986 resultados para Residential Density


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Imperatives to improve the sustainability of cities often hinge upon plans to increase urban residential density to facilitate greater reliance on sustainable forms of transport and minimise car use. However there is ongoing debate about whether high residential density land use in isolation results in sustainable transport outcomes. Findings from surveys with residents of inner-urban high density dwellings in Brisbane, Australia, suggest that solo car travel accounts for the greatest modal share of typical work journeys and attitudes toward dwelling and neighbourhood transport-related features, residential sorting factors and socio-demographics, alongside land use such as public transport availability, are significantly associated with work travel mode choice. We discuss the implications of our findings for transport policy and management including encouraging relatively sustainable intermodal forms of transport for work journeys.

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This research identifies residential mobility behaviour impacts of residential dissonance in Transit Oriented Developments (TODs) vs. non-TODs in Brisbane, Australia. Based on the characteristics of living environments (density, diversity, connectivity, and accessibility) and the travel preferences of 4545 individuals, respondents in 2009 were classified into one of four categories including: TOD consonants, TOD dissonants, non-TOD dissonants, and non-TOD consonants. Binary logistic regression analyses were employed to identify residential mobility behaviour of groups between 2009 and 2011; controlling for time varying covariates. The findings show that both TOD dissonants and TOD consonants move residences at an equal rate. However, TOD dissonants are more likely to move residences to their preferred non-TOD areas. In contrast, non-TOD dissonants not only moved residences at a lower rate, but their rate of mobility to their preferred TOD neighbourhood is also significantly lower due to costs and other associated factors. The findings suggest that discrete land use policy development is required to integrate non-TOD dissonant and TOD dissonant behaviours to support TOD development in Brisbane.

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Residential dissonance refers to the mismatch in land-use patterns between individuals’ preferred residential neighbourhood type and the type of neighbourhood in which they currently reside. Current knowledge regarding the impact of residential dissonance is limited to short-term travel behaviours in urban vs. suburban, and rural vs. urban areas. Although the prevailing view is that dissonants adjust their orientation and lifestyle around their surrounding land use over time, empirical evidence is lacking to support this proposition. This research identifies both short-term mode choice behaviour and medium-term mode shift behaviour of dissonants in transit oriented development (TODs) vs. non-TOD areas in Brisbane, Australia. Natural groupings of neighbourhood profiles (e.g. residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility levels) of 3957 individuals were identified as living either in a TOD (510 individuals) or non-TOD (3447 individuals) areas in Brisbane using the TwoStep cluster analysis technique. Levels of dissonance were measured based on a factor analysis of 16 items representing the travel attitudes/preferences of individuals. Two multinomial logistic (MNL) regression models were estimated to understand mode choice behaviour of (1) TOD dissonants, and (2) non-TOD dissonants in 2009, controlling for socio-demographics and environmental characteristics. Two additional MNL regression models were estimated to investigate mode shift behaviour of (3) TOD dissonants, and (4) non-TOD dissonants between 2009 and 2011, also controlling for socio-demographic, changes in socio-demographic, and built environmental factors. The findings suggest that travel preference is relatively more influential in transport mode choice decisions compared with built environment features. Little behavioural evidence was found to support the adjustment of a dissonant orientation toward a particular land use feature and mode accessibility they represent (e.g. a modal shift to greater use of the car for non-TOD dissonants). TOD policies should focus on reducing the level of dissonance in TODs in order to enhance transit ridership.

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The literature on residences and citizens’ transports has focused on either reforming traffic managing in response to residential relocation or post-evaluation of urban planning policies or the evolution of the urban spatial form. In a city there are hotspots that attract the citizens and most of the transportation in the city arises as the citizens’ movement between their residence and the hotspots. Little scholarly attention has been devoted to the possibility to minimize citizens’ transportation in the city by the urban planning of residential areas. In this paper we propose a method to evaluate the environmental impact (in terms of CO2-emissions) of urban plans of residential areas. The method is illustrated in a Swedish case of a midsize city which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. The residential plans aims to increase the compactness and residential density in the current center and sub centers leads to less CO2 emissions compare to urban expansion to the edge of the city. The plans of concentrated apartment buildings are more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.

