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• Applying InVEST model to determine ecological sources. • Building ecological resistance surfaces for highly urbanized region. • Proposing a local evaluation model for ecological networks. • Summarizing the ecological network development suggestions. Metropolitan regions usually encounter sustainability difficulties such as overexploitation of resources, severe land scarcity, and ecological degradation, resulting in the progressive collapse of ecological networks (ENs). It is therefore essential to strengthen the construction and protection of ENs by integrating various resources, improving the quality of the urban ecological environment and creating a favourable living environment. Using the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, in this paper, the ecological resistance indicator system that balances natural condition and human disturbance is rebuilt. In doing so, a construction scheme (applicable to highly urbanised areas) is established to simulate ENs at a more precise scale. Moreover, a local evaluation model of ENs is proposed and the spatial patterns of multiple indicators are fully summarised. The findings show that the ENs of the Guangdong-Hong Kong-Macao Greater Bay Area exhibit apparent spatial disparity. Disturbance through human activities seriously affects the spatial pattern of ENs, leading to structural imbalance and quality impairment of ecological corridors. Based on our assessment, the construction of complementary ecological corridors in the "two green belts" planning of the Guangdong-Hong Kong-Macao Greater Bay Area will improve structural problems. The findings of this paper can provide a reference to the harmonisation of urban development and ecological protection, by guiding the scientific management of ecological spaces in highly urbanised regions. [ABSTRACT FROM AUTHOR]

The construction of an ecological security pattern (ESP) is an important undertaking in ensuring the stability of the ecosystem and the long-term growth of humanity. Existing research, However, existing research often overlooks the quantification of policy implications in ESP development. The objective of this paper was to bridge this gap by integrating policy quantification analysis (PQA) with nature, society and into ESP construction and providing targeted ecological management recommendations. The policy texts were quantified into reusable research data, which served as a foundation for the selection of indicators and the optimization of ecological security patterns, by using machine learning techniques. The methodology "Patch-matrix-corridor" was used to create a spatially correlated ecological security pattern. Through factor analysis and Random Forest (RF), the impact of each indicator on ecological security was thoroughly examined, offering substantial support for policy development and ESP construction planning. The Guangdong-Hong Kong-Macao Greater Bay Area(GBA) was selected as the study area, the study found that: (1) The proposed framework PQA based-ESP could provide a useful eco-management tools. (2) Policy adaptability had a substantial impact on environmental security in the GBA, but the ecosystem service index has the highest impact. (3) Applying the framework, we identified a total of 1,993 km2 of ecological sources, 23 key ecological corridors, 58 general ecological corridors, and 31 ecological nodes. An improved ESP, characterized as "one circle, two bays, three rivers, multiple areas, corridors, and nodes," was constructed in the GBA. (4) Given the multi-scale analysis, tailored ecological management policy recommendations were proposed for each city in the GBA. The study's findings offer actionable solutions for the international community facing growing ecological challenges. [ABSTRACT FROM AUTHOR]

• A method based on Neural Network is proposed for provincial-level CO 2 emissions estimation. • An autoencoder is proposed to downscale the provincial-level CO 2 emissions to city-level. • A complete city-level CO 2 emissions inventory of GBA and surrounding cities is complied. • Spatial dependence and agglomeration characteristics of CO 2 emissions are analyzed. • Spatio-temporal heterogeneity of factors affecting CO 2 emissions is investigated. Significant attention has been given to the issue of CO 2 emissions worldwide, especially for China as the largest emitter. Cities, as the main carriers of China's economic development, account for up to 85 % of CO 2 emissions from energy use in the country. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and surrounding cities play important leading roles in low-carbon development. However, compiling city-level CO 2 emissions is challenging due to the limited availability of data. In this paper, a new idea is proposed by using SSA-BP for estimating provincial-level CO 2 emissions and downscaling provincial-level CO 2 emissions to city-level CO 2 emissions by reconstructing missing values of city-level CO 2 emissions with an autoencoder. This study compiles a city-level CO 2 emissions inventory and conducts a spatio-temporal analysis of CO 2 emissions in the GBA and surrounding cities. The results show that CO 2 emissions exhibit a spatial distribution pattern with spatial dependence. Furthermore, according to the analysis of spatio-temporal heterogeneity, GDP influenced CO 2 emissions the most within the five influencing factors, and the influences of GDP, population, and energy intensity were mainly positive, while the influence of patents was mainly negative, and that of trade was both positive and negative. [ABSTRACT FROM AUTHOR]

