In recent years, the sharing economy has taken on a leap-forward development in China, reaching into all aspects of urban life. This new mode of transportation has raised higher requirements for urban construction, but also exposed many problems. In terms of urban planning, it is necessary to make rational planning and construction of urban riding space to solve these problems. Shared bikes can provide data with time and space attributes in daily use. By means of big data analysis, we can more objectively understand the rules and the spatial characteristic of the citizen riding, providing strong support for the planning and design of urban riding space. The research area is selected as the downtown areas of Nanjing where the shared bikes are put into use, mainly including Gulou District, Jianye District, Xuanwu District, Qinhuai District and Yuhuatai District in the central urban area, as well as Qixia District, Pukou District and Jiangning District, which have developed rapidly in recent years. In this study, the data of Mobike APP system is captured by using Python crawler software programming. The bike data information collected include bike ID, bike type, longitude and latitude information of bike location, and the time of bike data collection. During the data collection period, the weather is sunny or cloudy, respectively on October 31st, 2017, November 2nd and November 4th, 2017, with the collection duration of 24 hours and the time interval of 1 hour. In the later period, due to the need of block level research, the bike data collection is carried out on the central street of Gulou District on December 22 during the whole day, with a time interval of 30 minutes. In this study, the line tracking tool based on GIS software is utilized to simulate and analyze the path of its riding OD data, and to study its riding rules such as moving distance and spatial distribution. The results show that there are four core areas of the use of shared bikes in Nanjing, namely, the center of Gulou, Jiangning Higher Education Mega Center, Pukou Higher Education Mega Center and Maqun Science Park. Through the field investigation and analysis, the common characteristics of these four blocks are centralized distribution of universities and high-tech enterprises, a large number of floating population, and a large number of young people with great demand for short-distance travel. In addition, Xianlin University Town, the surrounding area of Olympic Sports Center and Pukou riverside area have great development potential for the use of shared bikes, and are forming the core area of bike use. The latter two plots are large-scale residential function concentrated plots. Through the riding track OD analysis, it can be seen that many users have broken through the original habitual use area and distance limit, crossing several blocks, not only transfer, short journeys and other behaviors. All functional areas in the city are not necessarily independent and closed for bikes, and citizens need to carry out long-distance and large-scale riding. In addition, compared with rail transit hubs and bus stations, it is found that the high-density area of riding track is not limited to the vicinity of the stations, although the areas where shared bikes are put into use are mainly near the stations. Combined with the riding OD map, it can be seen that stations and places of residence in parts of Gulou District and Jiangning Higher Education Mega Center are no longer the only starting and ending points for riding. The high-density areas of riding tracks are distributed in the living areas. Riding has become an important means of transportation for short-distance life-style travel in the region. Thus it can be seen that a relatively independent life-style short-distance riding space system will be formed in various urban groups in the future. Through the research on the west side of Xuanwu Lake Park in Gulou District, the core plot of shared bike use in Nanjing City, it is found that the average riding distance in this area is 768 m, the median value is 541 m, and the maximum riding distance in this area is 8.2 km. The short-distance riding space within 2 km is mainly distributed in the area of the people flow distribution center at all levels, and the roads of all grades can be used as riding space. The medium- and long-distance riding more than 2 km mostly chooses the city’s main roads, and the riding space is associated with the city’s various transportation hubs, most of which are commutes. In view of the above conclusions, this paper puts forward the corresponding suggestions for the optimization design of riding space in Nanjing: Firstly, to set up riding space system in different regions and at different levels; Secondly, to set up bike lanes between the central groups of the city; thirdly, to enhance the comfort of riding space in streets and lanes, and relieve the pressure of urban riding demand.