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China’s rapid urbanization has attracted wide international attention. However, it may not be sustainable. In order to assess it objectively and put forward recommendations for future development, this paper first develops a four-dimensional Urbanization Quality Index using weights calculated by the Deviation Maximization Method for a comprehensive...
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Citations
... The promotion of collectivisation and the support of an agrarian society limited the urbanisation process, and only post 1978-reform did the country's urban areas start to expand (Gu et al., 2017). Since China's opening up, the country's society has changed drastically with industrialisation and urbanisation driving its economic growth, for example, urbanisation increased from 17.92% in 1978 to 58.52% in 2017 (Xiao et al., 2018). However, despite China's rapid growth, there has been a lack of reflection in policy and practice of landscape. ...
... President Xi urged the local government to plan Tianfu New Area well, to place their emphasis on highlighting the characteristics of parks in cities and taking ecological value into account. Xi's proposals were considered to clarify that Park City is not an equivalent to Park + City but an integrated process that includes various models: greenways, Shan-Shui, and town and/or country approaches (Xiao et al., 2018). It also promotes a people-park-city system highlighting that the value of ecology is important to the lived experience of residents and can be considered to support increased GDP via improved urban liveability. ...
The concept of green infrastructure has gained political momentum globally and, therefore, has been rapidly introduced into planning theory, policy, and practice in the USA and Europe. Yet, it does not have a single widely recognised or accepted definition and has been adopted fluidly by various disciplines. In this chapter, discussions of green infrastructure focus on landscape architecture interpretations in both planning and design at various scales in China and the UK. The aim of this chapter is to further understand the social, economic, and ecological values of urban green infrastructure within diverse development contexts and use China as a key focus of this discussion. However, an understanding of the legacy of ‘green infrastructure’ planning based on UK and North American conceptualisations is critical to appreciating the nuance of application in China. The process of urbanisation has escalated rapidly in China since it opened up economically from the late 1970s onward. A significant part of this was the adoption of Western approaches to the design, building, and management of green infrastructure in the urban areas. Consequently, there has been an increase in public space, parks, riverside walks, and squares built within Chinese cities that reflect a global understanding of landscape rather than classical Chinese interpretations. The clash of styles provides an interesting lens through which to review the spatial development of green infrastructure examining how the application of Western ideas is applied in a Chinese context. This reflects on the plan-making and design of green infrastructure as well as its contribution to people’s daily life, health, and well-being and the harmony between nature, the city, and people. The chapter concludes that green infrastructure plays a central role in promoting an urban melody through the design and provision of connected and high-quality green space. By creating a multi-scaled and multifunctional set of landscape resources, green infrastructure can be considered to orchestrate the symphony between nature and city.
... The promotion of collectivisation and the support of an agrarian society limited the urbanisation process, and only post 1978-reform did the country's urban areas start to expand (Gu et al., 2017). Since China's opening up, the country's society has changed drastically with industrialisation and urbanisation driving its economic growth, for example, urbanisation increased from 17.92% in 1978 to 58.52% in 2017 (Xiao et al., 2018). However, despite China's rapid growth, there has been a lack of reflection in policy and practice of landscape. ...
... President Xi urged the local government to plan Tianfu New Area well, to place their emphasis on highlighting the characteristics of parks in cities and taking ecological value into account. Xi's proposals were considered to clarify that Park City is not an equivalent to Park + City but an integrated process that includes various models: greenways, Shan-Shui, and town and/or country approaches (Xiao et al., 2018). It also promotes a people-park-city system highlighting that the value of ecology is important to the lived experience of residents and can be considered to support increased GDP via improved urban liveability. ...
