Public health is an essential urban issue attracting the increasing attention of scholars and decision-makers while urban planning is an important mechanism to promote health since mounting evidence has shown the planning elements, such as urban green spaces (UGS), could have a positive influence. In previous literature, the studies concerning the impacts of UGSs can be divided into two aspects: the first is to reveal the relationships between UGSs and health using statistical models based on self-reported data, while the second is to take their relationships as presumption and visualize the spatial distributions of UGSs in a geographical information system (GIS) to indicate the existence of health inequalities. I attempt to combine the two pathways, using GIS-based analyses to quantify and visualize UGSs, and subsequently employing the quantified indicators of UGSs to calculate their associations with public health by multiple linear regression (MLR) analysis in SPSS. The study describes a detailed methodology that could be taken as a generic approach to analyze other urban elements and services. A case study is conducted in Linköping central urban area with base areas selected as the spatial unit of analysis. As a consequence, although the elaborate relationships between different indicators of UGSs and public health are not directly provided by the regression models, the correlations between them are indicated to be weak and subtle and require larger samples to reveal. Potential improvements, including the application of panel data and other kinds of regression models, are also summarized for further research.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-187049 |
Date | January 2022 |
Creators | Liu, Lingzi |
Publisher | Linköpings universitet, Institutionen för tema |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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