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Accordingly, the objective of Pereira et al. ([33]) with their paper is to introduce a new package for the R statistical language project, to convert data in the format of GTFS into GPS-like data. In this context, to adapt the classic framework to our current hybrid physical-virtual world, the author proposes extensions to the following core time-geographic concepts: constraints, space-time path, space-time prism, bundle, project and situation, and diorama. Hägerstrand meets big data: time-geography in the age of mobility analytics By providing convenient tools to parse GTFS data into a format like that used to store GPS traces, the package gtfs2gps can greatly simplify data-related tasks and reduce the potential for error in workflows. [Extracted from the article]

Accessibility indicators are widely used in transportation, urban and healthcare planning, among many other applications. These measures are weighted sums of reachable opportunities from a given origin, conditional on the cost of movement, and are estimates of the potential for spatial interaction. Over time, various proposals have been forwarded to improve their interpretability: one of those methodological additions have been the introduction of competition. In this paper we focus on competition, but first demonstrate how a widely used measure of accessibility with congestion fails to properly match the opportunity-seeking population. We then propose an alternative formulation of accessibility with competition, a measure we call spatial availability. This measure relies on proportional allocation balancing factors (friction of distance and population competition) that are equivalent to imposing a single constraint on conventional gravity-based accessibility. In other words, the proportional allocation of opportunities results in a spatially available opportunities value which is assigned to each origin that, when all origin values are summed, equals the total number of opportunities in the region. We also demonstrate how Two-Stage Floating Catchment Area (2SFCA) methods are equivalent to spatial availability and can be reconceptualized as singly-constrained accessibility. To illustrate the application of spatial availability and compare it to other relevant measures, we use data from the 2016 Transportation Tomorrow Survey of the Greater Golden Horseshoe area in southern Ontario, Canada. Spatial availability is an important contribution since it clarifies the interpretation of accessibility with competition and paves the way for future applications in equity analysis (e.g., spatial mismatch, opportunity benchmarking, policy intervention scenario analysis). [ABSTRACT FROM AUTHOR]

Conventional therapeutic plasma exchange (TPE) is aimed at removing pathological agents from circulation using a medical device which separates out plasma from other components of blood. Usually, 1.0 to 1.5 plasma volumes are removed and replaced with a replacement solution. There is strong clinical evidence for the effectiveness of TPE in a wide spectrum of diseases, such as thrombotic thrombocytopenic purpura, severe acute inflammatory demyelinating polyneuropathy, and Guillain-Barré syndrome, among others. However, therapeutic approaches using lower plasma exchange volumes (LVPE) suggest some degree of effectiveness in a number of pathological conditions, although generally with low level of clinical evidence: hematology disorders (autoimmune hemolytic anemia), neuroimmunological diseases (Guillain-Barré syndrome, neuromyelitis optica, myasthenia gravis, multiple sclerosis), pulmonary disorders, liver failure, dermatology (pemphigus) and metabolic diseases (porphyria, cholesterol). Further or newer studies are needed to confirm LVPE as an alternative to TPE for such groups of pathologies. While plasma volume removed for TPE ranges 3-4.5 L per procedure, for LVPE ranges from 350 mL to 2 L (frequency and duration vary depending on the pathology treated). In the case of Alzheimer's disease (AD), the AMBAR trial recently investigated a combined sequence of intensive TPE with human albumin replacement followed by a maintenance phase LVPE (650-880 mL of plasma removed, similar to a plasma donation). The treatment slowed the decline or stabilized the disease symptoms. The AMBAR approach could justify investigating the use of LVPE in chronic conditions where plasma exchange strategies have proven successful. [ABSTRACT FROM AUTHOR]

Conventional therapeutic plasma exchange (TPE) is aimed at removing pathological agents from circulation using a medical device which separates out plasma from other components of blood. Usually, 1.0 to 1.5 plasma volumes are removed and replaced with a replacement solution. There is strong clinical evidence for the effectiveness of TPE in a wide spectrum of diseases, such as thrombotic thrombocytopenic purpura, severe acute inflammatory demyelinating polyneuropathy, and Guillain-Barré syndrome, among others. However, therapeutic approaches using lower plasma exchange volumes (LVPE) suggest some degree of effectiveness in a number of pathological conditions, although generally with low level of clinical evidence: hematology disorders (autoimmune hemolytic anemia), neuroimmunological diseases (Guillain-Barré syndrome, neuromyelitis optica, myasthenia gravis, multiple sclerosis), pulmonary disorders, liver failure, dermatology (pemphigus) and metabolic diseases (porphyria, cholesterol). Further or newer studies are needed to confirm LVPE as an alternative to TPE for such groups of pathologies. While plasma volume removed for TPE ranges 3-4.5 L per procedure, for LVPE ranges from 350 mL to 2 L (frequency and duration vary depending on the pathology treated). In the case of Alzheimer's disease (AD), the AMBAR trial recently investigated a combined sequence of intensive TPE with human albumin replacement followed by a maintenance phase LVPE (650-880 mL of plasma removed, similar to a plasma donation). The treatment slowed the decline or stabilized the disease symptoms. The AMBAR approach could justify investigating the use of LVPE in chronic conditions where plasma exchange strategies have proven successful. [ABSTRACT FROM AUTHOR]