Green infrastructure (GI) is a strategy to support sustainability, resilience, and climate mitigation/adaptation in the built environment. GI has been in use for several decades although under a variety of names, and continues to evolve a more holistic and multifunctional focus to address all four categories of ecosystem services (provisioning, regulating, supporting, and cultural). To address ecosystem services, GI can be practiced to guide urban form, spatial structure, and aesthetics – guided by the movement of urban water in cities. To support sustainability and resilience goals, GI requires a transdisciplinary process including the co-production of knowledge and a robust culture of evidence-based decision-making based on GI performance monitoring. A culture of learning-by-doing is emerging that conceives urban design and planning as experiments – capable of addressing the “moving target” of climate change in cities. These design experiments require that performance monitoring is consistent and robust – and that the findings are subsequently applied to decision-making in an adaptive mode. An application of the theories and practices associated with GI in the Sao Paulo, Brazil watershed of Jaguaré is presented as an example of the current state of practice – and identifies questions and research needs for future applications.
... With 17 SDGs (poverty eradication, zero Hunger, good health and well-being, clean water and sanitation, affordable and clean energy, decent jobs and economic growth, industry, innovation and infrastructure, inequality reduction, and sustainable cities and communities), the UN aims to thoroughly address the social, economic and environmental dimensions of development in an integrated manner between 2015 and 2030, shifting to a sustainable development path. (Chen, R. et al. (2021), Xiao Y. et al. (2018).) [24,25] Some studies consider the SDGs as "making cities and rural human settlement environment inclusive, safe, resilient and sustainable," with 11 goals, each with negotiated indicators. ...
... (Chen, R. et al. (2021), Xiao Y. et al. (2018).) [24,25] Some studies consider the SDGs as "making cities and rural human settlement environment inclusive, safe, resilient and sustainable," with 11 goals, each with negotiated indicators. [29,30]. ...
Sustainable development of rural has become an essential global plan. Habitat sustainability assessment of rural is a critical management tool to grasp the development status of rural in real-time and enable dynamic adjustment of policies. This paper combines the 2030 Sustainable Development Goals (SDGs) with the entropy weight method, TOPSIS, and grey correlation analysis to construct a multi-criteria decision-making (MCDM) evaluation model, which is finally used to assess the sustainability of the rural human settlement environment. Finally, this paper uses the rural of 11 prefecture-level cities in Zhejiang Province in 2021 as a case study for rural human settlement environment sustainability evaluation. The results show that the overall rural human settlement environment sustainability level in Zhejiang Province is better than in most regions in China. Hangzhou has the best rural human settlement environment sustainability, and Zhoushan has the worst. In addition, the production environment factor is the critical factor that constrains sustainability. The study results provide references and guidance to policymakers for sustainable development initiatives.
... Studies show that higher education in the United States is focused in the Northeast and Northwest, but less in the Southwest, more in cities, less in rural areas, more in large cities, and less in small towns (Haaga, 2000;Kominski et al., 1993). With the popularization of higher education in China, China's higher education population's spatial distribution has gradually attracted domestic scholars' attention (Xiao et al., 2018). The urban higher education population distribution is higher than in rural areas, the North is more elevated than South and the East is more heightened than Midwest. ...
In the past decade, China's rapid development has affected the higher education population's formation mechanism and spatial distribution. Therefore, this study aims to analyze the spatial distribution pattern and formation mechanism of the spatial agglomeration of the higher education population of 30 provinces in China from 1990 to 2017 through Exploratory Spatial Data Analysis (ESDA) and spatial econometric analysis. The study's main results are as follows: (1) The overall spatial distribution of China's higher education population is uneven, indicating that the population is distributed in the West and dense in the East. (2) The agglomeration of the higher education population is spatially dependent. The agglomeration of the higher education population is mainly high-high and low-low types. Moreover, due to social, economic, and environmental factors, the higher education population's formation mechanism in the study area and neighboring areas is uneven. Explanatory factors of the higher education population, namely gross domestic product (GDP), industrial structure (IS), urbanization (UP), number of universities (NU), and technological innovation (TI), have a positive and significant impact on the spatial agglomeration of the higher education population and living consumption expenditure (CON) and elevation (EL) has a negative and significant effect on the population of higher education. Outstanding economic factors such as industrial structure has driven the spatial agglomeration of the higher education population. In contrast, environmental factors such as EL have played a unique role in promoting the higher education population's outward diffusion. Therefore, the government should encourage the transfer of tertiary industry in the central and western regions to accelerate the infrastructure, social and economic development of these regions, which may reduce the uneven distribution of the higher education population in various areas.
