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
|
Dong L, Zhang L. Spatial Coupling Coordination Evaluation of Mixed Land Use and Urban Vitality in Major Cities in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15586. [PMID: 36497660 PMCID: PMC9736544 DOI: 10.3390/ijerph192315586] [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: 10/25/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
Based on the data from 35 major cities in China in 2020, this paper applies the Simpson's diversity index, the entropy value method, and the coupling coordination degree model to comprehensively measure the coupling coordination level of mixed land use and urban vitality in major cities in China and further analyze their spatial distribution characteristics. In addition, this paper analyzes the factors affecting the spatial variation of the coupling coordination level with the help of the geographic probe model. The study finds that: (1) The overall level of coupling coordination between mixed land use and urban vitality is high in 35 major cities in China. There is no disorder between mixed land use and urban vitality. (2) In terms of the spatial distribution of the coupling coordination between mixed land use and urban vitality in 35 cities in China, five cities, namely Beijing, Shenzhen, Shanghai, Guangzhou, and Chengdu, have the highest level of coupling coordination between mixed land use and urban vitality, reaching "good coordination" with a discrete spatial distribution. Central cities such as Hangzhou and Nanjing have the second highest level of coupling coordination and are at the "intermediate coordinate" with a "strip-like distribution" in space. Twenty cities in the north and south have the lowest coupling coordination levels and are in the "primary coordination." Among these twenty cities, seven cities in the south have a higher level of coupling coordination than thirteen cities in the north, with a spatial distribution of a "C" shape. The northern cities have the lowest level of coupling coordination, with a "W"-shaped distribution in space. (3) Population size plays an essential role in guiding the level of coupling coordination between mixed land use and urban vitality in major cities in China, followed by government regulation and economic level. At the same time, transportation conditions and industrial structure have the weakest influence on the level of coupling coordination between mixed land use and urban vitality in major cities in China.
Collapse
|
3
|
Understanding the Driving Factors for Urban Human Settlement Vitality at Street Level: A Case Study of Dalian, China. LAND 2022. [DOI: 10.3390/land11050646] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Vitality can effectively test the quality of regional space, put forward the concept of urban human settlement vitality, and explore the development status of urban human settlement vitality space, which is of great significance in promoting the high-quality development of urban human settlements. By constructing an evaluation index system of urban human settlement vitality and comprehensively using projection pursuit models, spatial correlation analysis, and spatial measurement models, the spatial pattern and influencing factors of the vitality of urban human settlements in the four districts of Dalian were studied. The results are as follows: (1) The spatial differentiation characteristics of the vitality of urban human settlements in Dalian are remarkable. Overall, it gradually decreased from the city center to the administrative boundary. (2) The spatial dependence of the vitality of urban human settlements among regions is relatively strong, with a more obvious “Matthew effect”. Among them, urban human settlement vitality hot spots were mainly distributed in the southeast of Dalian, showing a concentrated distribution trend, while the cold spots were distributed in the northern fringe area of Dalian, with spatial homogeneity characteristics. (3) Topography, ecological environment, social economy, commercial development, spatial structure, spatial form, regional scale, etc. have different impacts on the vitality of urban human settlements.
Collapse
|
4
|
An Equity Evaluation on Accessibility of Primary Healthcare Facilities by Using V2SFCA Method: Taking Fukuoka City, Japan, as a Case Study. LAND 2022. [DOI: 10.3390/land11050640] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The primary healthcare facilities are among the most basic needs of the residents, huge in quantity and widespread. Their distributions are directly related to people’s health, which affects the sustainable development of cities. The accessibility calculation of primary level healthcare facilities and the equity evaluation of accessibility from the perspective of medical service category and urban population is very important for the decision-making of layout and configuration but has been ignored for a long time. This study took the primary healthcare facilities of Fukuoka city in Japan as research objects; it first used the variable two-step floating catchment area (V2SFCA) method to calculate the healthcare catchment areas (HCAs) of medical service providers and the population catchment area (PCAs) of medical demand locations, and then obtained the accessibility to primary healthcare facilities. Finally, the spatial disparities of accessibility were evaluated from three aspects: overall space distribution by using Global and Local Moran’s I, service quality, and the population to be served. The results showed that HCAs were from 500 m to 6400 m, PCAs ranged from 500 m to 3000 m, the use of variable catchments can improve the accuracy of accessibility assessment results; the accessibility of primary healthcare facilities was clustered and had significant spatial differences, which were high in urban center and low in suburban area; the obvious differences in the accessibility distribution characteristics of clinics in differential diagnosis and treatment departments led to different degrees of unsaturation in the types of medical services obtained by residents; although the elderly’s demand for basic medical care was many times higher than that of other age groups, the accessibility in high-demand areas was generally low, and the situation in severely high-demand areas was more serious. This work puts forward a multi-dimensional realistic evaluation system for equality accessibility of primary healthcare facilities, providing the data support for the medical resources and facilities’ allocation and the intensive land use.
Collapse
|
5
|
Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights. LAND 2022. [DOI: 10.3390/land11010085] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Nighttime light images are valuable indicators of regional economic development, and nighttime light data are now widely used in town monitoring and evaluation studies. Using the nighttime light data acquired through Luojia1-01 and the geographic information system spatial analysis method, this study analyzed the spatial vitality pattern of 402 characteristic towns in six geographic divisions of China. The average DN (Digital Number) value of Guzhen, having the highest vitality level, was 0.05665221, whereas that of Xin’an, having the lowest vitality level, was 0.00000186. A total of 89.5% of towns have a low level of vitality. The regional differences were significant; high vitality towns are concentrated in economically developed coastal areas, mainly in two large regions of east China and south central. The average lighting densities of the towns in east China and south central were 0.004838 and 0.003190, respectively. The lighting density of the towns in west central was low, and the vitality intensity was generally low. A spatially significant positive correlation of small-town vitality was observed, and “high–high” agglomeration was primarily distributed in the Yangtze River Delta, Pearl River Delta, and Fujian coastal areas in east and south China. The towns with high vitality intensity had similarities in their geographical location, convenient transportation conditions, and profound historical heritage or cultural accumulation along with many industrial enterprises. This research empirically demonstrates the feasibility of using the 130-m-high resolution of the nighttime lighting data of Luojia1-01 to evaluate the vitality at the town scale, and the vitality evaluation focuses on the spatial attributes of the town, which is meaningful to guide the development of the town in each region given the vast area of China and the large differences in the development of different regions.
Collapse
|