This would provide enhanced support to the kind of critical spatial data science advocated by Brunsdon and Comber in their paper. Brunsdon and Comber ([13]) reflect on recent trends in the spatial sciences, which include the practice of coding as a core competency and a turn away from proprietary "black-box" software tools. Opening the spatial sciences The first two papers in the issue discuss two important aspects of opening the spatial sciences. The opening and closing of science Science, of course, has changed remarkably since its quasi-magical origins in the days of Dee and Newton. [Extracted from the article]

The transportation impacts of an increasingly urban population have led planners and policy makers to consider ways to encourage the use of active travel in urban areas. Active travel is attractive from a planning perspective because its environmental impact is considerably lower than the alternatives, and in addition is known to have a number of population health and social benefits. Not surprisingly, there has been a growth in interest in the factors associated with the use of active modes of transportation. The objective of this study is to investigate the individual (demographic and socio-economic) and contextual (geography and land use type) factors that correlate with the propensity to travel by active modes in Vitoria-Gasteiz. This is a medium sized city in the north of Spain, and a case study that has hitherto not been reported. Data obtained from a household travel survey (HTS) conducted in 2014 allow us to estimate a multinomial logit model of the propensity to travel by different modes of transportation. Furthermore, since the data are geocoded, we can estimate a model with spatially-varying coefficients to assess the geographical variations in the probability to use active modes. The results of the study provide valuable information concerning differences in active travel by gender and age, including significant and quite substantial variations by location. In addition, the effect of different urban fabrics indicates the relevance of density and mix of uses for active travel. In this way, the present research helps to increase our global knowledge-base regarding active travel in a medium-sized city. • Walking is preferred over cycling among the two active modes • Bicycle is preferred at younger ages, walking is the most probable mode for seniors • Women are more likely to walk than men in many cases, and more likely to cycle • Spatial variations were identified with high relevance of land-use fabric [ABSTRACT FROM AUTHOR]

Recent studies empirically support the role of the built environment in inducing or hindering violent crime. Particularly, studies of the broken window theory have provided evidence that physical disorder is an environmental correlate of crime. This includes broken windows, vacant/abandoned housings, abandoned cars on street, graffiti, and decayed street lighting, among other things. Current studies are limited by the difficulty involved in collecting fine-scale quantitative environmental data. The conventional environmental audit approach, which aims to assess environmental features, is costly, time-consuming, and burdensome. In this study, we use Google Street View to study the relationship between violent crime and physical features of urban residential environment. More concretely, a Poisson regression model with spatial filtering is used to identify socio-economic correlates of violent crime. Parting from the hypothesis that omission of built environmental factors results in systematic residual pattern, we proceed to analyze the spatial filter to select sites for virtual environmental audits. A series of physical environmental factors are identified using contingency table analysis. The results provide both theoretical and practical implications for several theories of crime and crime prevention efforts. [ABSTRACT FROM AUTHOR]

Numerous studies investigate the topic of industrial agglomeration, and in particular of localization economies that give rise to patterns of geographical clustering of firms. These studies have employed different indicators useful to assess a sector's degree of geographic clustering, or to characterize the nature of the scale on which localization occurs. However, less work has been conducted to identify significant clustering of industrial activity at the sub-regional level. The objective of this study is to investigate the spatial clustering of high-tech and knowledge-intensive firms in the Greater Toronto Area in Canada. We do this by means of the use of a spatial scan statistic. Application of this statistic leads us to conjecture that accessibility to transportation infrastructure and skilled labour contribute to the formation of industrial clusters in these sectors. Our conjecture is borne by a set of logit models that identify these two factors as significantly contributing to cluster membership. Le regroupement spatial des producteurs de technologie de pointe et de service à forte intensité de connaissances dans la région du Grand Toronto L'agglomération industrielle, notamment les économies de localisation qui donnent lieu à des formes de regroupement géographique des entreprises est le sujet de nombreuses études scientifiques. Celles-ci utilisent une variété d'indicateurs permettant d'évaluer l'ampleur du regroupement géographique d'un secteur, ou de décrire à quelle échelle la localisation s'effectue. Par contre, peu d'intérêt a été accordé à l'identification de regroupements majeurs d'activité industrielle à l'échelle infrarégionale. L'objet de cette étude consiste à explorer le regroupement spatial d'entreprises de technologie de pointe et de service à forte intensité de connaissances dans la région du Grand Toronto, Canada. Le recours à une statistique de balayage spatial nous amène à vérifier l'hypothèse que l'accessibilité aux infrastructures de transport et à la main-d'œuvre qualifiée contribue à la formation de grappes industrielles dans ces secteurs. Cette hypothèse est supportée par un ensemble de modèles logit où ces deux facteurs participent de manière significative à l'appartenance à une grappe. [ABSTRACT FROM AUTHOR]