... He et al. [36] maintained that the accumulating pressure on the environment caused by urbanization is the key issue during urban development, and they verified the relationship between urbanization and ecological environment with a coupling Sustainability 2022, 14, 5889 5 of 26 and coordination model. Xiao et al. [37] established a four-dimensional comprehensive evaluation system related to urbanization quality, and they revealed the spatial correlation of urbanization in China through exploratory spatial data analysis. Ma et al. [38] investigated the coordination between population urbanization and land urbanization and proposed a relevant development model. ...
In the context of accelerated urbanization, constructing resilient cities is an effective approach to tackling risks, such as extreme weather, and various urban challenges. The coupling and coordinated development of urbanization and urban resilience is a prominent embodiment of urban sustainable development and high-quality development capacity. In this study, Hunan Province, China, which is frequently affected by various disasters, is selected as a representative for examining the coupling and coordination relationship between urban resilience and urbanization level. The panel data are adopted to construct a dual-system evaluation framework integrating urban resilience and urbanization level based on the entropy weight-coefficient of variation (CV)-CRITIC method. The coupling coordination degree of this dual-system evaluation framework is calculated with the coupling model in physics and GM (1, 1) grey prediction model. Additionally, the spatial–temporal evolution characteristics of the coupling coordination degree are investigated and analyzed by ArcGIS and Geoda software. The following are indicated from the results: (1) The resilience of all cities is related to their geographical location and is characterized by a decrease from east to west; in addition, the resilience level of most cities presents a downward trend with time. (2) The urbanization level of most cities develops stably with time, but there is a growing gap in the urbanization level between regions. (3) There is a strong correlation between urban resilience and urbanization level in all cities; the unbalanced coupling and coordinated development emerge, specifically manifested by the polarization phenomenon. Eventually, a circle-difference spatial distribution pattern that starts from the central urban agglomeration and gradually decreases to the periphery is formed. (4) The prediction results of the coupling coordination degree suggest that there is an increasingly distinct polarization trend for the coupling and coordinated development between cities, and it is necessary to pay attention to those cities with a declined predicted value. (5) There is a significant positive spatial autocorrelation and agglomeration effects in the distribution of the coupling coordination degree of all cities, and the correlation is getting stronger with each passing year; the correlation mode is mainly characterized by homogeneity and supplemented by heterogeneity. Finally, several suggestions are proposed in this paper, in an attempt to lead the coordinated development of regions by novel urbanization and thus promote the sustainable development of cities. The methods and insights adopted in this study contribute to investigating the relationship between urban resilience and urbanization in China and other regions worldwide.
... China has experienced rapid urbanization and industrialization over the past several decades -the Chinese urban population increased from 17.9% in 1978 to 63.9% in 2020 [33]. Increasing attention has been paid to health behavior promotion in urban areas, where green space may play a critical role [34]. ...
Introduction:
This study systematically reviewed scientific evidence concerning the influence of green space on obesity in China.
Methods:
Keyword and reference search was conducted in PubMed, Web of Science, Scopus, EBSCO, and CNKI. Predetermined selection criteria included-study designs: experimental and observational studies; subjects: people of all ages; exposures: green space (i.e., any open land partly or entirely covered with grass, trees, shrubs, or other vegetation); outcomes: body weight status (e.g., body mass index [BMI], overweight, or obesity); and country: China.
