantly related to most aspects of travel even after the effects of spatial constraints have been controlled.     

Race,Gender, and Constrained Work Trips in Buffalo,NY, 1990

This study investigates whether women's short commutes should be interpreted as constrained or convenient work trips by examining how race, gender, travel mode, occupation, residential location, workplace location, and Inc.ome affect commuting time. The analysis is restricted to a sample of European American and African American male and female workers residing in Buffalo, New York, and the surrounding county using data drawn from the Public Use Microdata Samples of the 1990 U.S. census. Given the pervasive gender wage gap, women unsurprisingly have more compromised (short commutes to low-Inc.ome jobs) work trips than do men. Multivariate analysis reveals that among those who reverse commute to suburban locations, African American women have the longest work trips.     

Estimating the effect of turn penalties and traffic congestion on measuring spatial accessibility to primary health care

Geographic variations in spatial accessibility to public resources, such as health care services, raise important questions about the efficiencies and inequities of the processes that determine where these services are located. Spatial accessibility can be measured many different ways, but many of methods in use today involve some measure of travel cost (in time or distance). In this study we explore a simple methodological question: how much are models of spatial accessibility influenced by the precise metric of travel cost? We address this question by comparing spatial accessibility to primary care physicians for two different methods of calculating travel cost (in time) on a street network: free-flow travel time and congested with turn penalties travel time—which augments free-flow travel times with the burden of traffic congestion and traffic intersection controls. We consider the effect of these two metrics of travel cost on a gravity-based measure of spatial accessibility to primary health care services in Edmonton, Alberta, Canada. Our results suggest that while travel times between locations of demand and locations of primary care providers greatly differ based on how travel cost is calculated, the gravity-based measure of spatial accessibility provides similar information for both travel cost metrics. Using congested with turn penalties travel time can be an onerous addition to the analysis of spatial accessibility, and is more useful for measuring absolute travel time rather than modeling relative spatial accessibility.     

TRAVEL TO WORK AND LABOR FORCE PARTICIPATION OF MEN AND WOMEN IN AN AUSTRALIAN METROPOLITAN AREA

For a number of social and cultural reasons, labor force participation rates of Australian women are low. One reason not previously investigated is the problem of geographic accessibility to employment, especially for suburban women. Results from journey-to-work studies show that females either work locally or in the central-city area, whereas males travel to more dispersed locations. Further investigation of female travel patterns from each of fifty-five suburban local government areas shows that the socioeconomic status of an area, together with its job mix, explains much variety in female work travel and suggests that workforce participation rates depend in part on local job availability. The research contributes to an understanding of the nature of occupational and geographical disaggregation of the Melbourne metropolitan labor market.     

Do suburban residents prefer the fastest or low-carbon travel modes? Combining public participation GIS and multimodal travel time analysis for daily mobility research

Sustainability of urban transportation and residents' daily mobility is increasingly important for the future of urban regions. In this paper, we present a novel methodology combining mapped survey responses (gathered using public participation GIS) and sophisticated multimodal routing analysis to understand patterns of suburban residents' daily mobility. Our particular focus is on residents' mode choices and their optimality in terms of travel time. We also examine the carbon-intensity of potential mode choice mismatches where a comparatively slower travel mode is chosen for a particular trip. This paper shows how the combination of the two data sources create new possibilities for analysing daily mobility by enabling the comparison of self-reported, geographically referenced mobility patterns and modelled, objectively “optimal” patterns. Our case study results from a rapidly growing metropolitan area, Greater Helsinki in Finland, indicate that people have rather sustainable daily mobility practices. Their daily trips are typically short (median 1.8 km), and non-motorised travel modes are the most popular. Also the share of car travel is significant. While public transport clearly has the lowest modal share, it is frequently used on longer trips to destinations where public transport connections are good (particularly the city centre). In 44% of trips, the respondents choose the fastest travel mode. When a comparatively slower travel mode is chosen, it most often produces less CO₂ emissions than the fastest mode. However, particularly on shopping trips – the most commonly reported type of trip – car driving dominates as the fastest means of transportation. When a slower mode is chosen on a shopping trip, it is typically more carbon-intensive than the fastest mode would have been in that case. The methodology presented here can be used to support local decision making, particularly when daily services and transport infrastructure are planned or reorganised.     

A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks

Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts personalized tourist routes for travelers by mining their geographical preferences from these location-tagged data. Our method trains two types of base classifiers to jointly predict the next travel destination: (1) The K-nearest neighbor (KNN) classifier quantifies users’ location history, weather condition, temperature and seasonality and uses a feature-weighted distance model to predict a user’s personalized interests in an unvisited location. (2) A Bayes classifier introduces a smooth kernel function to estimate a-priori probabilities of features and then combines these probabilities to predict a user’s latent interests in a location. All the outcomes from these subclassifiers are merged into one final prediction result by using the Borda count voting method. We evaluated our method on geo-tagged Flickr photos and Beijing weather data collected from 1 January 2005 to 1 July 2016. The results demonstrated that our ensemble approach outperformed 12 other baseline models. In addition, the results showed that our framework has better prediction accuracy than do context-aware significant travel-sequence-patterns recommendations and frequent travel-sequence patterns.     

