理解骑行者对建成环境特征的偏好，对于促进可持续城市交通与主动出行至关重要。尽管已有研究探讨了骑行者的路径选择，但视觉与非视觉因素如何影响不同出行目的下的路径选择仍不明确；本文通过加拿大蒙特利尔的数据驱动案例研究填补这一空白。非视觉因素包括社会经济因素及二维环境变量，视觉因素则涉及骑行过程中的视觉感知，并利用街景图像进行计算。本研究分为两部分：一部分分析时空信息，以探究骑行行程起讫点间非视觉因素的影响；另一部分则比较最短路径与实际路径之间上述因素分布的差异。研究结果揭示了影响主动骑行选择的时空特征，例如绿化率提高与机动车化程度降低。这些发现可为街道网络规划及基础设施建设提供依据，从而提升主动交通方式的使用水平。

Understanding cyclist preferences for the characteristics of the built environment is important in promoting sustainable urban transportation and active mobility. Despite previous studies on cyclists' route choices, the influence of visual and non-visual factors on these choices for different trip purposes remains unclear; thus, this paper fills this gap through a data-driven case study in Montreal, Canada. Non-visual factors include socioeconomic factors and two-dimensional environments, while visual factors involve visual perception during cycling and are computed using street view images. The study consists of two parts: one part analyzes spatiotemporal information to explore the non-visual factors between the start and end points of cycling trips, and the other part investigates the discrepancies in distributions of these factors between the shortest path and the actual one. The findings reveal the spatiotemporal characteristics that influence active riding choices, such as increased greenery and lower levels of motorization. These insights can inform the planning of street networks and the development of infrastructure to improve the use of active transportation.