Results:
Ten studies met the selection criteria and were included in the review. All studies adopted a cross-sectional design. Overall greenness measures were found to be inversely associated with BMI, overweight, and obesity in most included studies. Street greenness, which measures the perceived greenness at the eye level on streets, was found to be inversely associated with BMI and obesity. By contrast, mixed results were observed for the relationship between green space accessibility and weight outcomes. Air quality was found to mediate the relationship between greenness and obesity. The influence of green space on obesity tended to vary by residents' gender, age, and socioeconomic status. Boys, women, older residents, and those with lower education or household income were more likely to benefit from greenness exposure.
Conclusion:
The literature on green space exposure in relation to obesity in China remains limited. Longitudinal and quasi-experimental studies are warranted to assess the causal link between green space and obesity. Future measures should better capture the self-perception, quality, and attractiveness of green space. The underlying pathways through which green space affects residents' weight outcomes should be further elucidated.
... (2) Exploratory Spatial Data Analysis (ESDA) This study applied ESDA to reveal the spatial correlation pattern of the RNCUE in Chongqing. First, the global Moran's I was introduced to study the spatial distribution pattern of the whole study area [80]. The calculation equation was defined as follows: ...
The efficient utilization and optimal allocation of natural capital play an important role in economic development and human well-being. The production process of natural capital is the input and output processing of its ecological resources and the environment. Improving the rural natural capital utilization efficiency (RNCUE) is an important goal of natural capital investment, and the efficient utilization of natural capital is an important factor for the efficient operation of the regional economy and society. This study uses the super slack-based measure (SBM) model based on undesirable outputs to measure the RNCUE, combines the exploratory data analysis method (ESDA) and spatial Markov transfer matrix to analyse the spatiotemporal evolution characteristics of efficiency, and analyses the influencing factors of the change of the RNCUE in Chongqing through a spatial econometric model. The results show that: (1) The RNCUE in Chongqing is still at a low level as a whole and there is a large space for efficiency improvement and efficient operation. There is a certain spatial dependence on the interaction of efficiency between adjacent districts and counties. (2) High-high agglomeration is concentrated in the western area of Chongqing One-hour Economic Circle, and low-low agglomeration is concentrated in Southeast and Northeast Chongqing. The probability of a large change in the RNCUE in consecutive years is small, and it is easy to form the phenomenon of “club convergence” in space. (3) The RNCUE in Chongqing has been affected by rainfall, temperature, NDVI, the per capita GDP, proportion of fixed asset investment, expenditure for agriculture, and proportion of primary industry and rural population. The influencing factors show that the spatial heterogeneity is significant. The RNCUE has a negative correlation with forest coverage and the expenditure for agriculture, is not significantly positive or negative with the proportion of the primary industry and is positively correlated with the rural population density. This study points out that we can improve the RNCUE in Chongqing by optimizing the spatial differentiation control mechanism, clarifying property rights, enhancing liquidity, and strengthening scientific and technological innovation.
... As for the unique demand-side factors, some scholars point out that the rising urban housing prices are driven by China's unprecedented rapid and prolonged economic growth and urbanization; both significantly faster than in other parts of the world (Fang et al., 2016). For instance, from 1978 to 2017, over 600 million Chinese migrated from the countryside to the cities, while the urbanization rate increased from 18% to 58% during the same period (Xiao et al., 2018). Moreover, there is a long-standing belief shared by the Chinese citizens that their government will not allow the collapse of the housing sector, making a residential property a seemingly risk-free and highly profitable investment. ...
This paper examines the future dynamics of the relative housing price-to-income ratio (RHPIR) in China. We find that the convergence in RHPIR will be more congregated in the non-center cities of city clusters, the cities from the eastern region, with a net outflow of population, and low economic policy uncertainty (EPU). The convergence clubs will emerge in the cities with a net outflow of population and from the central and northeastern regions. The center and the non-center cities of city clusters will converge to parallel affordability paths. We pinpoint the cities with precise ranges of RHPIR that require special attention from the policymakers aiming at convergence in housing affordability.
