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To quantify the chain transmission effect between disasters in assessing the emergency capacity of the disaster chain, the chain transmission relationship between disasters is quantified by superimposing (decrement) effect coefficients. The evaluation model and calculation method of emergency capacity of disaster chain are derived based on the conversion probability and threshold between disaster chains. Considering the two-dimensional emergency preparedness and recovery indicators, an index system of emergency capability assessment of the rainstorm-landslide disaster chain is constructed. Using the entropy weight method and the technique for order preference by similarity to an ideal solution (TOPSIS) method, the emergency capacity index of two single disasters, rainstorms and landslides, is calculated. The emergency capacity of the rainstorm-landslide disaster chain is obtained by combining it with the emergency capacity evaluation model of the disaster chain. An actual analysis is carried out of the typical rainstorm-landslide disaster chain in the Guangdong-Hong Kong-Macao Greater Bay Area. The results show that the emergency capability of the rainstorm-landslide disaster chain in the central Guangdong-Hong Kong-Macao Greater Bay Area shows a downward trend compared to the single landslide disaster. In contrast, the overall emergency capability of the eastern region shows an upward trend. The emergency capability of the rainstorm-landslide disaster chain in the northwest and southwest regions is consistent with that of the single landslide disaster. The results of the emergency response capability assessment of the rainstorm-landslide disaster chain are more scientific and reasonable, which can provide technical support for the assessment and improvement of the emergency response capacity of the rainstorm-landslide disaster chain. [ABSTRACT FROM AUTHOR]

The effectiveness of ecological security patterns (ESPs) in maintaining regional ecological stability and promoting sustainable development is widely recognized. However, limited research has focused on the early warning of risks inherent in ESPs. In this study, the Guangdong–Hong Kong–Macao Greater Bay Area (GHKMGBA) is taken as the study area, and ecological security risk zones are delineated by combining the landscape ecological risk index and habitat quality, and a multi-level ESP is constructed based on the circuit theory. The PLUS model was employed to simulate future built-up land expansion under different scenarios, which were then extracted and overlaid with the multi-level ESP to enable the multi-scenario early warning of ESP risks. The results showed the following: The ESP in the central plains and coastal areas of the GHKMGBA exhibits a high level of ecological security risk, whereas the peripheral forested areas face less threat, which is crucial for regional ecological stability. The ESP, comprising ecological sources, corridors, and pinch points, is crucial for maintaining regional ecological flow stability, with tertiary corridors under significant stress and risk in all scenarios, requiring focused restoration and enhancement efforts. There are significant differences in risk early warning severity within the ESP across various development scenarios. Under the ecological protection scenario, the ESP will have the best early warning situation, effectively protecting ecological land and reducing ecological damage, providing a valuable reference for regional development policies. However, it must not overlook economic development and still needs to further seek a balance between economic growth and ecological protection. [ABSTRACT FROM AUTHOR]

Rapid global urbanization and its progress have profoundly affected urban vegetation. The ecological quality of urban vegetation is a vital indicator of regional ecological stability and health. A comprehensive assessment of the coupling coordination and coercive relationship between urbanization and the vegetation ecological quality is essential for promoting sustainable regional green development. Using the rapidly urbanizing Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration in China as an example, this study evaluates the vegetation quality condition and the level of urbanization and explores the dynamic relationship between vegetation ecological quality and urbanization processes. This study introduces the vegetation ecological quality index (VEQI) based on net primary productivity (NPP) and fractional vegetation cover (FVC), as well as the comprehensive urbanization index (CUI) derived from gross domestic production (GDP), population density, and nighttime lighting data. The coupling coordination and Tapio decoupling models are employed to assess the degree of coupling coordination and the decoupling relationship between the VEQI and CUI across different periods. The results showed that (1) from 2000 to 2020, the VEQI in the GBA showed a significant increase, accompanied by continuous urbanization, particularly evident with the high CUI values in central areas; (2) the coupling coordination degree (CCD) exhibits high values and significant change slopes in the central GBA, indicating dynamic interactions between urbanization and vegetation ecological quality; (3) the decoupling states between the VEQI and CUI are dominated by weak decoupling (WD), strong decoupling (SD), expansive negative decoupling (END), and expansive coupling (EC), suggesting improvements in the relationship between urbanization and vegetation ecological quality; (4) the coordinated development level of the VEQI and CUI in the study area shows improvement, and their decoupling relationship displays a positive trend. Nevertheless, it remains crucial to address the impact of urbanization pressure on vegetation ecological quality and to implement proactive measures in response. The results of this study provide theoretical support for mesoscale development planning, monitoring vegetation ecological conditions, and formulating environmental policies. [ABSTRACT FROM AUTHOR]

Copyright of Urban Mass Transit is the property of Urban Mass Transit 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.)

The urban heat island (UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is inadequate. Combined with data (e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity (SUHII) in the GBA. The SUHII was calculated based on the urban-rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum (minimum) SUHII was found in summer (winter); similarly, the largest (smallest) diurnal difference in SUHII was during summer (winter). Generally, the Mann-Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban-rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI. [ABSTRACT FROM AUTHOR]

