scholarly journals Evolution of Spatial Pattern and Influencing Factors of Population in Guangdong-Hong Kong-Macao Greater Bay Area

2020 ◽  
Vol 08 (04) ◽  
pp. 33-46
Author(s):  
Hegang Yao
Keyword(s):  
Hong Kong ◽  
Spatial Pattern ◽  
Influencing Factors ◽  
Bay Area

scholarly journals Spatial Pattern Analysis of the Ecosystem Services in the Guangdong-Hong Kong-Macao Greater Bay Area Using Sentinel-1 and Sentinel-2 Imagery Based on Deep Learning Method

2021 ◽  
Vol 13 (13) ◽  
pp. 7044
Author(s):  
Dawei Wen ◽  
Song Ma ◽  
Anlu Zhang ◽  
Xinli Ke
Keyword(s):  
Hong Kong ◽  
Deep Learning ◽  
Ecosystem Services ◽  
Land Cover ◽  
Spatial Pattern ◽  
Sustainable Urban Development ◽  
Spatial Pattern Analysis ◽  
Bay Area ◽  
Urban Rural ◽  
Sentinel 2

Assessment of ecosystem services supply, demand, and budgets can help to achieve sustainable urban development. The Guangdong-Hong Kong-Macao Greater Bay Area, as one of the most developed megacities in China, sets up a goal of high-quality development while fostering ecosystem services. Therefore, assessing the ecosystem services in this study area is very important to guide further development. However, the spatial pattern of ecosystem services, especially at local scales, is not well understood. Using the available 2017 land cover product, Sentinel-1 SAR and Sentinel-2 optical images, a deep learning land cover mapping framework integrating deep change vector analysis and the ResUnet model was proposed. Based on the produced 10 m land cover map for the year 2020, recent spatial patterns of the ecosystem services at different scales (i.e., the GBA, 11 cities, urban–rural gradient, and pixel) were analyzed. The results showed that: (1) Forest was the primary land cover in Guangzhou, Huizhou, Shenzhen, Zhuhai, Jiangmen, Zhaoqing, and Hong Kong, and an impervious surface was the main land cover in the other four cities. (2) Although ecosystem services in the GBA were sufficient to meet their demand, there was undersupply for all the three general services in Macao and for the provision services in Zhongshan, Dongguan, Shenzhen, and Foshan. (3) Along the urban–rural gradient in the GBA, supply and demand capacity showed an increasing and decreasing trend, respectively. As for the city-level analysis, Huizhou and Zhuhai showed a fluctuation pattern while Jiangmen, Zhaoqing, and Hong Kong presented a decreasing pattern along the gradient. (4) Inclusion of neighborhood landscape led to increased demand scores in a small proportion of impervious areas and oversupply for a very large percent of bare land.

scholarly journals Study on the Spatial Pattern of Innovation Output and Influencing Factors in Guangdong-Hong Kong-Macao Greater Bay Area

2019 ◽  
Author(s):  
Dongliang Yang ◽  
Chunfeng Li
Keyword(s):  
Hong Kong ◽  
Spatial Pattern ◽  
Industrial Structure ◽  
Study Region ◽  
Bay Area ◽  
Innovation Activities ◽  
Level Of Economic Development ◽  
Innovation Output ◽  
Countermeasures And Suggestions ◽  
The Impact

The advantageous location, port clusters, strong economic strength, developed financial system, rational and orderly urban division of labor and modern industrial system of Guangdong-Hong Kong-Macao greater bay area provide sustainable driving force for innovation activities in this region. This paper selected the Gini-coefficient, first degree index and concentration index to measure the spatial pattern characteristics of innovation output in Guangdong-Hong Kong-Macao greater bay area. The results show that the innovation output presented a spatial pattern of center-periphery in the study region with Shenzhen and Guangzhou as the dual centers and engines of innovation and Dongguan and Foshan as the main innovative areas. Further empirical analysis of the impact of various factors on innovation output in the study region found that R&D expenditure, the number of R&D personnel, the level of economic development and industrial structure all have significant promoting effects on innovation output. Accordingly, this paper put forward countermeasures and suggestions to promote the innovative development of Guangdong-Hong Kong-Macao greater bay area and build a world-class scientific and technological innovation bay area.

