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Copyright of China Quarterly is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we focus on Guangdong province, which is a frontier area of Reform and Opening up, and analyze the variation of urban and rural temperature to detect the urbanization warming effect from 1951 to 2018, based on the daily temperature data of 85 weather stations. We classified the metrological stations into urban and rural stations according to the urbanization population size, population density and urban built-up area data. The combined methodology of mathematical statistics, trend analysis, urban/rural station comparison and spatial analysis was adopted to reveal the urbanization warming and its spatial–temporal heterogeneity. The results show that the warming process in Guangdong Province is very complex and has high temporal and spatial heterogeneity. From 1951 to 2018, the average temperature in the coldest month in Guangdong Province increased with the fastest (0.27 °C/10a) rate, and the annual average temperature increased slightly faster than the average temperature in the warmest month (0.15 °C/10a vs. 0.12 °C/10a). The comparative study on the temperature of urban and rural stations shows that the temperature increase rate of urban stations is faster than that of rural stations (0.30 °C/10a vs. 0.23 °C/10a), especially the average temperature in the coldest month, which is most significantly driven by urbanization, and the contribution rate of urbanization is about 24.09% in general. Affected by the background climate and the stages of urbanization, the warming effect of urbanization fluctuates obviously in different periods. Stronger urbanization effect can be witnessed during 1980–2000, when the urbanization developed into mid-level with highest rate. The spatial differentiation of urbanization warming effect is prominent. The temperature of urban stations in Eastern Guangdong increases most rapidly. The urbanization contribution rates to the coldest month average, annual average and the warmest month average temperature reach 33.86%, 25.70% and 17.64%, respectively, which are around 1.69, 1.50 and 1.19 times that of the Pearl River Delta. The average temperature of the warmest month in Western Guangdong shows a weak cooling effect. Multi-faceted, multi-level regulation of sustainable urbanization is the key to mitigating the warming caused by urbanization. [ABSTRACT FROM AUTHOR]

While rapid urbanization promotes social and economic development, it exacerbates human outdoor thermal comfort, which increases the risks to human health. This paper uses four thermal comfort indices and multiple satellite observations to explore the urbanization effect on summer heat stress in Guangdong from 1979–2018, a coastal province of China. Two types of thermal comfort index are used here, namely the direct thermal comfort index (Heat Index, HI; Temperature–Humidity Index, THI; Discomfort Index, DI) and the physiological thermal comfort index (Universal Thermal Climate Index, UTCI). We compare the differences in the urbanization effects on the changes in the three direct thermal comfort indices (HI, THI, and DI) and a physiological thermal comfort index (UTCI). The results show that all four thermal comfort indices indicate an overall warming trend. Of them, urban sites show a higher warming trend than rural sites, indicating that heat stress changes are significantly influenced by urbanization from 1979–2018, which is consistent with the effect of urbanization on surface air temperature. However, except for the UTCI, this warming of direct thermal comfort indices affected by urbanization has become insignificant under the regional vegetation greening from 2004–2018 (also consistent with surface air temperature). This is primarily attributed to the different effects of wind speed on the physiological thermal comfort index in urban and rural areas: Decreasing wind speeds in urban areas lead to an increase in UTCI, while wind speeds in rural areas increase instead and decrease UTCI, thus widening the UTCI differences between urban and rural areas. Our results indicate that urbanization has a different effect on thermal comfort indices. When using the thermal comfort index, it is necessary to consider that different thermal comfort indices may bring different results. UTCI considers more factors that affect human heat perception, so it can better describe human outdoor thermal comfort. It also highlights the importance of urban ventilation and urban greenness in mitigating urban outdoor thermal comfort in the sustainable construction of future urbanization in coastal cities. [ABSTRACT FROM AUTHOR]

The Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration, one of the world's four largest bay area urban agglomerations, occupies an important position in China's national development. In this paper, the expansion hotspot model, an urbanization index, a gravitation model, and a socioeconomic location model are used to explore changes in the characteristics of the urban agglomeration in the Guangdong–Hong Kong–Macao Greater Bay Area. The research results can provide decision support for government urban agglomeration planning. The research reveals the following. (1) In the skeleton maps of the expansion hotspots in the Guangdong–Hong Kong–Macao Greater Bay Area, Jiangmen shows an irregular shape, Shenzhen shows an irregular H-shape, Dongguan and Hong Kong show a shape somewhat between a circle and a star, Zhongshan shows a gourd-shape, and Guangzhou, Foshan, Huizhou, Zhaoqing, and Zhuhai show a polygon shape. (2) In 2000, 2010, and 2018, the urbanization index for the urban agglomerations were 41.78%, 50.87%, and 54.41%, respectively. The level of economic development, household registration policy, and urban planning are important factors affecting the development of urbanization. (3) The city quality and spatial connection strength of urban agglomeration have significant spatial nonequilibrium distribution characteristics. The total city quality of Shenzhen, Hong Kong, and Guangzhou accounted for more than 41.5% of the total city quality of the city cluster at the same time, and that of the east coast of the Pearl River is much stronger than the west coast. (4) There are "faults" in the socioeconomic location of the 11 cities in the urban agglomeration, with significant polarization. The socioeconomic locations of Jiangmen, Huizhou, and Zhaoqing have been below the reasonable socioeconomic location range in the past 20 years. [ABSTRACT FROM AUTHOR]

