Revealing Factors Driving Spatial Distribution of Shared Bicycles Connected to Urban Subway Using ArcGIS and GeoDetector

The flexibility, accessibility, and affordability of shared bicycles are an efficient way to supplement the “first/last kilometer” of residents’ travel chains. This paper analyzes the spatiotemporal distribution characteristics of shared bicycle Origin-Destination (OD) connecting to rail transit stations and the influencing factors, based on shared bicycle big data and Point of Interest (POI) data by using ArcGIS spatial statistics tools, and identifies cycling traffic hotspots and outliers. The spatiotemporal variability of the cycle distribution and interaction probes are explored using GeoDetector. Results show that shared bicycle traffic has heat source and outlier regions in the time and space distribution. The influence degree of different POI factors in factor detection and interaction detection is different in the time dimension, and the dominant interaction factors are all in a two-factor augmentation relationship with each other. Our findings can improve the connectivity new model of shared bicycle + urban subway in urban public transportation.