Dataset of Housing Rents and their Influencing Factors in the Guangdong-Hong Kong-Macao Greater Bay Area (2019)

GCdataPR ◽  
2021 ◽  
Author(s):  
Yang* WANG ◽  
Yang* WANG ◽  
Kangmin WU ◽  
Kangmin WU ◽  
Hongou ZHANG ◽  
...  
Keyword(s):  
Hong Kong ◽  
Influencing Factors ◽  
Bay Area

scholarly journals Patterns of the Network of Cross-Border University Research Collaboration in the Guangdong-Hong Kong-Macau Greater Bay Area

2020 ◽  
Vol 12 (17) ◽  
pp. 6846
Author(s):  
Jinyuan Ma ◽  
Fan Jiang ◽  
Liujian Gu ◽  
Xiang Zheng ◽  
Xiao Lin ◽  
...  
Keyword(s):  
Social Sciences ◽  
Hong Kong ◽  
Research Collaboration ◽  
Citation Impact ◽  
High Quality ◽  
High Quality Research ◽  
Cross Border ◽  
Bay Area ◽  
Research Areas ◽  
Industrial Distribution

This study analyzes the patterns of university co-authorship networks in the Guangdong-Hong Kong-Macau Greater Bay Area. It also examines the quality and subject distribution of co-authored articles within these networks. Social network analysis is used to outline the structure and evolution of the networks that have produced co-authored articles at universities in the Greater Bay Area from 2014 to 2018, at both regional and institutional levels. Field-weighted citation impact (FWCI) is used to analyze the quality and citation impact of co-authored articles in different subject fields. The findings of the study reveal that university co-authorship networks in the Greater Bay Area are still dispersed, and their disciplinary development is unbalanced. The study also finds that, while the research areas covered by high-quality co-authored articles fit the strategic needs of technological innovation and industrial distribution in the Greater Bay Area, high-quality research collaboration in the humanities and social sciences is insufficient.

scholarly journals Dynamic Changes of Local Climate Zones in the Guangdong–Hong Kong–Macao Greater Bay Area and Their Spatio-Temporal Impacts on the Surface Urban Heat Island Effect between 2005 and 2015

2021 ◽  
Vol 13 (11) ◽  
pp. 6374
Author(s):  
Yang Lu ◽  
Jiansi Yang ◽  
Song Ma
Keyword(s):  
Hong Kong ◽  
Land Surface ◽  
Morphological Changes ◽  
Mapping Method ◽  
Heat Radiation ◽  
Climate Zones ◽  
Local Climate ◽  
Bay Area ◽  
Local Climate Zones ◽  
Urban Heat

Local climate zones (LCZs) emphasize the influence of representative geometric properties and surface cover characteristics on the local climate. In this paper, we propose a multi-temporal LCZ mapping method, which was used to obtain LCZ maps for 2005 and 2015 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), and we analyze the effects of LCZ changes in the GBA on land surface temperature (LST) changes. The results reveal that: (1) The accuracy of the LCZ mapping of the GBA for 2005 and 2015 is 85.03% and 85.28%, respectively. (2) The built type category showing the largest increase in area from 2005 to 2015 is LCZ8 (large low-rise), with a 1.01% increase. The changes of the LCZs also vary among the cities due to the different factors, such as the economic development level and local policies. (3) The area showing a warming trend is larger than the area showing a cooling trend in all the cities in the GBA study area. The main reasons for the warming are the increase of built types, the enhancement of human activities, and the heat radiation from surrounding high-temperature areas. (4) The spatial morphology changes of the built type categories are positively correlated with the LST changes, and the morphological changes of the LCZ4 (open high-rise) and LCZ5 (open midrise) built types exert the most significant influence. These findings will provide important insights for urban heat mitigation via rational landscape design in urban planning management.

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