[Display omitted] • Groundwater vulnerability zonation investigation is conducted for GHM Greater Bay Area. • Three different perspectives are comprehensively considered in this study. • Groundwater risk, function value and contamination status are superposed using the AHP method. • Quantification and visualization of groundwater contamination prevention regionalization. • The AHP-DRASTICH model is an effective method to evaluate the groundwater risk in shallow aquifers. The groundwater contamination assessment and prevention regionalization are an important part of groundwater investigation, which is of great significance to groundwater environmental management and contamination control. Although the Guangdong-Hong Kong-Macao Greater Bay Area (GHM Greater Bay Area) has faced significant groundwater contamination since 2020, there's been no investigation into its vulnerability zonation. In this paper, groundwater in a typical area of south China was taken as the research object. We analyzed groundwater contamination risk by considering both the groundwater vulnerability and the load from contamination sources. Using the analytic hierarchy process (AHP) method, we superposed the groundwater risk, function value and contamination status, and realized the quantification and visualization of groundwater contamination prevention regionalization. Based on the DRASTIC model, the zones of low, moderate, high, and very high vulnerability are respectively 14.2 %, 24.28 %, 37.67 %, and 20.45 % of the study area. Results show that the groundwater vulnerability grade in the area is III-IV, which means it is easy to be polluted. The functional value of groundwater in the south-central part of the region is relatively high. Most of the areas with high prevention and control levels are located in plain areas and the Piedmont plain area with an area of 460 km2. The secondary control levels (key protection area) are mainly located in the middle, southwest, and northeast of the plain, with an area of 6944 square kilometers. Consequently, the ideas and contamination prevention zone maps might provide a scientific foundation for long-term planning and management and groundwater conservation in the Guangdong-Hong Kong-Macao Greater Bay Area and peripheral zones. [ABSTRACT FROM AUTHOR]

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

• A big data computational text analysis based on a corpus of 2.4 million words. • Comparison of major themes on air pollution in stakeholder discourse in Hong Kong. • Three stakeholder groups are studied; all focus on emissions and pollution control. • Public health is a greater concern in MEDIA compared with other groups. • More personalized health information to be shared with the vulnerable groups. Stakeholder engagement is critical to the successful formulation and implementation of environmental policies. Text analysis can serve as an important means to decipher stakeholder (dis)agreements. Traditionally, researchers analyze texts using qualitative text analysis. Relying only on qualitative text analysis can no longer be sufficient to handle very large amounts of textual data. Now computational methods can be applied to help extract opinions in electronic texts. Our paper adopts a big data computational text analysis approach (keyword analysis, keyword co-occurrence, thematic analysis), based on a corpus of 2.4 million words, to compare concerns towards air pollution among three stakeholder groups (i.e. the government (GOV), the environmental groups (NGO) and the news media (MEDIA)) in Hong Kong, between 2002 and 2012, a period when air pollution was subject to rigorous policy debates and discussions. Our analysis shows the somewhat different concerns of the stakeholders. The stakeholders focus heavily on emissions and end-of-pipe pollution control. Though the advocation of sustainability since 1990s, the government-led command-and-control approach still dictates the discourse. Sustainability is featured more intensively by the Hong Kong Special Administrative Region (HKSAR) Government. Transboundary pollution (e.g. from Guangdong, China) is not a major concern for all stakeholder groups. Public health is a greater concern in MEDIA, as compared to the other two stakeholder groups. Future air pollution policy-making may direct more of its attention to the pressing concerns over the negative impacts of air pollution on health and its associated costs, with health experts getting more closely involved in the regulatory decision-makings. More information should be given to vulnerable groups, such as young children or workers in polluted environments. To better relate differential health risks of pollution in everyday life, both local and international governments should consider developing more personalized air pollution monitoring and health management systems for their citizens in future. [ABSTRACT FROM AUTHOR]