Infrastructure networks, including transportation, telecommunications, and energy grids, are essential for the correct functioning of many economic and social processes. Considering the import of networked critical infrastructure, it is clear that understanding the characteristics of networks that make them vulnerable to disruption is a valuable endeavor. As recent research demonstrates, network vulnerability is a very relevant issue on the design and operation of any networked process in general, and transportation in particular, where the main interest is on identifying network elements that are singularly sensible to disruptions to their integrity. While there have been some suggestions from the literature that the configuration of the network may influence the vulnerability of individual elements, a systematic investigation of network topology and vulnerability has not been conducted. Furthermore, neither has there been an account of the relevance of coherence in the contents of the network, or in other words, the autocorrelation of flows. Accordingly, the objective of this paper is to investigate, from the perspective of the integrity of nodes, the vulnerability to disruption of individual network elements, while controlling for network topology and autocorrelation. Analysis is based on extensive numerical simulations for different network configurations and spatial autocorrelation levels, and the results obtained demonstrate that the proper evaluation of network vulnerability requires not only an understanding of its topology, but also of the distribution of flows. [ABSTRACT FROM AUTHOR]

The temporal persistence of crime hot spots is recognized as a valuable indicator of consistent problem areas. The current literature has not adequately addressed the mechanisms that perpetuate or interrupt persistent crime hot spots. Investigating the persistence of violent crime hot spots in Columbus, Ohio, from 1994 to 2002, this study fills a gap in the literature by identifying neighborhood structural correlates that drive the persistence of hot spots. Specifically, this study identifies yearly crime hot spots, and estimates an ordered probit model to explore the neighborhood structural determinants. The results indicate that socio-economic factors, identified from a synthesis of social disorganization theory and routine activity theory, significantly correlate with persistent patterns of violent crime hot spots. This gives evidence that a combination of the two ruling spatial theories of crime provides an applicable framework for understanding the temporal dimension of violent crime hot spots. By identifying the factors that contribute to the persistence of hot spots of crime, insights gained from the results can help to inform focused crime prevention efforts. [ABSTRACT FROM AUTHOR]

Open spaces in cities, such as green spaces and parks, are key elements of urban landscapes and urban sustainability. Open spaces improve the quality of the environment, quality of life, and promote social interaction and inclusion. There is evidence of positive impacts on health. This research analyses the potential accessibility to open spaces in two Chilean cities, Valdivia and Temuco. Analysis of accessibility is based on patterns of daily mobility by travelers while considering their trips and transport modes, in particular walking. Statistical analysis of trip length forms the basis of an adaptive threshold for the calculation of a cumulative potential measure of accessibility. The analysis shows that, for these two cities, variations in accessibility tend to be driven by age and gender, and less by income. There are also variations between the two cities, with Temuco showing better levels of accessibility, as a consequence of residents generally undertaking longer walking trips. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the attributes of walkable environments from the perspective of seniors in the Island of Montreal in Quebec, Canada. The research is based on a combination of statistical analysis of travel diary data and field work to conduct walkability audits. The approach follows a sequence of logical steps. The first step involves the estimation of a travel behavior model walking by seniors (people 65 years or older). The results of this model, in combination with cluster analysis, are used to identify sites where the model systematically under- or over-predicts walking. Subsequently, sites are targeted for walkability audits. It then becomes possible to assess the presence or absence of attributes of built environments where walking is more or less common than other factors would predict. A walkability audit of 403 street segments was used to proof the concept in this paper. The audited items were summarized in contingency tables and tested with the chi-squared test of independence to identify streetscape elements that correlate with walking for transportation. [ABSTRACT FROM AUTHOR]

With the graying of populations across the world, the travel behavior of seniors has become a topic of growing interest in planning and research. Most attention in the field of transportation has been devoted to motorized travel. However, the use of various modes of transportation, including nonmotorized travel, remains to be fully investigated. In this paper the multimodal trip generation of seniors in Montreal Island is studied. Personal, mobility tools, neighborhood, and accessibility variables are considered in a trivariate ordered probit model of three modes: car, transit, and walking. Geographical analysis of the walking component of the model helps to identify locations within the region where walking is more or less prevalent among older adults. [ABSTRACT FROM AUTHOR]

Two common practices in modeling of crime when crime data is available for multiple years are using single-year crime data corresponding to census data and taking the average of crime rate (or count) over multiple years. Current theoretical and empirical literature provides little, if any, rationale in support of either practice. Averaging multiple years is purported to reduce heterogeneity and minimize the measurement error in the year-to-year emergence of crime. However, it is unclear how useful the analysis of averaged and smoothed data is for revealing the relationship between crimes and socio-demographic and economic characteristics of every single year. In order to more clearly understand these two approaches, this paper applies a seemingly unrelated regression model to assess the temporal stability of model parameters. The model accounts for spatial autocorrelation among crime rates and social disorganization variables at the block group level. [ABSTRACT FROM AUTHOR]

