1
|
Wang Z, Xia N, Zhao X, Gao X, Zhuang S, Li M. Evaluating Urban Vitality of Street Blocks Based on Multi-Source Geographic Big Data: A Case Study of Shenzhen. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3821. [PMID: 36900828 PMCID: PMC10001719 DOI: 10.3390/ijerph20053821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 02/15/2023] [Accepted: 02/19/2023] [Indexed: 06/18/2023]
Abstract
Urban vitality is the comprehensive form of regional development quality, sustainability, and attractiveness. Urban vitality of various regions within the cities has difference, and the quantitative evaluation of urban vitality within the cities can help guide to future city constructions. Evaluation of urban vitality needs the combination of multi-source data. Existing studies have developed index method and estimation models mainly based on geographic big data to evaluate urban vitality. This study aims to combine remote sensing data with geographic big data to evaluate urban vitality of Shenzhen at street block scale and build the estimation model by random forest method. Indexes and random forest model were built, and some further analyses were conducted. The results were: (1) urban vitality in Shenzhen was high in the coastal areas, business areas, and new towns; (2) compared to indexes, the estimation model had advantages of more accurate results, combination of various data, and the ability to analyze feature contributions; and (3) taxi trajectory, nighttime light, and housing rental data had the strongest influence on urban vitality.
Collapse
Affiliation(s)
- Ziyu Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
| | - Nan Xia
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
- Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210023, China
| | - Xin Zhao
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
| | - Xing Gao
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
| | - Sudan Zhuang
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
| | - Manchun Li
- Jiangsu Provincial Key Laboratory of Geographic Information Technology, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
- Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210023, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University, Nanjing 210023, China
| |
Collapse
|
2
|
Liu Z, Wang F, Dang A. Creating Engines of Prosperity: Spatiotemporal Patterns and Factors Driving Urban Vitality in 36 Key Chinese Cities. BIG DATA 2022; 10:528-546. [PMID: 35446684 DOI: 10.1089/big.2021.0410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Under the requirements of new urbanization in China, the improvement of urban spatial vitality has become a key aspect of the territory development plan. Based on the theory of urban vitality by Jacobs, this study analyzed the spatiotemporal characteristics of mobility, diversity, and regularity from urban vitality in 36 key Chinese cities from 1990 to 2015; the urban vitality was evaluated by considering the society, economy, environment, culture, and cyberspace and by exploring its driving factors. The results suggest that vitality was higher in the southern/eastern coastal cities than in the northern/western inland ones. Cities with the highest vitality levels (top 10) were mostly located in the Pearl and Yangtze River deltas, the Beijing-Tianjin region, and the middle reaches of the Yangtze River. Shenzhen demonstrated the highest vitality in the stage of extremely high coordination. Most of the cities with a middle level of vitality were located in northern China, while cities with poor vitality were small-scale cities with underdeveloped economies in the west and provincial capitals in northeastern China with a shrinking population. Areas with high-density facilities, high-accessibility transportation, multiple functional land use, and a high standard of living always have high vitality. The point of interest density had a significant positive effect on daytime vitality in regions with moderate and high vitality, but varying effects on nighttime vitality; it had a higher influence on nighttime vitality than on daytime vitality in areas of extremely high vitality. The study also provides corresponding measures for infrastructure, which could be invested in and constructed at different urban development stages to promote vitality. This could provide guidance for creating a booming space and revitalize and increase urban vitality, and could help reasonably regulate and control urban population and land use.
Collapse
Affiliation(s)
- Zhao Liu
- NSFC-DFG Sino-German Cooperation Group on Urbanization and Locality (UAL), Peking University, Beijing, China
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Fang Wang
- NSFC-DFG Sino-German Cooperation Group on Urbanization and Locality (UAL), Peking University, Beijing, China
- College of Architecture and Landscape Architecture, Peking University, Beijing, China
| | - Anrong Dang
- School of Architecture, Tsinghua University, Beijing, China
| |
Collapse
|
3
|
Gupta V, Singh VK, Ghose U, Mukhija P. A quantitative and text-based characterization of big data research. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-179016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Vedika Gupta
- Department of Computer Science and Engineering, National Institute of Technology Delhi, Delhi, India
| | - Vivek Kumar Singh
- Department of Computer Science, Banaras Hindu University, Varanasi, India
| | - Udayan Ghose
- University School of Information and Communication Technology, Guru Gobind Singh Indraprastha University, Dwarka, Delhi, India
| | - Pankaj Mukhija
- Department of Electrical and Electronics Engineering, National Institute of Technology Delhi, Delhi, India
| |
Collapse
|
4
|
Correction to: Big Data 2016;4:60-66. BIG DATA 2016; 4:136. [PMID: 27441718 PMCID: PMC4985029 DOI: 10.1089/big.2015.0043.correx] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
|