This paper studies the structure and dynamics of urban agglomeration between 1992 and 2018 in one of most developed regions in China – the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) – based on the harmonized night-time light (NTL) data from the Defense Meteorological Satellite Program (DMSP) and Visible Infrared Imaging Radiometer Suite (VIIRS) imagery. We adopted Zipf's law as the rule to control the spatial clustering of adjacent lit pixels. The clustered pixels as patches are concentration of human activities and can then be used for regional urbanization analysis. Unlike conventional spatial units that are rarely changed, such as administrative boundaries, these patches change subtly each year and, more importantly, can help us to examine precisely the urbanization pattern in both development mode and intensity. We investigated the urban growth pattern during the 27-year timespan and conducted the analysis at both region and city levels. Interestingly, the results suggest that Zipf's law of derived patch sizes can hold nearly every year, showcasing the consistent spatial coherency of the urban agglomeration process in the entire region. The correlation between urbanization metrics for each city at three stages (1992–2000, 2000–2010, and 2010–2018) can further lead to deep insights towards the synergetic course of the coordinated and multi-center development. [Display omitted] • Identify the urbanized area using spatial clustering of time-series NTL data guided by Zipf's law related statistics. • Explore the urban expansion dynamics by conducting a correlation analysis between development mode and intensity. • Confirm the integrated, connected, and polycentric urbanization development process evidenced by the findings. [ABSTRACT FROM AUTHOR]

• We compared the structural characteristics of 18 urban agglomerations in China. • Our framework contained analysis of 3 different scales based on 4 elements' flows. • Guangdong-Hong Kong-Macao urban Agglomeration had the greatest average flow (5.15). • Shandong Peninsula Urban Agglomeration had the best performance in overall network. • Cities with high centrality were in the bidirectional or main spillover subgroups. Flows of different elements among cities can affect urban organizational structures, leading to specific links between and roles for cities within urban agglomerations. Previous studies have mainly focused on flows produced by specific elements in a single urban agglomeration, and they cannot reveal differences in organizational structures affected by multiple elements among different urban agglomerations. Therefore we selected 18 typical urban agglomerations in China and explored their structural characteristics under comprehensive effects of four elements: economy, resources, population and technology, with gravity model and social network analysis. Guangdong-Hong Kong-Macao Urban Agglomeration had a maximum flow intensity of 5.15, this concentration range was the largest from 0.65 to 3.75, indicating that more elements flowed internally. Shandong Peninsula Urban Agglomeration had the largest network density at 0.412, the lowest efficiency at 0.567, and the lowest hierarchy at 0.000, showing that intercity relationships within SP were the tightest among the18 urban agglomerations. Geographical proximity and topological structure of subgroups proved that connections among subgroups were not complex, and cities of different provinces lacked close interactions. Furthermore, most of the key cities with high centrality indexes were municipalities directly under the Central Government or provincial capitals; these cities played important roles in networks and were distributed into "main spillover" and "bidirectional spillover" subgroups. This paper provides a unified analytical framework aimed at urban agglomerations that accounts for flows of multiple types of elements and explores urban organizational structures, and our results could provide scientific guidance for promoting the coordinated and sustainable development of urban agglomerations. [ABSTRACT FROM AUTHOR]

Previous studies on land use have largely focused on characteristics of quota allocation and spatial distribution based on time series analysis. However, indwelling patterns, combined space–time characteristics and terrain gradient effects are often hidden from the regional territorial spatial planning process. By using spatial econometric techniques, including hot spot analysis, landscape theory, a space–time cube model and a terrain–niche index, this paper aimed to assist regional planning by revealing these hidden characteristics in Guangdong Province, China. The results were as follows: urban construction land had formed an agglomerated region at the center of the study area, surrounded by many smaller satellite cities, which resembled a mainland–island metapopulation pattern. Three hot spot types—oscillating (32.45 % of the region), sporadic (1.85 %) and persistent (6.83 %)—formed the main space–time pattern throughout the study period. The main patterns included persistent hot spots in the Pearl River Delta, approximating a strip pattern of sporadic and oscillating hot spots from the east to west, with persistent cold spots in the north. Dry land cropping showed an increase in area at terrain levels 3–6 while in other terrains the area of dry land cropping decreased over time. These findings indicate that more attention needs to be paid to maintaining or adjusting the shape and equilibrium between the mainland and the island cities in the future. Steeper terrain is normally considered for cropland when conflicts exist for land use, which might decrease cropland quality to some extent. Hence, current territorial and spatial planning should focus on changing spatial disequilibrium and the reduction in cropland quality, which might result from the land policy of "superior occupation and inferior compensation", to slow regional differences and to achieve sustainable development. • We synthesized case study evidence for land use change in Guangdong Province–Hong Kong–Macao region, China. • Urban construction land have formed an agglomerated region surrounded by many smaller satellite cities in the cases studied. • The landscape resembles a continent-island metapopulation pattern. • Terrain shapes landscape distribution and change of land use to a lesser extent. • There exist higher heterogeneous space patterns of land use change throughout the region. • Hot spot clusters, consisted of oscillating, sporadic and persistent, were the main spatiotemporal patterns during the past 40-years. [ABSTRACT FROM AUTHOR]

