Burnout among healthcare providers: Its prevalence and association with anxiety and depression during the COVID-19 pandemic in Macao, China.

INTRODUCTION: Burnout in healthcare providers (HPs) might lead to negative consequences at personal, patient-care and healthcare system levels especially during the COVID-19 pandemic. This study aimed to investigate the prevalence of burnout and the contributing variables, and to explore how, from health workforce management perspective, HPs' experiences related to carrying out COVID-19 duties would be associated with their burnout. METHODS: A cross-sectional, open online survey, informed by physical and psychological attributes reportedly related to burnout, the Copenhagen Burnout Inventory (CBI) and the Hospital Anxiety and Depression Scale (HADS), was completed by HPs in Macau, China during October and December 2021. Factors associated with burnout were analysed using multiple logistic regressions. RESULTS: Among the 498 valid responses, the participants included doctors (37.5%), nurses (27.1%), medical laboratory technologist (11.4%) and pharmacy professionals (10.8%), with the majority being female (66.1%), aged between 25-44years (66.0%), and participated in the COVID-19 duties (82.9%). High levels of burnout (personal (60.4%), work-related (50.6%) and client-related (31.5%)), anxiety (60.6%), and depression (63.4%) were identified. Anxiety and depression remained significantly and positively associated with all types of burnout after controlling for the strong effects of demographic and work factors (e.g. working in the public sector or hospital, or having COVID-19 duties). HPs participated in COVID-19 duties were more vulnerable to burnout than their counterparts and were mostly dissatisfied with the accessibility of psychological support at workplace (62.6%), workforce distribution for COVID-19 duties (50.0%), ability to rest and recover (46.2%), and remuneration (44.7%), all of which were associated with the occurrence of burnout. CONCLUSIONS: Personal, professional and health management factors were found attributable to the burnout experienced by HPs during the COVID-19 pandemic, requiring actions from individual and organizational level. Longitudinal studies are needed to monitor the trend of burnout and to inform effective strategies of this occupational phenomenon.

Research on Wind Environment and Morphological Effects of High-Rise Buildings in Macau: An Example from the New Reclamation Area around Areia Preta.

The Macau peninsula is close to the tropical ocean, with a high population density and a large number of high-rise buildings, which require a windy environment with good ventilation and heat dissipation. Based on residential samples and the degree of agglomeration, the high-rise residential area in Areia Preta was selected as the focus of this study. Meanwhile, summer typhoons pose serious safety risks to high-rise buildings. Therefore, it is necessary to study the connection between spatial form and the wind environment. First of all, this research is based on relevant concepts and the wind environment evaluation system of high-rise buildings and conducts research on high-rise residential areas in Areia Preta. PHOENICS software is used to simulate the prevailing monsoon in winter and summer, as well as a typhoon in an extreme wind environment, and summarize the wind environment's characteristics. Secondly, by comparing the parameter calculation and simulation results, the possible relationship between the causes of each wind field is studied. Finally, conclusions are drawn about the urban form and wind environment of the site, and corresponding control strategies are proposed to reduce the shielding effect between buildings and typhoon damage. It can be used as a theoretical basis and reference point for urban construction and high-rise building planning and layout.

Smoking Bans and Circulatory System Disease Mortality Reduction in Macao (China): Using GRA Models.

This study evaluates the association between smoking rates and mortality from circulatory system diseases (CSD) after implementing a series of smoking bans in Macao (China). (1) Background: Macao phased in strict total smoking bans since 2012. During the past decade, smoking rates among Macao women have dropped by half. CSD mortalities in Macao also show a declining trend. (2) Method: Grey relational analysis (GRA) models were adopted to rank the importance of some key factors, such as income per capita, physician density, and smoking rates. Additionally, regressions were performed with the bootstrapping method. (3) Results: Overall, smoking rate was ranked as the most important factor affecting CSD mortality among the Macao population. It consistently remains the primary factor among Macao's female population. Each year, on average 5 CSD-caused deaths were avoided among every 100,000 women, equivalent to about 11.45% of the mean annual CSD mortality. (4) Conclusions: After the implementation of smoking bans in Macao, the decrease in smoking rate among women plays a primary role in the reduction in CSD mortality. To avoid excess CSD mortality due to smoking, Macao needs to continue to promote smoking cessation among the male population.

