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1.
Health Place ; 78: 102899, 2022 11.
Artículo en Inglés | MEDLINE | ID: mdl-36242828

RESUMEN

Spatial and area-level socioeconomic variation in urban liveability (access to social infrastructure, public transport, open space, healthy food choices, local employment, street connectivity, dwelling density, and housing affordability) was examined and mapped across 39,967 residential statistical areas in Australia's metropolitan (n = 7) and largest regional cities (n = 14). Urban liveability varied spatially, with inner-city areas more liveable than outer suburbs. Disadvantaged areas in larger metropolitan cities were less liveable than advantaged areas, but this pattern was reversed in smaller cities. Local data could inform policies to redress inequities, including those designed to avoid disadvantage being suburbanised as cities grow and gentrify.


Asunto(s)
Planificación de Ciudades , Transportes , Humanos , Ciudades , Empleo , Australia
2.
Sci Total Environ ; 763: 143033, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33158537

RESUMEN

Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design.

3.
J Transp Health ; 19: 100931, 2020 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-32953454

RESUMEN

BACKGROUND: Since the late 19th century, city planners have struggled to cope with new types of urban transport and mobility that threatened the existing system, or even rendered it obsolete. PURPOSE: As city planners confront the range of disruptive urban mobilities currently on the horizon, this paper explores how we can draw on a vast body of evidence to anticipate and avoid unintended consequences to people's health and wellbeing. METHODS: This commentary involved a rapid review of the literature on transport disruption. RESULTS: We found that to avoid the unintended consequences of disruption, research, policy and practice must think beyond single issues (such as the risk of chronic disease, injury, or traffic management) and consider the broader consequences of interventions. For example, although autonomous vehicles will probably reduce road trauma, what will be the negative consequences for physical inactivity, sedentary behavior, chronic disease, land use, traffic congestion and commuting patterns? Research is needed that considers and informs how to mitigate the range of potential harms caused by disruptive mobilities. CONCLUSION: In the face of new disruptive mobilities, we must: (a) draw on existing evidence to shape new regulations that address the 'who, when and where' rules of introducing new mobilities (such as electric assisted bicycles (e-bikes) and scooters (e-scooters)) of which the health repercussions can be easily anticipated; (b) monitor and evaluate the implementation of any interventions through natural experiment studies; and (c) use innovative research methods (such as agent-based simulation and health-impact-assessment modelling) to assess the likely effects of emerging disruptive mobilities (e.g., autonomous vehicles) on health and wellbeing and on the environment.

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