Rule Sets for Identifying Conditional Attributes of Campus Green Spaces with Enhanced Mental Restoration Effect

The effect of creating green spaces on improving the mental well-being of university students has received increasing attention. Although previous studies have contributed some valuable discussions on what characteristics of green spaces a campus should provide, few have sought to explore the causal effects between conditional attributes of campus green spaces and mental restoration. To fill this gap, this study aimed to explore the causal rule sets for identifying conditional attributes of campus green spaces with enhanced mental restoration effects from a comprehensive perspective by using the fuzzy Delphi technique (FDT) and rough set analysis (RSA). As a result, 12 criteria were obtained by using FDT, and 6 key combination scenes that can cause different degrees of mental restoration were obtained by using RSA. This study not only contributes to the academic research of healthy campus green spaces but also provides new insights into the role of planning and maintaining campus green spaces.

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Publication Details

Journal
Journal of Urban Planning and Development
Published
2024-11-26
DOI
https://doi.org/10.1061/jupddm.upeng-5194
Citations
7
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
2.20
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article

Rule Sets for Identifying Conditional Attributes of Campus Green Spaces with Enhanced Mental Restoration Effect

Xianghua Zhang, Wei‐Quan Zheng, Gwo‐Hshiung Tzeng, Bo-Wei Zhu et al.
7 citations
Journal of Urban Planning and Development
Urban Green Space and Health
2.20
article

Rule Sets for Identifying Conditional Attributes of Campus Green Spaces with Enhanced Mental Restoration Effect

Xianghua Zhang, Wei‐Quan Zheng, Gwo‐Hshiung Tzeng, Bo-Wei Zhu, Lei Xiong, Guanqiang Wang, Chengcheng Feng
article en
7 citations

Abstract

The effect of creating green spaces on improving the mental well-being of university students has received increasing attention. Although previous studies have contributed some valuable discussions on what characteristics of green spaces a campus should provide, few have sought to explore the causal effects between conditional attributes of campus green spaces and mental restoration. To fill this gap, this study aimed to explore the causal rule sets for identifying conditional attributes of campus green spaces with enhanced mental restoration effects from a comprehensive perspective by using the fuzzy Delphi technique (FDT) and rough set analysis (RSA). As a result, 12 criteria were obtained by using FDT, and 6 key combination scenes that can cause different degrees of mental restoration were obtained by using RSA. This study not only contributes to the academic research of healthy campus green spaces but also provides new insights into the role of planning and maintaining campus green spaces.

Journal of Urban Planning and DevelopmentVol. 151(1)
Macau University of Science and Technology (MO), University of Macau (MO), Macao Polytechnic University (MO), National Taipei University (TW)
Sustainable cities and communities
Openalex Percentile: Top 12%
Urban Green Space and Health
2.20
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Rule Sets for Identifying Conditional Attributes of Campus Green Spaces with Enhanced Mental Restoration Effect — Xianghua Zhang, Wei‐Quan Zheng, et al. · Journal of Urban Planning and Development (2024) | TGRS Research Map | TGRS