Objectives This study aims to evaluate the changes in human mobility during a public health emergency.Methods Employing detailed spatiotemporal big data on human mobility from China and the USA, we constructed three mobility indices: Mobility change index, distance change index, and volatility change index. We investigated the mobility characteristics within China's Guangdong-Hong Kong-Macau Greater Bay Area (GBA) and the United States' San Francisco Bay Area (SBA) during the epidemic. The singular value decomposition (SVD) algorithm was applied to identified underlying structures and patterns of mobility in these regions.Results The results show that: (1) The GBA outperformed the SBA in terms of human mobility control with a greater decline in movement volumes, smoother volatility in daily movement and shorter average travel distances during the pandemic. (2) Human mobility patterns in the GBA were influenced by both the Chinese Spring Festival holiday and public health policies, from which the daily travel patterns, returning home travel characteristics and returning-to-work characteristics were identified. Human mobility patterns in the SBA show strong regularity (including daily travel characteristics, weekday travel characteristics and weekend travel characteristics), and public health policies do not have profound impacts.Conclusions We quantify the changes in human mobility patterns under different epidemic control measures in two Bay Areas of China and the United States, which is essential to assess and identify intervention effectiveness. It also provides important evidences and references for various infectious disease control in the future. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is threatened by potential tsunami hazards from the Littoral Fault Zone (LFZ) and the Manila subduction zone (MSZ), and may suffer huge damage because of its dense population, concentrated infrastructure, and low-lying coasts. Previous tsunami studies for the GBA made simple assumptions on the mechanisms of LFZ earthquakes, and used coarse bathymetry data in tsunami simulation, which limited the prediction of detailed tsunami hazard characteristics. In this paper, we develop a parallel dispersive tsunami model PCOMCOT to efficiently simulate dispersive, nonlinear, and breaking tsunami waves. We also construct large-scale and high-resolution bathymetry models for the GBA by correcting and integrating various data sources. Dynamic rupture simulation is performed for the LFZ to obtain a more reliable earthquake source model. We propose several representative earthquake scenarios for the LFZ and MSZ, and use PCOMCOT to calculate the resulting tsunami waves, currents, and inundation in the GBA. Our results indicate that if an Mw7.5 oblique-slip earthquake occurs in the LFZ off the Pearl River Estuary (PRE), the subsequent tsunami will primarily impact Hong Kong, causing maximum positive and negative waves of around 1 m and −2 m, respectively, along with slightly destructive currents (⩾1.5 m/s). An Mw9.0 MSZ megathrust earthquake can lead to widespread inundation with >1 m depth on the outlying islands of Macao and in the urban areas of Hong Kong around the Victoria Harbour. Besides, it will also cause catastrophic tsunami currents along the narrow waterways in Hong Kong and Macao, and the spatial distribution of strong currents (⩾3 m/s) shows a considerable discrepancy from the areas of serious inundation. Thus, more attention should be paid to the potential impacts of tsunami currents on the GBA. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Physical Education / Tiyu Xuekan is the property of Journal of Physical Education 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.)

Copyright of Pearl River is the property of Pearl River 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.)

In order to prevent and reduce the disaster losses caused by compound disasters to cities, it was of great theoretical and practical significance to study the exposure degree of chain compound disaster system. Through the research and analysis of the exposure degree of chain compound disaster system, considering the existing research and defining the connotation of the exposure degree of the compound disaster system, the evaluation model and calculation method of the exposure degree of the chain compound disaster system were deduced and established. Taking the rainstorm-landslide disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area as an example for empirical analysis, the evaluation index system of regional disaster chain exposure was screened and constructed from the aspects of population, economy and society. The order relationship analysis and TOPSIS method were used to calculate the single disaster exposure index of rainstorm and landslide in 52 districts and counties in the bay area. Then, the theoretical model of exposure degree of chain compound disaster system and ArcGIS image processing technology were used to obtain the zoning map of rainstorm-landslide disaster chain exposure in the Guangdong- Hong Kong-Macao Greater Bay Area, and the corresponding disaster prevention and mitigation measures were put forward according to the exposure degree attribute of each regional disaster chain. The results showed that the exposure index corresponding to the economically developed areas was significantly higher than that of other regions, and the low exposure were mainly in the relatively backward areas. Among the indicators, population density and GDP per land area account for the main position, which had the highest impact on regional exposure. By the exposure of regional compound disaster systems, reasonable scientific basis and decision-making support could serve for the government and relevant departments, helping the government, urban planners, and the public better understand and respond to disaster risks, thereby reduce the losses and impacts of disasters. [ABSTRACT FROM AUTHOR]

Objective Conventional fare calculation and settlement rules are not suitable for the complex interoperation scenarios of rail transit network in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). To ensure the accuracy of fare calculation and settlement results in GBA, it is necessary to conduct in-depth research on rail transit fare calculation and settlement rules in this scenario. Method Starting from GBA rail transit interoperation scenarios, the main influencing factors of fare calculation and settlement rules are analyzed. It is believed that the existence of complex parallel routes is a crucial factor influencing the accuracy of fare calculation and settlement. Regarding of different route recognition methods, schemes for fare calculation and settlement rules based on fuzzy route recognition and precise route recognition are determined，presenting implementation recommendation through comparatively analyzing the two schemes. Result & Conclusion Either one of the two schemes can be selected as the primary direction for further research and formulating detailed implementation plan due to their strong applicability. In the future, a variety of tracking and identification technologies can be integrated to achieve seamless tagging, thereby enabling precise identification of passenger travel routes and carrying out fare calculation and settlement without affecting interchange efficiency.

Owing to historical reasons, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) features a unique "one country, two systems" institutional framework. Facilitating the integration and connectivity of transportation among Hong Kong, Macao, and the Mainland is crucial for the high-quality development of the GBA. Previous studies about borders have primarily focused on national (supranational) or administrative boundaries within a country's territory. However, studies on the unique institutional differences in the GBA are insufficient. Additionally, most studies do not perform dynamic border effects measurements using big traffic flow data. This study utilizes toll-collection data from highways in the GBA for 2021 and 2023, as well as cross-border traffic data, to construct a traffic-flow network for the GBA. Complex network analysis and border-effect measurement methods are employed to investigate the spatial structure of the GBA traffic-flow network and its dynamic changes in border effects. The results indicate that, in terms of the overall spatial structure of traffic flow in the GBA, the network exhibits a unique "dual-core edge" structure, with the Guangzhou-Foshan, and Shenzhen-Dongguan-Huizhou regions serving as dual cores. In contrast, the overall coverage and connectivity strength of the passenger-flow network are higher than those of the freight-flow network. Regarding the dynamic changes in the spatial structure of traffic flow from Hong Kong and Macao, the coverage and density of the traffic-flow network in 2023 are significantly higher than those in 2021. Traffic flows from Hong Kong and Macao have begun to extend beyond the border toward the northern regions, thus accelerating the integration of transportation within the GBA and forming a spatial pattern of "cross-strait connectivity and all-area interconnection." However, because of their peripheral positions in the traffic network and the presence of border effects, the importance of Hong Kong and Macao in the GBA traffic-flow network remains relatively weak. Based on the dynamic measurement results of border effects, the obstruction coefficients between Hong Kong and the Mainland, as well as between Macao and the Mainland, are significantly higher than those between various counties within the Mainland. The obstruction coefficients for passenger vehicles are generally lower than those for freight vehicles. Following the outbreak of the pandemic, the obstruction coefficients of the GBA traffic-flow network have increased dynamically, thus indicating a reduction in obstructive border effects. This study expands the quantitative research framework of border effects in traffic-flow networks, thus promoting integrated transportation development in the GBA and facilitating its integration development goals.

