The Characteristics of Visitor Behavior and Driving Factors in Urban Mountain Parks: A Case Study of Fuzhou, China

Author:

Fan Shiyuan1,Huang Jingkai1,Gao Chengfei1,Liu Yuxiang2ORCID,Zhao Shuang3ORCID,Fang Wenqiang1ORCID,Ran Chengyu1,Jin Jiali45,Fu Weicong16

Affiliation:

1. College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, 15 Shangxiadian Rd., Fuzhou 350000, China

2. Stantec Architecture Ltd., 1100-111 Dunsmuir St., Vancouver, BC V6B 6A3, Canada

3. Metro Vancouver Regional District, 4515 Central Blvd, Burnaby, BC V5H 4J5, Canada

4. Research Institute of Forestry, Chinese Academy of Forestry, Xiangshan Road, Haidian District, Beijing 100091, China

5. Urban Forest Research Centre, The National Forestry and Grassland Administration, Xiangshan Road, Haidian District, Beijing 100091, China

6. Collaborative for Advanced Landscape Planning, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada

Abstract

Previous studies have focused on the linear relationship between recreation behavior and environmental variables. However, to inform the planning and design of recreational spaces, it is essential to understand the factors that contribute to differences in the spatial distribution of recreation behavior. This study investigates the characteristics of visitor behavior in urban mountain parks in Fuzhou City, Fujian Province, China. It describes the distribution of tourist numbers and the diversity of behaviors in these parks and explores the landscape driving factors of visitor behavior, as well as the interaction effects between the factors from the perspective of spatial driving forces. The results indicate that (1) The observed behaviors in the three parks are primarily access behaviors. The number of visitors and the diversity of behaviors show a high level in the morning and evening and a low level in the midday. (2) There was minimal variation in behavioral composition and behavioral diversity among the study plots of different elevation gradients in the three parks. However, the contrasts between different landscape types were more pronounced, with impermeable plazas exhibiting the highest behavioral diversity and park roads demonstrating the most homogeneous behavioral diversity. (3) The impact of environmental factors was more pronounced than that of landscape pattern factors. The environmental factors that most strongly influenced passing, dynamic, and static behaviors were spatial connectivity value, hard space proportion, and number of recreational facilities, respectively. In contrast, the hard space proportion was the strongest driver of behavioral diversity. Moreover, the interaction between the hard space proportion and spatial connectivity value was more pronounced in driving behavioral diversity, as well as the three behaviors.

Funder

Green Urbanization across China and Europe: Collaborative Research on Key Technological Advances in Urban Forests

The Horizon 2020 strategic plan: CLEARING HOUSE—Collaborative Learning in Research, Infor-nation sharing, and Governance on How Urban tree-based solutions support Sino-European urban futures

National Non-Profit Research Institutions of the Chinese Academy of Forestry

Publisher

MDPI AG

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