Urban Public Resources Research Articles

Improving access to urban parks through public transit optimization

This study establishes an evaluation and optimization framework for the public transit network based on social network analysis and a greedy algorithm, aiming to explore a quantitative approach to improving access to urban parks through public transit optimization. Social network analysis and the ArcGIS platform are used to build a public transit network model within Nanjing Old City and analyze its overall network structure characteristics. The study also focuses on a method to improve the convenience of reaching regional and city-level parks by public transit by increasing access and connecting points accordingly. A greedy algorithm is introduced to generate an optimized solution for improving public transit accessibility to regional and city-level parks, consequently enhancing their utilization. The major findings include: (1) The greedy algorithm effectively enhances the performance of the public transit network, but its benefits gradually diminish as more stations are added. (2) Strategically adding stations enhances the performance of most public transit access points, creating efficient pathways for other stations to directly reach these access points and enter regional and city-level parks. (3) The optimized public transit network model offers guidance for the planning and layout of regional and city-level parks. The site selection for new parks should prioritize establishing connections with the “hubs” in the public transit network. The proposed optimization of the public transit network in this study is specific to a single type of urban park, but subsequent research could be conducted to extend the optimization of public transit accessibility around more urban public resources.

A Deep Reinforcement Learning Model for a Two-Layer Scheduling Policy in Urban Public Resources

A Deep Reinforcement Learning Model for a Two-Layer Scheduling Policy in Urban Public Resources

Research on the Equity of Urban Green Park Space Layout Based on Ga2SFCA Optimization Method—Taking the Core Area of Beijing as an Example

(1) Background: The issue of equity in the layout of urban green park spaces is an essential dimension of urban public resource allocation. (2) Objective: To analyze the equity of the distribution of parkland in the core area of Beijing from a quantitative and spatial perspective. By measuring both vehicular and pedestrian transport modes, the study identifies areas with low levels of green space provision and provides strategies for optimization. It is hoped that this study can provide a basis for future green space construction in the core area of Beijing. (3) Methods: In this paper, the Gauss Two-step Floating Catchment Area Method (Ga2SFCA) is used to study the green park space layout in the core area of Beijing. The two modes of 30min-walk and 10min-car-journey were used to measure the fair values of the residential unit scale, the street district scale, and the overall scale, respectively. (4) Results: The study results show that the fair values based on the 30-min walk and the 10-min car journey differ significantly. For the 30-min walk-based travel mode, the proportion of fair (Class IV) and fairer (Class V) areas is approximately 20%, while for the 10 min car-based travel mode, the corresponding class is over 90%. (5) Conclusions: The overall equity of urban parkland in Beijing core area is better for car-based travel modes, while for walking modes, the supply is still insufficient, and the distribution of parkland is polarized.

Does High Spatial Density Imply High Population Density? Spatial Mechanism of Population Density Distribution Based on Population–Space Imbalance

Numerous studies have suggested a positive correlation between spatial and population densities. However, few have systematically conducted quantitative analysis and deciphered the detailed correlation in block scale. Here, we construct a population–space correlation algorithm to quantify and compare the correlation between mobile phone signalling data and vector spatial data and identify blocks with uneven population density. We analyse the influences of various urban spatial characteristics on population density and the distribution characteristics of the identified city blocks. Changzhou City, China, was selected as the study case. The results indicate that (1) population density distribution is unbalanced only when spatial density exceeds a critical value, reflecting the level and sphere of influence of blocks with varying spatial densities; (2) low population density distribution is concentrated in the zonal space, along the boundary between primary and secondary urban centres; (3) spatial characteristics affecting population density distribution vary with the type of block, and the green landscape’s attractiveness is reduced. Our study provides a novel perspective on quantifying the link between urban form and population distribution. It can help decision-makers and planners in accurately recommending urban intervention in population density distribution by adjusting the spatial morphology and promoting rational use of urban public resources.

Matching under school and home bundling

The consumption of urban public resources—for example public schooling—is typically geographically bundled with home locations. When households differ in valuations of housing and in student abilities, the positive and assortative matches between school qualities and student abilities sometimes fail to be achieved by the housing market equilibrium, resulting in a misallocation in education. We propose a mechanism that improves school matches by making the property tax imposed on the high-quality house–school bundle deductible conditional on school performance. Conditional deductibility induces a transaction of houses that improves school matches at the cost of a distortion in housing consumption, and we show that: (1) a small and positive tax is strictly welfare-improving; (2) such tax is Pigouvian corrective in terms of alleviating budget constraint; and (3) a lower degree of inter-jurisdictional differentiation in housing enhances the welfare effects of tax.