• A model is developed to assess the effectiveness of CDWM on a city scale. • Performance levels and weaknesses in CDWM practices of the GBA are identified. • Differences of CDWM across GBA cities are revealed through empirical study. The growing generation of construction and demolition waste (CDW) has emerged as a prominent challenge on global environmental agendas. However, the effectiveness of CDW management (CDWM) strategies varies among cities. Existing literature predominantly evaluates the effectiveness of CDWM at the project level, offering a localized perspective that fails to capture a city's comprehensive CDWM profile. This localized focus has certain limitations. To fill this gap in city-scale evaluations, this study introduces a novel model for assessing CDWM effectiveness at the municipal level. An empirical investigation was conducted across 11 cities within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to operationalize this model. The model defines five distinct levels of CDWM effectiveness. Findings indicate that Hong Kong consistently achieves the highest level (level I), while the majority of cities fall within levels III and IV. This pattern suggests that CDWM effectiveness in the GBA is moderately developed, with uneven progress in CDW management outcomes and supporting systems. Essentially, there is a lack of synchronous development of CDWM results and guarantee systems. The proposed evaluation model enriches existing CDWM research field and offers a framework that may inform future studies in other countries. [ABSTRACT FROM AUTHOR]

Aquaculture plays a vital role in global food production, with fish pond water quality directly impacting aquatic product quality. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) serves as a key producer of aquatic products in South China. Monitoring environmental changes in fish ponds serves as an indicator of their health. This study employed the extreme gradient boosting tree (BST) model of machine learning, utilizing Landsat imagery data, to assess Chlorophyll-a (Chl-a) concentration in GBA fish ponds from 2013 to 2022. The study also examined the corresponding spatiotemporal variations in Chl-a concentration. Key findings include: (1) clear seasonal fluctuations in Chl-a concentration, peaking in summer (56.7 μg·L−1) and reaching lows in winter (43.5 μg·L−1); (2) a slight overall increase in Chl-a concentration over the study period, notably in regions with rapid economic development, posing a heightened risk of eutrophication; (3) influence from both human activities and natural factors such as water cycle and climate, with water temperature notably impacting summer Chl-a levels; (4) elevated Chl-a levels in fish ponds compared to surrounding natural water bodies, primarily attributed to human activities, indicating an urgent need to revise breeding practices and address eutrophication. These findings offer a quantitative assessment of fish pond water quality and contribute to sustainable aquaculture management in the GBA. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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.)

As urbanization in China progresses, urban spatial development is transitioning from rapid expansion to more intensive and compact growth. This study examined the role of physical geography and environmental factors in shaping the urban spatial development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the current natural conditions, we selected evaluation indices from topography, hydrogeology, climatic conditions, and natural disasters. These indices were used to create a carrying capacity and suitability evaluation system for development land under natural constraints. Finally, the spatial development potential of the city was finalized by taking into account the current state of the built-up area of the city. Meanwhile, we employed the Optimal Parameters-based Geographical Detector and assessed the impact of 14 natural factors on the spatial development of urban built-up areas. In 2020, the GBA had 52,168.77 km2 of land suitable for construction, of which 34,241.13 km2 was highly suitable (61.29%) and 17,927.64 km2 was moderately suitable (32.09%). At the Bay Area level, 90.15% of the development potential remains untapped; at the city level, Zhaoqing City has the highest potential at 99.56%, while Macao has the lowest at 26.83%. Key factors influencing urban development include silty sand content, annual average relative humidity, and cumulative temperature above 0 °C, with varying impacts across different urban scales. At the Bay Area level, the silty sand content, annual average relative humidity, and cumulative temperature above 0 °C are the main influencing factors on the spatial development of urban built-up areas; at the city level, the main factors are annual average relative humidity and cumulative active temperature above 0 °C. This study reveals the important influence of natural environmental factors on urban spatial development, which is conducive to promoting sustainable development of land resources in GBA. [ABSTRACT FROM AUTHOR]

When considering the economic growth of the Greater Bay Area, digital transformation stands out as a crucial catalyst. Given its significance, it is imperative to delve into both the theoretical and empirical aspects of how digital transformation affects the region's position in the global value chain. Theoretical hypotheses are put forward regarding the impact and mechanisms of digital transformation on the global value chain position of the Greater Bay Area based on a global value chain perspective. A three-tier nested input–output table that incorporates the Greater Bay Area is constructed, and trade decomposition and global value chain position measurement models specific to the area are developed for analyzing its current state in terms of global value chain position. Empirical testing was conducted to examine how digital transformation impacts this position. Digital transformation will significantly enhance the position of the Greater Bay Area in the division of global value chains, mainly through enhancing technological innovation transformation capabilities and value added by exports from the Greater Bay Area. Digital transformation within the Greater Bay Area has had a more substantial positive impact than the digital transformation in other provinces in China and digital transformation from foreign sources. In terms of city heterogeneity, it is evident that the global value chain from Hong Kong and Macao has experienced a more significant impact from digital transformation compared to cities in the Pearl River Delta. Therefore, the Greater Bay Area should increase the use of both digital transformation and differentiated use of digital transformation. PRD cities should actively learn from Hong Kong and Macao's forms of digital construction and promote the Greater Bay Area's global value chain status. [ABSTRACT FROM AUTHOR]

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

Copyright of Pearl River is the property of Pearl River 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.)

Copyright of Pearl River is the property of Pearl River 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.)

Copyright of Journal of Shenzhen University Humanities & Social Sciences is the property of Journal of Shenzhen University (Humanities & Social Sciences) 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.)

This study evaluated the precipitation forecasts in the Guangdong-Hong Kong-Macao Greater Bay Area during the 2018 South China rainy seasons (April to September) using data from the THORPEX Interactive Grand Global Ensemble dataset. The dataset comprised deterministic forecasts, ensemble forecasts, and ground precipitation observations from models of five organizations: the European Centre for Medium-Range Weather Forecasts, the China Meteorological Administration, the Japan Meteorological Agency, the National Centers for Environmental Prediction of the United States, and the UK Meteorological Office. Three multi-model integrated forecast methods, namely the multi-model ensemble average (EMN), the bias-removed ensemble average (BREM), and the sliding training period superensemble method (R_SUP), were employed for the evaluation. The results showed that, in general, the root mean square error of precipitation forecasts in the first rainy season of the Guangdong-Hong Kong- Macao Greater Bay Area was higher than that in the second rainy season, with an average difference of 2 mm. The forecasting ability of the multi-mode integrated forecasting method showed a continuous and stable decline trend in the first rainy season as the forecast lead time increased. In contrast, in the second rainy season, it showed a stable decline in the short term (24~72 hours) and remained stable in the medium term (72~168 hours). EMN, which has a relatively simple mathematical principle, showed the best comprehensive performance in the precipitation forecast of the two rainy seasons. BREM and R_SUP achieved slightly lower spatial average scores, but they still demonstrated good forecasting skills in predicting precipitation areas. [ABSTRACT FROM AUTHOR]