Coastal areas are usually considered as pioneering areas for economic development and reform due to their unique geographical locations and ecological conditions. Correspondingly, rapid urbanization in coastal urban agglomerations has resulted in population concentration and land use/cover change (LUCC), leading to the decline of habitat quality and biodiversity. However, few studies have quantitatively explored the impacts of urban agglomeration expansion in coastal zones on habitat quality. Taking the Guangdong-Hong Kong-Macao-Great Bay Area (GBA) as a case study, we applied the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess the habitat quality based on land use data obtained from remote sensing images from 1980 to 2020 and developed a geographically weighted regression model to quantitatively analyze the response of habitat quality to urbanization. The results showed that (1) LUCC in the GBA was dramatic from 1980 to 2020, dominated by the shift from various land use types to construction land, which led to increased fragmentation; (2) the overall habitat quality showed a decreasing trend, characterized by low values in the central part and high values in the surrounding area; (3) population and construction land such urbanization elements had a more significantly negative effect on habitat quality changes, while the relationships among slope, road distance, and habitat quality changes were complex. Based on above analysis, this paper suggests that future land management in the GBA should develop in the direction of intensification, refinement, and regional integration. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Archaeology is the property of Agricultural Archaeology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the equivalent factor table of terrestrial ESV in China in 2010, this paper proposes a regionalized and interannual ESV correction method. Taking southern Guangzhou as the study area, which is located in the geometric center of the Guangdong–Hong Kong–Macao Greater Bay Area (GHM GBA), this study evaluated the ecosystem service equivalent value (ESEV) and ecosystem service value (ESV) and their changes in 2004, 2010 and 2016 and carried out grid processing, trend analysis and global/local spatial autocorrelation of the ecosystem service density (ESD) in the study area by using the Natural Resources Integrated Database of Guangdong Province (NRIDB). The results of data processing and spatial analysis computed in this study were published as Web services through the NRIDB and displayed in the visualization front-end. The results showed that (1) during 2004–2016, the urbanization process in the study area led to the expansion of built-up land, which occupied a large amount of ecological land and resulted in a decreasing trend of ESV. (2) Benefiting from socioeconomic development, the standard value volume of the ESEV (D value) kept increasing, which resulted in an increasing trend for the total ESV. (3) The spatial autocorrelation analysis results of ESD indicated that the spatial distribution of ESD in the study area had strong spatial agglomeration and positive spatial correlation. With the progress of urbanization and increases in research scale and interval distance, the spatial difference in ESD became larger over time. The research results provide a reference for the coordinated allocation of natural resources and environmental protection in the GHM GBA. [ABSTRACT FROM AUTHOR]

Guangdong Province is an important ecological barrier and the primary pillar of economic development in China. Driven by high-speed urbanization and industrialization, unreasonable land use change in Guangdong Province has exacerbated habitat degradation and loss, seriously affecting habitat quality. Thus, taking Guangdong Province as the study area, this paper quantifies the response of habitat quality on land use change using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and constructs a contribution index (CI). The following conclusions can be drawn from the results: (1) The habitat quality exhibits a spatial distribution pattern of low quality in plain areas and high quality in hilly and mountainous areas. (2) The annual average habitat quality gradually decreases from 1980 to 2020, with a total decrease of 0.0351 and a reduction rate of 4.83%; (3) The impact of land use change on habitat quality is mainly negative, and the habitat quality mainly decreases by the conversion of forest land to orchards, paddy field to urban land, and forest land to dry land, with CI values of −24.09, −11.67, and −8.04, respectively. Preventing the destruction of natural forests, increasing the diversity of plantation orchards, and rationalizing and mitigating the growth rate of construction land are key to maintaining and improving the habitat quality. [ABSTRACT FROM AUTHOR]

This paper analyses rural migrant children's access to public schools in urban China, focusing on the implications of the recent introduction of points systems for apportioning school places. This approach, first piloted by Zhongshan city in Guangdong province from 2009, has steadily been extended nationwide. Here, we analyse the reasons for its spread and for divergence in its implementation in various urban districts. Notwithstanding rhetorical claims that points systems promote "fairness" or "equality" in the treatment of migrants, our analysis suggests that they maintain or even exacerbate the stratification of urban society, lending new legitimation to the hierarchical differentiation of entitlements. This is consistent with the aim of the 2014 "New national urbanization plan" to divert urban growth from megacities towards smaller cities. However, we argue that the use of points systems should also be seen in the context of an evolving bureaucratic-ideological project aimed at more rigorously monitoring and assessing China's entire population, invoking the logic of meritocracy for the purpose of control. [ABSTRACT FROM AUTHOR]

This paper explores the question of extended urbanization by arguing for the need to overcome dualistic views to properly address the political specificities of urbanization in China. To this end, this paper understands state-territorial relations as a process of étatization by drawing on the particular literature on the role of the party-state in urbanization. Through a brief history of Guangdong, it elaborates on the political modalities of territorialization through China's administrative rank system. This has enabled the party-state to mediate the production of urban space. From this, I arrive at the concept of "territorially-nested urbanization", moving beyond limited accounts of hierarchical state powers in Chinese urban studies. Next, from a short periodization of Dongguan's urbanization, the paper exemplifies how a particular mode of territorialization has evolved into tense relationships between the city and towns in the ongoing dilemma of multi-centered versus concentrated direction of urbanization. Based on insights from in-depth fieldwork, the last part of this paper illustrates the contradictory mobilization of village collectives within extended state power through local government, and the development of villagers' politics and activism in contested land transformations. [ABSTRACT FROM AUTHOR]