• An assessment of conservation priorities for KBAs in highly urbanized regions was conducted. • Ecosystem conditions remain stable in most of KBAs over the past two decades. • Ecosystem conditions showed spatially significant negative correlations with anthropogenic threats. • Shenzhen Wutongshan is the highest priority KBA that needs to strengthen ecosystem conservation. The rapid and intense development in highly urbanized regions presents huge challenges to the conservation of biodiversity and ecosystem services. Progress on incorporating ecosystem conditions and anthropogenic threats into conservation assessments for key biodiversity areas (KBAs) in highly urbanized regions is still insufficient. To address this, this paper conducted an assessment of conservation priorities for key biodiversity areas in highly urbanized regions by integrating anthropogenic threats with ecosystem conditions. Taking 8 KBAs in the Guangdong - Hong Kong - Macao Greater Bay Area of China (GBA) as an example, this study found that the ecosystem condition of most of KBAs remains stable from 2000 to 2020. We found that the ecosystem conditions in most KBAs have not been negatively affected by anthropogenic threats. It is worth noting that Shenzhen Wutongshan (SZW) is the only KBA that faces a significant increase in anthropogenic threats with a significant decline in ecosystem condition during the past two decades. Overall, SZW is the highest priority KBA that needs to reduce the negative effects of anthropogenic threats and strengthen ecosystem conservation in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • Patch complexity and urban compactness indexes were developed to assess urban form. • The impact of urban form on PM 2.5 was explored in GBA by spatial panel models. • The complexity of urban patches had a negative effect on PM 2.5 concentrations. • The impact of urban compactness on PM 2.5 concentrations was positive. • A more complex and less compact urban form was adoptable in terms of reducing PM 2.5. Given the serious threat of PM 2.5 pollution to the environment and public health in China, reducing PM 2.5 concentrations through urban planning practices has become a common interest of urban planners and policymakers. In this regard, identifying the relationship between urban form and PM 2.5 concentrations has been a matter of much concern. This paper seeks to investigate how urban form influences PM 2.5 concentrations by taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study. First, the urban form was assessed by two indicators, i.e., the patch complexity index (PCI) and urban compactness index (UCI), which were developed based on multiple landscape metrics and the principal component analysis. Then, the relationship between PM 2.5 concentrations and the two urban form indicators was revealed by spatial panel models. Our results mainly showed that PCI and UCI were negatively and positively associated with PM 2.5 concentrations, respectively, indicating that less compact urban forms with high patch complexity had advantages in reducing the PM 2.5 concentrations. According to these empirical results, the mixed-use urban development with high green coverage, which is conducive to constructing a more complex and less compact urban form, would be adoptable in terms of mitigating PM 2.5 concentrations in the GBA urban agglomeration. [ABSTRACT FROM AUTHOR]

