OpenSystems, Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès, 1, 08028, Barcelona, Catalonia, Spain.
Universitat de Barcelona Institute of Complex Systems, Universitat de Barcelona, Barcelona, Catalonia, Spain.
Sci Data. 2023 Jul 4;10(1):428. doi: 10.1038/s41597-023-02328-3.
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 neighbourhoods 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.
分析行人 GPS 数据集对于进一步推进可步行城市的研究和设计至关重要。最高分辨率的 GPS 数据可以描述微观移动模式和行人在小尺度城市环境中的微观动机。基于目的的居民区内的移动数据是此类研究的重要来源。然而，人们家周围的微观移动通常不可用，而且如果存在数据，由于隐私问题，通常也无法共享。公民科学及其在科学研究中的公众参与实践是规避这些挑战并为可步行城市提供有意义数据集的有效选择。本研究展示了西班牙巴塞罗那大都市区 10 所学校为期一天的上下学行人移动 GPS 记录。该研究提供了来自年龄同质人群的行人移动数据。本研究分享了经过特定过滤、清理和插值处理的记录，这些处理可以促进和加速数据的使用。在整个研究过程中，公民科学实践得到了报告，以提供对所收集数据的全面视角。