The urbanization impacts on surface air temperature (SAT) change in the Guangdong‐Hong Kong‐Macau region (GHMR) from 1979 to 2018 are examined using homogeneous surface observations, reanalysis, and remote sensing. Results show that the warming due to urbanization tends to be smaller or insignificant as the spatial scale increases. The urbanization contribution to the local warming can reach as high as 50% in the center of each metropolis, remains high (~25%) in the Greater Bay Area (GBA), and decreases to about 10% in the whole GHMR. The warming in GHMR is nearly uniform throughout the day, and therefore, the observed trend of the diurnal temperature range (DTR) is not statistically significant. However, the urbanization contribution exhibits distinct seasonal variations, large in summer and autumn while smaller in winter and spring. Plain Language Summary: The Guangdong‐Hong Kong‐Macau region (GHMR), especially the Greater Bay Area (GBA), is a region typical of China's economic development and rapid urbanization. To precisely assess how much the urbanization contributes to the regional warming, we comprehensively evaluate the urbanization warming and its uncertainties in GHMR by using more careful processed and assessed data (observations, reanalysis, and remote sensing) and different analysis methods. The results show that the warming due to urbanization tends to be smaller as the spatial scale increases: The contribution to the local warming can reach as high as 50% in the metropolis, remains high (~25%) in GBA, and decreases to about 10% in GHMR. In addition, this paper systematically discusses the uncertainty in urbanization contribution detection, which was often neglected in the past detection. Based on the significance tests, urbanization warming is nearly uniform throughout the day, while it exhibits distinct seasonal variation. Our study also has important implications for understanding the influences of human activities on regional climate change for other regions experiencing rapid urbanization processes. Key Points: The contribution of urbanization to regional warming is robust in homogenized SAT data and ERA5 reanalysis using different methodsThe spatial scale dependence of urbanization warming is investigated; the contribution of urbanization warming decreases when the scale increasesUrbanization contribution exhibits distinct seasonal variation based on the uncertainty assessment [ABSTRACT FROM AUTHOR]

Urbanization brings great enrichment to human production and life, but also has certain environmental impact on the area where the city is located. Many studies have revealed the negative effects of urbanization on the ecological environment of urban or urban agglomerations, especially in the early stage of urbanization, but there are few studies on the impact on the peripheral ecological space environment. Will the peripheral environment be better off with less human interference as people move to cities during urbanization? In order to answer this question, we took the Guangdong-Hong Kong-Macao Greater Bay Area, the most economically dynamic area in China, as an example to explore the relationship between impervious changes of urban agglomerations monitored by remote sensing in the Bay Area and ecological indicators of forest and grassland in Guangdong Province outside the Bay area. The results showed that:(1) in the past 30 years, the area of grassland outside the bay area did not change regularly, while the area of forest decreased year by year. The landscape indices of forest and grassland were gradually fragmented and discrete. Moreover, the distribution of Fraction Vegetation Coverage (FVC) of forest and grassland has changed since before urbanization. (2) Through correlation analysis, it is found that the changes in forest area and the landscape index of forest and grassland are strongly correlated with the development of urbanization in the Greater Bay Area. This shows that the process of urbanization in the Greater Bay Area will have a non-negligible impact on the peripheral environment. In the process of urban development, we should not only focus on the inner city but also consider the outer environment of the city. [ABSTRACT FROM AUTHOR]

Since 2000, Guangdong has continued to increase investment in infrastructure construction in rural areas, and indicators for the main construction in the rural areas have met the requirement of remediation. However, the return visit has found that there are still huge gaps in urban and rural settlements. Therefore, this paper comprehensively investigated and scientifically analyzed existing problems in the rural settlements in Guangdong, and proposed that urbanization was the fundamental way to improve the rural settlements by carrying out the strategic planning of the provincial urbanization space and formulating different policies in urban areas and rural areas. Specifically, in the urban areas, the municipal government could coordinate the urban-rural development, formulate a transformation and development plan for villages to be urbanized, and classify the villages into three types in accordance with the degree of influence of villages affected by the cities to set different planning policies. In the rural areas, the provincial government was responsible for rural protection and development together with the county government, and divided the villages into three types according to the regional planning goals to implement different supporting policies for them. [ABSTRACT FROM AUTHOR]

The citizenization of peasant migrants is key to understanding China's long-term urban-rural imbalance and ongoing rural transformations. The majority of existing literature focused on structural/institutional or agentive/subjective factors, while an integrated perspective examining both structural and agentive factors related to the citizenization process is rarely seen. Borrowing theories from the strategic-relational approach, this paper unfolds the matching and mismatching mechanisms between the policy design and peasant migrants' intentions of citizenization. Drawing on a case study in China's Guangdong Province, this study finds that: (1) citizenization policies prefer to offer citizenship to the new generation of peasant migrants, which matches the age structure of peasant migrants; (2) although municipal governments are prone to attract young peasant migrants with high educational level and strong competitiveness, peasant migrants generally have a relatively low educational level and weak professional training; (3) the high threshold of citizenization in mega-metropolitan and metropolitan cities mismatches peasant migrants' preference towards the first-tier cities. This paper describes the matching and mismatching mechanisms between structure and agency associated with the citizenization of peasant migrants. The policy reflections proposed by this study point towards enhancing nearby urbanization and in situ urbanization, so as to increase the attraction of young peasant migrants by ordinary cities. Besides, this paper calls for the promotion of rural-urban co-governance, making rural revitalization an alternative and supplement to the urbanization driven by rural-urban migration. • The strategic-relational approach is a critical perspective for understanding citizenization. • As a progressive and dynamic process, the citizenization of peasant migrants intersects with local strategies of urbanization. • Governments should realize that ordinary cities are critical places for most peasant migrants to realize citizenization. [ABSTRACT FROM AUTHOR]

As the population and industries continue to gather in cities, such cities face acute shocks caused by various natural disasters and high pressure caused by human interference. The means of accurately assessing and improving the level of urban resilience (UR) to cope with disturbances and shocks, enhance regional resilience, and improve sustainable urban development has become a hot topic. In this study, we constructed an UR assessment framework using "social-economic-institutional-ecological-engineering" to explore the dynamic evolution of spatial and temporal patterns in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China, to reveal the main factors influencing the evolution of this spatial pattern and the strength and interaction mechanisms among such influencing factors and to dynamically simulate the spatial and temporal evolution characteristics in the next 16 years. The results show that from 2000 to 2019, the difference in UR level in the GBA is obvious. Hong Kong and Macao are obviously ahead of other cities, and the comprehensive resilience level of Guangzhou and Shenzhen cities in the mainland is developing rapidly. The difference in per capita consumption capacity, industrial structure optimization, foreign trade vitality, infrastructure support and other factors are the main causes of the spatial differentiation of UR in the GBA. In the future, the UR level of the GBA urban agglomeration will show an overall upwards trend. The three development poles of Guangzhou-Foshan, Shenzhen-Hong Kong, and Zhuhai-Macao have obvious advantages in spatial distribution. The results of the study can enrich regional UR research, and also provide theoretical references to facilitate the high-quality development of the area. [Display omitted] • We constructed a "social-economic-institutional-ecological-engineering" urban resilience assessment framework. • The paper developed an evaluation system for the urban resilience to reveal its spatial and temporal evolution patterns. • The main factors influencing the evolution of the spatial patterns of urban resilience is investigated. • Our results provide a basis for the development of comprehensive management framework for urban resilient. [ABSTRACT FROM AUTHOR]

