来自巴塞罗那地区一项公民科学实验的家校步行移动 GPS 数据
Home-to-school pedestrian mobility GPS data from a citizen science experiment in the Barcelona area
AI总结：
本研究通过公民科学方式采集并共享巴塞罗那大都会区10所学校学生的单日家校步行GPS数据，辅以过滤、清洗与插值流程，为步行城市研究提供高分辨率微观移动数据集。
摘要：
行人 GPS 数据集分析对于进一步推进步行城市的研究与设计具有基础性意义。最高分辨率的 GPS 数据能够刻画微观移动模式，以及行人在小规模城市环境中的微观动机。在这类研究中，人们社区内部基于目的的周期性移动数据是重要来源。然而，人们住所周围的微观移动数据通常难以获得；即使存在相关数据，也往往因隐私问题而无法共享。公民科学及其让公众参与科学研究的实践，是规避这些挑战并为步行城市提供有意义数据集的有效选择。本研究展示了来自西班牙巴塞罗那大都会区 10 所学校的单日家校步行移动 GPS 记录。该研究提供了一个年龄同质人群的行人移动数据。研究共享了经过特定过滤、清洗和插值流程处理的记录，这些流程可促进并加快数据使用。文中还报告了整个研究过程中的公民科学实践，以提供所收集数据的完整视角。
英文摘要：
The analysis of pedestrian GPS datasets is fundamental to further advance on the study and the design of walkable cities. The highest resolution GPS data can characterize micro-mobility patterns and pedestrians' micro-motives in relation to a small-scale urban context. Purposed-based recurrent mobility data inside people's neighborhoods is an important source in these sorts of studies. However, micro-mobility around people's homes is generally unavailable, and if data exists, it is generally not shareable often due to privacy issues. Citizen science and its public involvement practices in scientific research are valid options to circumvent these challenges and provide meaningful datasets for walkable cities. The study presents GPS records from single-day home-to-school pedestrian mobility of 10 schools in the Barcelona Metropolitan area (Spain). The research provides pedestrian mobility from an age-homogeneous group of people. The study shares processed records with specific filtering, cleaning, and interpolation procedures that can facilitate and accelerate data usage. Citizen science practices during the whole research process are reported to offer a complete perspective of the data collected.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
