Landscape urbanization and economic growth in China: positive feedbacks and sustainability dilemmas

Distribution dynamics and urbanization-related factors of Hantaan and Seoul virus infections in China between 2001 and 2020: A machine learning modelling analysis

Objectives

The epidemical and clinical features of distinct hantavirus infections exhibit heterogeneity. However, the evolving epidemics and distinct determines of the two hantavirus infections remain uncertain.

Methods

Data on hemorrhagic fever with renal syndrome (HFRS) cases and genotyping were collected from multiple sources to explore the distribution dynamics of different endemic categories. Four modelling algorithms were used to examine the relationship between infected hantavirus genotypes in HFRS patients, as well as assess the impacts of urbanization-related factors on HFRS incidence.

Results

The number of cities dominated by Hantaan (HTNV) and Seoul (SEOV) viruses was projected to decrease between two phases, while the mixed endemic cities increased. Patients with SEOV infection predominantly presented gastrointestinal symptoms. The modeling analysis revealed that built-up land and real GDP demonstrated the highest contribution to HTNV and SEOV infections, respectively. The impact of nightlight index and park green land was more pronounced in HTNV-dominant cities, while cropland, impervious surface, and floor space of commercialized buildings sold contributed more to HFRS incidence in SEOV-dominant cities.

Conclusions

Our findings fill a gap for the three endemic categories of HFRS, which may guide the development of targeted prevention and control measures under the conditions of urbanization development.

Short-term air pollution and greenness exposures on oxidative stress in urban and peri-urban residents in Beijing: A part of AIRLESS study

BACKGROUND

Exposure to air pollution has been associated with increased risks of cardiopulmonary diseases, cancer, and mortality, whereas residing near green spaces may reduce the risks. However, limited research explores their combined effect on oxidative stress.

METHODS

A total of 251 participants with multi-time measurements were included in the longitudinal-designed study. Personal gaseous air pollutants (CO, NO, NO2, and O3,) and particulate pollution (PM1, PM2.5, and PM10) were measured and followed in two 7-day windows while ambient exposure levels and urine samples were collected simultaneously. Participants' Normalized Difference Vegetation Index (NDVI) was estimated and used to represent greenness exposure. Urinary oxidative stress biomarkers include free malondialdehyde (MDA), total MDA, and 8-hydroxydeoxyguanosine (8-OHdG). Linear mixed-effects models were used to independently and jointly estimate the associations of greenness and air pollution with oxidative stress biomarkers.

RESULTS

We found consistent positive associations of personal ozone (O3) exposure with 8-OHdG percent changes, and this association was modified by gender and outdoor activity frequency. Consistent positive associations of personal lag 2-day carbon monoxide (CO) exposure with the percent changes of the three oxidative stress biomarkers were significant. We additionally observed that individuals who lived in greener areas had lower levels of urinary-free and total MDA. Participants in the highest NDVI tertile had 0.38 and 0.46 lower free and total MDA levels, [95 % CI: (-0.70, -0.05) and (-0.78, -0.13)], compared to the lowest NDVI tertile. There was also evidence indicating the modification effects by area, education, and outdoor activity frequency on associations between NDVI exposure and creatinine adjusted free MDA (all Pfor interaction < 0.05). Additional greenness modification effects on personal O3 exposure with urinary 8-OHdG was observed.

CONCLUSION

Our study provides biological evidence of the modification effect of the built environment on the impact of air pollution.

Perceptible landscape patterns reveal invisible socioeconomic profiles of cities

Urban landscape is directly perceived by residents and is a significant symbol of urbanization development. A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive, resilient, and sustainable cities and human settlements. Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing, potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes. This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators. Here, we propose four urban landscapes indicators in three dimensions (UL3D): greenness, grayness, openness, and crowding. We construct the UL3D using 4.03 million street view images from 303 major cities in China, employing a deep learning approach. We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities. The results show that UL3D indicators differs from two-dimensional landscape indicators, with a low average correlation coefficient of 0.31 between them. Urban landscapes had a changing point in 2018-2019 due to new urbanization initiatives, with grayness and crowding rates slowing, while openness increased. The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles. Specifically, GDP per capita, urban population rate, built-up area per capita, and hospital count correspond to improvements of 25.0%, 19.8%, 35.5%, and 19.2%, respectively. These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities.

The prediction of urban growth boundary based on the ANN-CA model: An application to Guangzhou

Urban growth boundary (UGB) delineation is critical not only for China's urban planning policies, such as the "three control lines" of the Ministry of Natural Resources, but also for addressing global challenges related to sustainable urban development. This study contributes to the international discourse on urban growth management by developing an innovative artificial neural network-cellular automata (ANN-CA) model, tailored for cities experiencing rapid expansion. Using Guangzhou as a case study, we constructed an impact factor model that incorporates a wide range of factors, including urban spatial terrain, natural environment, current urban land classification, and industrial and economic conditions, along with the layout of modern service networks. The ANN-CA model was then employed to simulate urban spatial expansion and UGB delineation for the year 2030 under various constraints, such as strict protection zones and sustainable development scenarios. Our findings indicate that between 2020 and 2030, Nansha, Panyu, and Zengcheng districts will witness the most significant urban expansion, with respective area increases of 13.81 km2, 8.94 km2, and 5.8 km2, marking them as key growth areas. Furthermore, we propose that future urban expansion in Guangzhou should prioritize the southern and eastern regions, aligning with the city's strategic spatial objectives of "moving east, expanding south, connecting west, and optimizing north." By emphasizing ecological protection and intensive land use, this study provides a robust framework for urban planning in Guangzhou and offers insights applicable to rapidly urbanizing regions worldwide.

The rapid increase of urban contaminated sites along China's urbanization during the last 30 years

Contaminated sites pose serious threats to the soil environment and human health. However, the location and temporal changes of urban contaminated sites across China remain unknown due to data scarcity. Here, we developed a machine-learning model to identify the contaminated sites using public data. Results show that the trained model with 2,005 surveyed site samples and six variables can achieve a model performance evaluation value of 0.86. 43,676 contaminated sites were identified from 83,498 polluting enterprise plots in China. However, these contaminated sites have significant spatiotemporal heterogeneity, mainly located in economically developed provinces, urban agglomerations, and core urban areas. Moreover, the contaminated sites increased by 325% along with urban expansion from 1990 to 2018. The abandoned contaminated sites increased rapidly, but the contaminated sites in production decreased continuously. This methodological framework and our findings contribute to the precise management of contaminated sites and provide insights into urban sustainable development.

Urbanization and flood risk analysis using geospatial techniques

This research investigates the relationship between urbanization as a land use/land cover change and the increased flood disasters in Accra. Understanding this relationship will provide evidence for urban development planners, policy makers and flood managers to coordinate in responding to the problems effectively. This study maps and analyzes the changes in urbanization from 1991 to 2015. The research reviews the trends of flood events in Greater Accra and analyzes the relationship between the pattern of urbanization and the increase in flood disaster events from 1991 to 2015. The research revealed that there was an increase in urban land use/land cover change of up to 95.51% and 129.14% in the periods 1991-2002 and 2002-2015 respectively. The pattern of urbanization took place in an unplanned style, where physical developments in waterways became high. The findings show that the pattern of flood disasters increased from 1991 to 2015 with evidence showing two years having repeated flood events.

Haze pollution and urbanization promotion in China: How to understand their spatial interaction?