This paper studies the urbanization impacts on tourism development in four regions Guangdong province, using time-series data of Guangdong province in China in 1996–2011. Urbanization has been operationalized by population, economic, geographical landscape and social cultural dimensions. This study suggests that urbanization, though in general increases tourism development, does not affect different regions in Guangdong uniformly. Tourism development in different regions will receive different impacts from urbanization. Therefore, policy-makers, while promoting tourism development, should be aware of the different levels of impact of urbanization towards tourism development. [ABSTRACT FROM PUBLISHER]

China has high biodiversity and is rapidly urbanizing. However, there is limited understanding of how urban expansion in the country is likely to affect its habitats and biodiversity. In this study, we examine urban expansion patterns and their likely impacts on biodiversity in China by 2030. Our analysis shows that most provinces are expected to experience urban expansion either near their protected areas or in biodiversity hotspots. In a few provinces such as Guangdong in the south, urban expansion is likely to impinge on both protected areas and biodiversity hotspots. We show that policies that could facilitate the integration of natural resource protection into urban planning exist on paper, but the prevailing incentives and institutional arrangements between the central and local governments prevent this kind of integration. Removing these obstacles will be necessary in order to safeguard the country's rich biodiversity in light of the scale of urbanization underway. [ABSTRACT FROM AUTHOR]

Purpose: There is a close relationship between FDI and the level of urbanization. the objective of this research is to analyze the relationship between FDI and the level of urbanization in Jiangsu and Guangdong provinces in costal areas. Design/methodology/approach: The author uses the modern econometric methods by panel unit root test, cointegration test, random effects models and fixed effects models, and the data of FDI (2000-2012), urbanization rate, industrial structure and regional GDP of Nanjing, Xuzhou, Suzhou, Wuxi and other 13 cities in Jiangsu Province, Guangzhou, Shenzhen and other 19 cities in Guangdong province, researches the relationship between FDI and urbanization rate. Findings: Models show, FDI was closely correlated with urbanization rate in Jiangsu province and Guangdong province, the highly correlated with industrial structure, while it negatively correlated with the growth of GDP, and the degree of correlation is not high in Jiangsu province, but the high negative correlation in Guangdong province. The results shows the industrial structure and the urbanization rate mainly cause FDI growth. Research limitations/implications: There are many provinces in costal areas of China, this paper just research the relationship between FDI and the level of urbanization in Jiangsu province and Guangdong province, there are some limitations in the study areas and results. Originality/value: The study was the first to successfully apply on random effects model and fixed effects model to study the relationship between FDI and the level of urbanization in coastal areas by competitive analysis. Guangdong and Jiangsu province are the most developed regions, they are the most representative provinces in costal areas of China. Taking these two province as an example, we can analyze the relationship between FDI and the level of urbanization in central and western regions. [ABSTRACT FROM AUTHOR]

Promoting urban green growth necessitates a dual focus on reducing carbon emissions and fostering high-quality development. However, the body of research on the coupling relationship between high-quality urban development and carbon emissions remains remarkably limited. Taking Guangdong province as an example, this study strived to establish a comprehensive evaluation system for high-quality urban development encompassing economic, societal, and ecological dimensions and further conducted an in-depth examination of the spatiotemporal pattern and driving forces of coupling coordination degree between high-quality urban development and carbon emission intensity during 2000–2017. The coupling coordination degree in Guangdong province has shown continuous growth, transitioning from moderate incoordination to moderate coordination. The coupling coordination degree showed the overall spatial distribution characteristics of "high in southeast and low in others", with Zhuhai, Zhongshan, Foshan, Guangzhou, Dongguan, and Shenzhen as the core. Notably, technological advancement, environmental governance, and economic development emerge as pivotal factors that positively affect carbon emission intensity reduction, environmental quality improvement, and coupling coordination enhancement. This research provides valuable insights for achieving harmonized high-quality development in Guangdong province involving policies of regional differences, industrial competitiveness, and new-type urbanization. [ABSTRACT FROM AUTHOR]

