scholarly journals The Heterogeneous Impact of High-Speed Railway on Urban Expansion in China

2021 ◽  
Vol 13 (23) ◽  
pp. 4914
Author(s):  
Dan He ◽  
Zixuan Chen ◽  
Jing Zhou ◽  
Ting Yang ◽  
Linlin Lu
Keyword(s):  
Significant Role ◽  
Vegetation Cover ◽  
High Speed ◽  
Urban Expansion ◽  
Urban Land ◽  
Cultivated Land ◽  
High Speed Railway ◽  
Barren Land ◽  
Multi Stage ◽  
The Impact

High-speed railway (HSR) promote the efficient flow of the population and materials between cities and have profoundly affected urban economic development in China. However, there is currently limited research about how HSR influences urban expansion, especially related to the variable impacts on different urban agglomerations, different size cities, and the conversion of non-urban land to urban land. In this study, from two levels of regional heterogeneity and type heterogeneity, a multi-stage difference-in-differences (multi-stage DID) model and land use remote sensing data are used to investigate these research areas. The main conclusions are as follows: (1) The first opening of HSR had a more significant role in promoting urban expansion than HSR frequency, but several years after opening, HSR no longer promotes urban expansion. (2) The opening of HSR only played a significant role in promoting urban expansion in Beijing–Tianjin–Hebei. HSR frequency had a significant role in promoting urban expansion in the Yangtze River Delta. (3) The opening of HSR had no significant impact on urban expansion for different size cities, and HSR frequency only had a significant negative impact on urban expansion of small cities. (4) The first opening of HSR led to urban expansion dominated by the occupation of cultivated land. Cities in Xinjiang and Inner Mongolia mainly converted barren land and vegetation cover to urban land after the first opening of HSR. In northeast China, the first opening of HSR made the conversion of vegetation cover and cultivated land to urban land roughly equivalent in size. The results of this study are helpful to understand the impact of the first opening of HSR and the scale of conversion of different types of non-urban land into urban land on urban expansion. In the era of HSR, these findings provide a valuable reference for regional planning and preventing the disorderly expansion of cities.

scholarly journals Spatiotemporal Evolution of Urban Expansion Using Landsat Time Series Data and Assessment of Its Influences on Forests

2020 ◽  
Vol 9 (2) ◽  
pp. 64 ◽  
Author(s):  
Meng Zhang ◽  
Huaqiang Du ◽  
Fangjie Mao ◽  
Guomo Zhou ◽  
Xuejian Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Decision Tree ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
Series Data ◽  
Cultivated Land ◽  
The Impact ◽  
C5.0 Decision Tree

Analysis of urban land use dynamics is essential for assessing ecosystem functionalities and climate change impacts. The focus of this study is on monitoring the characteristics of urban expansion in Hang-Jia-Hu and evaluating its influences on forests by applying 30-m multispectral Landsat data and a machine learning algorithm. Firstly, remote sensed images were preprocessed with radiation calibration, atmospheric correction and topographic correction. Then, the C5.0 decision tree was used to establish classification trees and then applied to make land use maps. Finally, spatiotemporal changes were analyzed through dynamic degree and land use transfer matrix. In addition, average land use transfer probability matrix (ATPM) was utilized for the prediction of land use area in the next 20 years. The results show that: (1) C5.0 decision tree performed with precise accuracy in land use classification, with an average total accuracy and kappa coefficient of more than 90.04% and 0.87. (2) During the last 20 years, land use in Hang-Jia-Hu has changed extensively. Urban area expanded from 5.84% in 1995 to 21.32% in 2015, which has brought about enormous impacts on cultivated land, with 198,854 hectares becoming urban, followed by forests with 19,823 hectares. (3) Land use area prediction based on the ATPM revealed that urbanization will continue to expand at the expense of cultivated land, but the impact on the forests will be greater than the past two decades. Rationality of urban land structure distribution is important for economic and social development. Therefore, remotely sensed technology combined with machine learning algorithms is of great significance to the dynamic detection of resources in the process of urbanization.

scholarly journals Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 303
Author(s):  
Xinhai Lu ◽  
Yifeng Tang ◽  
Shangan Ke
Keyword(s):  
Economic Growth ◽  
Land Use ◽  
High Speed ◽  
Urban Land ◽  
Urban Land Use ◽  
Western China ◽  
High Speed Rail ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
The Impact

The construction and operation of high-speed rail (HSR) has become an important policy for China to achieve efficiency and fairness and promote high-quality economic growth. HSR promotes the flow of production factors such as labor and capital and affects economic growth, and may further affect urban land use efficiency (ULUE). To explore the impact of HSR on ULUE, this paper uses panel data of 284 cities in China from 2005 to 2018, and constructs Propensity Score Matching-Differences in Differences model to evaluate the effect of HSR on ULUE. The result of entire China demonstrates that the HSR could significantly improves the ULUE. Meanwhile, this paper also considers the heterogeneity of results caused by geographic location, urban levels and scales. It demonstrates that the HSR has a significantly positive effect on ULUE of Eastern, Central China, and large-sized cities. However, in Western China, in medium-sized, and small-sized cities, the impact of HSR on ULUE is not significant. This paper concludes that construction and operation of HSR should be linked to urban development planning and land use planning. Meanwhile, the cities with different geographical locations and scales should take advantage of HSR to improve ULUE and promote urban coordinated development.

scholarly journals Does the Opening of High-Speed Railway Lines Reduce the Carbon Intensity of China’s Resource-Based Cities?

