Using Tencent location data in three times: working days, rest days, and holidays, we studied the temporal variation characteristics of the activity space in Nanchang City. First, the activity spatial cohesion structure of the study area is analyzed by the nuclear density analysis method. Then, the specific urban activity area is divided and analyzed by the method of heat peak point extraction and Tyson polygon.The research found that: 1)The area of ??high-frequency activity area on working day is obviously higher than that of rest day and holiday. The larger the thermal value of the classification interval is, the smaller the number of pixels is. 2)There are four kinds of condensed structures of ??urban activity space in the study area, namely “mononuclear structure”, “dual-core structure”, “trinuclear structure” and “aggregate structure”. Each structure has unique morphological characteristics and representativeness. 3)Divide the study area into six kinds of activity space function zoning: comprehensive activity area, residential area, learning activity area, leisure and entertainment area, transportation hub area, employment area, and different activity patterns correspond to their respective activities frequency changes. Using the method of superposition analysis, the core area and the marginal area of ??the six functional modes are divided. 4)The activity function areas in the study area are unevenly distributed. Most of the activity types are residential activity areas and learning activity areas. 5)According to the distribution characteristics of the activity space structure and the distribution characteristics of the activity area discovered by big data mining, combined with the urban development plan of Nanchang City, the current activity space structure of Nanchang City was evaluated, and based on the above analysis, we made some recommendations on improving the planning of the city.