The Nonlinear Impact of Mobile Human Activities on Vegetation Change in the Guangdong-Hong Kong-Macao Greater Bay Area.

Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.

Home or hospital as the place of end-of-life care and death: A survey among Chinese residents of Macao.

Objectives: The study was the first to explore Chinese residents' preferred place of care at the end of life and preferred place of death in Macao. Methods: A cross-sectional questionnaire survey was conducted online and face-to-face. The questionnaire was designed in Chinese, and both online and face-to-face surveys were conducted in Chinese. The study was conducted in Macao. Macao residents aged 18 years and older were recruited. Results: A total of 737 responses were valid, 65% were female, aged between 19 and 101 years; 43.4% of respondents preferred to be cared for at home in the last 6 months; however, less than one-fifth preferred to die at home. One-third of respondents chose to die in the hospice, and over a quarter of them preferred to die in hospitals. Compared with people aged between 18 and 39 years, people aged between 40 and 64 years did not want to be cared for at home in the last 6 months, and they did not want to die at home either. Conclusion: The results of the study suggested that there is a need for palliative home care in Macao, and the government should consider developing such a service and review current laws and regulations in supporting the service. Education is equally important for healthcare professionals, enabling them to support palliative care development in the community.

Source or sink role of an urban lake for microplastics from Guangdong-Hong Kong-Macao greater bay area, China.

Plastic production and consumption in China are larger than others in the world, and the challenge of microplastic pollution is widespread. With the development of urbanization in the Guangdong-Hong Kong-Macao Greater Bay Area, China, the environmental pollution of microplastics is becoming an increasingly prominent issue. Here, the spatial and temporal distribution characteristics, sources, and ecological risks of microplastics were analyzed in water from an urban lake, Xinghu Lake, as well as the contribution of rivers. Importantly, the roles of urban lakes for microplastics were demonstrated through the investigations of contributions and fluxes for microplastic in rivers. The results showed that the average abundances of microplastics in water of Xinghu Lake were 4.8 ± 2.2 and 10.1 ± 7.6 particles/m3 in wet and dry seasons, and the average contribution degree of the inflow rivers was 75%. The size of microplastics in water from Xinghu Lake and its tributaries was concentrated in the range of 200-1000 µm. In general, the average comprehensive potential ecological risk indexes of microplastics in water were 247 ± 120.6 and 273.1 ± 353.7 in wet and dry seasons, which the high ecological risks of them were found through the adjusted evaluation method. There were also mutual effects among microplastic abundance, the concentrations of total nitrogen and organic carbon. Finally, Xinghu Lake has been a sink for microplastics both in wet and dry seasons, and it would be a source of microplastics under the influence of extreme weather and anthropogenic factors.

The Effect of Mindfulness Intervention on the Psychological Skills and Shooting Performances in Male Collegiate Basketball Athletes in Macau: A Quasi-Experimental Study.

BACKGROUND: This study adopted a quasi-experimental design to examine the effect of a 7-week mindfulness intervention on the psychological coping ability and shooting performance of college-level male basketball athletes in Macau. METHODS: A total of 43 male college basketball athletes in Macau were selected as the participants. Besides the regular basketball training, the intervention group (n = 23) received a 7-week mindfulness training; the weekly mindfulness intervention session lasted around one hour according to the mindfulness training manual for athletes, while the control group (n = 20) did not receive any mindfulness training. Before and immediately after the 7-week intervention, all players performed the following tests: the "Five-Facet Mindfulness Questionnaire", the "Acceptance and Action Questionnaire", the "Sport Competition Anxiety Test", the "Mindfulness Attention Awareness Scale", and three shooting tests. An independent-sample t-test and a paired-sample t-test were used to analyze the between- and within-group differences. Moreover, a repeated measures ANOVA was used to assess the group, time, and group-by-time effects on psychological skills and shooting performances. RESULTS: The intervention resulted in both significant between-group and within-group differences in mindfulness level, acceptance level, attention level, three-point, and free-throw shooting performances (all p < 0.05, Cohen's d ranging from 0.565 to 1.117). CONCLUSION: While further study is necessary, the present study suggests that the 7-week mindfulness training program can significantly improve psychological outcomes and shooting performance in Macau college basketball athletes. Future studies involving competition settings and objective metrics will aid in verifying mindfulness as the prevalent practice among basketball practitioners and athletes.

