Spatial Mismatch between the Supply and Demand of Urban Leisure Services with Multisource Open Data

• Published in: ISPRS international journal of geo-information 2020-08, Vol.9 (8), p.466
• Main Authors: Deng, Yue, Liu, Jiping, Luo, An, Wang, Yong, Xu, Shenghua, Ren, Fu, Su, Fenzhen
• Format: Article
• Language: English
• Subjects: Construction; Correlation analysis; Data; Demand analysis; Developing countries; Economic development; Economic growth; Economics; Ecosystems; GDP; Geographic information systems; Gross Domestic Product; Happiness; LDCs; Leisure; leisure services; multisource data; Open data; Population; Quality of life; Recreation demand; Research methodology; Smart cities; Spatial distribution; spatial mismatch; Spatial planning; Standard of living; Suburban areas; Supply & demand; supply and demand; urban; Urban areas; Urban planning; Urban research; Urbanization
• ISSN: 2220-9964; 2220-9964
• DOI: 10.3390/ijgi9080466

Understanding the balance between the supply and demand of leisure services (LSs) in urban areas can benefit urban spatial planning and improve the quality of life of residents. In cities in developing countries, the pursuit of rapid economic growth has ignored residents’ demand for LSs, thereby leading to a high demand for and short supply of these services. However, due to the lack of relevant research data, few studies have focused on the spatial mismatch in the supply and demand of LSs in urban areas. As typical representatives of multisource geographic data, social sensing data are readily available at various temporal and spatial scales, thus making social sensing data ideal for quantitative urban research. The objectives of this study are to use openly accessible datasets to explore the spatial pattern of the supply and demand of LSs in urban areas and then to depict the relationship between the supply and demand by using correlation analysis. Therefore, taking Beijing, China, as an example, the LS supply index (SI) and societal needs index (SNI) are proposed based on open data to reflect the supply and demand of LSs. The results show that the spatial distribution of the LS supply and demand in Beijing varies with a concentric pattern from the urban center to suburban areas. There is a strong correlation between the supply and demand of commercial and multifunctional services in Chaoyang, Fengtai, Haidian and Shijingshan, but there is no obvious correlation between the supply and demand of ecological and cultural services in Beijing. Especially in Dongcheng and Xicheng, there is no obvious correlation between the supply and demand of all services. The proposed approach provides an effective urban LS supply and demand evaluation method. In addition, the research results can provide a reference for the construction of “happy cities” in China.