... The implementation of the rapid economic growth (RED) scenario in the area of Mouzaki under the CLUE-S model predicted for the year 2040 an increase in the area of settlements by 15.71% compared to 2020, an increase less than those predicted by Samie et al. [50] and Wang et al. [39] for some regions of Pakistan and China, respectively. This differentiation can be attributed to the very high rates of population growth, the prevailing political conditions, the astyphilia, and the very intense pressures to find housing in urban centers that is observed in these countries (Jabeen et al. [66], Xiao et al. [67]). ...
Investment in biology-based technological innovations is a key requirement for the development of modern agriculture/forestry. The expansion of innovative biological technologies includes changes in crops/cultivations, such as the transition from intensive monocultures to multiple crops of lower agrochemical inputs with the integration of woody trees/shrubs or animals, represented by Agroforestry. This innovative biological technology is further promoted at the European Union (EU) level by powerful institutions such as the Green Deal and the new CAP, mainly by tools such as ecoschemes and agri-environmental and climate measures (AECMs). The use of integrated regional spatiotemporal models, such as CLUE-S, to predict land use changes in the framework of Agroforestry is rather restricted. This paper examines Agroforestry as a vehicle that can contribute to achieving the rural development of the region of Thessaly, Greece. It sets a time horizon for reviewing the changes that are expected in the most important units of land uses of the rural landscape of the municipality of Mouzaki, western Thessaly plain, in the year 2040, which serves as model land for the region of Thessaly. It examines these changes with the effect of three (3) socio-economic scenarios: (a) a linear operating scenario (business as usual, BAU), (b) an ecological land protection (ELP) scenario, and (c) a rapid economic development (RED) scenario. These scenarios were introduced in the non-spatial module of the CLUE-S spatiotemporal model, while in the spatial module sixteen (16) characteristic landscape parameters were introduced as independent variables. The most important land use units, including traditional silvoarable and silvopastoral woodland systems, were the dependent variables. The simulations of the changes of the land use units showed that under the RED scenario, in the year 2040 the extent of the silvoarable systems is expected to increase significantly (57%) compared to the reference year of 2020, while the rest of the land use units under the other scenarios are mainly regulated by depopulation/abandonment of the rural areas and the processes of natural succession. The fact that the extent of silvoarable systems is increasing, in combination with the favorable institutional environment created by European rural policies, gives impetus to regional rural development through investments in the agricultural sector and mainly in Agroforestry systems.
... The spatial pattern of urbanization quality in Jiangsu suggests that economic development has been a determining factor, which is consistent with views advanced by and Wang et al. (2010) [56,57]. Conversely, the experiences of Suzhou and Xuzhou demonstrate that location is also a key factor in improving the quality of urbanization [58]. Nanjing is the provincial capital of Jiangsu and benefits from advantages such as preferential policies. ...
The relationship between urbanization and ecology environment is a current research hotspot. Most literature to date focuses on the interaction between urbanization and a single component of the ecosystem (e.g., water, forests, and ecosystem services), while little attention has been given to the relationship between urbanization quality and ecosystem health. Accordingly, this paper used the entropy method and vigor—organization–resilience model to measure the urbanization quality and ecosystem health in Jiangsu Province. Based on the results, this paper analyzed the spatial-temporal pattern and evolution characteristics of the coordination degree between urbanization quality and ecosystem health in Jiangsu Province in 2000, 2005, 2010, 2015, and 2017 and then used the geographic detector and Tobit regression model to explore its internal driving forces and external influencing factors. The results show the following: 1. The changing trend of urbanization quality and ecosystem health in the Jiangsu Province share some traits; it first descends and then ascends; 2. The cities in Jiangsu Province are all between primary coordination and high-quality coordination. Central Jiangsu has the best coupling coordination degree, and Northern Jiangsu has the worst coupling coordination degree, but the overall coordination degree is on the rise; 3. The internal and external factors that drive the coordinated development of urbanization and ecosystem health differ based on periodic and regional characteristics. We need to tailor policies to ensure the sustainable development of the region.