Identifying urban patterns in the cities in the Brazilian Amazon can help to understand the impact of human actions on the environment, to protect local cultures, and secure the cultural heritage of the region. The objective of this study is to produce a classification of intra-urban patterns in Amazonian cities. Concretely, we produce a set of Urban and Socio-Environmental Patterns (USEPs) in the cities of Santarém and Cametá in Pará, Brazilian Amazon. The contributions of this study are as follows: (1) we use a reproducible research framework based on remote sensing data and machine learning techniques; (2) we integrate spatial data from various sources into a cellular grid, separating the variables into environmental, urban morphological, and socioeconomic dimensions; (3) we generate variables specific to the Amazonian context; and (4) we validate these variables by means of a field visit to Cametá and comparison with patterns described in other works. Machine learning-based clustering is useful to identify seven urban patterns in Santarém and eight urban patterns in Cametá. The urban patterns are semantically explainable and are consistent with the existing scientific literature. The paper provides reproducible and open research that uses only open software and publicly available data sources, making the data product and code available for modification and further contributions to spatial data science analysis. [ABSTRACT FROM AUTHOR]

Two important objectives in hedonic price analysis are to predict sale prices and delineate submarkets based on geographical and functional considerations. In this paper, we applied Bayesian models with spatially varying coefficients in an analysis of housing sale prices in the city of Toronto, Ontario to address these objectives. We evaluated model performance and identified patterns of submarkets indicated by the spatial coefficient processes. Our results show that Bayesian spatial process models predict housing sale prices well, provide useful inference regarding heterogeneity in prices within a market, and may be specified to include expert market opinions. [ABSTRACT FROM AUTHOR]

Background Walking for transport is increasingly considered an important component for meeting physical activity guidelines. This is true for individuals of all ages, and particularly important for seniors, for whom other physical activities may not be recommended. In order to evaluate the potential contributions of walking to physical activity, in this paper the concept of Compliance Potential Mapping is introduced. The concept is illustrated using seniors as a case study. Methods Based on estimates of walking trip distance and frequency, estimates of expected total daily walking distance are obtained. These estimates are converted to weekly walking minutes, which are in turn compared to recommended physical activity guidelines for seniors. Once estimates of travel behavior are available, the approach is straightforward and based on relatively simple map algebra operations. Results Compliance Potential Mapping as a tool to assess the potential contributions of walking towards physical activity is demonstrated using data from Montreal's 2008 travel survey. The results indicate that the central parts of Montreal Island display higher potential for compliance with physical activity guidelines, but with variations according to age, income, occupation, possession of driver's license and vehicle, and neighborhood and accessibility parameters. Conclusions Compliance Potential Maps offer valuable information for public health and transportation planning and policy analysis. [ABSTRACT FROM AUTHOR]

Highlights: [•] Providing information about levels of accessibility can encourage the use of different modes. [•] Internet mapping provides the tools to conveniently convey information to the public and planners. [•] A prototype accessibility calculator is created for the Greater Montreal Area. [•] Different possible uses of the accessibility calculator are illustrated. [ABSTRACT FROM AUTHOR]

Abstract: An important goal for blood agencies, especially in the context of aging populations, is to ensure the sufficiency of the blood supply. Of the eligible population, only a small proportion donates. A question therefore is how to expand the donor base. Previous research has shown that accessibility to clinics positively associates with donor turnout. Since accessibility depends on the allocation of resources to clinic sites it provides a policy handle to facilitate donor participation. Generation and examination of clinic accessibility landscapes can be part of a strategy to increase donor turnout. The research uses donor and clinic databases provided by Canadian Blood Services for calendar year 2008. Donor numbers were aggregated at the level of Dissemination Areas for the city of Toronto, Canada, and complemented with socio-economic and demographic information from the Census. Multivariate statistical analysis confirms the positive association between number of donors and accessibility, calculated using a two-step floating approach. The model becomes the objective function in a heuristic search procedure (genetic algorithms) to investigate the potential effect on donor turnout of allocation of resources to clinics. The results of the analysis indicate that the current number of donors is at the lower end of the range of solutions obtained from generating accessibility landscapes. Gains in the total number of estimated donors range between 1% and 22%. An advantage of generating several solutions is the possibility of examining the magnitude of change required, in terms of the (re-)allocation of resources to clinics. Detailed examination of the results can assist decision-makers to evaluate the trade-offs between the magnitude of the change required and the potential payoff. Given current trends, there is a need for planning to ensure that the supply of blood is sufficient. Even small gains can make an important difference between a sufficient blood supply and shortages. The approach presented here to generate clinic accessibility landscapes constitutes a useful tool for blood agencies to explore scenarios for increasing their donor base. [Copyright &y& Elsevier]

Highlights: [•] Discrete choice analysis is increasingly conducted using geo-referenced information. [•] An indicator of spatial fit is developed for discrete choice models. [•] The inferential framework to test for spatial fit is also developed. [•] Numerical experiments provide guidelines for the application of the indicator. [•] Application of the indicator is demonstrated with an example of vehicle ownership in Montreal. [ABSTRACT FROM AUTHOR]