Assessing the algal population dynamics using multiple machine learning approaches: Application to Macao reservoirs.

The quality of reservoir water is important to the health and wellbeing of human and animals. Eutrophication is one of the most serious problems threatening the safety of reservoir water resource. Machine learning (ML) approaches are effective tools to understand and evaluate various environmental processes of concern, such as eutrophication. However, limited studies have compared the performances of different ML models to reveal algal dynamics using time-series data of redundant variables. In this study, the water quality data from two reservoirs in Macao were analyzed by adopting various ML approaches, including stepwise multiple linear regression (LR), principal component (PC)-LR, PC-artificial neuron network (ANN) and genetic algorithm (GA)-ANN-connective weight (CW) models. The influence of water quality parameters on algal growth and proliferation in two reservoirs was systematically investigated. The GA-ANN-CW model demonstrated the best performance in reducing the size of data and interpreting the algal population dynamics data, which displayed higher R-squared, lower mean absolute percentage error and lower root mean squared error values. Moreover, the variable contribution based on ML approaches suggest that water quality parameters, such as silica, phosphorus, nitrogen, and suspended solid have a direct impact on algal metabolisms in two reservoirs' water systems. This study can expand our capacity in adopting ML models in predicting algal population dynamics based on time-series data of redundant variables.

Driving factors and emission reduction scenarios analysis of CO2 emissions in Guangdong-Hong Kong-Macao Greater Bay Area and surrounding cities based on LMDI and system dynamics.

As one of the most open and economically dynamic regions in China, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is at the forefront of low-carbon development and has an exemplary and leading role for other regions. This study provides a research framework based on the Logarithmic Mean Divisia Index (LMDI) and system dynamics (SD) by first compiling an inventory of CO2 emissions in the GBA and surrounding cities from 2000 to 2019 and then systematically and comprehensively analyzing the driving factors, future trends and policy implications of CO2 emissions in the GBA and surrounding cities. The results show that (a) CO2 emissions in the GBA and surrounding cities grew from 253.39 Mt in 2000 to 627.86 Mt in 2019, with an average annual growth rate of 4.89 %. The per capita CO2 emissions showed a continuous decreasing trend, and the overall carbon intensity of each sector showed a decreasing trend. (b) GDP per capita growth has the greatest effect on CO2 emissions, followed by the number of transport vehicles and population. The negative effects are energy intensity, average output of transportation vehicles, and residential energy intensity, with energy intensity being the most critical. (c) In the baseline scenario, regional CO2 emissions in 2030 are 1.25 times higher than those in 2019 and continue to grow. (d) Technological innovation measures are the most effective among individual emission reduction policies, followed by optimization of industrial structure. Furthermore, energy structure adjustment, vehicle licensing restrictions, and residents' green living are less effective. (e) Under comprehensive emission reduction measures, the region can achieve carbon emissions peaking in 2026 and reduce the regional carbon intensity by 66.24 % in 2030 compared with 2005. This study provides effective data support for the GBA and surrounding cities to formulate low carbon policies, promote carbon emission reduction and achieve carbon emissions peaking early.

Epidemiology of SARS-CoV-2 Omicron BA.5 Infections, Macau, June-July 2022.

A SARS-CoV-2 Omicron BA.5 outbreak occurred in Macau from mid-June through July 2022. Out of >1,800 laboratory-confirmed cases, most were mild or asymptomatic; only 6 deaths were recorded. The outbreak was controlled through stringent public health and social measures, such as repeated universal testing and a stay-at-home order lasting 2 weeks.