The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration. [ABSTRACT FROM AUTHOR]

The integration of modern service and advanced manufacturing industries represents deep industrial reform and profound change in quality concepts, mechanisms, and practices. Integrating these two industries is important for achieving high-quality development and is an area of interest for policymakers and academia. This study analyzes the data of 11 regions in 2021 in the Guangdong–Hong Kong–Macao Greater Bay Area using the fuzzy set qualitative comparative analysis method from the configuration perspective. This study explores the effects of multiple factors, such as economic efficiency, technological innovation, and the policy environment, on improving the coupling coordination level of the modern service and advanced manufacturing industries, and analyzes the path selection of industrial integration development. Overall, economic efficiency, technological innovation, and policy environment factors are not necessary conditions for the integration development of the modern service and advanced manufacturing industries. The multiple impacts of economic efficiency, technological innovation, and policy environment form a multi-restructuring path that drives the integration of the two industries. Owing to the economic development level and resource endowment of different regions, the path dictating the degree of integration between the two industries varies by region. From a holistic perspective, all regions should strive to coordinate the multiple conditions of economic efficiency, technological innovation, and policy environment to break through objective constraints such as the government's conditions and external environment based on their own organizational conditions and resource endowments. Additionally, all regions should strengthen exchanges, cooperation, and integration mechanisms and implement complementary development and distinctive development in core cities in the Greater Bay Area. The results clarify the factors affecting industrial convergence in the Greater Bay Area, enriching existing research methods and laying a foundation for a decision-making theory of industrial integration development.

With the rapid expansion of urban areas, intercity highways have become crucial for daily transportation. Traffic administrators and planners increasingly rely on evaluating highway traffic volume. This paper aims to investigate the relationship between various factors and intercity traffic volume, with a specific focus on exploring the advancing and lagging effects of weather conditions on traffic volume in the districts of urban agglomerations. Using multiple data sources in the Guangdong-Hong Kong-Macao Greater Bay Area, including weather factors (i.e., rain, temperature, wind, and visibility), traffic factors (i.e., total traffic volume and travel time), and other factors (i.e., node degree, hub cities, and time of day), a mixed geographically weighted regression (MGWR) model is applied to examine the spatial heterogeneity of these factors. The results show that intercity traffic volume is influenced by weather, traffic, and other factors. Additionally, the advancing and lagging effects of different weather factors exhibit spatial heterogeneity across districts. Moreover, the weather lagging effect has a more significant impact than the advancing effect on intercity traffic volume. These findings provide valuable insights into the impact of weather on intercity travel volume and offer precise traffic guidance for intercity travelers.

[Objective] Identifying the sensitivity of disasters is an important prerequisite for disaster prevention and reduction, and sensitivity assessment of complex disaster systems is an important component of risk assessment of composite disaster systems. [Methods] Firstly, the sensitivity assessment index system of the composite disaster system was constructed according to the characteristics of the rainstorm landslide disaster chain, and then the susceptibility of the rainstorm-landslide disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area was evaluated by using Convolutional Neural Network (CNN) and Optimal Parameters-based Geographical Detectors-Analytic Hierarchy Process (OPGD-AHP). Through the sensitivity analysis of rainstorm and landslide, the sensitivity classification maps of rainstorm and landslide in the Greater Bay Area were obtained respectively. And the threshold value and conversion probability of landslide induced by rainstorm were obtained through statistical analysis, so as to analyze the sensitivity of rainstorm landslide disaster chain and finally the sensitivity classification map of the rainstorm-landslide disaster chain in the Greater Bay Area was obtained. [Results] (1) The highly sensitive areas of the rainstorm landslide disaster chain in Guangdong, Hong Kong and Macao were mainly distributed in the northwest of Guangning County and Huaiji County, and in the east of Huiyang District and Huidong County. (2) The sub high sensitivity and medium sensitivity areas were mainly distributed in areas such as Fengkai, Deqing, Conghua, Longmen, Boluo, etc. (3) Low sensitivity areas and sub low sensitivity areas were mainly distributed in central areas such as South China Sea, Liwan, Chancheng, Shunde, Nansha, Panyu, Sanshui, Baiyun, etc. [Conclusion] The research results could provide scientific basis and technical support for disaster prevention and reduction, as well as enhancing the resistance and resilience of the disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area.

High-quality air service is important for achieving high-quality aviation development. As the primary customers of air travel services, passengers are the most important evaluators of the service. Therefore, research on their air travel choices is key for promoting the coordination of multi-airport regions. Based on stochastic utility psychological perception theories, this study discusses the impact of the key dimension of airport service quality on air travel choices using the structural equation model-logit model. The results show that air travel choice is not a simple linear extension of behavioral intentions as there are two key dimensions of airport service quality: First, mandatory service processing is inevitably the most time-consuming and tedious process for passengers at airports. This waiting time is perceived as a sign of low airport service capability, whereas the level and quality of service provided by staff in this process is an intangible factor for passengers. This in turn affects the level of passengers' ratings of airport services, especially for business travelers. Therefore, airports need to recognize the time and resource constraints of passengers and work with airlines to streamline the check-in process, ensure security control, and reduce waiting time. One solution is to use shared self-service devices or automated robots that allow any passenger of any airline or flight to check-in and check-out on the same device. Second, while facilities, equipment, and environment are not universal considerations for passengers, differences in passenger perceptions are evident between airport types. Within multi-airport regions, the facilities, equipment, and environment of major airports are above passengers' psychological expectations, while auxiliary or other airports need to pay more attention to this service, which illustrates that the improvement of airport service quality requires changes to unidimensional and monolithic thinking but also focus on passengers' overall perception of service experience from a multidimensional perspective, as well as consideration of the spatial and temporal characteristics of different airport types in the multi-airport region to make targeted improvements. Moreover, passengers do not have an obvious preference for particular airlines, but low-cost airlines still hold a certain appeal for passengers when they take off from regional airports, which also means that low-cost airlines ' entry into the market has anti-risk properties for regional airports. Within the limits of China's aviation controls, the presence of low-cost carriers can still improve the chances of an airport being chosen. Therefore, different airport types within the same multi-airport region often need to compete differently to achieve regional synergistic development. To enhance airport service quality, it is essential to fine tune service quality standards, based on airport's types. The improvement of airports' performance should include a phased integration of assessments of service experience settings. Airports should adopt differentiated spatial designs for their service functions based on the goal of airport integration, with a view to achieving optimal management at minimal cost while being able to effectively guide passengers in their air travel choices.