Identification of suitable instruments is a critical step for the implementation of instrumental variable (IV) estimation. A challenge is that, as the level of correlation between the instruments and the endogenous variable increases, so also do the chances that the instruments themselves will be correlated with the error terms. Contrariwise, when the correlation with the endogenous variable is low, the instruments may be weak and perform poorly. The objective of this paper is to explore the use of synthetic variables in IV estimation when the analysis is of spatial data series. The point of departure is the use of eigenvector analysis of the usual spatial weights matrix used in spatial statistics. Eigenvectors obtained from a transformed weights matrix are known to represent latent map patterns. Our proposal is to use these patterns to obtain synthetic variables for use as instruments in IV estimation. By their very nature, instruments based on synthetic variables are exogenous. Furthermore, they can provide relatively high levels of correlation with the endogenous variable. In this paper we consider two situations of interest: first, the case where there are no clear candidates for instrumentation and the instruments are comprised of purely synthetic variables; second, the case when there are substantive but weak instruments that can be enhanced by the addition of synthetic variables. The approach proposed is illustrated with an empirical example. [ABSTRACT FROM AUTHOR]

Highlights: [•] Active modes of travel are more prevalent among students than in the general population. [•] A multinomial logit discrete choice model is used to identify the factors that influence modal choices. [•] Higher street network density increases the probability of using motorized modes. [•] Higher sidewalk density decreases the probability of using motorized modes. [•] We find a positive utility of travel time by car and bicycle. [Copyright &y& Elsevier]

Highlights: [•] The multi-modal travel behavior of seniors in Montreal is investigated. [•] Joint discrete–continuous modeling of mode choice and trip length is conducted for the case of seniors in Montreal. [•] The analysis identifies various determinants of propensity to travel by different modes, and the length of trips. [•] Use of spatial analysis highlights the existence of substantial intra-urban variations in walking behavior. [Copyright &y& Elsevier]

Abstract: Exploratory Spatial Data Analysis of attitudinal variables can provide useful information about underlying behavioral processes. In this paper, elemental symbol mapping and spatial association analysis techniques are applied to travelers’ attitudes. Attitudinal data, drawn from a recent travel survey conducted in McMaster University (Hamilton, Canada) among staff, students, and faculty, are analyzed. The place of residence of the respondents is geocoded in order to map the responses, and the spatial pattern of the qualitative/ordinal attitudinal variables is analyzed using the Q(m) statistic. Analysis of a selection of variables shows how some attitudes appear to develop independently from the local environments, whereas others are related to a preference towards certain types of local environments or social aspects of the local environment, which suggests underlying processes of self-selection or adaptation. [Copyright &y& Elsevier]

Abstract: Transit operators face a difficult fiscal environment and an imperative to contribute to urban sustainability. Under these circumstances, operators must find innovative ways to make public transportation attractive to broader segments of the public, while simultaneously trying to raise revenue to reduce reliance on public subsidies. Development of commercial partnerships is seen as a promising way to achieve these goals. Previous research has examined the potential of using geodemographics to assist transit agencies in the task of identifying potential partners for developing mutually beneficial commercial agreements. In this paper we describe an approach to model isoexposure to transit users as a tool to assess market potential. The approach is based on the analysis of walking behavior of transit users, and specifically distance walked at the end of their transit trip. Spatial modeling is used to geographically project estimates of walking distance for a desired demographic profile at a specific transit facility. After expanding the estimates using sample weights, overlays of these estimates can be used to generate variations in exposure to transit travelers at different locations in space. The approach is demonstrated using the case of Metro users in Montreal, Canada. The case study demonstrates the use of isoexposure profiles as a novel approach to generate marketing intelligence. This should be of interest to transit agencies and businesses interested in developing partnerships. [Copyright &y& Elsevier]

Abstract: Walkability audits provide valuable information about pedestrian environments, but are time-consuming and can be expensive to implement. In this paper, we propose a model-based approach to select sites for conducting walkability audits. The key idea is to estimate a model of travel behavior at the meso-scale level, which can be examined to identify locations where the behavior is under- and over-estimated. We conjecture that systematic under- and over-estimation can be caused by micro-level factors that influence the behavior. The results can be used to identify sites for walkability audits. The approach is demonstrated with a case study in Hamilton, Canada. A model of walk shares forms the basis of the site selection procedure. After identifying areas with higher and lower shares than predicted by the model we select a sample of neighborhoods for audits. Analysis of the results reveals elements of the local environment that associate with greater-than-expected walk shares. The case study demonstrates that the proposed model-based strategy can be used to better target limited resources, and produce valuable insights into micro-level factors that affect travel behavior. [Copyright &y& Elsevier]

Abstract: Accessibility is a concept of continuing relevance in transportation research. A number of different measures of accessibility, defined as the potential to reach spatially dispersed opportunities, have been proposed in the literature, and used to address various substantive planning and policy questions. Our objective in this paper is to conduct a review of various commonly used measures of accessibility, with a particular view to clarifying their normative (i.e. prescriptive), as well as positive (i.e. descriptive) aspects. This is a distinction that has seldom been made in the literature and that helps to better understand the meaning of alternative ways to implement the concept of accessibility. Our discussion of the positive and normative aspects of accessibility measurements is illustrated using the city of Montreal, Canada, as a case study. The example highlights the differences in the measured levels of accessibility depending on implementation. Comparison of the two by means of a relative indicator of accessibility helps to identify the gap between desired (as normative defined) and actual (as revealed) accessibility levels. [Copyright &y& Elsevier]