Development and Psychometric Evaluation of a Chinese Instrument of Knowledge, Attitude and Preventive Practice on Dementia Care in Macao.

BACKGROUND: Very few instruments to integrate knowledge, attitude and practice into dementia care as a holistic perspective were available to the Chinese. METHOD: This article documented the development of a 30-item self-administered Chinese instrument of knowledge, attitude and preventive practice on dementia care and reported the results of psychometric testing among 1500 Chinese in Macao Special Administrative Region (SAR), including 234 primary health professionals, 272 staff working at day-care centers and nursing homes, 586 high school students and 408 community-dwelling older people. The Chinese instrument was developed through literature review and committee review. The psychometric methods were used to evaluate the reliability and validity of the Chinese instrument as measures of knowledge, attitude and preventive practice on dementia care for the Chinese. RESULTS: The preliminary results indicated that the Content Validity Index of the Chinese instrument was .973 and Cronbach's alpha coefficient of the Chinese instrument was .842, among which Knowledge subscale, Attitude subscale and Preventive Practice subscale were .749, .633 and .845 respectively. The means and standard deviation were 65.13 ± 24.56 for Knowledge subscale, 74.76 ± 8.37 for Attitude subscale, 73.22 ± 14.05 for Preventative Practice subscale, and 70.99 ± 11.27 for the Chinese instrument. CONCLUSION: The 30-item self-administered Chinese instrument of knowledge, attitude and preventive practice on dementia care had satisfied the psychometric evaluation well enough to warrant further use, and could also have particular implications for other Chinese populations all over the world.

A compensation mechanism for air pollutants generated by tourism-related land-based transportation: An exergy-based case study from Macao.

This paper discusses the compensation standard for exhaust pollution and devises a compensation mechanism for Macao's tourism-related transport sector based on an integration of chemical exergy and universal exergy, using data on gasoline consumption by automobile sector retrieved from the transportation industry. The results reveal that: (1) the exergy values of air pollutant emissions increased from 1.53 × 1012 kJ in 2010 to 2.03 × 1012 kJ in 2019 (an increase of 1.33 times), and the exergy of CO, NOx, and SO2 emissions accounted for 77.5%, 20.4% and 2.1% of total exhaust emissions in Macao respectively. (2) In 2019, the monetary value of emission exergy, and the environmental costs of air pollution, were 1.7 times greater than in 2010. (3) If Light Rail Transit is compensated for, then the mean interval's values of the upper and lower limits of the compensation standard are 0.55 USD and 0.05 USD, respectively. When gasoline tax is used as a means of compensation it is necessary to raise its rate by about 8% based on the tax rate. A three-stage bargaining game model is used to provide evidence that this compensation standard is practical and acceptable.

Epidemiology of SARS-CoV-2 Omicron BA.5 Infections, Macau, June-July 2022.

A SARS-CoV-2 Omicron BA.5 outbreak occurred in Macau from mid-June through July 2022. Out of >1,800 laboratory-confirmed cases, most were mild or asymptomatic; only 6 deaths were recorded. The outbreak was controlled through stringent public health and social measures, such as repeated universal testing and a stay-at-home order lasting 2 weeks.

Urban Heat Island Intensity Changes in Guangdong-Hong Kong-Macao Greater Bay Area of China Revealed by Downscaling MODIS LST with Deep Learning.