Ecological restoration zoning is the concept of carrying out ecological restoration scientifically. In existing zoning studies, an effective technical solution is to use ecosystem service supply and ecological security pattern analysis as starting points. These studies have mostly focused on the negative ecological effects of high-intensity human activities and are still essentially focused on at-risk areas. Zoning is used for identification, the potential for effective regional ecological restoration is not considered systematically, and there is insufficient support for the theory and practice of ecological restoration. However, ecological restoration is a product of human society and economic processes of input and output. In addition to accurately identifying ecological risk areas, research on restoration zones should also consider regional ecological protection policies and economic differences to increase investment in environmental protection and improve the effectiveness of ecological protection in a targeted manner. Based on the current paradigm, the spatio-temporal matching of social economy and natural resources is taken into consideration, to realize the optimization of an ecological restoration zoning technical scheme. Taking the Guangdong-Hong Kong-Macao Greater Bay Area as an example, a regional framework for the ecological restoration of land space based on ecological background pattern and potential was constructed. The results show that ecosystem services have declined significantly in the past ten years, and there are areas with good natural resilience and strong support from protection policies. Township as the unit of ecological restoration zoning. 1) The ecological maintenance area accounts for 7.7% of the total area, and focus should be on comprehensive improvement to promote economic and ecological sustainability. 2) The ecological protection area accounts for 44.5%, and focus should be on protection and stronger policy control. 3) The ecological improvement area account for 11.9%, and diversified and continuous maintenance measures should be adopted to strengthen the redundancy of regional ecological network. 4) The ecological restoration area accounts for 35.9%, and the priority for restoration should be areas with high natural resilience and policy support, and should mainly comprise long-term restoration projects. The coordinated restoration area has a high natural restoration; however, the policy support is insufficient. Cooperation with higher-level governments or with regional joint governance should be initiated to improve efficiency of the overall restoration in the region.

Urban flooding caused by heavy rainfall is a common natural hazard in cities globally. Impervious surfaces are often increased during urban development, but there is limited research on the impact of large-scale and long-term land use/land cover (LULC) changes on urban flooding, while considering the influence of using different remote sensing data sources. In this study, a framework to evaluate the correlation between LULC changes and flooding extents is proposed, mainly comprising: 1) classifying remote sensing time series, using different sources but adopting the same classifier, to obtain the LULC of the Greater Bay Area, China, over a one decade period; 2) designing flooding scenarios with different rainfall intensities, and using the soil conservation service curve number (SCS-CN) model and local equal volume method to extract the inundation extent of urban flooding; and 3) analyzing the influence of different data sources on flood simulation results, and calculating the correlations between LULC and inundation area over the decade to analyze the impact of LULC changes on urban flooding. The resulting correlation coefficients of water and built-up land are 0.93 and 0.42, and those of bare land, grassland, orchard, and forest are −0.40, −0.61, −0.57, and −0.75, respectively. The inundation derived by Sentinel and Landsat data showed around 99% consistency, while Landsat tends to derive more inundation areas, with the differences mainly scattered in flat areas.

ABSTRACTIt is crucial to mangrove management by understanding its conservation efforts. This study proposed a spatiotemporal analysis model to evaluate mangrove changes in the Guangxi Beibu Gulf (GBG) and the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), focusing on past, present, and future dynamics. The analysis covered mangrove loss, stability, and gain from 1990 to 2020 and provided projections for 2020 to 2035 across multiple scenarios. Then further assessed the efficacy of past mangrove conservation with the Sustainable Development Goals (SDGs) and the prospective conservation potential with the Global Mangrove Alliance Goal (GMAG) indicators. Findings indicate that by 2020, the GBG and GBA had 81.65 km² and 40.92 km² of mangroves, respectively, with increases of 31.51% and 164.09% since 1990. Projected expansions are anticipated under all three scenarios during 2020- 2035, with the highest growth projected under the trend continuation scenario, followed by ecological restoration and protection, and economic development. While mangrove protection in these regions met SDG targets 6.6.1 and 14.5.1 from 2015 to 2020, the 80% conservation milestone set by GMAG for 2030 was not achieved, necessitating the establishment of nature reserves. The study offers novel insights for sustainable governance of mangrove forests at local, regional, and global levels.

ABSTRACTMapping detailed wetland types can offer useful information for wetland management and protection, which can strongly support the Global Biodiversity Framework. Many studies have conducted wetland classification at regional, national, and global scale, whereas fine-resolution wetland mapping with detailed wetland types is still challenging. To address this issue, we developed an integration of pixel- and object-based algorithms with knowledge (POK) by combining pixel-based random forest and an object-based hierarchical decision tree. Taking the Guangxi Beibu Gulf Economic Zone (GBGEZ) and Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as our study areas, we produced wetland maps with 10 wetland types and 6 non-wetland types using Landsat-8 time series. In addition, to comprehensively evaluate the accuracy of our wetland classification, we implemented accuracy validation based on test samples and data inter-comparison based on existing datasets, respectively. The results indicate that the overall accuracy of our wetland map was 91.6% ±1.2%. For wetland types, agricultural pond, coastal shallow water, floodplain, mangrove, reservoir, river, and tidal flat achieved good accuracies, with both user accuracy and producer accuracy exceeding 88.0%. For non-wetland types, most accuracies were greater than 72.0%. By comparison with existing datasets, it was found that our wetland map had good consistencies with the China Ecosystem-type Classification Dataset (CECD) land use dataset, MC_LASAC mangrove dataset, and Tidal Wetlands in East Asia (TWEA) tidal flat dataset. In 2020, the wetland area was 4,198.8 km2 in the GBGEZ and 10,932.2 km2 in the GBA. The main wetland types in the two coastal urban agglomerations were agricultural ponds, coastal shallow waters, mangroves, reservoirs, rivers, and tidal flats. Our study successfully mapped detailed wetland types in the GBGEZ and GBA, serving the Global Biodiversity Framework of Convention on Biological Diversity.

