We examine the potential of using large-scale open crowdsourced sidewalk data from Project Sidewalk to study the distribution and condition of sidewalks in Seattle, WA. While potentially noisier than professionally gathered sidewalk datasets, crowdsourced data enables large, cross-regional studies that would be otherwise expensive and difficult to manage. As an initial case study, we examine spatial patterns of sidewalk quality in Seattle and their relationship to racial diversity, income level, built density, and transit modes. We close with a reflection on our approach, key limitations, and opportunities for future work.

我们研究了使用大规模开放的众包人行道数据的潜力 从《人行道工程》入手，研究安徽省人行道的分布和状况 华盛顿州西雅图虽然可能比专业人士聚集的人行道更嘈杂 数据集，众包数据使大型跨区域研究成为可能 否则成本高昂且难以管理。作为最初的案例研究，我们 西雅图人行道质量空间格局及其关系研究 种族多样性、收入水平、建筑密度和交通方式。我们关门了 反思我们的方法、主要限制和机遇 未来的工作。