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The recent emergence of dockless bike sharing systems has resulted in new patterns of urban transport. Users can begin and end trips from their origin and destination locations rather than docking stations. Analysis of changes in the spatiotemporal availability of such bikes has the ability to provide insights into urban dynamics at a finer granularity than is possible through analysis of travel card or dock-based bike scheme data. This study analyses dockless bike sharing in Nanchang, China over a period when a new metro line came into operation. It uses spatial statistics and graph-based approaches to quantify changes in travel behaviours and generates previously unobtainable insights about urban flow structures. Geostatistical analyses support understanding of large-scale changes in spatiotemporal travel behaviours and graph-based approaches allow changes in local travel flows between individual locations …