Wetland ecosystem has been under the dual stress of climate change and human activities in Guangdong-Hong Kong-Macao Greater Bay Area in recent years, resulting in sharp decline of wetland area and more complexities in structure, function, service, and ecological process of the wetland ecosystem, which all intensified the assessment and protection of wetland ecosystem services. Based on the above problems, how to build a targeted and applicable ecosystem service evaluation system in the wetland ecosystem with diverse types and complex structures of the Greater Bay Area, and then to carry out systematic and targeted ecological services and asset evaluations on natural resource and ecological safety assessment become one of key and important subjects in the Greater Bay Area. Taking the wetland ecosystem in the Guangdong-Hong Kong-Macao Greater Bay Area as the analysis object, it clarifies the research progress of wetland ecosystem services and their value. There are still insufficient wetland remote sensing monitoring capabilities, and wetland ecosystem service value evaluation system is not applicable and other key issues. Limited by the climatic characteristics, complex surface environment and wetland types of Guangdong-Hong Kong-Macao Greater Bay Area, the evaluation of wetland ecosystem service value in this area has become more difficult. In view of the current challenges in the assessment of the wetland ecosystem service value in Guangdong-Hong Kong-Macao Greater Bay Area, three important research and application directions of wetland ecosystem service value assessment in the Greater Bay Area are prospected, achieving accurate extraction of wetland parameters and construct a high-time resolution wetland data set, constructing a service value evaluation system for the wetland ecosystem in the Greater Bay Area, and establishing a wetland resource value evaluation system to realize the development of wetland from "resource evaluation" to "asset accounting". [ABSTRACT FROM AUTHOR]

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This article presents an analysis of the evolution and mechanisms of the intercity cooperation network of the Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA). Based on spatial analysis, social network analysis, and zero‐inflated negative binomial regression analysis, the following key findings are reported: First, the GBA's intercity cooperation network unfolds a strong trend away from a centralized structure towards a polycentric pattern and networked regional governance. Second, the GBA's intercity cooperation is marked by unevenness and path dependence, with high‐level linkages almost exclusively the purview of the area's most economically developed cities. Third, heavily cultivated by economic globalization and national power, the heightening of intercity cooperation is the result of condensed switching among jurisdictions where both endogenous and exogenous factors have rearranged and characterized by uneven development trends. [ABSTRACT FROM AUTHOR]

High-quality air service is important for achieving high-quality aviation development. As the primary customers of air travel services, passengers are the most important evaluators of the service. Therefore, research on their air travel choices is key for promoting the coordination of multi-airport regions. Based on stochastic utility psychological perception theories, this study discusses the impact of the key dimension of airport service quality on air travel choices using the structural equation model-logit model. The results show that air travel choice is not a simple linear extension of behavioral intentions as there are two key dimensions of airport service quality: First, mandatory service processing is inevitably the most time-consuming and tedious process for passengers at airports. This waiting time is perceived as a sign of low airport service capability, whereas the level and quality of service provided by staff in this process is an intangible factor for passengers. This in turn affects the level of passengers' ratings of airport services, especially for business travelers. Therefore, airports need to recognize the time and resource constraints of passengers and work with airlines to streamline the check-in process, ensure security control, and reduce waiting time. One solution is to use shared self-service devices or automated robots that allow any passenger of any airline or flight to check-in and check-out on the same device. Second, while facilities, equipment, and environment are not universal considerations for passengers, differences in passenger perceptions are evident between airport types. Within multi-airport regions, the facilities, equipment, and environment of major airports are above passengers' psychological expectations, while auxiliary or other airports need to pay more attention to this service, which illustrates that the improvement of airport service quality requires changes to unidimensional and monolithic thinking but also focus on passengers' overall perception of service experience from a multidimensional perspective, as well as consideration of the spatial and temporal characteristics of different airport types in the multi-airport region to make targeted improvements. Moreover, passengers do not have an obvious preference for particular airlines, but low-cost airlines still hold a certain appeal for passengers when they take off from regional airports, which also means that low-cost airlines' entry into the market has anti-risk properties for regional airports. Within the limits of China's aviation controls, the presence of low-cost carriers can still improve the chances of an airport being chosen. Therefore, different airport types within the same multi-airport region often need to compete differently to achieve regional synergistic development. To enhance airport service quality, it is essential to fine tune service quality standards, based on airport's types. The improvement of airports' performance should include a phased integration of assessments of service experience settings. Airports should adopt differentiated spatial designs for their service functions based on the goal of airport integration, with a view to achieving optimal management at minimal cost while being able to effectively guide passengers in their air travel choices. [ABSTRACT FROM AUTHOR]

Ecological restoration zoning is the concept of carrying out ecological restoration scientifically. In existing zoning studies, an effective technical solution is to use ecosystem service supply and ecological security pattern analysis as starting points. These studies have mostly focused on the negative ecological effects of highintensity human activities and are still essentially focused on at-risk areas. Zoning is used for identification, the potential for effective regional ecological restoration is not considered systematically, and there is insufficient support for the theory and practice of ecological restoration. However, ecological restoration is a product of human society and economic processes of input and output. In addition to accurately identifying ecological risk areas, research on restoration zones should also consider regional ecological protection policies and economic differences to increase investment in environmental protection and improve the effectiveness of ecological protection in a targeted manner. Based on the current paradigm, the spatio-temporal matching of social economy and natural resources is taken into consideration, to realize the optimization of an ecological restoration zoning technical scheme. Taking the Guangdong-Hong Kong-Macao Greater Bay Area as an example, a regional framework for the ecological restoration of land space based on ecological background pattern and potential was constructed. The results show that ecosystem services have declined significantly in the past ten years, and there are areas with good natural resilience and strong support from protection policies. Township as the unit of ecological restoration zoning. 1) The ecological maintenance area accounts for 7.7% of the total area, and focus should be on comprehensive improvement to promote economic and ecological sustainability. 2) The ecological protection area accounts for 44.5%, and focus should be on protection and stronger policy control. 3) The ecological improvement area account for 11.9%, and diversified and continuous maintenance measures should be adopted to strengthen the redundancy of regional ecological network. 4) The ecological restoration area accounts for 35.9%, and the priority for restoration should be areas with high natural resilience and policy support, and should mainly comprise long-term restoration projects. The coordinated restoration area has a high natural restoration; however, the policy support is insufficient. Cooperation with higher-level governments or with regional joint governance should be initiated to improve efficiency of the overall restoration in the region. [ABSTRACT FROM AUTHOR]