Complex interaction between urbanization and climate change has been showing significant impacts on natural and human ecosystems. Increasing urban flooding and waterlogging are associated with urbanization. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) experiences a rapid and extensive urbanization, leading to intensified land use and cover changes. Concurrently, the frequent occurrence of extreme precipitation events pose great challenges of urban flood control and water resource management to GBA. This research statistically analyzes the spatiotemporal evolution characteristics of precipitation extremes from 1979–2018 which relates to the urbanization in GBA using various statistical methods including the Mann-Kendall test, bivariate Moran's test, and Spearman correlation analyses. The findings indicate that the impervious surface area in GBA exhibited a nonlinear growth trend from 1985–2018, particularly concentrated in the five major cities, i.e., Guangzhou, Foshan, Dongguan, Shenzhen, and Zhongshan. GBA urbanization can be categorized into three stages including Stage I (pre-1990, no urbanization), Stage II (1991–2009, rapid urbanization), and Stage III (2010–2018, slow urbanization). Compared to cities with low urbanization, the highly urbanized areas of GBA, including Guangzhou, Foshan, Zhongshan, and Dongguan, show statistically significant increases in precipitation extremes. The increasing trends of seven extreme precipitation indices show significant positive, spatiotemporal correlations with the change rate of urbanization in GBA. Moreover, the influence of urbanization on precipitation extremes in highly urbanized regions of the GBA is progressively strengthened along with urban development. During the stage of slow urbanization, urbanization contributes to 56.13% of increase in annual precipitation totals in GBA, and its contribution to increases in precipitation extremes ranges from 20–80%. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, it is important to reasonably evaluate the development status of the regional manufacturing industry. Given this, this article expands the evaluation indicators of urban advanced manufacturing (UAM) from the perspective of the push–pull-mooring (PPM). Then, it uses a machine learning (ML) method to predict the evaluation results of other cities through a small amount of sample data. The results show that: (1) From the current development status of UAM in Guangdong Province (GD), cities in the Pearl River Delta region occupy a dominant position. However, cities in eastern, western, and mountainous regions have strong development potential and lead cities. Therefore, each region has cities with high levels of development and has a demonstrative role. (2) By comparison, it was found that the overall development level of UAM in GD is not significantly different from that of the Yangtze River Economic Belt. However, due to significant differences in their extreme values, the proportion of cities above the average in the overall population is relatively small. This indirectly proves that GD's UAM not only has a phased nature, but also has a demonstrative role. (3) The prediction effect of the perceptron model is better than other methods. Although neural network models have better prediction performance than other machine learning models, they should not overly rely on complex network structure prediction data. By comparing the results, the reliability is verified. Finally, according to the life cycle theory, we propose a targeted development path for different UAM. [ABSTRACT FROM AUTHOR]

Accurately identifying the boundary of urban clusters is a crucial aspect of studying the development of urban agglomerations. This process is essential for comprehending and optimizing smart and compact urban development. Existing studies often rely on a single category of data, which can result in coarse identification boundaries, insufficient detail accuracy, and slight discrepancies between the coverage and the actual conditions. To accurately identify the extent of urban clusters, this study proposes and compares the results of three methods for identifying dense urban areas of three major agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area. The study then integrates the results of these methods to obtain a more effective identification approach. The social economic method involved extracting a density threshold based on the fused nuclear density of socio-economic vitality data, including population, GDP, and POI, while the remote sensing method evaluated feature indices based on remote sensing images, including the density index, continuity index, gradient index, and development index. The traffic network method utilizes land transportation networks and travelling speeds to identify the minimum cost path and delineate the boundary by 20–30 min isochronous circles. The results obtained from the three methods were combined, and hotspots were identified using GIS overlay analysis and spatial autocorrelation analysis. This method integrates the multi-layered information from the previous three methods, which more comprehensively reflects the characteristics and morphology of urban clusters. Finally, the accuracy of each identification result is verified and compared. The results reveal that the average overall accuracy (OA) of the three areas delineated by the first three methods are 57.49%, 30.88%, and 33.74%, respectively. Furthermore, the average Kappa coefficients of these areas are 0.4795, 0.2609, and 0.2770, respectively. After performing data fusion, the resulting average overall accuracy (OA) was 85.34%, and the average Kappa coefficient was 0.7394. These findings suggest that the data fusion method can effectively delineate dense urban areas with greater accuracy than the previous three methods. Additionally, this method can accurately reflect the scope of urban clusters by depicting their overall boundary contour and the distribution of internal details in a more scientific manner. The study proposes a feasible method and path for the identification of urban clusters. It can serve as a starting point for formulating spatial planning policies for urban agglomerations, aiding in precise and scientific control of boundary growth. This can promote the rational allocation of resources and optimization of spatial structure by providing a reliable reference for the optimization of urban agglomeration space and the development of regional spatial policies. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization in China, the urban surface thermal environment has undergone significant changes. This work aims to calculate the urban thermal comfort index using a temperature and humidity model with the land surface temperature and relative humidity. It also aims to explain the association between the land use/land cover change (LUCC) and urban surface thermal environment of the Beijing–Tianjin–Hebei (BTH) Region, the Guangdong–Hong Kong-Macao Greater Bay Area (GBA) and the Yangtze River Delta (YZD) in 2020, 2015, 2010 and 2005 using geographically weighted regression. The results reveal that (1) the three urban agglomerations have substantial heat island intensity regions, which are clustered and zonally distributed, and the annual average rates of the heat island area growth in the three regions are 1.01%, 1.41% and 1.09%, respectively. (2) Many uncomfortable areas exist in the three urban agglomerations, with an exponential growth trend in summer, and the annual average proportion of the uncomfortable areas in the three regions are 60.8%, 56.8% and 49.4%, respectively. (3) From the spatial point of view, the high-thermal comfort index areas of Beijing, Tianjin, Hebei, Guangdong, Hong Kong and Macao expand to the coast, and the high-index areas of the Yangtze River Delta expand to the inland. In terms of time, the annual distribution of thermal comfort in Beijing–Tianjin–Hebei is discrete, but the annual distribution of thermal comfort in Guangdong, Hong Kong, Macao and the Yangtze River Delta is concentrated. (4) In LUCC, the change intensity in construction land has a remarkable effect on the change in thermal comfort. The areas where the thermal comfort index increases positively correlate with the areas where the construction land increases. This study enriches the research on the impact of LUCC on urban ecological performance, and thus provides the necessary scientific basis for urban environment construction. [ABSTRACT FROM AUTHOR]

