Prediction of land use around urban metro stations using the CA-Markov model

Abstract

Analyzing how rail transit stations affect the land use changes around them in space and time is important for forecasting the future interaction between new stations and land use and for adjusting and optimizing planning schemes. Based on the design concept of station-city integration, this paper uses Zhongshanba Station of Guangzhou Metro as a case study. It examines the land use evolution around the station and predicts the future land use changes around the double-track transfer station of Line 5 and Line 11, using the POI kernel density and the passenger flow heat map of the existing station in the old city. The results show that the POI and passenger flow heat map are innovative driving variables that can increase the simulation accuracy of the CA-Markov model to 91.86%. The prediction results also show that public management-service land and residential land will increase while industrial land will decrease. Although garden land will expand, the surrounding ecological area is still inadequate. Finally, this paper provides some strategies for optimizing subway stations and planning urban land use.

Keywords

• ca-markov model
• urban space
• rail transit
• interactive influence
• temporal and spatial evolution