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Megaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context. [ABSTRACT FROM AUTHOR]

China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China's hotspot regions, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to 2017 were used to derive forest, and landscape metrics and geographic information system (GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in 1987–2017; meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60% (1034.42 km2) was converted to urban land; 2) the percentages of forest loss to urban land in Dongguan (19.14%), Guangzhou (18.35%) and Shenzhen (15.81%) were higher than those in other cities; 3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from 2007 to 2017); 4) the landscape responses to forest changes varied with the scale; and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong. Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation. [ABSTRACT FROM AUTHOR]

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the largest bay areas in the world. However, the spatiotemporal characteristics and driving mechanisms of urban expansions in this region are poorly understood. Here we used the annual remote sensing images, Geographic Information System (GIS) techniques, and geographical detector method to characterize the spatiotemporal patterns of urban expansion in the GBA and investigate their driving factors during 1986–2017 on regional and city scales. The results showed that: the GBA experienced an unprecedented urban expansion over the past 32 years. The total urban area expanded from 652.74 km2 to 8137.09 km2 from 1986 to 2017 (approximately 13 times). The annual growth rate during 1986–2017 was 8.20% and the annual growth rate from 1986 to 1990 was the highest (16.89%). Guangzhou, Foshan, Dongguan, and Shenzhen experienced the highest urban expansion rate, with the annual increase of urban areas in 51.51, 45.54, 36.76, and 23.26 km2 y−1, respectively, during 1986–2017. Gross Domestic Product (GDP), income, road length, and population were the most important driving factors of the urban expansions in the GBA. We also found the driving factors of the urban expansions varied with spatial and temporal scales, suggesting the general understanding from the regional level may not reveal detailed urban dynamics. Detailed urban management and planning policies should be made considering the spatial and internal heterogeneity. These findings can enhance the comprehensive understanding of this bay area and help policymakers to promote sustainable development in the future. [ABSTRACT FROM AUTHOR]

• The proposed comprehensive ecological evaluation index (CEEI) is an effective method in revealing ecological quality. • Urbanization process and policy variation play dominant roles in ecological quality evolution. • Poor and fair ecological quality areas shift from suburbs to urban areas gradually. • Both positive and negative signals for ecological conservation were found in the GBA. As one of the major bay areas in the world, the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) has been experiencing a remarkable urbanization process, and its ecological quality also has been suffering from intense human activities and urbanization inevitably. This study aimed to reveal the spatiotemporal characteristics of ecological quality evolution under the pressure of urbanization in the GBA from 1987 to 2017. A comprehensive ecological evaluation index (CEEI) was proposed to describe the spatiotemporal characteristics change of ecological quality by integrating the remote sensing-based parameters of vegetative cover (VC), vegetative health index (VHI), normalized differential build-up and bare soil index (NDBSI), land surface moisture (LSM) and land surface temperature (LST). The results revealed that: (1) the evolution of ecological quality showed a trend of first improvement then degradation from 1987 to 2017 and the regions with poor and fair ecological quality gradually shifted from suburbs to urban areas; (2) the ecological quality was not optimistic in 1987, with the areas with poor and fair ecological quality reaching 3.45% and 30.36% of total area, respectively; (3) the ecological quality greatly improved in 1997 and 2007, and the areas with poor ecological quality only accounted for 0.41% and 0.70% of total area, respectively; and (4) the ecological quality degraded again in 2017, and the degraded area reached 52% and the areas with poor and fair ecological quality reached 4.3% and 17.35%, respectively. The changes of ecological quality were mainly driven by urbanization process and policy variation, and these results may provide helpful information for the ecological conservation and sustainable development of GBA. [ABSTRACT FROM AUTHOR]