Exploring the Equity and Spatial Evidence of Educational Facilities in Hangzhou, China

Wu, Yizhou; Zheng, Xiaohong; Sheng, Li; You, Heyuan

doi:10.1007/s11205-020-02417-5

Cited by 19 publications

(19 citation statements)

References 31 publications

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“…These studies have shown that first, the rapid growth of the urban population and the greatly increased need for land use for urban construction have created a demand for infrastructure that far exceeds the service capacity of the existing service facilities [17,18]. The lack of space in the urban center and the shortage of educational facilities in the suburbs often leads to the uneven distribution of schools in the core and peripheral areas of a city [19], thus exacerbating the inequities in educational resource distribution. Liu et al [20] used quantitative methods, such as spatial interpolation and cluster analysis, based on resource data such as elementary school building conditions, faculty, and the total amount of educational resources in Dalian City, and found that its elementary school resources exhibited a "center edge" circled layout; that is, the central urban areas were dominated by high-level secondary schools while the peripheral county cities were dominated by elementary schools, exhibiting a circled "decay" pattern.…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data

Zhang

Luan

Tian

et al. 2021

Land

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Basic education is about improving the quality of life of a country’s population and promote social cohesions, and it is also an important factor in shaping a country and region’s person-to-person relationship. This study analyzes the spatial morphological patterns, aggregation characteristics, and distribution inequality among kindergarten, elementary, and junior high schools within districts in Shanghai, using point of interest data, kernel density estimation, Ripley’s K-function, location quotient, and grid analysis to investigate the effect on the distribution of schools using construction land growth data. The findings were as follows. (1) There was little difference in the spatial distribution characteristics of the three school types. They all exhibited the spatial distribution characteristics of core area clustering and the coexistence of multiple circadian layers, in which both the agglomeration size and the aggregation intensity showed the order of kindergarten > elementary school > junior high schools. The spatial distribution characteristics of the three types of schools are highly positively correlated with the population distribution. (2) Spatially, low-level schools were adjacent to high-level schools, and the structure of the three school types showed an uneven distribution overall. The aggregation characteristics of the seven inner districts within Shanghai were relatively balanced, while Pudong District showed the phenomenon of being “high in the southeast and low in the northeast,” and the suburban areas showed an uneven distribution of core district aggregation overall. (3) The longer the construction land growth cycle, the greater the density of school points, and the more consistent the distribution of school points with the direction of construction land expansion.

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Section: Introductionmentioning

confidence: 99%

Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data

Zhang

Luan

Tian

et al. 2021

Land

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“…In addition, in view of spatial characteristics of educational resources, researchers conduct a series of studies based on GIS technology [12][13][14][15][16]. Zhang [12] constructsequilibrium analysis indicators for basic education based on educational opportunities, resource allocation, and educational quality and derives school distance and accessibility through GIS overlay analysis and network analysis.…”

Section: Introductionmentioning

confidence: 99%

“…RG Taylor et al [13]adopt GIS spatial analysis technology to study school distribution and layout adjustment plan in Johnston County, North Carolina. Wu et al [14]study distribution and spatial pattern of educational facilities in Hangzhou, and evaluate fairness of educational resources. Guo et al investigates distribution characteristics and layout efficiency of educational resources in towns/streets, finding significant spatial distribution clustering characteristics [15].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Teacher Allocation in Regional Compulsory Education Industry Based on K-means clustering and GIS Spatial analysis: A Case Study of teacher-student ratio

Liu¹

2021

converter

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The allocation of teacher resources can reflect the situation of regional education disequilibrium. It is an important research content to effectively evaluate the differences of regional teacher resource allocation and reveal the characteristics of spatial location. Take teacher-student ratio of compulsory education of five adjacent cities in China as an example, this paper focus on difference analysis and balanced evaluation of teacher resource allocation. Combined with geographical location, Differentiation coefficient, K-means clustering and GIS hot spot analysis methods are used to carry out the classification of teacher resource allocation and the spatial aggregation model of cold and hot spots. The results show that: there is an imbalance between different cities, as well as between districts and counties in same city.The results of K-means clustering and GIS hot spot analysis also show that regional teacher resource allocation has the characteristics of numerical classification and spatial aggregation. The k-means algorithm can aggregate the teacher-student ratio of 30 districts into three categories, revealing the category characteristics of teacher allocation. The results of GIS hotspots show that there are high value aggregation and low value aggregation in teacher configuration. The methods and research results of this paperprovide newresearch ideas for resource balance evaluation and spatial pattern analysis of education industry.

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“…Even so, high density information and material flow continue to gather in the central area of a city, connected to the surrounding decentralized structure through urban facilities 3 , 29 . Given the massive migration of rural population to urban areas, built-up areas continue to expand to the suburbs 30 , resulting in an aggravation of the living gap between urban and rural residents 15 , 27 , 31 . When dividing the urban–rural boundary, the majority of related studies have adopted the density grade of impervious layer, the boundary of night lights, the concentration area of population density or administrative boundary of a city to explore the facility pattern, service distribution 2 , 11 , and landscape pattern on the urban–rural gradient 2 , 30 , 32 , 33 .…”

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confidence: 99%

“…Interestingly, urban residents have different demand preferences for supporting facilities at different levels or sizes 19 , either focusing on distance factors (e.g., clinics and pharmacies) or preferring service quality 39 , 40 (e.g., hospitals). However, in the current research on the equality of education or medical facilities, more people tend to quantitatively evaluate the spatial differences of inequality of a certain type of facilities 15 , 22 , often disregarding the fact that even facilities with similar functions have differences between different levels or types of facilities 4 , 19 . In addition, urban sustainability is multidimensional and multi-scale in nature, and solutions focusing on one spatial scale or dimension may not produce the same effect on different spatial scales or dimensions 20 , 41 .…”

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confidence: 99%

Inequality of public facilities between urban and rural areas and its driving factors in ten cities of China

Yue

Wei

et al. 2022

Sci Rep

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Urban development continues to face the dilemma of spatial inequality of public facilities, particularly educational and medical facilities. Identifying inequalities in various types of public facilities and their driving mechanisms is crucial in reducing social inequality. However, information on this topic is limited. This study took 10 typical cities in China as cases. We used the methods of the Gini coefficient and hedonic price model as bases in evaluating the equality of nine types of education and medical facilities, focusing on the differences between urban and rural areas. Moreover, we further analyzed the driving factors of facility equality. Results showed that equality of public facilities in urban areas was significantly higher than that in rural areas. Primary schools, middle schools, and health service centers were relatively equal, and kindergartens and pharmacies were unequal only in rural areas. However, the equality of facilities with large-size or commercial attributes was not optimistic. Furthermore, there remained a significant gap among counties (or districts), which was mainly driven by population, economy, and building density in the form of logarithm and logarithmic linear models. Our research contributes to an in-depth understanding of the inequality of public facilities and further supports decision-making to improve social equality.

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Exploring the Equity and Spatial Evidence of Educational Facilities in Hangzhou, China

Cited by 19 publications

References 31 publications

Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data

Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data

Evaluation of Teacher Allocation in Regional Compulsory Education Industry Based on K-means clustering and GIS Spatial analysis: A Case Study of teacher-student ratio

Inequality of public facilities between urban and rural areas and its driving factors in ten cities of China

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