Can promoting urbanization and controlling haze pollution result in a win-win situation? Based on panel data from 287 prefecture-level cities in China, this paper uses the three-stage least-squares estimator method(3SLS) and generalized space three-stage least-squares estimator method (GS3SLS) to study the spatial interaction between haze pollution and urbanization. The results show the following: (1) There is a spatial interaction between haze pollution and urbanization. On the whole, haze pollution and urbanization have a typical inverted U-shaped relationship. (2) Haze and urbanization show different relationships in different regions. The haze pollution in the area left of the Hu Line has a linear relationship with urbanization. (3) In addition to haze, urbanization also has a spatial spillover effect. When the haze pollution in the surrounding areas increases, the haze pollution in the area will also increase, but the level of urbanization will increase. When the level of urbanization in the surrounding areas increases, it will promote the level of urbanization in the local area and alleviate the haze pollution in the local area. (4) Tertiary industry, greening, FDI and precipitation can help alleviate haze pollution. FDI and the level of urbanization have a U-shaped relationship. In addition, industry, transportation, population density, economic level and market scale can promote regional urbanization.

Urban-rural disparities of carbon storage dynamics in China's human settlements driven by population and economic growth

China has experienced a rapid expansion of human settlement in both urban and rural areas over the past three decades. Regarding the impacts on carbon storage, previous studies that only focus on certain ecosystems cannot reflect urban-rural disparities, resulting in the carbon storage changes in human settlement remaining unknown. In this study, we aimed to explore China's urban-rural disparities in human settlement expansion and direct impacts on carbon storage by using the big Earth data technology. The results showed that from 1990 to 2018, the total amount of China's human settlement expansion reached 175,703.80 km², and the inner-city, peri-urban, and rural components accounted for 21.00 %, 20.18 %, and 58.82 %, respectively. Along with the general tendency of impervious surface area (ISA) growth, there was more soil organic carbon (SOC) (1254.33 TgC) being sealed beneath ISA (0-100 cm depth), compared to a huge reduction in vegetation biomass carbon (VBC) (91.44 TgC) during the study period. The results further indicated that the change density of either VBC or SOC presented a slightly rising trend along the urban-rural gradient, due to the increasingly common encroachment on vegetation and soil types with higher carbon content. We also found that socioeconomic drivers had a greater influence in urban areas than rural areas, and the related correlation exhibited a descending trajectory in both urban and rural areas. There is thus an urgent need to preserve lands with abundant carbon storage and contain the waste of land resources in rural areas. All stakeholders should pay more attention to concerted and targeted regulation policies for well-planned and eco-friendly human settlement expansion such as enhancing rural land use efficiency and promoting large-scale afforestation and continuous urban greening, which will be critical not only for guiding sustainable urbanization all over China but also for mitigating climate change for the entire world.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km² during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m^-2·a^-1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m^-2·a^-1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

Trends in the evolution of sustainable development research in China: a scientometric review

Because of the extensive attention of global scholars on the sustainable development in China, much research has been published over the past 30 years. Based on the 12,635 journal papers from the Web of Science database, we explore the trends in the evolution of China's sustainable development research by a knowledge graph. The result indicates that the attention of China's sustainable development research increased exponentially during 1991-2021, and it continues to shift from a macroperspective to the exploration of specific methods and implementation paths. During 2001-2005, China's sustainable development research developed rapidly and formed a complete cluster structure. In addition, China's sustainable development research has experienced three stages and two topic drifts. Staged development and topic drifts lead to a wide range of disciplinary drifts. In general, the trends in the evolution of China's sustainable development research mainly focus on three aspects: research methods, research scope, and theoretical innovation. China's sustainable development provides a case or a path for other developing countries. Economic incentives and policy promotion remain important measures to promote sustainable development.

Remote sensing of fluorescent humification levels and its potential environmental linkages in lakes across China

The pollution or eutrophication affected by dissolved organic matter (DOM) composition and sources of inland waters had attracted concerns from the public and government in China. Combined with remote sensing techniques, the fluorescent DOM (FDOM) parameters accounted for the important part of optical constituent as chromophoric dissolved organic matter (CDOM) was a useful tool to trace relative DOM sources and assess the trophic states for large-scale regions comprehensively and timely. Here, the objective of this research is to calibrate and validate a general model based on Landsat 8 OLI product embedded in Google Earth Engine (GEE) for deriving humification index (HIX) based on EEMs in lakes across China. The Landsat surface reflectance was matched with 1150 pairs fieldtrip samples and the nine sensitive spectral variables with good correlation with HIX were selected as the inputs in machine learning methods. The calibration of XGBoost model (R² = 0.86, RMSE = 0.29) outperformed other models. Our results indicated that the entire dataset of HIX has a strong association with Landsat reflectance, yielding low root mean square error between measured and predicted HIX (R² = 0.81, RMSE = 0.42) for lakes in China. Finally, the optimal XGBoost model was used to calculate the spatial distribution of HIX of 2015 and 2020 in typical lakes selected from the Report on the State of the Ecology and Environment in China. The significant decreasing of HIX from 2015 to 2020 with trophic states showed positive control of humification level of lakes based on the published document of Action plan for prevention and control of water pollution in 2015 of China. The calibrated model would greatly facilitate FDOM monitoring in lakes, and provide indicators for relative DOM sources to evaluate the impact of water protection measures or human disturbance effect from Covid-19 lockdown, and offer the government supervision to improve the water quality management for lake ecosystems.

Scaling of Chinese urban CO2 emissions and multiple dimensions of city size

Cities are both the primary cause of global climate change and the key to the mitigation agenda. China's unprecedented urbanization has paralleled a growth in energy demand and urban areas have emerged as the crux of CO₂ emissions reduction in China. There is a crucial need for policymakers to understand how CO₂ emissions scale with city size and adopt economies of scale (cost savings) for mitigation, particularly through a multidimensional lens of city size. This study reveals a set of scaling relations between urban scope 1 CO₂ emissions and five dimensions of city size in 340 Chinese cities, including population (POP), built-up area (BA), building height (BH), specific built-up area (SBA), and built-up volume (BV). The findings show that CO₂ emissions in Chinese cities scale linearly with POP and BA but sublinearly with BA, SBA, and BV, and more diverse regimes exist across various geographic zones, population hierarchies, administrative hierarchies, and governance contexts. The prevalent sublinear scaling regime between CO₂ emissions and SBA and BV demonstrates the potential importance of optimizing the vertical built-up landscapes for establishing a zero‑carbon society. Furthermore, the top 10 % and bottom 10 % performance of individual cities in emissions identified by the Scale-Adjusted Metropolitan Indicator (SAMI) (the smaller the better) highlights the imprints of the socioeconomic context (e.g., Low Carbon City Initiative) on the scaling of CO₂ emissions in Chinese cities, which is critical for developing decarbonization strategies. Our multidimensional analysis can assist in the local-tailored low-carbon development of Chinese cities.

Introduction

This research focuses on the political nature of urban redevelopment from a governance perspective; characteristics of its governance will be analysed within the Chinese authoritarian regime. Urban redevelopment is chosen as the research object because it is significant and complex enough to be a typical case in Chinese economic growth. The main problem in urban redevelopment is the issue of social cooperation among different stakeholders; it is the problem of governance. Theories of governance origin from the developed world and their applications into Chinese context will bring about interesting development of governance studies and exciting reflection of Chinese politics. In this perspective, the most important characteristic of China’s political system, an authoritarian regime can strongly affect the characteristics of governance. Guangzhou, as the third largest city in China and the political-economic centre of south China, has been chosen as the studied site to reveal its political nature in Urban redevelopment. Based on this analysis, a resilient mode of governance in Guangzhou redevelopment can be established. This mode is a small fragment of mirror to reflect the whole political picture of China.

