通过可达性和社会脆弱性地图识别迈阿密戴德县交通服务差距

Q3 Social Sciences
H. Hochmair, Eli Brossell, Z. Fu
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引用次数: 1

摘要

公共交通服务提供不足可能导致弱势人口群体(如低收入家庭、老年人)被排斥在与流动性相关的社会之外,而且就业、健康食品、娱乐和社会活动的可及性有限。本研究的目的是确定佛罗里达州迈阿密-戴德县的弱势群体无法获得这些机会的地区,以及改善公共交通服务可以使这些群体特别受益的地区。这涉及开发一种基于交通的无障碍指数,该指数使用三家公共交通机构的时间表数据。它还需要根据社会经济变量的组合设计一个脆弱性指数,以确定在流动性方面处于不利地位的人口群体。这两个指数可以合并成一个服务提供得分,该得分量化了需要改善过境服务的人口的存在。结果表明,结合不同的指数图和热点分析法,可以识别出需要改善公交服务的区域,以实现可达性公平。分析和解释无障碍地图和选定的人口层次,例如没有车辆的家庭百分比,有助于确定依赖公共交通的用户比例高于平均水平的地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Transit Service Gaps through Accessibility and Social Vulnerability Mapping in Miami-Dade County
Inadequate provision of public transportation services can lead to mobility-related social exclusion for disadvantaged population groups (e.g., lower-income families, the elderly), and limited accessibility to jobs, healthy food, and recreational as well as social activities. The aim of this study is to identify areas in Miami-Dade County, Florida, where disadvantaged populations lack transit-based access to these opportunities, and where transit service improvement could benefit these groups especially. This involves developing a transit-based accessibility index which uses timetable data from three public transit agencies. It also entails devising a vulnerability index based on a combination of socioeconomic variables to identify disadvantaged population groups with regards to mobility. Both indices can be combined into a service provision score which quantifies the presence of populations in need of transit service improvements. Results show that the combination of the different index maps and the application of Hotspot analysis can help to identify areas requiring transit service improvement in order to achieve accessibility equity. The analysis and interpretation of accessibility maps and selected demographic layers, such as percentage of households without vehicle, facilitates the identification of areas with above-average rates of users who rely on public transportation.
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来源期刊
GI_Forum
GI_Forum Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
23 weeks
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