农民工回流务工区位研究——以河南省45个村为例

回流已成为中国农民工流动的重要趋势,未来将重塑农村人口流动的空间格局。论文基于901份田野调查数据,采用描述性统计和多元Logistic回归方法,对农民工回流务工区位及影响因素进行了研究。结果表明：农民工回流后务工区位选择主要以县城为主,其次为村庄,中心城区和集镇较少。省外回流和省内回流是农民工回流的基本形式,但二者在务工区位选择上存在一定差异。回流务工区位以本属区位为主,但也存在少量非本属区位。影响回流农民工务工区位选择的显著性因子主要包括年龄、居住区位、村人均收入、村务工比、村地形、前务工地类和回流源地等。农民工回流后,虽然整体上解决了跨区域的长距离奔波问题,但仍在更小的空间尺度上继续存在务工和务家的平衡问题,距离在回流务工区位选择中具有重要作用。居住区位与务工区位具有对等性,社区内部的信息交流影响着回流者对务工收益的评价,成为务工区位决策的重要机制。在回流务工区位选择上,存在路径依赖现象。县城应成为农区新型城镇化发展的重点和主要载体。     

基于最优供需分配的公共设施空间可达性分析

空间可达性是衡量公共服务设施公平性的重要指标,在医疗、教育、休闲等公共服务的布局规划中得到广泛应用。然而已有设施服务可达性模型难以充分反映服务供需关系,计算指标也缺乏物理意义。本文提出新的最优供需分配的公共设施空间可达性计算方法（OSD）取代现有方法。该方法基于最优供需分配模型,将设施服务分配给需求者,根据分配结果计算空间可达性指标。给定服务设施与需求的空间分布,以最小化旅行成本为目标,顾及设施服务能力,采用经典的运输问题模型确定最优的服务供需分配方案,进而度量服务的空间可达性。以郑州市金水区社区卫生服务为例,求解25个中心与1333个居住小区的最优服务配置。使用最优配置结果确定每个设施的服务范围、每个居住小区使用服务的旅行时间,以及特定时间阈值的服务覆盖比率。与流行的两步移动搜索法相比,新方法的计算指标具有明确的物理意义。本文提出的可达性评价方法无需参数,计算高效,结果易于解释,在公共服务评价及设施布局规划方面具有应用潜力。     

Anisotropy in the continental upper mantle: possible evidence from explosion seismology

Summary. Peculiarities of propagation in the upper mantle of western Europe are documented by profiles of stations recording body waves generated by explosions. Azimuthal variations of travel times and amplitudes of P waves and possible birefringence of S waves may be associated with an anisotropic layer at depths where the lithosphere-asthenosphere transition is supposed to be.     

Regularities in Spatial Information Processing: Implications for Modeling Destination Choice

This paper investigates the determinants of spatial knowledge and how our knowledge of space varies according to geographic location. By using data on U.S. city names recalled at 22 test locations, a multivariate model of the information surface specific to each test location is calibrated. This model links the probability of a city being recalled from memory to its distance from the test site, its population size, its location with respect to other cities, and whether or not it is a state capital. The paper then suggests that these recall data provide information on spatial knowledge surfaces from which large-scale spatial choices, such as migration destinations, are made. Results from the analysis lend further evidence to the idea that spatial knowledge is stored and processed hierarchically and that individuals underrepresent information in large clusters. Consequently, the results have important implications for modeling any spatial behavior based on individuals' spatial information surfaces. In particular, the results cast further doubt on the validity of traditional large-scale spatial choice frameworks and lend support to the competing destinations hypothesis.     

A Nationwide Comparison of Driving Distance Versus Straight-Line Distance to Hospitals

Many geographic studies use distance as a simple measure of accessibility, risk, or disparity. Straight-line (Euclidean) distance is most often used because of the ease of its calculation. Actual travel distance over a road network is a superior alternative, although historically an expensive and labor-intensive undertaking. This is no longer true, as travel distance and travel time can be calculated directly from commercial Web sites, without the need to own or purchase specialized geographic information system software or street files. Taking advantage of this feature, we compare straight-line and travel distance and travel time to community hospitals from a representative sample of more than 66,000 locations in the fifty states of the United States, the District of Columbia, and Puerto Rico. The measures are very highly correlated (r ² > 0.9), but important local exceptions can be found near shorelines and other physical barriers. We conclude that for nonemergency travel to hospitals, the added precision offered by the substitution of travel distance, travel time, or both for straight-line distance is largely inconsequential.