Abstract: Accessibility to transit facilities is a factor thought to influence the level of usage of services. Past examinations of accessibility to transit have considered the built environment and levels of service of transit. In contrast, accessibility by transit has received more limited attention in transit mode share analysis. The objective of this paper is to investigate the implications of accessibility to transit and by transit for mode shares in the city of Hamilton, Canada. We model transit shares by means of a logistic regression that takes into account over-dispersion and spatial autocorrelation. The results of the final model indicate that accessibility by transit is a significant predictor of modal share in our case study. Technically, our analysis clearly illustrates that ignoring over-dispersion and autocorrelation can result in misleading inference and erroneous policy prescriptions. [Copyright &y& Elsevier]

An emerging interest in transport research concerns the factors that can help to create strong, sustainable and ‘livable’ communities; however, relatively limited empirical work has been conducted to date. In this paper the perception of sense of community among neighbourhood residents is investigated. Drawing from research on tertiary street-communities (t-communities), the paper explores the effect of the urban landscape, particularly street networks, and neighbourhood and individual characteristics on sense of community. A sample of students at McMaster University in Hamilton, Canada, is used for the analysis. In addition to providing an opportunity to study sense of community, a student sample is interesting in its own right, as students are often a component of essential but at times uneasy relations between universities and towns. Analysis is based on the application of an ordered probit model with a spatial lag. The results provide evidence that t-community membership can influence sense of community. [ABSTRACT FROM PUBLISHER]

Abstract: The balance between supply and demand of blood products is a question of great interest for the long-term prospects of health care systems. Trends that affect this balance include an aging population and increasingly large immigrant communities with lower donation rates. Blood agencies must implement several strategies to ensure a sustained supply of blood products. A better understanding of the determinants of donation frequency is essential to develop strategies that encourage new and existing donors to donate more frequently. In this study, we investigate the individual and contextual determinants of the decision to donate multiple times, with a particular focus on accessibility to clinics. The case study is the Toronto Census Metropolitan Area. Analysis is based on discrete choice models estimated using the attributes of the geocoded donors and clinics, and Census data for contextual variables. The results indicate that higher levels of accessibility increase the probability of donor return and more frequent donations. [Copyright &y& Elsevier]

Population segregation measurement is a topic of broad interest in the social sciences. In this paper we draw from recent advances in the spatial analysis literature to derive individualized measures of clustering and exposure. Recent research on accessibility has seen a shift from place-based measures to person-based ones. Similarly, the notion of residential clustering and exposure patterns, while typically related to the distribution of population in zonal systems, can be modified to account for heterogeneous experiences of urban space. In particular, at the individual level, the degree of clustering and exposure is related to personal mobility and the individual experience of space. In this paper we turn to the question of whether individuals belonging to different groups and living in different areas of a city observe differences in their clustering and exposure to population groups over space. The proposed procedure is applied empirically to the case of Montreal to explore how native English speakers of various levels of mobility experience exposure. [ABSTRACT FROM AUTHOR]

The study of population patterns has animated a large body of urban social research over the years. An important part of this literature is concerned with the identification and measurement of segregation patterns. Recently, emphatic calls have been made to develop measures that are better able to capture the geography of population patterns. The objective of this article is to demonstrate the application of the Q statistic, developed for the analysis of spatial association of qualitative variables, to the detection of ethnic clustering and exposure patterns. The application is to historical data from 1880 Newark in the United States, with individuals classified by ethnicity and geocoded by place of residence. Three ethnic groups, termed Irish, Germans, and Yankees, are considered. Exploratory analysis with the Q statistic identifies significant differences in the tendency of individuals and building occupancy to cluster by ethnicity. In particular, there is evidence of a strong affinity within ethnic clusters and some intermingling between Yankee and Irish residents. In contrast, the exposure of Germans to individuals of other groups is found to be more limited. [ABSTRACT FROM AUTHOR]

Large variability and correlations among the coefficients obtained from the method of geographically weighted regression (GWR) have been identified in previous research. This is an issue that poses a serious challenge for the utility of the method as a tool to investigate multivariate relationships. The objectives of this paper are to assess: (1) the ability of GWR to discriminate between a spatially constant processes and one with spatially varying relationships; and (2) to accurately retrieve spatially varying relationships. Extensive numerical experiments are used to investigate situations where the underlying process is stationary and nonstationary, and to assess the degree to which spurious intercoefficient correlations are introduced. Two different implementations of GWR and cross-validation approaches are assessed. Results suggest that judicious application of GWR can be used to discern whether the underlying process is nonstationary. Furthermore, evidence of spurious correlations indicates that caution must be exercised when drawing conclusions regarding spatial relationships retrieved using this approach, particularly when working with small samples. [ABSTRACT FROM AUTHOR]