The urban heat island (UHI) effect caused by urbanization negatively impacts the ecological environment and human health. It is crucial for urban planning and social development to monitor the urban heat island effect and study its mechanism. Due to spatial and temporal resolution limitations, existing land surface temperature (LST) data obtained from remote sensing data is challenging to meet the long-term fine-scale surface temperature mapping requirement. Given the above situation, this paper introduced the ResNet-based surface temperature downscaling method to make up for the data deficiency and applied it to the study of thermal environment change in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2000 to 2020. The results showed (1) the ResNet-based surface temperature downscaling method achieves high accuracy (R2 above 0.85) and is suitable for generating 30 m-resolution surface temperature data from 1 km data; (2) the area of severe heat islands in the GBA continued to increase, increasing by 7.13 times within 20 years; and (3) except for Hong Kong and Macau, the heat island intensity of most cities showed an apparent upward trend, especially the cities with rapid urban expansion such as Guangzhou, Zhongshan, and Foshan. In general, the evolution of the heat island in the GBA diverges from the central urban area to the surrounding areas, with a phenomenon of local aggregation and the area of the intense heat island in the Guangzhou-Foshan metropolitan area is the largest. This study can enrich the downscaling research methods of surface temperature products in complex areas with surface heterogeneity and provide a reference for urban spatial planning in the GBA.

Spatial Relationships and Impact Effects between Urbanization and Ecosystem Health in Urban Agglomerations along the Belt and Road: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area.

A healthy ecosystem is fundamental for sustainable urban development. Rapid urbanization has altered landscape patterns and ecological functions, resulting in disturbances to ecosystem health. Exploring the effects of urbanization on ecosystem health and the spatial relationships between them is significant for cities along the "Belt and Road" aiming to achieve sustainable regional development. This study took the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as an example and measured the urbanization level (UL) and ecosystem health index (EHI) from 2000 to 2020 using multisource data. We used bivariate spatial autocorrelation, the geographically weighted regression model (GWR), and the optimal parameters-based geographical detector (OPGD) model to clarify the impact of urbanization on ecosystem health and the spatial relationship between them from multiple perspectives. The major findings of this study were: (1) the EHI in the GBA decreased significantly during the study period, dropping from 0.282 to 0.255, whereas the UL increased significantly, exhibiting opposite spatial distribution features; (2) there was a significant negative spatial correlation between UL and the EHI and significant spatial heterogeneity between high-low and low-high types in the GBA; (3) the negative effects of urbanization on ecosystem health were predominant and becoming more pronounced in the central GBA. Moreover, urbanization had an increasingly significant negative effect, leading to the deterioration of ecosystem health, in the central GBA. Population urbanization drove land urbanization, which became the main factor affecting ecosystem health in the GBA. Overall, urbanization had a significant negative effect on ecosystem health, with this impact being particularly prominent in the core urban junctions of the GBA, which require urgent attention. The results of the study provide a basis for decision making in the context of the steady urbanization and ecosystem health protection of cities along the "Belt and Road".

The Willingness to Help People With Dementia Symptoms Among Four Occupation Practitioners in Macao.

BACKGROUND: Dementia-friendly community has been promoted in Macao since 2016. There is no study investigating the understanding of nor attitudes towards dementia among public contact staff in Macao. This study aimed to (i) understand the level of knowledge of dementia, (ii) examine the attitudes towards people living with dementia, and (iii) explore the associated factors of the willingness to help people with dementia symptoms among police officers, bank officers, bus drivers, and building superintendents. METHODS: A cross-sectional survey was conducted between January and May 2019 using a structured questionnaire. RESULTS: A total of 351 valid questionnaires were received. Building superintendents had more knowledge while police officers and bank officers had more positive attitudes. All practitioners were more willing to help people with dementia symptoms when they were on official duty. Participants who had more knowledge about dementia were associated with a higher willingness to help people with dementia symptoms.

How working-age population education and health of older people shape the burden of population aging: A comparative study of Macau, Hong Kong, and Singapore.

