A financing mode of Urban Rail transit based on land value capture: A case study in Wuhan City

2017 ◽  
Vol 57 ◽  
pp. 59-67 ◽  
Author(s):  
Jun Sun ◽  
Tian Chen ◽  
Zuchen Cheng ◽  
Cynthia C. Wang ◽  
Xin Ning
2021 ◽  
Vol 14 (1) ◽  
pp. 563-582
Author(s):  
Wenbin Tang ◽  
Qingbin Cui ◽  
Feilian Zhang ◽  
Hongyan Yan

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.


2021 ◽  
Vol 12 (7) ◽  
pp. 1448
Author(s):  
Mohammed Ali Berawi ◽  
Nyoman Suwartha ◽  
Agatha Vania Salim ◽  
Gunawan Saroji ◽  
Mustika Sari

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shiping Wen ◽  
Jiangang Shi ◽  
Wei Zhang

Urban rail transit can improve a city’s accessibility. However, high construction and operation costs restrict the development of urban rail transit. Value capture recoups the additional value that the investments of urban rail transit confer to local land and is considered to be an effective measure to alleviate this financial problem. Understanding the land value uplift effects of urban rail transit is essential for understanding value capture. This study applied a Space-P model of urban rail transit network based on complex network theory and demonstrated the influence of urban rail transit network characteristics on residential and commercial land prices. The model was tested with eight metropolises in China, using the 2003 to 2022 timeframe as the context. The results showed a significant positive correlation between the number of nodes and the land prices, the average clustering coefficient was highly positively correlated with the land prices, and there was a significant negative correlation between the average path length and the land prices. This study provides theoretical support for value capture, is beneficial for urban rail transit planning, and supports improvements in the development quality of urban rail transit networks.


2019 ◽  
Vol 11 (22) ◽  
pp. 6322 ◽  
Author(s):  
Annunziata Esposito Amideo ◽  
Stefano Starita ◽  
Maria Paola Scaparra

Urban rail transit systems are highly prone to disruptions of various nature (e.g., accidental, environmental, man-made). Railway networks are deemed as critical infrastructures given that a service interruption can prompt adverse consequences on entire communities and lead to potential far-reaching effects. Hence, the identification of optimal strategies to mitigate the negative impact of disruptive events is paramount to increase railway systems’ resilience. In this paper, we investigate several protection strategies deriving from the application of either single asset vulnerability metrics or systemic optimization models. The contribution of this paper is threefold. Firstly, a single asset metric combining connectivity, path length and flow is defined, namely the Weighted Node Importance Evaluation Index (WI). Secondly, a novel bi-level multi-criteria optimisation model, called the Railway Fortification Problem (RFP), is introduced. RFP identifies protection strategies based on stations connectivity, path length, or travel demand, considered as either individual or combined objectives. Finally, two different protection strategy approaches are applied to a Central London Underground case study: a sequential approach based on single-asset metrics and an integrated approach based on RFP. Results indicate that the integrated approach outperforms the sequential approach and identifies more robust protection plans with respect to different vulnerability criteria.


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