• ERA5 describes moderate-intensity rainfall, but fails for hourly/daily precipitation. • ERA5-HRES outperforms ERA5-Land in detecting rainfall magnitude and rainfall events. • ERA5 performs best in coastal cities and mountainous vegetation areas during the wet and dry season, respectively. • ERA5 is insufficient in reproducing precipitation in areas with high urbanization level. Precipitation is an important component of the global water cycle. A comprehensive understanding of precipitation characteristics, especially that in urban areas, is essential for practical applications in hydrology. ERA5, a state-of-the-art reanalysis product with wide temporal coverage as well as fine spatial and temporal resolution, has greater potential to reproduce precipitation than many other products. However, how ERA5 precipitation performs has not been well investigated in urban areas. Therefore, we evaluate and compare the ability of two ERA5 products, ERA5-Land and ERA5-HRES, in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) using observations from over 3000 rain gauges in a high-density network during 2018. The results show that ERA5 products generally characterize moderate-intensity rain. Due to the different causes of seasonal precipitation as well as the combined influence of coastal effects and topography, the best performance of ERA5 products is found in the southern coastal plains during the wet season and in the northern mountainous vegetation areas during the dry season. Meanwhile, it is challenging for ERA5 products to model precipitation in areas with higher urbanization levels. We also find that ERA5-Land data with finer spatial resolution fails to deliver any preferable results than ERA5-HRES. ERA5 products needs further improvement in the GBA for providing accurate precipitation patterns. This paper gives a detailed insight into the performance of ERA5 products, which offers a valuable reference for its probable applicability in the coastal urban areas. [ABSTRACT FROM AUTHOR]

With continuous growth of economy and population in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), pressure of resources and environment is increasing. Therefore, sustainable green development of the GBA has attracted more and more attention from society. What is relationship among economy, resource and environment in the GBA? How to balance and analyze relationship between Green Economy and carrying capacity of resource and environment in the GBA? It is an important scientific question facing sustainable development of the GBA. This paper constructs a comprehensive ECC index system for economy - resources – environment with data from statistics yearbooks, calculates weights of indicators by entropy weight method and Ecological Carrying Capacity by TOPSIS model later using C++ programming language. It also carries out exponential smoothing for ECC prediction by SPSS software and coupling coordination of economy - resources - environment system in this area. The results show that the comprehensive ECC of the GBA has an upward trend from 2000 to 2017. In the next five years, Comprehensive Ecological Carrying Capacity of GBA will continue to increase linearly. In the process of GE development in the GBA, the environmental carrying capacity has steadily increased. There is a negative correlation between resource carrying capacity and GE but a positive correlation between environmental carrying capacity and GE. The coordination of economy - resource - environment system in the GBA has been continuously strengthened, and development of economy is advancing towards direction of high resource carrying capacity and high environmental carrying capacity. From perspective of comprehensive ecological carrying capacity to explore the world's two kinds of different political and economic system under comparative analysis of the urban Green Economy development. We found that the Macao and nine cities of the GBA are basically stable but Hong Kong is experiencing tortuous growth with dramatic changes. This research would provide theoretical reference for subsequent development direction of GBA and other bay areas. The future research can carry out deep simulation on the economy - resource - environment dynamics system model and formulate specific development plans. Government departments concerned with development of China's GBA should be committed to reducing pressure on resources, developing new energy and clean energy, while continuing to maintain even increase investment in environmental protection • An Eco-Carrying Capacity evaluation index system of the GBA was constructed to economy-resources-environment. • The comprehensive Eco-Carrying Capacity of the GBA were analyzed. • Coupling analysis of green economy and carrying capacity of resource and environment in the GBA was explored. • Provide comparative analysis under two different political and economic systems of the urban green economic development. [ABSTRACT FROM AUTHOR]

Noncooperative policies for transboundary pollution abatement are inefficient and ineffective, but cooperative policies for pollution abatement are seldom successful in regions that have different development goals and conflicting interests. In this paper, by extracting the key components that lead to the success of pollution reduction policies between Hong Kong (HK) and Guangdong, we aim to construct a general framework for cooperative environmental management. The incentive for and the dynamic trajectory, core measures, and outcomes of cooperative pollution abatement policies to address transboundary air pollution were studied using incrementalism analysis. The context that drives the abnormal increment of cooperative policies between HK and Guangdong was analyzed to determine the factors that affect the full cooperation process. The political union between HK and China is the main driving force for fostering cooperative policies in these two regions that have highly asymmetric economic development levels and pollution emission intensities. The factors for successfully designing cooperative pollution reduction policies are revealed from trust building, political support, efficient governance, precise policies, a rational cost-sharing mechanism, and detailed management and implementation plans. Innovative multi-level and cross-department governance, and an unequal but rational cost-sharing scheme sustain long-term cooperation. A general framework is derived from these empirical key components and constructed as a systematic approach to provide a guide for designing cooperation in transboundary pollution reduction for the sustainable management of cross-border natural resources in different regions with conflicts of interest. • An empirical framework of cooperative air pollution abatement model is constructed. • Factors contributing to foster cooperative polices is analyzed via incrementalism model. • Political support produces adequate institutional arrangements and precise policies. • A matching cost-sharing mechanism can catalyze and stabilize the cooperation model. • Multi-level and cross-department policies sustain long-term cooperation. [ABSTRACT FROM AUTHOR]