How does air quality affect the willingness of graduate students to stay? Evidence from Beijing city, China

Since the reforming and opening up started in the late 1970s, China’s economy boomed with the urbanization rate increasing consistently, in which urbanization has been playing a crucial role undoubtedly. As China’s political and cultural center, Beijing city has gained dramatic development, which to a great extent is attributed to the great efforts of various kinds of talents, and college graduate students are a momentous component. However, since 2011, partly due to increasingly serious air pollution, college graduate students in Beijing have attached greater importance to air quality, and the proportion of staying in Beijing has been decreasing year by year. This study focuses on the impact of air quality on the willingness of college graduate students to stay in Beijing. Using the first-hand data of 522 valid samples collected by questionnaire survey, a carefully designed structural equation model with 5 latent variables and 25 effective observed variables is employed to conduct the empirical study. The empirical results indicate that subjective acceptance, urban public resources, family status and career planning have significant positive influences on the willingness of college students to stay in Beijing. Among them, urban public resources play the most important role. In contrast, living cost has a negative yet insignificant impact.

School Inequalities and Urban Welfare: Going beyond Socioeconomic Status with Data Science

The fast-changing Brazilian urban reality segregates people in socio-spatial terms and distributes urban public resources unfairly, threatening student’s access to the structure of educational opportunities and causing school inequalities. Factors such as the existence of public lighting, open sewage and garbage accumulated around the homes, as well as electricity and water supply, sanitation, and the number of residents per bathroom, are discussed as predictors of school achievements as measured using their average IDEB (Basic Education Development Index) outcomes using Data Science methods. It was found that the resident/bathroom density and the household wall material indicators in a municipality have a higher correlation with its average school achievements than the average students’ socioeconomic status, relations that are clearly illustrated through bivariate choropleth maps across all the 5,388 Brazilian municipalities with available valid data. These results are compatible with research that reveals the presence of a “neighbourhood effect,” such that the distributional inequalities in infrastructure access and ultimately the notion of urban welfare reduces educational opportunities and engenders social inequalities, what is incompatible with the ideal of a sustainable society.

Land-Acquisition and Resettlement (LAR) Conflicts: A Perspective of Spatial Injustice of Urban Public Resources Allocation

Land acquisition and resettlement (LAR) is an important step in urban development. As one of the ‘externalities of development’, LAR conflicts have affected social stability and development in rural areas of China. With social conflict research shifting from value identity to resource allocation, few studies have examined the relationship between the spatial injustice of urban public resources and LAR conflict. To mitigate this research gap and formulate effective policies, this study aims to reinterpret the obstacles of LAR conflicts from the perspective of the spatial injustice of urban public facilities allocation in Hangzhou City by examining 195 administrative litigation cases. Spatial accessibility was used for estimating the spatial justice of urban public resources allocation. A classification and regression tree (CART) model was applied to identify the advantage and disadvantage factors behind LAR conflict, and explored the logical and structural relationships among these factors. Results showed that a spatial mismatch between the spatial behavior preferences of human activity and the spatial injustice of urban public resources allocation had significantly accelerated LAR conflicts. When the spatial behavior preferences of human activity and spatial distribution of urban public resources correspond to each other pre- and after LAR, basic rights to social space are safeguarded and various groups can equitably share spatial resources. There are no conflicts. Conversely, respondents expressed a high level of dissatisfaction in comparison to their pre-LAR conditions, and LAR conflict undeniably occurs. This approach also proposes some good LAR policies by regulating the spatial injustice of urban public resources allocation associated with LAR with the aim of long-term urban sustainable development for Hangzhou.

Network Voronoi Diagram Heuristic-based Particle Swarm Continuous Spatial Optimization Modeling

Spatial optimization modeling for multi facilities in urbanized area is a practical and key technique,and it can provide balance configuration optimization and spatial decision support for urban public resource. A method of particle swarm spatial optimization modeling for multi facilities location based on network Voronoi diagram heuristic is proposed in this paper, in which we presented respectively some p-median location models and maximal covering location models by using ordinary Voronoi diagram heuristic and network Voronoi diagram heuristic. Those models can quantitatively extract the demands coved by the function and service of facilities through the Voronoi diagrams, and inspire spatial optimization to maximize the coverage for distributed demands by minimizing overlapped coverage. The proposed p-median location model considers the factor of demand attenuation with path distance, and the proposed maximal covering model takes it into account that facility's service provides full coverage for the demands within maximal coverage radius and partial attenuation coverage for the demands without maximal coverage radius. The genetic evolution mechanism and the dynamic neighborhood structure of particles simulated by ordinary Voronoi diagram are integrated in the particle swarm spatial optimization to improve global search and optimization performance of the algorithm. Through the research of spatial optimization configuration experiments for multi facilities in experimental city, the proposed method has been verified to be the effective and practical, it can be applied for the spatial location optimization decision in urbanized area.