• Coupling relation between urbanization and energy-environment efficiency was explored. • Energy-environment efficiency is measured using undesirable output SBM model. • Urbanization quality and energy-environment efficiency show spatial differentiation. • Coupling relationship in Guangdong province was from low to medium coupling stages. • Most cities in Guangdong were still at the low and medium coupling stages. Rapid urbanization has been accompanied by a series of environmental and energy-related issues. It is essential to better understanding the coupling relation between energy-environment efficiency and urbanization in achieving the goal of sustainable urbanization. In this paper, an index system was firstly established for the measurement of urbanization quality scores based on the four aspects of population, economy, society, and space. We then undertook a slack-based measure data envelopment analysis in order to measure energy-environment efficiency. This allowed us to establish a coupling coordination degree model to investigate the coupling relationship between energy-environment efficiency and urbanization. Our findings include the following: (1) Spatiotemporal diversity was apparent in the estimated urbanization quality scores within the province, with high-values areas mainly being concentrated in the Pearl River Delta; (2) A growth trend was identified in energy-environment efficiency values in western Guangdong and the Pearl River Delta, while in eastern Guangdong energy-environment efficiency followed a downward trend, and it stayed stable at a low level in northern Guangdong. Energy-environment efficiency also displayed significant spatial differentiation; (3) The coupling relationship between the energy-environment efficiency and urbanization of Guangdong throughout the research period went from a low coupling stage to a medium coupling stage. Most cities in Guangdong remained in the moderate and low coupling stages, with the exception of Guangzhou and Shenzhen, which took the lead in entering the highly coupling stage. The findings of this paper are of great implications for government in achieving the coordinated development of energy-environment efficiency and urbanization. [ABSTRACT FROM AUTHOR]

Relative contributions of greenhouse gases (GHGs) concentration and land use/cover (LULC) change induced by urbanization on future temperature over the Guangdong-Hong Kong-Macao Greater Bay Area in China under different climate scenarios are investigated in this study. The Weather Research and Forecasting model is used to downscale the future mean and extreme temperature using the Representative Concentration Pathways (RCP) 4.5&8.5 simulations from the Community Earth System Model. Results show that GHGs concentration is the key dominate factor for future mean and extreme temperature over the Greater Bay Area in the next 10–30 years, LULC change (urbanization) has relative slight effect on the future regional temperature. On the urban local scale, the LULC change in urban area has an obvious warming effect on urban local temperature under future different GHGs concentration scenarios. The regional-averaged annual mean surface air temperature (SAT) of urban area will increase 0.51 °C (0.73 °C), 0.83 °C (1.17 °C) and 1.26 °C (1.74 °C) resulting from the combined contributions of urbanization and GHGs forcing for the year of 2030, 2040, and 2050 under RCP4.5(RCP8.5) scenario, respectively. The contributions of the GHGs forcing are 0.33 °C (0.53 °C), 0.66 °C (1.00 °C) and 1.12 °C (1.58 °C), the urbanization forcing are 0.18 °C (0.20 °C), 0.17 °C (0.17 °C) and 0.14 °C (0.16 °C). Same as regional-averaged annual mean SAT, for the extreme high- and low-temperature, the contribution of GHGs forcing is more important than that of the urbanization forcing. The extreme temperatures are more sensitively to GHGs concentration under RCP8.5 scenario than that under RCP4.5, especially for the extreme low-temperature. GHGs are the most important factor for dominating the future mean and extreme temperature of the Greater Bay Area. [ABSTRACT FROM AUTHOR]

Urban land development alters landscapes and carbon cycle, especially net primary productivity (NPP). Despite projections that NPP is often reduced by urbanization, little is known about NPP changes under future urban expansion and climate change conditions. In this paper, terrestrial NPP was calculated by using Biome-BGC model. However, this model does not explicitly address urban lands. Hence, we proposed a method of NPP-fraction to detect future urban NPP, assuming that the ratio of real NPP to potential NPP for urban cells remains constant for decades. Furthermore, NPP dynamics were explored by integrating the Biome-BGC and the cellular automata (CA), a widely used method for modeling urban growth. Consequently, urban expansion, climate change and their associated effects on the NPP were analyzed for the period of 2010–2039 using Guangdong Province in China as a case study. In addition, four scenarios were designed to reflect future conditions, namely baseline, climate change, urban expansion and comprehensive scenarios. Our analyses indicate that vegetation NPP in urban cells may increase (17.63 gC m −2 year −1 –23.35 gC m −2 year −1 ) in the climate change scenario. However, future urban expansion may cause some NPP losses of 241.61 gC m −2 year −1 , decupling the NPP increase of the climate change factor. Taking into account both climate change and urban expansion, vegetation NPP in urban area may decrease, minimally at a rate of 228.54 gC m −2 year −1 to 231.74 gC m −2 year −1 . Nevertheless, they may account for an overall NPP increase of 0.78 TgC year −1 to 1.28 TgC year −1 in the whole province. All these show that the provincial NPP increase from climate change may offset the NPP decrease from urban expansion. Despite these results, it is of great significance to regulate reasonable expansion of urban lands to maintain carbon balance. [ABSTRACT FROM AUTHOR]

China experienced a shift from net forest losses to gains (forest transition) between 1976 and 1981. Such transition has increased timber volume in natural forests and expanded the provision of forests ecosystem services. However, the timing, magnitude, and impact of the forest transition varied at provincial scales due to heterogeneous socio‐economic and institutional conditions. The aim of this study is to quantify the impact of spatial drivers of forest transition in China through integrated comparative and spatial regression methods. This approach allows the documentation of feedbacks and interactions of theoretical pathways to forest transition at different geographical scales, which is of relevance for large‐scale land restoration efforts. Our analysis also accounts for changes in forest volumes, a parameter that is usually not studied in the forest transition literature. Here, we used key indicators of demographic, economic, agricultural, and urbanization processes coupled with forest area data to investigate factors influencing forest transitions at multiple geographic scales between 1973 and 2013. Stepwise and geographically weighted regression models were adapted to quantify the key drivers' integrated and distributed magnitude effects on forest transition patterns, respectively. We assessed changes across forest types (i.e., primary and secondary forests, plantation forests) and investigated pathways to forest transition at provincial scales. The results indicate that increasing demand for timber and other forest ecosystem services, rising gross domestic product and population, forest policy, and increasing employment in the industry and service sectors generated multiple pathways to forest transition. The impact of those drivers varied within provinces, and some transition pathways were more relevant than others at sub‐national scales. Despite the Country scale shift to net forest gains, the loss of natural forests continued in some provinces (e.g., Guangdong, Guangxi) until recent years. The loss of ecosystem services from mature forests offset some of the benefits of China's forest transition. Coordinated forest management strategies across political jurisdictions could speed up the path to net forest gains, reduce trade‐offs of forest transitions processes, and achieve sustainable afforestation processes. Such an effort could have significant contributions to the preservation and increase of key forest ecosystem services for the Country and the world. [ABSTRACT FROM AUTHOR]