Evaluating the Impact of Institutional Performance and Government Trust on Farmers' Subjective Well-Being: A Case of Urban-Rural Welfare Gap Perception and Family Economic Status in Shaanxi, Sichuan and Anhui, China

In the modern world, fostering comprehensive social sustainability has become one of the major concerns. Interestingly, rural livelihood may significantly comprise the compelling performance evaluations of governmental institutions' performances. Governmental institutions' performances in rural areas largely depend on whether they can gain relatively higher trust levels of marginal farmers. However, the critical interaction between these two prospects may foster farmers' subjective well-being (SWB). Therefore, the study aims to model and test institutional performance, government trust, and farmers' subjective well-being by utilising a survey of data from 963 farmer households in Shaanxi, Sichuan, and Anhui provinces, China. We have adopted structural equation modelling (SEM) to craft the study's findings. However, in the literature, political performance is widely quantified by the urban-rural welfare and economic status gap; thus, in the core model, we have incorporated and measured the mediating role of the urban-rural welfare gap and household economic status. The results show that institutional performance, social insurance performance, and ecological livability performance have a significant and positive impact on institutional performance and government trust and eventually derive farmers' SWB. However, the role of environmental livability performance is more substantial than social insurance performance in quantifying governmental trust and institutional performance. Moreover, it has a significant positive impact on the subjective well-being of farmers, and the effect of policy trust is not substantial. The results of further mediation and moderation effects show that social insurance performance and ecological livability performance can enhance the subjective well-being of farmers through the indirect transmission of institutional trust. In contrast, the mediating impact of policy trust is not significant. For farmers with higher economic status, institutional performance has a more substantial effect on the subjective well-being of farmers with a relatively smaller perception of the urban-rural welfare gap and lower family economic status.

Factor mobility, transportation network and green economic growth of the urban agglomeration

Understanding the externalities of transportation networks in the process of the agglomeration and diffusion of production factors has theoretical and practical significance for the coordinated development of China's economic growth in urban agglomerations. Therefore, the social network analysis method is introduced in this paper with the case of the Pan Pearl River Delta Urban Agglomeration to analyze the characteristics of the traffic connection network of the production factor flow within this urban agglomeration, and subsequently, an econometric panel model is adopted to quantitatively analyze the effect of the connection network on the economic growth of the urban agglomeration. The results show that (1) the traffic connection of the Pan Pearl River Delta Urban Agglomeration has network characteristics typical of a "small world". Although the connections between cities are gradually strengthening, the regional differences are obvious, showing a core-edge pattern of eastern agglomeration and western sparseness. (2) Among the network nodes, Guangzhou, Shenzhen and other cities have obvious agglomeration and diffusion effects, stabilizing economic growth while driving the development of surrounding cities. The "polarization effect" in Chongqing and Chengdu has significantly increased, and the accumulation of factors mainly meets their own economic development but has not yet spread. (3) The Pan Pearl River Delta Urban Agglomeration's transportation network influences the region's economic growth through the structural effect, as it strengthens the economic ties between cities, and through the action of resource factors, as the network represents the aggregation and diffusion path of factor flow. (4) Due to the different traffic connections and industrial structures across the Pan Pearl River Delta Urban Agglomeration, the factor flow of each suburban agglomeration has a differentiated impact on the regional economic growth under the traffic connection network. Therefore, to realize the coordinated economic development of the Pan Pearl River Delta Urban Agglomeration, it is necessary to "adjust measures to local conditions" and formulate accurate and precise policies.

Spatiotemporally Explicit Mapping of Built Environment Stocks Reveals Two Centuries of Urban Development in a Fairytale City, Odense, Denmark

The urban built environment stocks such as buildings and infrastructure provide essential services to urban residents, and their spatiotemporal dynamics are key to the circular and low-carbon transition of cities. However, spatiotemporally explicit characterization of urban built environment stocks remains hitherto limited, and previous studies on fine-grained mapping of built environment stocks often focus on an urban area without consideration of temporal dynamics. Here, we combined the emerging geospatial data and historical maps to quantify the spatially and temporally refined stocks of buildings and infrastructure and developed a novel indexing method to track the construction, demolition, and renovation for each building across various historical snapshots, with a case study of Odense, Denmark, from 1810 to 2018. We show that built environment stock in Odense increased from 80 t/cap in 1810 to 279 t/cap in 2018. Their dynamics appear overall in line with urban development of Odense over the past two centuries and well reflect the combined effects of industrialization, infrastructure development, socioeconomic characteristics, and policy interventions. Such spatiotemporally explicit stock mapping offers a physical and resource perspective for measuring urbanization and provides the public and government insight into urban spatial planning and related resource, waste, and climate strategies.

Waterbody loss due to urban expansion of large Chinese cities in last three decades

Urban waterbodies are one of the most pertinent issues involved in multiple aspects of Sustainable Development Goals (SDGs). However, waterbodies in large Chinese cities are highly vulnerable to urban-land expansion, which is mostly due to economic development, population growth, and rural-urban migration. In this work, we selected 159 Chinese cities of over one million in population to investigate the encroachment on waterbodies due to rapid urbanization from 1990 to 2018. Overall, 20.6% of natural waterbody area was lost during this period to urban expansion, and this fraction varied from city to city which was related to waterbody abundance. With the acceleration of urbanization, waterbody occupation is becoming more serious (P < 0.01). However, in all cities, this encroachment has eased since 2010, which justifies the effective implementation of national-scale policies to conserve urban waterbodies. Meanwhile, gains have occurred during urbanization, in addition to the loss of waterbodies. Especially, cities lacking waterbody placed a greater emphasis on ecological factors, whose urban waterbody areas showed an increasing trend. In the future, ecological resources, including waterbody, should be considered in urban planning to provide reasonable protection to waterbodies in the quest for urban sustainability.

Evaluating the Coordinated Development between Urban Greening and Economic Growth in Chinese Cities during 2005 to 2019

Balancing economic growth with environmental protection is vital for the sustainable development of cities and regions. However, urban greening has rarely been considered in extensive studies. This study incorporates urban greening into a coupling coordination degree (CCD) model, in order to evaluate its coordination with economic performance. A total of 286 cities in China between 2005 and 2019 were selected as specific study subjects. Meanwhile, clustering method was used to classify different clusters based on CCD values, the Gini coefficient analysis was applied to discover the CCD values inequality characteristics and the exploratory spatial data analysis (ESDA) method was employed to study the CCD values spatial aggregation features. The results indicate that the CCD values presented significant spatial heterogeneity. Spatially, the CCD values were divided into eight clusters, with those in the eastern region generally being higher than in the central and western regions. Temporally, the CCD in all cities showed an increasing trend, but more than 60% of cities were still in the uncoordinated or low-level coordination stage. In addition, inequality and spatial aggregation characteristics were observed in CCD values, both of which presented decreasing trends. Greening has a stronger influence on the linked and coordinated growth of the two systems; therefore, we propose policy recommendations for pursuing the development of environmentally friendly cities from different aspects. In summary, this research allows for a better understanding of economic and environmental relationships, thus contributing to the objective of creating sustainable cities and communities.