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Purpose. To explore the role of the neighborhood environment in supporting walking Design. Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting. The Brisbane City Local Government Area, Australia, 2007. Subjects. Brisbane residents aged 40 to 65 years. Measures. Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis. The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results. After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion. The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

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A substantial body of research is focused on understanding the relationships between socio-demographics, land-use characteristics, and mode specific attributes on travel mode choice and time-use patterns. Residential and commercial densities, inter-mixing of land uses, and route directness in conjunction with transportation performance characteristics interact to influence accessibility to destinations as well as time spent traveling and engaging in activities. This study uniquely examines the activity durations undertaken for out-of-home subsistence; maintenance, and discretionary activities. Also examined are total tour durations (summing all activity categories within a tour). Cross-sectional activities are obtained from household activity travel survey data from the Atlanta Metropolitan Region. Time durations allocated to weekdays and weekends are compared. The censoring and endogeneity between activity categories and within individuals are captured using multiple equations Tobit models. The analysis and modeling reveal that land-use characteristics such as net residential density and the number of commercial parcels within a kilometer of a residence are associated with differences in weekday and weekend time-use allocations. Household type and structure are significant predictors across the three activity categories, but not for overall travel times. Tour characteristics such as time-of-day and primary travel mode of the tours also affect traveler's out-of-home activity-tour time-use patterns.

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Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

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Proxy reports from parents and self-reported data from pupils have often been used interchangeably to identify factors influencing school travel behaviour. However, few studies have examined the validity of proxy reports as an alternative to self-reported data. In addition, despite research that has been conducted in a different context, little is known to date about the impact of different factors on school travel behaviour in a sectarian divided society. This research examines these issues using 1624 questionnaires collected from four independent samples (e.g. primary pupils, parent of primary pupils, secondary pupils, and parent of secondary pupils) across Northern Ireland. An independent sample t test was conducted to identify the differences in data reporting between pupils and parents for different age groups using the reported number of trips for different modes as dependent variables. Multivariate multiple regression analyses were conducted to then identify the impacts of different factors (e.g. gender, rural–urban context, multiple deprivations, and school management type, net residential density, land use diversity, intersection density) on mode choice behaviour in this context. Results show that proxy report is a valid alternative to self-reported data, but only for primary pupils. Land use diversity and rural–urban context were found to be the most important factors in influencing mode choice behaviour.

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Internationally, transit oriented development (TOD) is characterised by moderate to high density development with diverse land use patterns and well connected street networks centred around high frequency transit stops (bus and rail). Although different TOD typologies have been developed in different contexts, they are based on subjective evaluation criteria derived from the context in which they are built and typically lack a validation measure. Arguably there exist sets of TOD characteristics that perform better in certain contexts, and being able to optimise TOD effectiveness would facilitate planning and supporting policy development. This research utilises data from census collection districts (CCDs) in Brisbane with different sets of TOD attributes measured across six objectively quantified built environmental indicators: net employment density, net residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility. Using these measures, a Two Step Cluster Analysis was conducted to identify natural groupings of the CCDs with similar profiles, resulting in four unique TOD clusters: (a) residential TODs, (b) activity centre TODs, (c) potential TODs, and; (d) TOD non-suitability. The typologies are validated by estimating a multinomial logistic regression model in order to understand the mode choice behaviour of 10,013 individuals living in these areas. Results indicate that in comparison to people living in areas classified as residential TODs, people who reside in non-TOD clusters were significantly less likely to use public transport (PT) (1.4 times), and active transport (4 times) compared to the car. People living in areas classified as potential TODs were 1.3 times less likely to use PT, and 2.5 times less likely to use active transport compared to using the car. Only a little difference in mode choice behaviour was evident between people living in areas classified as residential TODs and activity centre TODs. The results suggest that: (a) two types of TODs may be suitable for classification and effect mode choice in Brisbane; (b) TOD typology should be developed based on their TOD profile and performance matrices; (c) both bus stop and train station based TODs are suitable for development in Brisbane.

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In policy circles, transit oriented development (TOD) is believed to enhance social capital, however empirical evidence of this relationship is lacking. This research compares levels of social capital between TOD vs. non-TOD areas in Brisbane, Australia. Using a Two Step cluster analysis technique, three types of neighbourhood groupings were identified based on net employment density, net residential density, land use diversity, intersection density, and public transport accessibility: TODs, transit adjacent development (TADs) and traditional suburbs. Two dimensions of social capital were measured (trust and reciprocity, connections with neighbours) based on factor analysis of eight items representing elements of social capital. Multivariate regression analyses were conducted to identify links between the distributions of the dimensions of social capital on areas defined as TODs, TADs, and traditional suburbs controlling for socio-demographics and environmental factors. Results show that individuals living in TODs had a significantly higher level of trust and reciprocity and connections with neighbours compared with residents of TADs. It appears that TODs may foster the development of social sustainability.

