Accurate evaluation of land value-added benefit brought by urban rail transit (URT) is critical for project investment decision making and value capture strategy development. Early studies have focused on the value impact strength under the assumption of the same impact range for all stations. However, the value impact range at different stations may vary owing to different accessibilities. Therefore, the present study releases this assumption and incorporates the changed impact range into the land value-added analysis. It presents a method to determine the range of land value-added impact and sample selection using the generalized transportation cost model, then spatial econometric models are further developed to estimate the impact strength. On the basis of these models, the entire value-added benefit brought by URT is evaluated. A case study of the Changsha Metro Line 2 in China is discussed to demonstrate the procedure, model, and analysis of spatial impact. The empirical analysis shows a dumbbell-shaped impact on the land value-added benefit along the transit line with a distance-dependent pattern at each station. In addition, the land value-added benefit from Changsha Metro Line 2 reached 12.099 billion USD. Lastly, two main value-added benefit capture modes are discussed, namely, land integration development and special land tax.
Deep Learning Architecture for Short-Term Passenger Flow Forecasting in Urban Rail Transit