Towards Carbon Neutrality: The Innovation Efficiency of China’s Forestry Green Technology and Its Spatial Spillover Effects

This study evaluates China’s forestry green technology innovation efficiency (FGTIE) using slack-based Data Envelopment Analysis (DEA) based on Chinese provincial panel data from 2011 to 2020. This research endeavours to explore the spatiotemporal dynamics of FGTIE in China and identify its influencing factors. The results demonstrate obvious spatial distribution differences among Chinese FGTIEs, with the southwestern region being relatively stable and the central and southeastern regions being more variable, revealing a general state of clustered development. FGTIE demonstrates a significant spatial correlation. The correlation intensity reveals a ‘W’-shaped, ‘down–up–down’ trend, suggesting that a universal spatial pattern of FGTIE has not yet developed a steady state and that stable spatial aggregation characteristics among provinces are evident. The influencing factors of FGTIE are confirmed to have significant spillover effects. Increases in social security, foreign direct investment and environmental policy stringency will promote efficiency improvements in neighbouring provinces through positive spillover effects, and the economic development level and forestry scale will inhibit efficiency improvements in neighbouring provinces through negative spillover effects.

A Review of Ecosystem Services Research Focusing on China against the Background of Urbanization

The change in landscape patterns caused by urbanization is one of the main reasons for the degradation of global ecosystem services. Reducing the negative impact of rapid urbanization on ecosystems and promoting the coordinated development of cities and ecosystems have become a hot topic around the world. Based on Web of Science Core Collection and CNKI database papers, this study conducts a bibliometric analysis of ecosystem services research against the background of global urbanization from 2000 to 2022. At the same time, the research hot spots, regional distribution, research trends, and research contents are summarized by taking China as the key research area. The results show that: (1) the research hot spots of ecosystem services against the background of urbanization are generally the same in China and the world. Both of them are based on landscape pattern or land use; the research scale is from macro to micro; and the research method is from static to dynamic. (2) From the perspective of ecosystem service types, the four types of ecosystem service have been studied in China and other parts of the world, but there are differences in the specific types, quantity, and regional distribution. (3) Whether in China or other regions of the world, the studies on the trade-offs of ecosystem services against the background of urbanization are mainly at medium and large scales. Finally, ecosystem service bundles research, systematic thinking, and the combination of ecosystem services and territorial spatial planning against the background of urbanization are pointed out as key aspects of future research.

How does new-type urbanization affect air pollution? Empirical evidence based on spatial spillover effect and spatial Durbin model

To alleviate the ecological and environmental problems caused by rapid urban development, China has formulated and implemented the new-type urbanization strategy. However, there is insufficient empirical research on the specific relationship between new-type urbanization and air pollution. Therefore, based on the panel data of 30 provinces in China from 2005 to 2018, this paper constructs a comprehensive evaluation index system of new-type urbanization using the five dimensions of population, economy, space, society, and green. The spatial Durbin model and the spatial mediating model are used to discuss the spatial effect, transmission mechanism, and regional heterogeneity of new-type urbanization on air pollution. The results show that China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration, and there are spatial fluctuations. The construction of new-type urbanization significantly reduces local air pollution, and the industrial structure optimization, technological innovation, and energy structure adjustment are considered as important transmission mechanisms. However, under the fiscal decentralization and political tournament system in China, the policy implementation deviation may weaken the emission reduction effect of new-type urbanization, which is not conducive to regional environmental governance. From the sub-regional level, the impact of new-type urbanization on air pollution has regional heterogeneity. A robustness test confirms the reliability of our research conclusions. This study also proposes some policy suggestions that the government can utilize in grasping the policy focus of new-type urbanization construction to discover effective ways of controlling air pollution.

Intercomparison of Local Warming Trends of Shanghai and Hong Kong Based on 120-Year Temperature Observational Data

Using surface air temperature observations from 1901 to 2020, this study compared the warming trends of Shanghai and Hong Kong over a period of 120 years. The statistical results reveal the following: (1) The average temperatures of the two cities underwent fluctuating increases during the past 120 years, with linear warming rates of 0.23 °C/decade in Shanghai and 0.13 °C/decade in Hong Kong. (2) The fluctuation ranges of maximum temperature in the two cities were considerably higher than those of mean temperature. Moreover, in both cities, the annual mean maximum temperature decreased during a phase of more than a decade. The fluctuation ranges of minimum temperature were smaller, whereas the linear increases were higher than those for the mean temperature. (3) The diurnal temperature ranges (DTRs) of the two cities decreased; a certain phase of the decreases in DTR in the two cities was caused by decreases in the maximum temperature. (4) At a certain stage of urban development, owing to the shading effect of new high-rise buildings, the solar shortwave radiation reaching the Earth’s surface decreased, and anthropogenic heat generated by the energy consumption of buildings and urban human activities at that time was not sufficient to make up for the reduced shortwave radiation. This result may have led to the declines in the maximum temperature experienced by both cities. (5) Currently, the number of hot days and extremely hot days in the two cities has increased significantly compared with that a century ago, indicating that climate warming has an adverse impact on human settlements.

Optimization of Production–Living–Ecological Space in National Key Poverty-Stricken City of Southwest China

Trade-offs and conflicts among different sectors of production, living, and ecology have become important issues in regional sustainable development planning due to both the versatility and limitation of land resources, especially in poverty-stricken mountainous areas. This study builds an optimization model to assist policymakers in simulating land demand and allocation in the future. The model takes socioeconomic and demographic development into consideration and couples local planning policy with land use data from the perspective of system integration. The model was employed for a case study of Zhaotong city to optimize production–living–ecological (PLE) space. The results show that the model provides a feasible method to explore the sustainable development pattern of territorial space, especially in distressed regions.

Expressing carbon storage in economic terms: The case of the upper Omo Gibe Basin in Ethiopia

Terrestrial carbon storage is important for planning decisions regarding climate change. Therefore, modelling the spatial distribution of carbon storage and valuation can help restore the sustainability of the ecosystems. This study aimed at showing the spatial and temporal variations in carbon storage and valuation in the upper Omo Gibe Basin. Land use/cover and carbon pool data based on field data collection and laboratory analyses supported by GIS and remote sensing were used. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software was used for modelling carbon storage. The Global voluntary carbon market price and Tropical Economics of Ecosystems and Biodiversity (TEEB) data were used for describing carbon storage in economic terms. ANOVA was carried out to detect significant differences in carbon stock correlation with parameters. The results show that the annual carbon stock declined by 0.37 t/ha and the carbon market declined from USD 25.04 billion in 1988 to USD 24.01 billion in 2018. The highest loss of carbon storage and valuation was found in forest land followed by grazing land. Moreover, carbon stock was positively correlated with NDVI and habitat quality (p < 0.05). Slopes did not affect carbon stock (p > 0.05). This study helps promote and enhance carbon trading.

The Impacts of Urbanization to Improve Agriculture Water Use Efficiency—An Empirical Analysis Based on Spatial Perspective of Panel Data of 30 Provinces of China

China has witnessed accelerated urbanization since the reforms and open policies which began in 1978. This eventually resulted in increased residential water requirements and worsening water shortages, particularly in the current century. In the context of resource and environmental constraints, improving agricultural water use efficiency (AWUE) is a crucial issue to ensure food security, improve the ecological environment, and meet the needs of sustainable agricultural development. Based on the panel data of 30 provinces in China from 1999 to 2018, the article uses the Super-SBM model to measure the AWUE. Moreover, the study uses the entropy method to establish the urbanization evaluation index system from the dimensions of population, land, economy, measures the comprehensive level of urbanization development, and further constructs a dynamic spatial econometric model. We use the unconditional maximum likelihood estimation method to evaluate the impact of urbanization development on AWUE and its heterogeneity. The findings reveal that the AWUE considering undesired outcomes has generally shown a steady improvement, but there is ample space for resource conservation and environmental protection, and there are noticeable differences among regions. The decomposition of spatial effects shows that urbanization development in each region has a short-term positive effect on AWUE in the region and neighboring regions, and a long-term effect exists only in the western region. The impact of urbanization in different dimensions has been found that both land urbanization and economic urbanization contribute to the improvement of AWUE, while population urbanization helps to improve AWUE by improving the awareness level of the farmers.