Macau, Hong Kong and Singapore are all facing increasing population aging. Those aged 65 and over make up the old-age population. The working-age population refers to the population aged 15 to 64. Conventionally, the burden of population aging is measured by the Old-Age Dependency Ratio, which is the ratio of the old-age population to the working-age population. As life expectancy rises, depending exclusively on age to calculate the burden of aging hinders the development of effective anti-aging strategies. The working-age population's education and the elderly's health affect the aging burden's support and generator, respectively. Including them in the calculation gives us a fuller view of the burden of aging. Objective: To compare the population aging burden in Macau, Hong Kong, and Singapore by including working-age population education and elderly health. Methods: The overall, working-age and old-age population and proportion, as well as the Old-Age Dependency Ratio of Macau, Hong Kong, and Singapore, were collected from the World Bank database. The life expectancy at 65 was extracted from the 2022 World Population Prospect. The tertiary education rate of the working-age population and the self-rated health status of the old-age population were retrieved from governments' statistical reports. We then calculated the Education-Health Adjusted Old-Age Dependency Ratio, a set of four equations showing the support of the working-age population on the old-age population, where OADRh_t and OADRuh_t represent the burden of healthy and unhealthy old-age population on the working-age population with tertiary education; similarly, OADRh_nt and OADRuh_nt indicate the burden placed on the working-age population without tertiary education by healthy and unhealthy old-age population. Lastly, for comparison with the conventional Old-Age Dependency Ratio, we generated the Weighted Education-Health Adjusted Old-Age Dependency Ratio. Results: Hong Kong has the greatest old-age population proportion and Old-Age Dependency Ratio, yet its growth rates are moderate and stable, ranging from 0 to 4% and 0 to 6%, respectively. Macau and Singapore experienced sharper changes in old-age population proportion and the Old-Age Dependency Ratio, with Macau's Old-Age Dependency Ratio varying between -2.66 and 8.50% and Singapore's ranging from -1.53 to 9.70%. Three cities showed different patterns in four Education-Health Adjusted Old-Age Dependency Ratio indicators. In Macau, the OADRh_nt and OADRuh_nt increased by 0.4 and 6.2, while the OADRh_t and OADRuh_t decreased by 13.5 and 15.3 from 2004 to 2016. In Hong Kong, only the OADRuh_t fell by 9.4, and the other three increased from 2003 to 2015. In Singapore, the OADRh_nt and OADRh_t increased by 3.8 and 1.0, while OADRuh_nt and OADRuh_t decreased by 1.2 and 3.9 from 2007 to 2011. The Weighted Education-Health Adjusted Old-Age Dependency Ratios are all smaller than the conventional Old-Age Dependency Ratio in the three regions, particularly in Singapore. The Weighted Education-Health Adjusted Old-Age Dependency Ratio of Singapore was reduced by 9.5 to 30.5% compared with the conventional Old-Age Dependency Ratio, that of Hong Kong reduced by 6.2 to 22.5%, and that of Macau reduced by 4.4 to 16.1%. Conclusion: This is the first study to compare the aging burden in Macau, Hong Kong, and Singapore in connection to working-age population education and elderly health. With the new assessment, the burden of population aging in three regions has been reduced, showing that improving the education of the working-age population and maintaining older people's wellbeing can assist authorities to deal with population aging, especially in Macau and Hong Kong.

A study on the evolution of economic patterns and urban network system in Guangdong-Hong Kong-Macao greater bay area.

The COVID-19 pandemic has seriously affected China's macroeconomy, industrial transformation, and high-quality development. Research on economic patterns and urban network systems can provide a reference for healthy development of the regional economic system. The evolution of the economic pattern and urban network system of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 is investigated using methods (e.g., the gravity center model, the gravitational force model, social network analysis, and geographic information system). (1) The gravity center of gross domestic product (GDP) of the GBA is located in Nansha district, Guangzhou, with a skewing direction northwest-east-northwest and a movement rate of "large-small-large." The center of import and export and the center of consumption show a "zigzagging migration" in which the center of investment shows an "irregular (random) migration". (2) The economic connection degree of cities in the GBA exhibits a high ascending velocity, and the whole area tends to be mature, with a significant effect of spatial proximity. With the steady increase in network density, there is significant polarization of network centrality in the region. The four major cohesive subgroups have been relatively stable and consistent with the degree of geographic proximity of the cities. The center-periphery structure is more significant, in which the core area is extended to the cities on the east coast of the Pearl River Estuary, thus forming the core cluster of "Hong Kong-Shenzhen-Guangzhou-Dongguan." In this study, the evolution of economic patterns and urban network systems in the GBA over the past decade is analyzed using multiple methods (i.e., gravity model, urban network system analysis, and geographic information system) based on urban socioeconomic data by starting from various spatial elements (e.g., "points, lines, and networks") to gain insights into and optimize research on regional economic development after the COVID-19 pandemic.

