The Nonlinear Impact and Spatial Characteristics of TOD Built Environment on Land Value:A Case Study of Beijing
The improvement of land value brought by urban rail transit can be attributed to three aspects:the premium of adjacent transit stations,the premium of accessibility improvement,and the construction premium around the station.However,the research on the impact of the latter two factors on the improve-ment of lane value remains insufficient.In response,integrating multi-source urban big data,this paper pro-poses the"5D"indicator system and its calculation methodology for the Transit-Oriented Development(TOD)built environment of urban rail transit.Relaxing the assumption of linear relationship between house price and its influencing factors in the exiting research,the paper employs a nonlinear model for fea-ture pricing based on the XGBoost machine learning algorithm and the local interpretation method SHAP to analyze the nonlinear impact of TOD built environment on the promotion of land value and its spatial distribution characteristics.Case studies in Beijing demonstrate that the TOD built environment around rail stations significantly influence the land value,accounting for 64.30%,and the relative importance of tran-sit accessibility holds is 17.66%,which is more important than station proximity.The impact of TOD built environment on land value has obvious nonlinear relationship and threshold effect.The spatial distribution characteristics of TOD built environment indicate that station land development strategies should be tai-lored to specific regions,according to local conditions,the stations in the peripheral areas of cities should pay attention to the accumulation of resource,and the stations in the central urban area should focus on the improvement of travel quality and environmental quality.
urban rail transitbuilt environmentland value upliftaccessibilitymachine learningthresh-old effectBeijing
NETL
NSTL
万方数据
