Approximating Accessibility of Regions from Incomplete Volunteered Data

Hadi Asghari, Jakob Stolberg-Larsen, Theresa Züger
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Abstract

Being informed about the accessibility of neighborhoods, cities, and regions can help persons with disabilities in making travel and daily decisions. This information can also be useful and a pushing factor for supportive public policies. While accessibility mapping initiatives, such as Wheelmap.org, have enjoyed tremendous success and scale, they are still far from exhaustive, and their coverage contains biases stemming from volunteer practices. With the aid of the framework of causal statistics, we suggest approaches to adjust for these biases, with the end goal of providing helpful approximations of overall accessibility in different European geographical regions.
利用不完全自愿数据逼近区域可达性
了解社区、城市和地区的无障碍情况可以帮助残疾人作出旅行和日常决定。这些信息也可以是有用的,是推动支持性公共政策的一个因素。虽然无障碍地图倡议,如Wheelmap.org,已经取得了巨大的成功和规模,但它们还远远不够详尽,而且它们的报道中包含来自志愿者实践的偏见。在因果统计框架的帮助下,我们提出了调整这些偏差的方法,最终目标是提供欧洲不同地理区域总体可达性的有用近似值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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