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Spatial population data, obtained through the pixeling method, makes many related researches more convenient. However, the limited methods of precision analysis prevent the spread of spatial distribution methods and cumber the application of the spatial population data. This paper systematically analyzes the different aspects of the spatial population data precision, and re-calculates them with the reformed method, which makes breakthrough for the spread of the pixeling method and provides support and reference for the application of spatial population data. The paper consists of the following parts: (2) characters of the error; (2) origins of the error; (3) advancement on the calculating methods of the spatial population data. In the first place, based on the analysis of the error trait, two aspects of the spatial population data precision are characterized and analyzed: numerical character and spatial distributing character. The later one, placed greater emphasis on in this paper, is depicted in two spatial scales: county and town. It is always essential and meaningful to the research in this paper that spatial distribution is as important as numerical value in analyzing error of the spatial distributed data. The result illustrates that the spatial population data error appears spatially in group, although it is random in the aspect of data statistics, all of that shows there lies spatial systematic error. Secondly, this paper comes to conclude and validate the lineal correlation between the residential land area (from 1:50000 map and taken as real area) and population. Meanwhile, it makes particular analysis on the relationship between the residential land area, which is obtained from the land use map and the population in three different spatial scales: village, town and county, and makes quantitative description of the residential density variation in different topological environment. After that, it analyzes the residential distributing traits and precision. With the consideration of the above researches, it reaches the conclusion that the error of the spatial distributed population is caused by a series of factors, such as the compactness of the residents, loss of the residential land, the population density of the city. Eventually, the paper ameliorates the method of pixeling the population data with the help of the analysis on error characters and causes. It tests 2-class regionalization based on the 1-class regionalization of China, and resorts the residential data from the land use map. In aid of GIS and the comprehensive analysis of various data source, it constructs models in each 2-class district to calculate spatial population data. After all, LinYi Region is selected as the study area. In this area, spatial distributing population is calculated and the precision is analyzed. All it illustrates is that new spatial distributing population has been improved much. The research is fundamental work. It adopts large amounts of data in different types and contains many figures to make convincing and detailed conclusions.

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Physical inactivity is the fourth leading risk factor for global mortality, with most of these deaths occurring in low and middle-income countries (LMICs) like India. Research from developed countries has consistently demonstrated associations between built environment features and physical activity levels of populations. The development of culturally sensitive and reliable measures of the built environment is a necessary first step for accurate analysis of environmental correlates of physical activity in LMICs. This study systematically adapted the Neighborhood Environment Walkability Scale (NEWS) for India and evaluated aspects of test-retest reliability of the adapted version among Indian adults. Cultural adaptation of the NEWS was conducted by Indian and international experts. Semi-structured interviews were conducted with local residents and key informants in the city of Chennai, India. At baseline, participants (N = 370; female = 47.2%) from Chennai completed the adapted NEWS-India surveys on perceived residential density, land use mix-diversity, land use mix-access, street connectivity, infrastructure and safety for walking and cycling, aesthetics, traffic safety, and safety from crime. NEWS-India was administered for a second time to consenting participants (N = 62; female = 53.2%) with a gap of 2–3 weeks between successive administrations. Qualitative findings demonstrated that built environment barriers and constraints to active commuting and physical activity behaviors intersected with social ecological systems. The adapted NEWS subscales had moderate to high test-retest reliability (ICC range 0.48–0.99). The NEWS-India demonstrated acceptable measurement properties among Indian adults and may be a useful tool for evaluation of built environment attributes in India. Further adaptation and evaluation in rural and suburban settings in India is essential to create a version that could be used throughout India.

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The built environment is part of the physical environment made by people and for people. Because the built environment is such a ubiquitous component of the environment, it acts as an important pathway in determining health outcomes. Zoning, a type of urban planning policy, is one of the most important mechanisms connecting the built environment to public health. This policy analysis research paper explores how zoning regulations in Austin, Texas promote or prohibit the development of a healthy built environment. A systematic literature review was obtained from Active Living Research, which contained literature published about the relationships between the built environment, physical activity, and health. The results of these studies identified the following four components of the built environment that were associated to health: access to recreational facilities, sprawl and residential density, land use mix, and sidewalks and their walkability. A hierarchy analysis was then performed to demonstrate the association between these aspects of the built environment and health outcomes such as obesity, cardiovascular disease, and general health. Once these associations had been established, the components of the built environment were adapted into the evaluation criteria used to conduct a public health analysis of Austin's zoning ordinance. A total of eighty-eight regulations were identified to be related to these components and their varying associations to human health. Eight regulations were projected to have a negative association to health, three would have both a positive and negative association simultaneously, and nine were indeterminable with the information obtained through the literature review. The remaining sixty-eight regulations were projected to be associated in a beneficial manner to human health. Therefore, it was concluded that Austin's zoning ordinance would have an overwhelmingly positive impact on the public's health based on identified associations between the built environment and health outcomes.^

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Thesis (Master's)--University of Washington, 2016-06