Are there differences in the forces driving the conversion of different non-urban lands into urban use? A case study of Beijing

Examining the heterogeneous factors behind the conversion of various types of non-urban land into urban use is of great significance for controlling urban land expansion and formulating reasonable land use policies. Taking Beijing as an example, this study identified the spatial patterns of urban expansion in China's large cities and then explored the different driving factors behind its various sources. The results showed that, from 2001 to 2010, Beijing's urban land presented a compound expansion mode in which multiple spatial modes coexisted. Urban encroachment contributed differently to the loss of different non-urban lands. Cultivated land and ecological land were the main sources of newly developed urban land, of which the conversion was driven jointly by topography, location, transportation, socioeconomic development, and spatial planning. Moreover, the main factors behind the conversion of various land types varied: closing to existing built-up area and infrastructures increases the conversion probability of most land types; socioeconomic development has common but differentiated effects; governments at different levels have their influences on the conversion of different types of non-urban land. Based on the results, this study suggested the importance of considering varied approaches in managing non-urban lands to better controlling their conversion into urban use and the different roles that could be played by governments at various levels.

Continuous integration in urban social-ecological systems science needs to allow for spacing co-existence : This article belongs to Ambio's 50th Anniversary Collection. Theme: Urbanization

Urbanization brings benefits and burdens to both humans and nature. Cities are key systems for integrated social-ecological research and the interdisciplinary journal of Ambio has published ground-breaking contributions in this field. This reflection piece identifies and discusses integration of the human and natural spheres in urban social-ecological research using the following foundational papers as important milestones: Folke et al. (1997), Ernstson et al. (2010) and Andersson et al. (2014). These papers each take unique approaches that aim to uncover core properties-processes, structures, and actors-of urban systems and set them into mutual relationship. This piece will end with a forward-looking vision for the coming 50 years of urban sustainability and resilience study in Ambio.

A land-use decision approach integrating thermal regulation, stormwater management, and economic benefits based on urbanization stage identification

Driven by global climate change and urbanization, urban heat island (UHI) and urban storm flood (USF) have become the most frequent and influential hazards in recent decades. Land-use optimization can effectively cope with these hazards. However, the trade-offs between multi-hazard mitigation and economic development impose many limitations in practice. Furthermore, current region-based optimization methods no longer meet the precise management demand, and both subdivision and spatial heterogeneity identification have the potential for wider applicability. Hence, a systematic integration of climate adaptation and urban construction through land-use planning is urgently required. This paper proposes a new land-use decision approach for improving climate adaptability of urbanization. This approach involves multi-objective optimization, spatial subdivision, and urbanization stage identification, which enable the simultaneous achievement of environmental and economic benefits. Taking Xiamen as case study, the results showed that excessive pursuit of land economic output (LEO) limits the chance of mitigating UHI and USF. Improving the LEO per unit area of construction land could disrupt the link between land exploitation and the increasing side effects of climate hazards. Future urbanization hotspots in Xiamen will likely emerge at the urban fringe in Tong'an District and Xiang'an District. Within each developing unit, the upper limit of construction land was 81.06 hm² and the green space was recommended to be 7.29-21.94 hm². Construction land and bare land contributed most to UHI and USF, while forest and grassland were highly efficient in heat and runoff mitigation. The developed approach proved to be effective and practicable, especially for reducing the impacts of extreme UHI and USF.

Quantification of chlorophyll-a in typical lakes across China using Sentinel-2 MSI imagery with machine learning algorithm

Lake eutrophication has attracted the attention of the government and general public. Chlorophyll-a (Chl-a) is a key indicator of algal biomass and eutrophication. Many efforts have been devoted to establishing accurate algorithms for estimating Chl-a concentrations. In this study, a total of 273 samples were collected from 45 typical lakes across China during 2017-2019. Here, we proposed applicable machine learning algorithms (i.e., linear regression model (LR), support vector machine model (SVM) and Catboost model (CB)), which integrate a broad scale dataset of lake biogeochemical characteristics using Multispectral Imager (MSI) product to seamlessly retrieve the Chl-a concentration. A K-means clustering approach was used to cluster the 273 normalized water leaving reflectance spectra [Rrs (λ)] extracted from MSI imagery with Case 2 Regional Coast Colour (CR2CC) processor into three groups. The pH, electrical conductivity (EC), total suspended matter (TSM) and dissolved organic carbon (DOC) from three clustering groups had significant differences (p < 0.05**), indicating that water quality parameters have an integrated impact on Rrs(λ)-spectra. The results of machine learning algorithms integrating demonstrated that SVM obtained a better degree of measured- and derived- fitting (calibration: slope = 0.81, R² = 0.91; validation: slope = 1.21, R² = 0.88). On the contrary, the documented nine Chl-a algorithms gave poor results (fitting 1:1 linear slope < 0.4 and R² < 0.70) with synchronous train and test datasets. It demonstrated that machine learning provides a robust model for quantifying Chl-a concentration. Further, considering three Rrs(λ) clustering groups by k-means, Chl-a SVM model indicated that cluster 1 group gave a better retrieving performance (slope = 0.71, R² = 0.78), followed by cluster 3 group (slope = 0.77, R² = 0.64) and cluster 2 group (slope = 0.67, R² = 0.50). These are related to the low TSM and high DOC levels for cluster-1 and cluster-3 Rrs(λ) spectra, which reduce the influence of particle in red bands for Rrs(λ) signal. Our results highlighted the quantification of lake Chl-a concentrations using MSI imagery and SVM, which can realize the large-scale monitoring and more appropriate for medium/low Chl-a level. The remote estimation of Chl-a based on artificial intelligence can provide an effective and robust way to monitor the lake eutrophication on a macro-scale; and offer a better approach to elucidate the response of lake ecosystems to global change.

Does Financial Excess Support Land Urbanization—An Empirical Study of Cities in China

Most countries have experienced land urbanization, which is indispensable for financial support, especially for their financing function achievement through land appreciation and other channels in the urbanization process. By using 34 provincial capital (sub-provinces) cities in China as the sample, this paper studies the impact of finance on land urbanization construction based on the panel data from 2003 to 2018 under a differential GMM method; besides, the causes of excessive financial support and results generated on different regions are reported. Moreover, a moderate range of financial support for land urbanization is found under the influence of land finance. We obtain the following results: first, there is excessive financial support for land urbanization with regional differences exhibited; for instance, the eastern and central regions have an excessive financial support but the western region does not. Second, land urbanization with an excessive financial support correlates with financial efficiency, while the relatively large financial efficiency leads to the waste of a large number of financial resources. Third, financial support has a single and significant threshold effect on land urbanization construction, and finance has a promoting effect when land finance is less than the threshold value; otherwise, it has an inhibiting effect.

Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China

Land use land cover (LULC) transition analysis is a systematic approach that helps in understanding physical and human involvement in the natural environment and sustainable development. The study of the spatiotemporal shifting pattern of LULC, the simulation of future scenarios and the intensity analysis at the interval, category and transition levels provide a comprehensive prospect to determine current and future development scenarios. In this study, we used multitemporal remote sensing data from 1980–2020 with a 10-year interval, explanatory variables (Digital Elevation Model (DEM), slope, population, GDP, distance from roads, distance from the city center and distance from streams) and an integrated CA-ANN approach within the MOLUSCE plugin of QGIS to model the spatiotemporal change transition potential and future LULC simulation in the Greater Bay Area. The results indicate that physical and socioeconomic driving factors have significant impacts on the landscape patterns. Over the last four decades, the study area experienced rapid urban expansion (4.75% to 14.75%), resulting in the loss of forest (53.49% to 50.57%), cropland (21.85% to 16.04%) and grassland (13.89% to 12.05%). The projected results (2030–2050) also endorse the increasing trend in built-up area, forest, and water at the cost of substantial amounts of cropland and grassland.