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4648
Author(s):  
Zhipeng Tang ◽  
Ziao Mei ◽  
Jialing Zou
Keyword(s):  
High Speed ◽  
National Average ◽  
Carbon Intensity ◽  
Time Varying ◽  
Low Carbon ◽  
High Speed Railway ◽  
Different Types ◽  
Endogenous Selection ◽  
Mode Of Development ◽  
The Impact

The carbon intensity of China’s resource-based cities (RBCs) is much higher than the national average due to their relatively intensive mode of development. Low carbon transformation of RBCs is an important way to achieve the goal of reaching the carbon emissions peak in 2030. Based on the panel data from 116 RBCs in China from 2003 to 2018, this study takes the opening of high-speed railway (HSR) lines as a quasi-experiment, using a time-varying difference-in-difference (DID) model to empirically evaluate the impact of an HSR line on reducing the carbon intensity of RBCs. The results show that the opening of an HSR line can reduce the carbon intensity of RBCs, and this was still true after considering the possibility of problems with endogenous selection bias and after applying the relevant robustness tests. The opening of an HSR line is found to have a significant reducing effect on the carbon intensity of different types of RBC, and the decline in the carbon intensity of coal-based cities is found to be the greatest. Promoting migration of RBCs with HSR lines is found to be an effective intermediary way of reducing their carbon intensity.

Impacts of high-speed railway on the industrial pollution emissions in China

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2713-2735 ◽  
Author(s):  
Xiaomin Fan ◽  
Yingzhi Xu ◽  
Yongqing Nan ◽  
Baoli Li ◽  
Haiya Cai
Keyword(s):  
Environmental Effects ◽  
Industrial Pollution ◽  
High Speed ◽  
Assessment Method ◽  
Economic Effects ◽  
High Speed Railway ◽  
Central Cities ◽  
Content Type ◽  
Pollution Emissions ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of high-speed railway (HSR) on industrial pollution emissions using the data for 285 prefecture-level cities in China from 2004 to 2016. Design/methodology/approach The research method used in this paper is the multi-period difference-in-differences (DID) model, which is an effective policy effect assessment method. To further address the issue of endogeneity, the DID integrated with the propensity score matching (PSM-DID) approach is employed to eliminate the potential self-selection bias. Findings The results show that the HSR has significantly reduced industrial pollution emissions, which is validated by several robustness tests. Compared with peripheral cities, HSR exerts a greater impact on industrial pollution emissions in central cities. In addition, the mechanism test reveals that the optimised allocation of inter-city industries is an important channel for HSR to mitigate industrial pollution emissions, and this is closely related to the location of HSR stations. Originality/value Previous studies have paid more attention to evaluating the economic effects of HSR, however, most of these studies overlook its environmental effects. Consequently, the impact of HSR on industrial pollution emissions is led by using multi-period DID models in this paper, in which the environmental effects are measured. The results of this paper can provide a reference for the pollution reduction policies and also the coordinated development of economic growth and environmental quality.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

2021 ◽  
pp. 095440972110421
Author(s):  
Minling Feng ◽  
Chaoxian Wu ◽  
Shaofeng Lu ◽  
Yihui Wang
Keyword(s):  
High Speed ◽  
Applied Force ◽  
Mixed Integer ◽  
High Speed Railway ◽  
Train Operation ◽  
Train Speed ◽  
Automatic Train Operation ◽  
The Impact ◽  
Trajectory Optimisation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.

scholarly journals Examining partial proportional odds model in analyzing severity of high-speed railway accident

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Wang ◽  
Yinghan Wang ◽  
Yichuan Peng ◽  
Jian John Lu
Keyword(s):  
High Speed ◽  
Proportional Odds Model ◽  
Impact Factors ◽  
Proportional Odds ◽  
High Speed Railway ◽  
Severity Level ◽  
Content Type ◽  
Factors Affecting ◽  
Partial Proportional Odds Model ◽  
The Impact

Purpose The operation safety of the high-speed railway has been widely concerned. Due to the joint influence of the environment, equipment, personnel and other factors, accidents are inevitable in the operation process. However, few studies focused on identifying contributing factors affecting the severity of high-speed railway accidents because of the difficulty in obtaining field data. This study aims to investigate the impact factors affecting the severity of the general high-speed railway. Design/methodology/approach A total of 14 potential factors were examined from 475 data. The severity level is categorized into four levels by delay time and the number of subsequent trains that are affected by the accident. The partial proportional odds model was constructed to relax the constraint of the parallel line assumption. Findings The results show that 10 factors are found to significantly affect accident severity. Moreover, the factors including automation train protection (ATP) system fault, platform screen door and train door fault, traction converter fault and railway clearance intrusion by objects have an effect on reducing the severity level. On the contrary, the accidents caused by objects hanging on the catenary, pantograph fault, passenger misconducting or sudden illness, personnel intrusion of railway clearance, driving on heavy rain or snow and train collision against objects tend to be more severe. Originality/value The research results are very useful for mitigating the consequences of high-speed rail accidents.

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