Previous studies show that the environment in the Guangdong, Hong Kong, and Macao region is under the double stress of global warming and urbanization. Here, we show that due to the increase of regional greenness, the effect of urbanization warming on surface air temperature (SAT) decreased with time and became statistically insignificant from 2004 to 2018, compared to 1979 onward; while the urbanization itself has significantly warmed land surface temperature (LST), with a warming rate of 0.14°C ± 0.04°C/10a at daytime and 0.02°C ± 0.02°C/10a at nighttime during 2004–2018, respectively. The anthropogenic heat was found to have a limited influence on SAT, but more significant and tangible effects on LST. It is essential to improve the control of additional warming effects caused by urbanization. Plain Language Summary: The Guangdong, Hong Kong, and Macao region is the most economically developed region in China, and the urbanization impact on the regional warming is frequently discussed during recent decades. We found that the urbanization warming on surface air temperature (SAT) has decreased to insignificant during the recent decade due to regional greening, while the warming of land surface temperature (LST) remains tangible. This result is related to the different effects of two moderating drivers (anthropogenic heat and vegetation index) on both SAT and LST. Thus, it is essential to increase urban greenness and reduce anthropogenic heat fluxes in parallel. Key Points: The effect of urbanization on the surface air temperature (SAT) decreases over time as regional vegetation greening increasesThe urbanization effect on the land surface temperatures (LSTs) from the long time series of satellite retrievals remains significantThe anthropogenic heat was found to have a limited influence on SAT, but more significant and tangible effects on LST [ABSTRACT FROM AUTHOR]

Land use land cover (LULC) of Guangdong, Hong Kong, and Macao (GHKM), south china, has undergone significant changes in the last few decades. This study analyze the spatio-temporal LULC changes and urban expansion during 2010–2017 using Landsat TM, ETM+, and OLI. The Landsat images were classified using support vector machine (SVM) into seven classes as forest, grassland, water, fishponds, built-up, bareland, and farmland. Several socioeconomic factors were also obtained to determine their impact on LULC. The result shows that during the studied period, massive economic development and urbanization has increased the built-up area from 8.26% (16,209.61 km2) to 10.31% (20241.77 km2) and substantial reduction in both farmland from 37.64% (73,897.77 km2) to 33.05% (64932.19 km2) and fishponds from 1.25% (2451.12 km2) 0.85% (1674.71 km2). The most dominant conversion were from farmland to built-up and to forest. Furthermore, forest cover increased to 45.02 % (88384.97 km2) in 2017 from 42.38% (83215.59 km2) in 2010 as a result of different afforestation scheme and policies in order to make Greener study area. The analysis of socioeconomic factors shows that increase in gross domestic product (GDP), total investment in fixed assets, and industrialization has led to urbanization growth on a large scale and reduction of farmland. Therefore, there is pressing need for sustainable development and protection of farmlands. [ABSTRACT FROM AUTHOR]

Impervious surface (IS) is a key indicator to measure the urbanization process and ecological environment. Many studies have observed an urbanization process based on IS at the city scale. Understanding the changes in the IS over a period at a regional level offers an alternative and effective approach to characterize and quantify the spatial process of urban agglomeration. This study focuses on the urban agglomeration of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) by utilizing the sensor-based Landsat data during 1987-2017 and investigates the spatiotemporal distribution of IS expansion at both regional and city scales. The modified linear spectral mixture analysis (MLSMA) method is used to extract the IS of the GBA. Then, the IS mapping accuracies were assessed after comparison with high-resolution historical data. The spatiotemporal and directional changes of IS surfaces for GBA are analyzed by using Gravity Center (GC) and Standard Deviational Ellipse (SDE). Finally, Shannon's Diversity Index (SHDI) is used to analyze the overall characteristics of landscape level, and the Patch Density (PD) and Landscape Shape Index (LSI) are used to describe the characteristics of different classes of the IS. The results show that the IS of the whole region experienced rapid and massive expansion during the past 30 years and exhibited a distinct characteristic along the Pearl River Delta (PRD) and the coastline. Furthermore, the IS area increased rapidly in the PRD, while it is relatively stable in Hong Kong and Macao. We believe that the findings of this study can help policy makers to better understand and maintain the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

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The influences of urbanization on weather in Guangdong Province, China, were studied using the Weather Research and Forecasting model from 31 December 2009 through 3 January 2010. Model outputs were compared with extensive monitoring of meteorological data to examine the simulation ability. Model results between tests (with and without land-use change) show that the urbanization had major effects on meteorological fields across nearly the entire Pearl River Delta region and particularly in urban areas. Studied fields (wind speed, temperature, precipitation, and sensible and latent heat fluxes) were affected by the urbanization of the PRD region. The major influences occurred in urban areas, where wind speeds decreased greatly, while the daytime surface upward sensible heat flux clearly increased. Unlike the sensible heat flux, the latent heat flux had a nonmonotonic increase or decrease. As a consequence of the two heat fluxes, 2-m temperature varied with location and time. Change of precipitation was complex. The main rain band became more concentrated, while precipitation decreased upwind of the urban area and increased downwind. [ABSTRACT FROM AUTHOR]

