Activity spaces are used to capture patterns in urban mobility and to portray the spatial distribution of day-to-day activities. The literature exploring variation in individual activity spaces identifies strong associations between several activity space characteristics and the built environment of the residential location. This cross-sectional study adds to this evidence by examining whether these associations persist after adjusting for residential self-selection. Adults’ everyday mobility was studied using public participation GIS, a participatory mapping method allowing the large-scale collection of laymen-produced spatial data. Activity spaces were defined with a customized minimum convex polygon modelled on the respondents’ frequently visited locations. We used linear regression and multinomial logistic regression analyses to study the associations between residential preferences, residential location, and activity space size and centricity. According to our results, residential location significantly influences activity space size and polycentricity in models adjusted for stated residential preferences and individual-level covariates.

活动空间用于捕捉城市流动性的模式并描绘日常活动的空间分布。探索单个活动空间变化的文献确定了多个活动空间特征与住宅位置的建成环境之间的强烈关联。这项横断面研究通过检查在针对居民的自我选择进行调整后这些关联是否持续存在，为这一证据增添了证据。使用公众参与GIS研究了成年人的日常出行方式，这是一种参与式映射方法，可以大规模收集外行生产的空间数据。活动空间是使用自定义的最小凸多边形定义的，该最小多边形以受访者经常访问的位置为模型。我们使用线性回归和多项式逻辑回归分析来研究居住偏好，居住位置以及活动空间大小和中心性之间的关联。根据我们的结果，在针对陈述的居住偏好和个人水平协变量进行调整的模型中，居住位置显着影响活动空间的大小和多中心性。