Identification of Typical Ecosystem Types by Integrating Active and Passive Time Series Data of the Guangdong-Hong Kong-Macao Greater Bay Area, China.

The identification of ecosystem types is important in ecological environmental assessment. However, due to cloud and rain and complex land cover characteristics, commonly used ecosystem identification methods have always lacked accuracy in subtropical urban agglomerations. In this study, China's Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was taken as a study area, and the Sentinel-1 and Sentinel-2 data were used as the fusion of active and passive remote sensing data with time series data to distinguish typical ecosystem types in subtropical urban agglomerations. Our results showed the following: (1) The importance of different features varies widely in different types of ecosystems. For grassland and arable land, two specific texture features (VV_dvar and VH_diss) are most important; in forest and mangrove areas, synthetic-aperture radar (SAR) data for the months of October and September are most important. (2) The use of active time series remote sensing data can significantly improve the classification accuracy by 3.33%, while passive time series remote sensing data improves by 4.76%. When they are integrated, accuracy is further improved, reaching a level of 84.29%. (3) Time series passive data (NDVI) serve best to distinguish grassland from arable land, while time series active data (SAR data) are best able to distinguish mangrove from forest. The integration of active and passive time series data also improves precision in distinguishing vegetation ecosystem types, such as forest, mangrove, arable land, and, especially, grassland, where the accuracy increased by 21.88%. By obtaining real-time and more accurate land cover type change information, this study could better serve regional change detection and ecosystem service function assessment at different scales, thereby supporting decision makers in urban agglomerations.

Research on Multi-Scale Ecological Network Connectivity-Taking the Guangdong-Hong Kong-Macao Greater Bay Area as a Case Study.

The Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration is an urban agglomeration with some of the most intensive urbanization since 1980s. A large amount of cultivated land, forest land, water bodies and other land types in the region has been occupied by construction land, resulting in fragmented ecological landscapes and biodiversity in the region and causing many other ecological problems. Based on this, this paper takes the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, constructs an ecological network of the dispersion scale of five species from 1990 to 2020 based on a morphological spatial pattern analysis (MSPA) method, identifies the ecological groups in the network and uses the core node-based community evolution path tracking algorithm to analyze the ecological groups in order to explore the changes of ecological network connectivity at different scales in the region and to reveal the overall and local characteristics and changes of the migratory space of terrestrial mammals with different dispersion capabilities. The research results show that: (1) From 1990 to 2020, the area of construction land in the Guangdong-Hong Kong-Macao Greater Bay Area increased sharply, with good connectivity in the northwest, southwest and eastern regions and poor connectivity in the central region. (2) There are obvious differences between the overall and local changes in the connectivity trends of multi-scale regional ecological networks. On the whole, the overall ecological connectivity of the ecological network at each scale showed a gradual upward trend, and the overall connectivity index IIC and the possible connectivity index PC gradually increased with the increase of the maximum dispersal distance of species. From the perspective of local patches, the larger the species dispersion scale, the larger the value of the revised betweenness centrality index and the patch possible connectivity index. (3) The distribution of ecological groups at different species dispersion scales is different, and the smaller the dispersal scale of the species, the greater the distribution of ecological groups. Small-scale species are limited by the maximum dispersal distance, and the range of their ecological groups is generally small. Small-scale (3 km), mesoscale (10 km) and large-scale (30 km) core nodes of ecological groups show a gradual increase trend, and the overall connectivity of ecological groups has improved. However, the core nodes of the extra-large-scale (60 km) and ultra-large-scale (100 km) ecological groups show a trend of decreasing fluctuations, and the overall connectivity within the ecological group has declined. This study is helpful to clarify the structural characteristics of regional ecological space and provide a theoretical basis for regional ecological planning.