Japanese rail transit hub station has gradually changed from being high-intensity to ultra-high intensity with the guidance from the urban regeneration policy. This change aims to promote compact urban construction and optimize public transportation system for sustainable urban development. Along with demand for city expansion and city intensification, land utilization around hub stations gradually change from incremental development mode to redevelopment mode that tends to stock. This study summarizes the implementation of typical ultra-high-intensity redevelopment projects, which are classified into three categories. This study also provides a comparative study of the design methods and strategies of these cases from the perspective of developing intensity, functional layout, pedestrian system, and landscape space. Finally, this study provides relevant references and suggestions for the ultra-high-intensity redevelopment of the core area of hub stations by analyzing the aforementioned factors.
Direct forecasting method for Urban Rail Transit (URT) ridership at the station level is not able to reflect nonlinear relationship between ridership and its predictors. Also, population is inappropriately expressed in this method since it is not uniformly distributed by area. In this paper, a new variable, population per distance band, is considered and a back propagation neural network (BPNN) model which can reflect nonlinear relationship between ridership and its predictors is proposed to forecast ridership. Key predictors are obtained through partial correlation analysis. The performance of the proposed model is compared with three other benchmark models, which are linear model with population per distance band, BPNN model with total population, and linear model with total population, using four measures of effectiveness (MOEs), maximum relative error (MRE), smallest relative error (SRE), average relative error (ARE), and mean square root of relative error (MSRRE). Also, another model for contribution rate of population per distance band to ridership is formulated based on the BPNN model with nonpopulation variables fixed. Case studies with Japanese data show that BPNN model with population per distance band outperforms other three models and the contribution rate of population within special distance band to ridership calculated through the contribution rate model is 70%~92.9% close to actual statistical value. The result confirms the effectiveness of models proposed in this paper.
This study aims to evaluate the landscape performance of rural microlandscapes in highly urbanized areas and propose optimization strategies based on the evaluation results. As a sustainable promotion mode, microlandscapes can effectively improve the damage caused by the development of rugged urbanization to the living environment. To improve the rural living environment, some achievements have been made in the construction of microlandscapes in the highly urbanized rural areas of southeast coastal areas, represented by Fujian Province, but there are still problems such as low utilization rate and difficult maintenance. As a qualitative and quantitative weighting method, the combination weighting method is widely used in the construction of evaluation models of safety engineering, environmental management, and other disciplines. This study constructed a landscape performance evaluation system based on the American landscape performance series and combined it with performance evaluation methods in other related fields to establish a landscape performance evaluation system suitable for rural microlandscapes in highly urbanized areas. Taking social benefits as an example, five main factors affecting social benefits are highlighted: comfort and health; safety and accessibility; sociability and service; aesthetics and education; and culture and inheritance. Each factor contains different sub-criteria to identify specific problems. Field observation, questionnaire survey, and interview records of 25 microlandscape projects in Yinglin Town, Jinjiang City were conducted. The combination weight calculation based on the AHP-entropy weight method and the comprehensive benefit ranking calculation based on the TOPSIS method is carried out. It was found that stress relief and the number of visitors were the main factors affecting the social benefits of microlandscape performance, and the top-ranked projects also had such characteristics. The seasonal phase and color richness had the least effect on social benefits. Therefore, the microlandscape should improve the healing effect of the project on users as much as possible in the design stage, so that users can better relax through the microlandscape. In addition, strategies such as space selection and path optimization should be adopted to improve the utilization rate of the microlandscape as much as possible, and the fairness of the use of vulnerable groups should be fully considered.
This paper discusses the evaluation system based on the Combined Weights-Technique for Order Preference by Similarity to Ideal Solution(CW-TOPSIS) method and evaluates and optimizes the landscape performance of rural microlandscapes in highly urbanized areas by taking rural areas in Jinjiang, Fujian Province, as an example. As a quantitative study on microlandscapes in rural areas, this study constructed evaluation indicators based on the U.S. landscape performance series and combined them with performance evaluation methods in other related fields to establish a landscape performance evaluation system suitable for rural microlandscapes in highly urbanized areas. Taking social benefit as an example, 25 microlandscape projects in Yinglin town, Jinjiang city, comprehensive rankings were based on the AHP-Entropy method and TOPSIS method. In addition, this paper also analyzes the qualitative results reflected in the quantitative data and proposes appropriate optimization schemes and improvement measures to further improve the living environment in rural areas.
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