• Carbon emissions of Guangdong cities were estimated. • The new-type urbanization levels were calculated by Principal Component Analysis. • Spatial Lag Model (SLM) and Spatial Error Model (SEM) were employed. • There are spatial clusters of carbon emissions in the study area. • The new-type urbanization has negative impact on carbon emission growth. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has an important strategic position in the overall development of China. Low-carbon development and the new-type urbanization are significant parts of the world-class greater bay blueprint. However, there is still insufficient literature about the carbon emission estimation and spatial analysis of the region. Based on the latest city-level data, this paper not only estimated the carbon emission and the new-type urbanization level of Guangdong cities but also applied spatial analysis of their carbon emissions, carbon emission per capita, and carbon intensity. It also used spatial data in the STIRPAT model to investigate the relationship between carbon emission and population, affluence, and the new-type urbanization. The results show that in 2017 Guangdong province emitted 603.92 million tonnes of CO 2. Of all the cities Guangzhou emerges as the biggest emitter, followed by Shaoguan and Zhanjiang which are industrial cities. There are spatial clustering effects among these cities and the GBA cities are the low carbon intensity clusters. The new-type urbanization level (NUL) has negative impact on carbon emission and the GBA cities have higher NUL than the others. Targeted policy implications are proposed based on the findings of the study. [ABSTRACT FROM AUTHOR]

The recent intensification of extreme rainfall events has the potential to aggravate the frequency and intensity of floods in urban areas and signals the urgent need for accurate and high spatiotemporal resolution precipitation data for flood monitoring and warning to alleviate the associated damages. In this context, this paper aims to statistically assess the latest Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) multisatellite constellation and radar quantitative precipitation estimation (QPE) products against dense rain gauge network observations under multiple temporal scales (hourly and 3-hourly) and three spatial scales (grid cumulative, regional, and grid) over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. The results indicate that (1) at the grid cumulative scale, QPE significantly outperforms IMERG products. The correlation coefficients of QPE (0.83 ≤ CORR ≤ 0.85) are much higher than those of IMERG products (0.35 ≤ CORR ≤ 0.56), the estimation of QPE is generally significantly underestimated (−0.23 ≤ BIAS ≤ -0.16), and the BIAS of IMERG products is larger than that of QPE (−0.24 ≤ BIAS ≤ 0.23). (2) At the regional scale, the accuracy of IMERG products has been significantly improved, with relatively high correlation coefficients (CORR≥0.8) and decreased root mean squared error (RMSE) values (1.18 mm ≤ RMSE ≤ 0.22 mm), and Taylor diagrams visually show that QPE is closer to the gauge observations than are IMERG products. (3) The evaluation results at the grid scale show that both IMERG products and QPE can accurately reflect the spatial distribution of precipitation. Among these results, the spatial distribution of QPE is the most consistent with the actual rainfall, although an obvious underestimation of rainfall occurs in areas with strong rainfall. (4) In terms of detection indicators, the three IMERG products are superior to QPE at capturing rainfall events and have more advantages over QPE in the estimation of instantaneous precipitation, especially for light rain events. However, QPE has better detection effects for rainfall events under rainstorm and heavy rainstorm events, indicating the hydrologic utility of this product. Among the three IMERG products, the IMERG Early Run (ER) product has the advantages of a short lag time and high accuracy, and it has the potential to be applied in flood forecasting. Future studies should improve IMERG algorithms and promote the application of QPE in urban rainstorm and flood research. • The quality of the IMERG products and radar quantitative precipitation estimation (QPE) is compared over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. • The dense rain gauge network observations are used for evaluation in the GBA. • The evaluation of multisource precipitation products under different temporal and spatial scales has different results and effects. [ABSTRACT FROM AUTHOR]