Abstract: Smart card automated fare payment systems are being adopted by transit agencies around the world. The data-storage characteristics of smart cards present novel opportunities to enhance transit services. On the one hand, there are fare policies, where smart card holders are given specific rebates on the use of the service based on usage patterns or levels. On the other, there are non-fare policies, for instance if holders receive advantages, such as rebates and offers, from commercial partners. The purpose of this paper is to present a geodemographic framework to identify potential commercial partnerships that could exploit the characteristics of smart cards. The framework is demonstrated using data from Montreal, Canada. Household survey data, specifically trip ends, and business data points are jointly used to determine the exposure of various types of establishments to users of the Montreal Metro network. Spatial analysis of business establishments in the neighborhood of metro stations helps to identify potential commercial partners. The results illustrate the potential of geodemographic analysis to generate intelligence of commercial interest. [Copyright &y& Elsevier]

Abstract: A fundamental role of an urban transportation system is to provide a means for individuals in society to access locations and participate in activities. This paper investigates how automobility, a system of land-use and mobility, imposes on the ability to participate in discretionary activities. A theoretical argument couched in time-geography is used to describe the mechanism through which activity dispersion and traffic congestion, both features of the current realization of automobility, hampers accessibility. The concept is illustrated with an analysis of synthetic space–time prisms constructed under a variety of travel speed and activity dispersion assumptions. Following this, a descriptive analysis of time-use data drawn from several cycles of the General Social Survey of Canada is used to empirically test the argument. The empirical investigation provides evidence of declining participation in a variety of discretionary, out-of-home activities, and an increase in the amount of travel required to reach activity destinations. The work trip in particular is shown to have increased significantly between 1992 and 2005 and activity profiles for drivers and non-drivers show that participation in discretionary activities is severely affected by the duration of the daily work commute. Participation however is more severely impacted by commute duration amongst non-drivers, indicating the relative benefit of being a non-driver in a compact urban form, versus potentially being excluded from participation as a non-driver in an urban spatial structure supportive of and constructed for the automobile. [Copyright &y& Elsevier]

Abstract: The effect of social interactions on decision-making is a topic of current interest in the travel behavior literature. These interactions have been investigated primarily from an intra-household perspective, but increasingly too in other types of social settings. In the case of interactions within a workplace, it has been suggested that the decision to telecommute may have some important social components. Previous research has concentrated on social isolation, and the effect on job satisfaction of qualitatively different (i.e., telecommunications-mediated) relationships with managers and colleagues. A topic that remains unexplored is the way social norms, in effect the influence of other people’s behavior, may influence the decision to adopt telecommuting. In this paper we set to investigate, within a qualitative framework, the role of social contact in the process of acquiring information on, and making decisions about, telecommuting. The results indicate that social contact does play a subtle but non-trivial role in the adoption and continuation process, and offer some insights about the importance of the social dimension, institutional set-up, and how they interact to influence the decision to telecommute. [Copyright &y& Elsevier]

Abstract: This paper examines the provision of mobility options being one of the important policy areas vital to addressing transportation accessibility of the elderly. A provincial analysis, taking the case of the Province of Ontario in Canada, is warranted given that the country’s highly decentralized system puts provincial policies at the forefront in meeting this challenge. The paper evaluates the important progress made in this policy area and stressed the need to go beyond the traditional policy focus on the less able-bodied elderly and consider the increased heterogeneity of the elderly population with respect to lifestyle, preferences, resources, health and physical abilities. While significant efforts have been made, a more explicit recognition of population aging in Ontario’s transport policy motivation that could strongly influence transport strategies and investments attuned to the mobility concerns in an aging society remains to be seen. The paper summarizes the general concerns in the literature, policy developments, and the challenges in crafting solutions in terms of policy and research for Ontario and other regions with similar institutional setup. [ABSTRACT FROM AUTHOR]

Abstract: This study investigates how socio-demographic and attitudinal variables of university students affect their desire to increase or decrease their daily commute. The case study is McMaster University in Hamilton, Canada, and data was obtained by means of a web-based survey that included questions regarding travel behavior, socio-demographic information, and attitudes toward travel, land use, and the environment. The objective variable is defined as the ratio of ideal to actual commute time, and regression analysis is implemented to test the relationship between this variable and socio-demographic variables and attitudinal scores. The impact of different attitudes on the gap between ideal and actual commute time is expanded to include three different modes, active travel (walk/cycle), transit, and personal automobile. Interestingly, the results indicate that active travelers tend to be less dissatisfied with their commute, followed by those who travel in a personal vehicle and transit users. A number of attitudinal responses are shown to impact the desire to travel more or less, including variables that relate to the social environment, availability of local activities, quality of facilities, productive use of the commute, and the intrinsic value found in the commute travel. The picture emerges of a traveler who would like to spend more time commuting, as someone who is an active traveler, thinks that getting there is half the fun, dislikes traveling alone, but rather likes to live in an active neighborhood where there is a sense of community. The results suggests that enjoyment of commuting, while a challenge from the perspective of motorized mobility, may provide valuable policy opportunities from the perspective of active transportation. [Copyright &y& Elsevier]

Accessibility research, within the context of the social exclusion dimensions of transport, has provided valuable tools to understand the potential of people to reach daily life activity locations. In this paper, model-based estimates of distance travelled are used to calculate a cumulative opportunities measure of accessibility. Multivariate, spatially expanded models produce estimates of distance travelled that are speciic to both geographical location and type of individual. Opportunity landscapes obtained based on these estimates are used for comparative accessibility analysis by means of what are termed relative accessibility deprivation indicators. The indicators proposed are demonstrated with a case study of food deserts in the city of Montreal, Canada. The results of the analysis illustrate the variations in accessibility between individuals in low-income households and the reference group, and the effect of vehicle ownership for accessibility to food services, thus highlighting the social exclusion implications of these factors. [ABSTRACT FROM AUTHOR]

The article discusses various papers published within the issue including one on the neighborhood effects of foreclosure and another on the impact of community development projects.