With a series of redevelopment activities, such as land consolidation and urban renewal, many cities in China have experienced land de-urbanization phenomena. These include the conversion of construction land into green spaces (such as parks, forests, and lawns), blue spaces (such as rivers, lakes, and wetlands), and farmland. However, there is currently limited research on diverse land de-urbanization types and pathways. This study focuses on investigating the land de-urbanization in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2014 to September 2023 using the Continuous Change Detection and Classification (CCDC) method. The results demonstrate that the GBA experienced 72.74 square kilometers of de-urbanization during the study period, primarily through the conversion of construction land to land with low plant coverage, including grassland and farmland. There were significant differences in the quantity and spatial agglomeration of de-urbanization between cities and within individual cities. Temporally, de-urbanization predominantly occurred in the period of 2016 to 2021, with a sharp decline in 2022. The temporal changes were significantly influenced by urban renewal policies and the impact of the COVID-19 pandemic. In terms of spatial clustering characteristics, the de-urbanization process in the GBA exhibited spatial agglomeration but was primarily characterized by low-level clustering. This study also examines the correlations between de-urbanization and factors including location and the stage of urbanization. The analysis showed that de-urbanization within cities tended to concentrate near the main urban roads within a range of 10–30 km from city centers. The trend of de-urbanization followed a pattern that is consistent with the Northam curve, where de-urbanization tends to increase during the rapid urbanization phase and decline as urbanization reaches a mature stage. Overall, this study provides valuable insights for the redevelopment of construction land within the context of ecological civilization construction. It also offers suggestions for urban land development and redevelopment in metropolitan areas. [ABSTRACT FROM AUTHOR]

This article examines the dynamics of scientific and technological innovation and cooperation in the Guangdong–Hong Kong–Macao Greater Bay Area. It focuses on unraveling the intricate web of influences that steer patenting and transformation within 34 universities in this region. The study reveals the spatial spillover of university patent applications and delves into the nuanced choices universities make in transforming patents. The findings underscore the antecedents of university patent applications and reveal their propensity for spatial spillovers across the region. Key determinants, in particular the government funding and the economic prosperity of the region in which the university is located, do not positively affect university patent applications. Interestingly, institutional distance can assist colleges in the region in generating more patents. Moreover, the study delineates two central pathways for patent transformation within universities: one involves the strategic allocation of internal resources, while the other depends on collaborative ventures between universities and their respective regional ecosystems. This dual approach illuminates viable pathways for the evolution of university patents and provides insights into leveraging internal dynamics and fostering collaborative networks with the broader regional innovation milieu. [ABSTRACT FROM AUTHOR]

Understanding the economic impact of COVID-19 is the foundation for formulating targeted policies promoting economic recovery. This study uses panel data of the county economy in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2017 to 2022. Firstly, the evolution characteristics of the economic structure in the GBA were analyzed using the standard deviation ellipse, geographical concentration, and spatial autocorrelation methods. Then, we revealed the changes in various economic indicators. Finally, a spatial Durbin model was constructed to study the factors affecting economic growth and spatial spillover effects in different periods. The results reveal that the economic distribution in the GBA presents a "core–edge" structure. The FDI, consumption, and exports of the Greater Bay Area fluctuate greatly, while investment growth is relatively stable. There is a significant spatial spillover effect in the county economy of the GBA. Investment, consumption, exports, labor, and innovation all have significant positive effects on economic growth, with investment having the greatest impact, while FDI has a significant negative impact. The impact of COVID-19 on the economy of the GBA is mainly reflected in the weakening of spatial spillovers, the strengthening of economic agglomeration, the decline in factor growth, and the change in the driving effect of factors on the economy. These findings can provide a reference for formulating targeted economic development policies. [ABSTRACT FROM AUTHOR]

The construction of ecological security pattern (ESP) is of great scientific significance for solving the problem of habitat fragmentation in urban environment. However, previous studies mainly focused on the ESP in land area, leaving the sea area to be ignored. This study took the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and its offshore area as an example and integrated the land-sea coordination into the construction of ESP based on the minimum resistance model, gravity model, and graph theory centrality. The results showed that there are 171 and 56 ecological sources for land area and offshore area, accounting for 31.46% and 21.51% of total area, respectively. Twenty-four important ecological corridors with a total length of 2738.05 km were identified in GBA, and the width is proposed to be less than 100 m. Moreover, the α, β, and γ index of the ecological network in the study area is 0.19, 1.33, and 0.5, respectively, indicating that the ecological network structure is complex and the connectivity between ecological nodes is good. The ecological restoration area includes 286.6 km2 of ecological pinch points and 140.44 km2 of ecological barrier. The overall ESP of the study area is "one ring, two belts, and four zones." The main body of the area with a superior ecological environment is distributed in a ring-like pattern near the outer edge of the study area, and two belts (important ecological corridor and ecological corridor) are distributed in a network. According to the ecological characteristics, the study area was divided into four zones: ecological preservation areas, ecological restoration areas, limited construction areas, and optimized construction areas. The ESP established herein institute provides a reference for the revision of ecological space control and optimization measures in the GBA. It also provides effective and systematic means to solve ecological problems in the current territorial spatial planning and territorial ecological restoration of coastal urban agglomeration. [ABSTRACT FROM AUTHOR]

As a critical engine for national economic growth, mega urban agglomerations have significant scale effects and economic and environmental spillover effects. This paper aims to study the green and low-carbon coordinated development of mega urban agglomerations to evaluate the country’s level of ecological civilization and its green and low-carbon development. The traditional research on green and low-carbon urban development tends to homogenize the redistribution theme, leading to significant errors in spatial allocation. This results in a lower accuracy of spatial distribution calculations for green development. Additionally, the research is constrained by data precision and methodology, making it challenging to measure the spatial differences in green and low-carbon development within urban clusters at the block level. This limitation hinders the ability to conduct detailed studies on the efficiency variations of green and low-carbon development in urban clusters. To achieve this aim, the study adopts the DPSR framework of the economic, resource, social, and ecological environment complex system and focuses on the Guangdong-Hong Kong-Macao Greater Bay Area in China. The study uses the entropy method, Gini coefficient method, and non-expected output super-efficiency SBM model to analyze the spatial effects and development efficiency of green and low-carbon development in this region from 2006 to 2020. The study results indicate that: (1) the overall level of green and low-carbon development in the Greater Bay Area is on the rise, with Shenzhen, Guangzhou, Foshan, and Zhuhai showing more stable development than other cities. Foreign direct investment and fixed asset investment in science and technology have significantly promoted green and low-carbon development. (2) The spatial differences in the region’s level of green and low-carbon development have narrowed trends, mainly due to differences between regions. However, well-developed cities such as Guangzhou and Shenzhen have taken the initiative to lead the development of other cities, fully leveraging their advantages in science and technology, geographical location, and other resources to promote the improvement of the external orientation of other cities. (3) The overall development efficiency of green and low-carbon in the Greater Bay Area is on the rise, with Guangzhou region showing overall stability, and Shenzhen region and Zhuhai region experiencing multiple ups and downs in their development. The three sub-regions show significant differences, but the balance and coordination of development have significantly improved. Finally, this study provides theoretical support for the future green and low-carbon development of urban clusters. It is advantageous for integrating the mainstream policy analysis framework of environmental economics with the complex adaptive systems of urban clusters. The research expands the boundaries of existing theoretical studies and offers new methodological approaches for interdisciplinary research. The study achieves a balance between the opportunity effects of green and low-carbon development and environmental policy constraints in super large urban clusters, effectively enhancing resource utilization efficiency in these clusters.

