A Study on the Mechanism of How Nature Education Space Characteristics in Country Parks Influence Visitor Perception: Evidence from Beijing, China
Year: 2025
Type: article
Study design: Observational Study
Abstract: In the context of rapid urbanization, the connection between humans and nature has progressively diminished. As an essential approach to fostering public ecological awareness and well-being, nature education requires greater integration into urban green space planning and management. This study examines 14 country parks, urban parks, and forest parks in Beijing, conducting questionnaire surveys in six representative parks and collecting 820 valid responses. Combining image semantic segmentation techniques, the research employs the PSPNet model trained on the ADE20K dataset to automatically extract landscape features of nature education spaces. These features are then integrated with visitor perception evaluations through univariate linear regression models to analyze the impact of spatial variables on visitor perceptions. Results indicate that building coverage, plant species density, interpretation sign density, number of artificial interpretations, and number of nature education activities offerings show significant positive correlations (p < 0.05) with visitor perceptions. In contrast, excessive artificial structures exert a negative influence. The R2 values of each model ranged from 0.12 to 0.34, indicating that natural education space features possess explanatory power for visitor perceptions but remain influenced by multiple interacting factors. This study establishes a quantitative evaluation framework linking natural education space landscape features to visitor perceptions, providing a scientific basis for natural education planning and spatial optimization in parks within megacity contexts.
Source: Sustainability
DOI: 10.3390/su18010083
Authors: Yijin Dong, Lili Zhang, Peiyao Hao, Tiantian Fu
Language: English
Topic: Urban Green Space and Health
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G7252993936
OpenAlex ID: W7117156579