Land-Use Change Impacts from Sustainable Hydropower Production in EU28 Region: An Empirical Analysis

Under the current European Union (EU) constitution approved in May 2018, EU countries ought to guarantee that estimated greenhouse-gas releases from land use, land-use change, or forestry are entirely compensated by an equivalent accounted removal of carbon dioxide (CO2) from the air during the period between 2021 and 2030. This study investigates the effect of sustainable hydropower production on land-use change in the European Union (EU28) region countries during 1990–2018, using the fully modified ordinary least squares (FMOLS). The results revealed that land-use change incline with an increase in hydropower energy production. In addition, economic growth, carbon dioxide emissions, and population density are found to be increasing land-use changes, while institutional quality is found to be decreasing land-use change significantly. The finding implies that land-use change in EU28 region countries can be significantly increased by mounting the amount of hydropower energy production to achieve Energy Union aims by 2030. This will finally be spread to combat climate change and environmental pollution. The findings are considered robust as they were checked with DOLS and pooled OLS. The research suggests that the EU28 countries pay attention to the share of hydropower in their renewable energy combination to minimize carbon releases. Politicians and investors in the EU28 region ought to invest further in the efficiency and sustainability of hydropower generation to increase its production and accessibility without further degradation of forest and agricultural conditions. The authorities of the EU28 region should emphasize on efficiency and sustainability of hydropower energy with land-use management to achieve the international commitments for climate, biodiversity, and sustainable development, reduce dependence on fossil fuel, and energy insecurity.

Changes in Ecosystems and Ecosystem Services in the Guangdong-Hong Kong-Macao Greater Bay Area since the Reform and Opening Up in China

Ecosystem services provide important support for the sustainable development of humans; these services are provided by various ecosystems, but they have been severely influenced by anthropogenic activities globally in the past several decades. To respond to the Sustainable Development Goals of the United Nations, this study investigated the changes in ecosystem structure and estimated the associated ecosystem services value (ESV) since China’s reform and opening-up policy in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of the most developed and populous areas of China. Our results showed that dramatic changes in ecosystem structure occurred in the GBA, characterized by unpresented construction land sprawl (an average of 148 km2/yr) and extensive farmland loss (an average of 111 km2/yr). The change size and rate of ecosystems from 2000 to 2010 was the biggest and fastest, followed by that from 1990 to 2000. The ESV of the study area showed an overall decreasing trend, declining from 464 billion yuan to 346 billion yuan. The ESV supported by forest ecosystems and water body ecosystems made dominant contributions to the total ESV, ranging from 92% to 95%. Strong spatial heterogeneity of the ESV of the GBA might be noted throughout the study period, with lower values in the central region and higher values in the surrounding region. To realize sustainable development in the GBA; this study strongly suggests that local governments, and the public, scientifically use various ecosystems and their services, focusing on vigorously protecting ecosystems with high and important ESVs, such as water body, wetland, forest, and farmland ecosystems.

The varying driving forces of urban land expansion in China: Insights from a spatial-temporal analysis

The impacts of socioeconomic development on urban land expansion in China vary across space and time; however, comprehensive investigation of this issue remains scarce in the existing literature. This study used a geographically and temporally weighted regression model (GTWR) to examine the spatiotemporally heterogeneous impacts of socioeconomic factors on urban land expansion in China using a newly available annual urban land-use dataset from 2000 to 2015. We found that although the eastern region has maintained its leading role (53.79%) in terms of urban expansion, the share of the central (20.34%) and western (16.13%) regions is gradually increasing. Cities with a higher administrative status tended to expand more rapidly; however, increasingly expansion has also taken place in the prefecture-level cities in recent years. We further found that Gross domestic product (GDP) growth, population density, and capital investment positively contributed to the expansion, although the directions and strengths of association between these factors and urban expansion varied across space and time. Industrial structure and foreign direct investment (FDI) showed a similar variation change trend, with the number of cities evidencing a negative relationship rapidly expanding and increasingly being seen not just in northwest China but also in the southeast during the study period. We also found that the correlation between public finance expenditure and urban expansion presented significant north-south differentiation. It is worth noting that governmental behavior plays a significant role in driving urban land expansion. Our empirical study confirmed the spatiotemporal heterogeneous effects of socioeconomic factors on urban expansion in China, providing useful insights for city governments and urban planners.

Urbanization can benefit agricultural production with large-scale farming in China

Urbanization has often been considered a threat to food security since it is likely to reduce the availability of croplands. Using spatial statistics and scenario analysis, we show that an increase in China's urbanization level from 56% in 2015 to 80% in 2050 would actually release 5.8 million hectares of rural land for agricultural production-equivalent to 4.1% of China's total cropland area in 2015. Even considering the relatively lower land fertility of these new croplands, crop production in 2050 would still be 3.1-4.2% higher than in 2015. In addition, cropland fragmentation could be reduced with rural land release and a decrease in rural population, benefiting large-scale farming and environmental protection. To ensure this, it is necessary to adopt an integrated urban-rural development model, with reclamation of lands previously used as residential lots. These insights into the urbanization and food security debate have important policy implications for global regions undergoing rapid urbanization.

Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

The urban agglomerations in the middle reaches of the Yangtze River (MYR-UA) are facing a severe challenge in reducing carbon emissions while maintaining stable economic growth and prioritizing ecological protection. The energy consumption related to land urbanization makes an important contribution to the increase in carbon emissions. In this study, an IPAT/Kaya identity model is used to understand how land urbanization affected carbon emissions in Wuhan, Changsha, and Nanchang, the three major cities in the middle reaches of the Yangtze River, from 2000 to 2017. Following the core idea of the Kaya identity model, sources of carbon emissions are decomposed into eight factors: urban expansion, economic level, industrialization, population structure, land use, population density, energy intensity, and carbon emission intensity. Furthermore, using the Logarithmic Mean Divisia Index (LMDI), we analyze how the different time periods and time series driving forces, especially land urbanization, affect regional carbon emissions. The results indicate that the total area of construction land and the total carbon emissions increased from 2000 to 2017, whereas the growth in carbon emissions decreased later in the period. Energy intensity is the biggest factor in restraining carbon emissions, followed by population density. Urban expansion is more significant than economic growth in promoting carbon emissions, especially in Nanchang. In contrast, the carbon emission intensity has little influence on carbon emissions. Changes in population structure, industrial level, and land use vary regionally and temporally over the different time period.

Spatial-Temporal Changes and Driving Factors of Land-Use Eco-Efficiency Incorporating Ecosystem Services in China

With rapid urbanization in China, the dramatic land-use changes are one of the most prominent features that have substantially affected the land ecosystems, thus seriously threatening sustainable development. However, current studies have focused more on evaluating the economic efficiency of land-use, while the loss and degradation of ecosystem services are barely considered. To address these issues, this study first proposed a land use-based input–output index system, incorporating the impact on ecosystem services value (ESV), and then by taking 30 provinces in China as a case study. We further employed the super-efficiency slacks-based model (Super-SBM) and the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model to explore the spatial–temporal changes and driving factors of the evaluated land-use eco-efficiency. We found that the evaluated ESV was 28.09 trillion yuan (at the price of 2000) in 2015, and that the total ESV experienced an inverted U-shaped trend during 2000–2015.The average land-use eco-efficiency exhibited a downward trend from 0.87 in 2000 to 0.68 in 2015 with distinct regional differences by taking into account the ESV. Our results revealed that northeastern region had the highest efficiency, followed by the eastern, western, and central region of China. Finally, we identified a U-shaped relationship between the eco-efficiency and land urbanization, and found that technological innovation made great contributions to the improvement of the eco-efficiency. These findings highlight the importance of the ESV in the evaluation of land-use eco-efficiency. Future land development and management should pay additional attention to the land ecosystems, especially the continuous supply of human well-being related ecosystem services.