The article introduces a series of topics discussed within this issue, including one on the developments and applications in spatial statistics and econometrics, and another on the development and convergence in regional economic systems.

Abstract: The role of social contact as a motivator for mobility has gained interest in recent years with conceptual and empirical work that provides evidence of the importance of social context on travel behavior. On the other hand, the impact of different modes of transportation on the frequency and duration of contact has not been explored. Using the 1994 Portland Household Activity and Travel Behavior Survey, this paper investigates the potential relationship between automobility and the expected participation in and duration of a variety of in-home and out-of-home social activities. The analysis makes use of descriptive and inferential statistics to illustrate a broad variation in the effect of car use on duration of activity, both in terms of polarity and magnitude. Furthermore, multivariate regression analysis reveals that reliance on the automobile acts by enabling longer durations in less mobile and more time-constrained segments of the population. Conversely it acts by decreasing durations in more mobile and less time-constrained subgroups. The paper ends by discussing directions for future research into the potential social implications of automobility. [Copyright &y& Elsevier]

Social network analysis has been identified as a promising direction for further applications of spatial statistical and econometric models. The type of network analysis envisioned is formally identical to the analysis of geographical systems, in that both involve the measurement of dependence between observations connected by edges that constitute a system. An important item, which has not been investigated in this context, is the potential relationship between the topology properties of networks (or network descriptions of geographical systems) and the properties of spatial models and tests. The objective of this article is to investigate, within a simulation setting, the ability of spatial dependency tests to identify a spatial/network autoregressive model when two network topology measures, namely degree distribution and clustering, are controlled. Drawing on a large data set of synthetically controlled social networks, the impact of network topology on dependency tests is investigated under a hierarchy of topology factors, sample size, and autocorrelation strength. In addition, topology factors are related to known properties of empirical systems. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study is to investigate the determinants of mean trip distance traveled by different mode types. The study uses data from the Hamilton CMA in Canada, and multilevel models to investigate the variables that impact distance traveled, with a specific focus on demographic aging factors. The results of the study validate previous findings regarding the decline in distance traveled as age advances. In addition, it is found that: (1) while this effect of age is present for all modes analyzed (car driving, car passenger, and bus) it is considerably more marked for car driving; (2) there are significant effects compounded by the interrelated factors of gender, employment constraints, household contextual factors; and (3) neighbourhoods with high commercial and residential mix showed a negative relation with distance traveled only in the case of car driver. [Copyright &y& Elsevier]

In this paper we analyze the changes in accessibility to emergency and community food services before and during the COVID-19 pandemic in the City of Hamilton, Ontario. Many of these food services are the last line of support for households facing food insecurity; as such, their relevance cannot be ignored in the midst of the economic upheaval caused by the pandemic. Our analysis is based on the application of balanced floating catchment areas and concentrates on households with lower incomes (

Individual decision making is commonly studied using discrete choice models. Models of this type are applied extensively to the study of travel behavior, residential location, and employment decisions, among other topics of interest. A notable characteristic of the underlying economic theory is the assumption that individuals seek to maximize utility on the basis of their personal attributes and the attributes of the alternatives available to them. This approach ignores the interrelated nature of decision making in social situations—in other words, the role that social structures play in shaping behavior. In this paper we describe a multinomial discrete choice approach to analyzing individual behavior in social situations where position in a social network may encourage or discourage different courses of action. By means of a simulation example, we explore some properties of the model, in particular the effect of network topology. [ABSTRACT FROM AUTHOR]

The article discusses several papers related to social networks, travel and land use. It examines the scope of transportation analysis by paying attention to the effects of social and spatial dependencies on travel behaviour. It claims that the papers focus on intrahousehold interactions and work pertaining the influence of social networks on travel behaviour. The research looks to an increased interest in the social motivators for travel and mobility and their potential to improve the understanding and ability to model urban systems.

Recognition of the limitations of traditional hedonic models to account for spatial effects has led in recent years to the development and use of spatial econometric and statistical techniques in real estate applications. It seems appropriate, as the number of applications grows, to evaluate the relative ability of some newer approaches in terms of producing accurate spatial predictions. This article compares a selection of techniques to assess their performance. The focus is on moving window approaches that can be conceptualised as sliding neighbourhoods (i.e. soft market segmentations) and that can incorporate spatial dependency effects. Comparison of moving windows regression (MWR), geographically weighted regression (GWR) and moving windows Kriging (MWK) sheds light on the relevance of different spatial effects. Results using Toronto as a case study indicate that market segmentation may be more important than spatial dependencies. The findings suggest practical guidelines with regard to the use of the models investigated. [ABSTRACT FROM AUTHOR]