Urban Forest Health Benefits Analysis: Ecological, Colour, and Spatial Factors in Kunming
by Kaiyuan Yi·Updated 1mo ago
5.7 MB1files
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Description
Supplementary file 1 contains the research document for a study analyzing how vegetation landscapes enhance health benefits from urban forests. The study, authored by Kaiyuan Yi and last updated in April 2026, employed an integrated SEM-ISM-DEMATEL methodology with psychological, physiological, and eye-tracking experiments in Kunming, China.
Use Cases
Modeling the causal relationships between ecological features and restorative benefits based on the described SEM-ISM-DEMATEL framework.
Analyzing seasonal colour expression's impact on physiological arousal based on the HSV colour analysis of plant communities.
Identifying key drivers like Plant Species Richness and Plant Health & Phenology for urban forest management based on the ISM-DEMATEL results.
Studying the mediating role of Perceived Restorative Experience (PRE) between spatial features and health outcomes as described in the results.
Strengths
The study integrates multiple data collection methods, including psychological scales, physiological monitoring, and eye-tracking.
Research is grounded in a specific geographic context, with data collected in Kunming, China.
The document is licensed under CC-BY-4.0, permitting open sharing and adaptation.
Limitations
The dataset is a 5.7 MB DOCX file; the underlying quantitative data and its structure are not directly accessible.
Row count and column-level documentation are unknown, which may limit suitability assessment for direct analysis.
Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
Kaiyuan Yi via figshare.
Collection Method
Integrated quantitative HSV colour analysis and human-factors experiments incorporating psychological scales, physiological monitoring, and eye-tracking.
Time Range
Study period not specified; document last updated April 2026.
Freshness
Last updated 2026-04-27 12:57:58; freshness should be verified.
Geography
Data collected in Kunming, China.
The primary file is a DOCX document; the raw experimental data referenced within may not be included.