Spatial Determinants of Land Conversion for Various Urban Use: A Case Study of Beijing

Studying the factors that influence the expansion of different types of construction land is instrumental in formulating targeted policies and regulations, and can reduce or prevent the negative impacts of unreasonable land use changes. Using land use survey data of Beijing (2001 and 2010), an autologistic model quantitatively analyzed the leading driving forces and differences in four types of construction land expansion (industrial, residential, public service, and commercial land types), focusing on the impact of spatial autocorrelation. The results showed that the influencing factors vary greatly for different types of construction land expansion; the same factor may have a different impact on different construction land, and both planning factors and spatial autocorrelation variables have a significant positive effect on the four types. Accordingly, the municipal government should consider the differences in the expansion mechanisms and driving forces of different construction land and formulate suitable planning schemes, observe the impact of spatial autocorrelation on construction land expansion, and guide spatial agglomeration through policies while appropriately controlling the scale of expansion. The methods and policy recommendations of this research are significant for urban land expansion research and policy formulations in other transition economies and developing countries.

Urban Public Green Space Equity against the Context of High-Speed Urbanization in Wuhan, Central China

This study examines the relationship between equity of public green space and urban expansion/sprawl under high-speed urbanization. Equity of urban public green space indicates the degree to which urban public green spaces are distributed spatially in an equal way, with regard to the spatial variation of residents’ “need” for green space. In emerging economies such as China, especially in developing or underdeveloped cities such as Wuhan, central China, rapid urban growth challenges the capacity of the state to provide infrastructure and services for its urbanites equally. In order to research the relationship between industrial development and green space equity under the background of rapid urbanization, the use of quantitative methods to more accurately measure the degree of spatial inequality is essential. In this study, the accessibility of urban public green space in Wuhan is examined based on the two-step floating catchment area method (2SFCA) method at multilevel radius; the urban public green space accessibility of Wuhan in 2013 and 2016 are acquired, and the link between changes in accessibility of urban public green spaces and urban expansion in Wuhan is discussed. It is found that industrial development takes precedence over green space. With its vigorous development, industrial land attracts increasing population, resulting in the drastic decline of the service capacity of green spaces, which is not conducive to the long-term development of the city.

Reoccupying Ecological Land for Excessively Expanded Rust Belt Cities in Traditional Grain Bases: An Eco-Economic Trade-Off Perspective

The optimization of ecological resource allocation is increasingly seen as a potential solution for urban revitalization and sustainable land use planning, and the key point is to assess and simulate the spatial arrangement of the ecological land. In this study, we proposed a conceptual framework with the aim of reoccupying ecological resources for rust belt cities from the perspective of eco-economic trade-offs. The ecological security pattern, the urban development pattern, and the ecological quality of cropland were constructed and evaluated to measure the development level of an ecological system and a socio-economic system. Furthermore, the results were used as the constraints that influenced land use distribution to simulate the ecological land reoccupation pattern. The suitable area, the preservation area, the configurable area, and the unsuitable area in the reoccupation pattern accounted for 6.94%, 49.97%, 28.17%, and 0.69%, respectively. Significantly, under strict cropland protection policies, the available space for ecological land expansion was heavily compressed. Therefore, the emphasis on agricultural production should be reexamined to release more space for ecological resources. This method could be an effective pathway to alleviate the pressures on urban and natural space caused by the competition between land-use activities, such as economic development, agricultural production, and ecological conservation. The findings are expected to promote urban revitalization, green agriculture, and sustainable social development in rust belt cities, and provide certain references for the utilization of land resources and regional policy making.

Assessing the coordination between economic growth and urban climate change in China from 2000 to 2015

The balance between economic growth and environmental protection has been a critical concern for sustainable urban development. However, among the multiple research efforts exploring the coordination between the two aspects, the widespread urban climate change has rarely been considered. This study encompasses urban climate change into the cross-system coupling analysis framework to assess its coordination with economic growth using the Coupling Coordination Degree (CCD) model. The two aspects are respectively represented using indicators of Surface Urban Heat Island Intensity (SUHII) and Gross Domestic Product (GDP). Specifically, China is selected as case study, and a total of 259 cities from the 2000-2015 period are analyzed. The spatio-temporal patterns of CCD are investigated through time series clustering to uncover its performance under diversified economic and climatic contexts. The regional inequality and spatial agglomeration effects are also examined. Results reveal significant spatio-temporal heterogeneity of CCD. Geographically, CCD varies from uncoordinated to high-level coordination. Wealthier cities in the eastern coastal region are significantly better coordinated than their inland counterparts. Temporally, the uptrend of CCD is not significant for most cities due to the relatively insufficient emphasis on urban heat island (UHI) mitigation in previous efforts. Evident spatial inequality and agglomeration patterns are also observed with slight downtrends. The spatio-temporal patterns of CCD revealed in this study indicate great necessity for the central government to develop policies suiting cities' special characteristics and contexts, and more efforts should be targeted on reducing regional imbalance. Hence, a nation-city-community policy skeleton is last outlined to enhance the pursuit of a more climate-friendly urban environment under rapid economic development. Overall, this study advances the understanding of economy-urban climate interactions and facilitates the future pursuit of better sustainable cities. The proposed workflow can be utilized for other countries with diversified urbanization processes and potentially used for comparison among different countries.

Spatial production or sustainable development? An empirical research on the urbanization of less-developed regions based on the case of Hexi Corridor in China

The relationships between spatial production, urbanization and sustainable development are becoming a focus of the international academic cycle. Urbanization dominated by spatial production driven by capital and power often produces and enlarges uneven development, which leads to multiple eco-environmental problems. Thus, the key to development lies in whether the pattern of urbanization is in harmony with the ecological environment. However, previous researches mainly concentrate on spatial production in developed countries or regions. The urbanization and sustainable development of less-developed regions, with complex and fragile ecological environments, are often overlooked. It is a new idea to explain the relationships and interactions between spatial production, urbanization and sustainable development based on less-developed regions by the theory of spatial production. The paper chooses the Hexi Corridor as a typical case, puts forward a conceptual framework and explores the process of spatial production from 2000 to 2017. The results reveal that urbanization in the Hexi Corridor is a multidimensional socio-spatial process: power and capital gave birth to a higher urbanization and accelerated the process of urbanization, however, the urban-rural gap between regions has not narrowed accordingly. Driven by comprehensive interests, local governments often take some extreme measures to forcefully promote the urbanization process, thereby violating the goals and requirements of sustainable development. At present, there is an urgent need to coordinate the relationship between urban and rural regions on different scales and transform the urbanization model from traditional spatial production to a new-type of urbanization with people-oriented and sustainable development.

