| 刊名 | Journal of Landscape Research |
| 作者 | XIA Yuan1, WANG Bin2, 3 |
| 作者单位 | 1. Guangzhou Urban Planning and Design Co., Ltd., Guangzhou, Guangdong 510060, China; 2. Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou, Guangdong 510060, China; 3. Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou, Guangdong 510060, China |
| DOI | 10.16785/j.issn 1943-989x.2024.4.011 |
| 年份 | 2024 |
| 刊期 | 4 |
| 页码 | 47-50 |
| 关键词 | Baidu migration data, Social network analysis, Urban agglomeration network structure, Greater Bay Area urban agglomeration |
| 摘要 |
The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure of urban agglomeration in the Greater Bay Area through the use of social network analysis method. This is the inaugural application of big data based on location services in the study of urban agglomeration network structure, which represents a novel research perspective on this topic. The study reveals that the density of network linkages in the Greater Bay Area urban agglomeration has reached 100%, indicating a mature network-like spatial structure. This structure has given rise to three distinct communities: Shenzhen-Dongguan-Huizhou, Guangzhou-Foshan-Zhaoqing, and Zhuhai-Zhongshan- Jiangmen. Additionally, cities within the Greater Bay Area urban agglomeration play different roles, suggesting that varying development strategies may be necessary to achieve staggered development. The study demonstrates that large datasets represented by LBS can offer novel insights and methodologies for the examination of urban agglomeration network structures, contingent on the appropriate mining and processing of the data. |