The rapid expansion of aquaculture ponds at the end of the last century raised concerns about their environmental and ecological impacts in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This study aims to comprehensively investigate the spatiotemporal evolutionary characteristics and explore the influencing factors of aquaculture development in the GBA. An automated approach was established to extract the aquaculture pond areas on the Google Earth Engine (GEE) platform using Landsat images and showed high accuracy. The aquaculture development in the GBA underwent three phases of rapid expansion (1986–1996), constant transformation (1996–2010), and drastic contraction (2010–2020), and was closely related to the important aquaculture policies in China and Guangdong Province. The local aquaculture ponds showed three evolutionary patterns of continuous shrinkage, earlier shrinkage, and later shrinkage, which were mainly influenced by the economic development level and urbanization in each city. Rapid urbanization created great demands for aquaculture products and intense land use competition, which drove the conversion of aquaculture ponds into impervious land and migration from the central GBA towards the surrounding coast and upstream areas. Government policies promoted the initial rapid increase and regulated the aquaculture ponds to develop towards a more environment-friendly and intensive mode, which led to a steady increase of aquaculture products despite the drastic decrease in aquaculture pond areas in the past decade. These evolutionary features are of significance for policymakers and farmers to maintain the sustainable development of aquaculture in the GBA and Guangdong Province.

City regions, as the most significant geographical consequence of globalization, have received constant attention by economic geographers. However, although mainstream theories such as the Global Production Network (GPN) theory explain the emergence of global urban areas well, there remains a lack of strong explanation for the obvious functional heterogeneity phenomenon of major cities within the Guangdong Hong Kong Macao Greater Bay Area (GBA). This study draws on the structuralist thinking method and introduces the perspective of civilization interaction, examining the historical reasons for the functional differentiation of core cities in different historical periods dominated by trade and production networks to explore the mechanism of forming a unique spatial order within the GBA. From the macro perspective of the formation of the world system and the transfer of China's basic economic zone, this study highlights that the development history of the GBA reflects the history of continuous interaction between continental and marine civilizations, which is finally embedded in the world system. Based on the evolution of the major city relations in the GBA, this study investigates the core-city relations across different periods—from the classical trade network era to the global production network era—and analyzes the formation mechanism of core-city relations in different periods. By analyzing the changes in the way civilizations interact in the era of innovation, the study looks forward to the direction of future spatial paradigm transformation in the GBA and posits that the Inner Bay Area may play a leading role. By expanding the dimension of historical observation, the study enriches the perspective of research on the global city regions and the GBA by combining the civilization interaction and the structuralist transformation characteristics with the analysis of the internal order of urban areas. Owing to the continuity and comparability of the interaction of civilizations, this study is able to apply the conclusions of the analysis of the relationships and spatial order of major cities across past historical stages to the new stage dominated by innovation for the future, as well as providing theoretical assistance for the analysis of regional development trends and formulating response plans.

Rapid global urbanization and its progress have profoundly affected urban vegetation. The ecological quality of urban vegetation is a vital indicator of regional ecological stability and health. A comprehensive assessment of the coupling coordination and coercive relationship between urbanization and the vegetation ecological quality is essential for promoting sustainable regional green development. Using the rapidly urbanizing Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration in China as an example, this study evaluates the vegetation quality condition and the level of urbanization and explores the dynamic relationship between vegetation ecological quality and urbanization processes. This study introduces the vegetation ecological quality index (VEQI) based on net primary productivity (NPP) and fractional vegetation cover (FVC), as well as the comprehensive urbanization index (CUI) derived from gross domestic production (GDP), population density, and nighttime lighting data. The coupling coordination and Tapio decoupling models are employed to assess the degree of coupling coordination and the decoupling relationship between the VEQI and CUI across different periods. The results showed that (1) from 2000 to 2020, the VEQI in the GBA showed a significant increase, accompanied by continuous urbanization, particularly evident with the high CUI values in central areas; (2) the coupling coordination degree (CCD) exhibits high values and significant change slopes in the central GBA, indicating dynamic interactions between urbanization and vegetation ecological quality; (3) the decoupling states between the VEQI and CUI are dominated by weak decoupling (WD), strong decoupling (SD), expansive negative decoupling (END), and expansive coupling (EC), suggesting improvements in the relationship between urbanization and vegetation ecological quality; (4) the coordinated development level of the VEQI and CUI in the study area shows improvement, and their decoupling relationship displays a positive trend. Nevertheless, it remains crucial to address the impact of urbanization pressure on vegetation ecological quality and to implement proactive measures in response. The results of this study provide theoretical support for mesoscale development planning, monitoring vegetation ecological conditions, and formulating environmental policies.

The effectiveness of ecological security patterns (ESPs) in maintaining regional ecological stability and promoting sustainable development is widely recognized. However, limited research has focused on the early warning of risks inherent in ESPs. In this study, the Guangdong–Hong Kong–Macao Greater Bay Area (GHKMGBA) is taken as the study area, and ecological security risk zones are delineated by combining the landscape ecological risk index and habitat quality, and a multi-level ESP is constructed based on the circuit theory. The PLUS model was employed to simulate future built-up land expansion under different scenarios, which were then extracted and overlaid with the multi-level ESP to enable the multi-scenario early warning of ESP risks. The results showed the following: The ESP in the central plains and coastal areas of the GHKMGBA exhibits a high level of ecological security risk, whereas the peripheral forested areas face less threat, which is crucial for regional ecological stability. The ESP, comprising ecological sources, corridors, and pinch points, is crucial for maintaining regional ecological flow stability, with tertiary corridors under significant stress and risk in all scenarios, requiring focused restoration and enhancement efforts. There are significant differences in risk early warning severity within the ESP across various development scenarios. Under the ecological protection scenario, the ESP will have the best early warning situation, effectively protecting ecological land and reducing ecological damage, providing a valuable reference for regional development policies. However, it must not overlook economic development and still needs to further seek a balance between economic growth and ecological protection.