Assessment on China's urbanization after the implementation of main functional areas planning

China has implemented main functional areas planning (MFAP) since 2010, which is essential for improving the efficiency of land space utilization and achieving sustainable urban development. Quantitative assessments of the urban development levels (UDLs) at the county level across China after the implementation of MFAP have not been well-documented. In this study, a unified indicator system was developed, and the UDLs of 2850 counties in China after MFAP implementation were evaluated. The results showed that MFAP played a positive role in urban development in China. The UDLs in China generally increased but showed obvious spatial differences. The higher UDLs were mostly found in the counties in the five urban belts, which reflects the overall urban layout of China. The UDLs were generally low in the western counties in comparison with those in the eastern part of China. The differences in the UDLs from east to west were greater than those from north to south. Moreover, the differences in the UDLs presented a spatial agglomeration effect. This study could offer insight into the refinement of MFAP in China and sustainable urban development in developing countries.

Trade-Offs between Economic Benefits and Ecosystem Services Value under Three Cropland Protection Scenarios for Wuhan City in China

Over the past few decades urbanization and population growth have been the main trend all over the world, which brings the increase of economic benefits (EB) and the decrease of cropland. Cropland protection policies play an important role in the urbanization progress. In this study, we assess the trade-offs between EB and ecosystem services value (ESV) under three cropland protection policy scenarios using the LAND System Cellular Automata for Potential Effects (LANDSCAPE) model. The empirical results reveal that trade-offs between EB and ESV in urbanizing areas are dynamic, and that they considerably vary under different cropland protection policy scenarios. Especially, the results identify certain “turning points” for each policy scenario at which a small to moderate growth in EB would result in greater ESV losses. Among the three scenarios, we found that the cropland protection policy has the most adverse effect on trade-offs between EB and ESV and the results in the business as usual scenario have the least effect on the trade-offs. Furthermore, the results show that a strict balance between requisition and compensation of cropland is an inappropriate policy option in areas where built-up areas are increasing rapidly from the perspective of mitigating conflict between EB and ESV and the numbers of cropland protection that restrained by land use planning policy of Wuhan is a better choice.

Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100

In response to a growing demand for subnational and spatially explicit data on China’s future population, this study estimates China’s provincial population from 2010 to 2100 by age (0–100+), sex (male and female) and educational levels (illiterate, primary school, junior-high school, senior-high school, college, bachelor’s, and master’s and above) under different shared socioeconomic pathways (SSPs). The provincial projection takes into account fertility promoting policies and population ceiling restrictions of megacities that have been implemented in China in recent years to reduce systematic biases in current studies. The predicted provincial population is allocated to spatially explicit population grids for each year at 30 arc-seconds resolution based on representative concentration pathway (RCP) urban grids and historical population grids. The provincial projection data were validated using population data in 2017 from China’s Provincial Statistical Yearbook, and the accuracy of the population grids in 2015 was evaluated. These data have numerous potential uses and can serve as inputs in climate policy research with requirements for precise administrative or spatial population data in China.

Measurement(s)	population
Technology Type(s)	computational modeling technique
Factor Type(s)	age • sex • education level • Shared Socioeconomic Pathway • year • province
Sample Characteristic - Location	China

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11898405

A comparative analysis of urban impervious surface and green space and their dynamics among 318 different size cities in China in the past 25 years

Urban impervious surface (UIS) and urban green space (UGS) fractions in a city are essential indicators in supporting urban planning and management. However, little is known about the dynamics of urban expansion and the resultant UIS/UGS fraction in different size cities in China over time. We comparatively analyzed the urban expansion, UIS/UGS, and their dynamics among 318 different size cities during 1990-2015 derived from the China Land Use/cover Datasets (CLUDs) and the UIS/UGS datasets. The results indicate that the urban expansion area for the 318 cities increased by 2.32 × 10⁴ km² during 1990-2015, with an average growth percentage of 4.37%. Megacities experienced dramatic expansion between 1990 and 2000, and the urban expansion of large and medium cities increased rapidly in the following decade. During 2010-2015, the urban expansion of small cities notably increased. Meanwhile, the proportion of the UIS fraction in newly expanded urban land continuously decreased during 1990-2015. Compared to the other three size cities, the proportion of the UGS fraction in megacities was the highest (24.55%) in 1990 and then increased (27.99-31.97%) in newly expanded urban land during 1990-2015 due to ecological construction. Thus, more attention should be paid to the dynamics of urban expansion, especially in small cities. The proportions of UGS in large, medium, and small cities are relatively low, and urban environment needs to be improved for greenness and livability in the future.

Monitoring Three-Decade Expansion of China’s Major Cities Based on Satellite Remote Sensing Images

As the largest developing country, China has experienced dramatic urban expansion since the “reform and opening-up” policy started at the end of the 1970s. In this paper, we monitor three decades of urban expansion in China’s 36 major cities, based on the spectral mixture analysis of remotely sensed satellite images. The results demonstrated that these major cities have expanded by 5.85 times from 1986 to 2015, with 15.51 km2 average expansion area per city per year. We found the urban expansion trajectories showed three different modes, i.e., exponential, linear and s-shaped, which were closely related to the city development level. In the old city zones, however, there was an interesting common tendency of the impervious surface area (ISA) first increasing and then decreasing, which could be largely attributed to the phenomenon of urban village reconstruction in China’s cities. Based on the Granger Causality Test (GCT), the interaction between urban ISA and Gross Domestic Product (GDP) per capita (GDPPC) suggested that the former was the driver of the latter. Meanwhile, taking the Yangtze River as the division between north and south China, there exists a north–south territorial differentiation for the interaction between ISA and total population at the year-end (TP).

Daily Precipitation Threshold for Rainstorm and Flood Disaster in the Mainland of China: An Economic Loss Perspective

Exploring precipitation threshold from an economic loss perspective is critical for rainstorm and flood disaster risk assessment under climate change. Based on the daily gridded precipitation dataset and direct economic losses (DELs) of rainstorm and flood disasters in the mainland of China, this paper first filtered a relatively reasonable disaster-triggering daily precipitation threshold (DDPT) combination according to the relationship between extreme precipitation days and direct economic loss (DEL) rates at province level and then comprehensively analyzed the spatial landscape of DDPT across China. The results show that (1) the daily precipitation determined by the combination of a 10 mm fixed threshold and 99.3th percentile is recognized as the optimal DDPT of rainstorm and flood disasters, and the correlation coefficient between annual extreme precipitation days and DEL rates reached 0.45 (p < 0.01). (2) The optimal DDPT decreases from southeast (up to 87 mm) to northwest (10 mm) across China, and the DDPTs of 7 out of 31 provinces are lower than 25 mm, while 5 provinces are higher than 50 mm on average. These results suggest that DDPTs exist with large spatial heterogeneity across China, and adopting regional differentiated DDPT is helpful for conducting effective disaster risk analysis.

Fiscal Incentives and Sustainable Urbanization: Evidence from China

Fiscal incentives can affect governments’ behavior and further influence economic and social development. Due to the specific conditions of the household registration system and the land ownership system in China, the urbanization process is dominated by the government. This article conceptually and empirically investigates the influence of fiscal incentives on sustainable urbanization. We theoretically analyze the fiscal reasons why land urbanization occurs faster than the population urbanization. Then we employ panel data of 30 provinces and autonomous regions in China from 2000 to 2012 to discuss the impact of fiscal incentives on urbanization from four aspects: fiscal revenue, types of taxes, fiscal self-financing rate, and tax losses. The econometric results show that both the local tax revenue and fiscal self-financing rate have a significantly negative effect on the gap between land urbanization and population urbanization. The larger the proportion of business tax, the smaller the gap, and vice versa for value-added tax. The greater the local governments’ tax losses, the greater the gap. The results explain why local governments in China choose land urbanization rather than population urbanization from the perspective of fiscal incentives.