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Accessibility Inequality in Houston

机译:休斯顿的可达性不平等

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Recent research has reported that residents from different types of neighborhoods exhibit divergent patterns of urban mobility. However, these analyses have not considered the accessibility enabled by transportation networks. Furthermore, the data are typically not collected at a fine-grained enough temporal resolution, which impedes upon the accurate identification of more frequently visited locations. Here, we develop a data fusion framework to integrate individuals’ mobility, transportation routing, and census data to quantify urban dwellers' accessibility to their frequently visited locations. The framework has been applied to a random sample of 1000 Houstonians. The analytical results show that Houston residents visit a median of nine locations five times or more in the period of one week. Residents from primarily poor and black neighborhoods experience longer travel times compared to individuals from nonpoor and white neighborhoods when using public transit, even though their travel durations by driving are similar. The differences are problematic given that residents from poor and black neighborhoods often have lower rates of car ownership. The results indicate that urban dwellers’ accessibility is strongly impacted by their neighborhood characteristics, which has implications for equitable access in urban environments.
机译:最近的研究报告说,来自不同类型社区的居民表现出不同的城市流动模式。但是,这些分析并未考虑到交通网络带来的可访问性。此外,通常不会以足够细粒度的时间分辨率来收集数据,这妨碍了对更频繁访问的位置的准确识别。在这里,我们开发了一个数据融合框架,以整合个人的出行,交通路线和人口普查数据,以量化城市居民到其常去地点的可及性。该框架已应用于1000名休斯顿人的随机样本。分析结果表明,休斯敦居民在一周内访问五处或五处以上的九个地点的中位数。与非贫困和白人社区居民相比,在使用公共交通时,主要来自贫困和黑人社区的居民的出行时间更长,即使他们开车的旅行时间相近。考虑到来自贫困和黑人社区的居民通常拥有较低的汽车拥有率,因此存在差异。结果表明,城市居民的可及性受到其邻里特征的强烈影响,这对城市环境中的平等获取产生了影响。

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