The characteristics of heat waves (HWs) in southern China in 1979-2010 are studied by using both reanalysis and station datasets. Guangdong Province of China (GDPC) is taken as an example. It is found that the westward movement of the western North Pacific subtropical high (WNPSH) is the primary factor for large-scale HWs occurring in GDPC. When an HW occurs, a hot and dry atmospheric column prevails over southern China. The region is overlaid by anomalous subsidence, which leads to warming, and clear sky, which causes greater solar heating. HWs are accompanied by an anomalous high pressure center and anticyclone near the surface, with anomalous land-sea northwesterly flow, thus reducing sea-land moisture transport and drying the atmosphere over land. The evolution of the high pressure anomaly and high temperature is associated with the westward displacement of WNPSH, with a prominent positive anomaly in 500-hPa height migrating westward. All these features associated with HWs in GDPC coincide with high-temperature extremes in the whole region of southern China and parts of Indochina. Significant increases in HW frequency (+0.19 events decade-1), HW days (+2.86 days decade-1), the duration of the longest event (+0.38 days decade-1), and the hottest temperature of the hottest event (+0.23°C decade-1) are also observed. These upward trends are more prominent in the Pearl River delta (PRD) region, and urbanization contributes to nearly 50% of the increase in HW frequency in PRD. It is also noticed that HWs are commencing earlier and ending later, and urbanization may advance the timing of the onset of HW events. [ABSTRACT FROM AUTHOR]

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China has experienced rapid urbanization over recent decades. The tourism literature, however, has rarely explored this issue. This article examines the historical process of urbanization and tourism development, using time-series data of Guangdong Province in China for the period 1994–2010. Research results are based on a systematic analysis studying the relationship between tourism development and urbanization. Tourism development is measured by the total income generated by tourism. Urbanization has been operationalized by population, economic, geographic landscape, and sociocultural dimensions. This study suggests that urbanization, though generally increasing tourism development, does not affect all types of tourism development uniformly. The results show that urbanization is an important factor for domestic tourism development, but not for foreign tourism development in China. Therefore, policy-makers, while assessing the effect of urbanization on tourism development, should be cautioned on the different policy goals the province would want to achieve. [ABSTRACT FROM PUBLISHER]

The green vegetation fraction (GVF) and surface albedo are important land surface parameters often used for validation of climate and land surface models that are influenced largely by environmental gradients and human activities. In this study, fine resolution GVF and albedo values derived from Landsat Thematic Mapper/Enhanced Thematic Mapper Plus images from 1990 to 2000 were used to examine the relationship of both GVF and albedo values to the spatial gradients of parameters related to dramatic urbanization in the Greater Guangzhou metropolitan area, Guangdong Province, in South China. Moderate resolution GVF and albedo datasets derived from the MODIS Collection 5 product were used to analyze the seasonal variation of GVF and albedo with rapid urban expansion from 2001 to 2007. The results show that the shortwave albedo had a clear declining trend from the urban center to natural land in 1990. However, no obvious trend in shortwave albedo change was observed along urban-rural gradients caused by the expansion of low-albedo urban buildings and more heterogeneous land cover patterns in 2000. A threshold of GVF (~0.21) was estimated for determining the change of albedo associated with vegetation fraction. Vegetation cover modified by urban expansion changed surface reflectance and influenced the surface energy balance. It is suggested that a large portion of energy absorbed in an urban area is likely to be converted to thermal energy that heating up is near the surface and emitted as longwave radiation. [ABSTRACT FROM AUTHOR]

Urban agglomeration is an advanced spatial form of integrating cities, resulting from the global urbanization of recent decades. Understanding spatiotemporal patterns and evolution is of great importance for improving urban agglomeration management. This study used continuous time-series NTL data from 2000 to 2018 combined with land-use images to investigate the spatiotemporal patterns of urbanization in the three most developed urban agglomerations in China over the past two decades: the Beijing–Tianjin–Hebei urban agglomeration (BTH), the Yangtze River Delta urban agglomeration (YRD), and the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The NTL intensity indexes, dynamic thresholds, extracted urban areas, and landscape metrics were synthetically used to facilitate the analysis. This study found that the urbanization process in the study areas could be divided into three stages: rapid urbanization in core cities from 2000 to 2010, a fluctuating urbanization process in both core cities and surrounding cities from 2010 to 2015, and stable urbanization, mainly in surrounding cities with a medium size after 2015. Meanwhile, the urbanization level of GBA was higher than that of YRD and BTH. However, with the acceleration of urban development in YRD, the gap in the urbanization level between GBA and YRD narrowed significantly in the third stage. In addition, this study confirmed that the scattered, medium-sized cities in YRD and GBA were more developed than those in BTH. This study showed that continuous NTL data could be effectively applied to monitor the urbanization patterns of urban agglomerations. [ABSTRACT FROM AUTHOR]

Unprecedented urbanization has occurred globally, which has converted substantial natural landscapes into impervious surfaces and further impacted ecosystem services and functioning. In this study, we quantified the spatiotemporal patterns of urbanization and investigated the impacts of urbanization on the ecosystem service value (ESV) in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 1980 to 2018. The results show that the GBA has experienced extensive urbanization, with the urban area increasing from 2607.4 to 8243.5 km2 from 1980 to 2018. Zhongshan, Zhuhai, Dongguan, Shenzhen, and Foshan exhibited the top five highest urban expansion rates. Throughout the study period, edge expansion was the most dominant growth mode, with a decreasing trend, while infilling increased in the GBA. The total ESV loss induced by urban expansion in the GBA reached 40.5 billion yuan over the past four decades. The ESV loss due to the water body decrease caused by urbanization was the largest. Our study suggests that decision-makers should control new urban areas and protect water bodies, wetlands, and forests with high ESVs to promote the sustainable development of urban agglomerations. [ABSTRACT FROM AUTHOR]