Interpolated Stand Properties of Urban Forest Parks Account for Posted Facial Expressions of Visitors

Fei Yu, Jianfeng Deng, Xiaogang Ding and Hongyan Ma
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Fei Yu: Guangdong Academy of Forestry, Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangzhou 510520, China
Jianfeng Deng: Guangdong Academy of Forestry, Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangzhou 510520, China
Xiaogang Ding: Guangdong Academy of Forestry, Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangzhou 510520, China
Hongyan Ma: Guangzhou Tanhui Forestry Co., Ltd., Guangzhou 510520, China

Sustainability, 2022, vol. 14, issue 7, 1-22

Abstract: Posted facial expressions on social networks have been used as a gauge to assess the emotional perceptions of urban forest visitors. This approach may be limited by the randomness of visitor numbers and park locations, which may not be accounted for by the range of data in local tree inventories. Spatial interpolation can be used to predict stand characteristics and detect their relationship with posted facial expressions. Shaoguan was used as the study area where a tree inventory was used to extract data from 74 forest stands (each sized 30 m × 20 m), in which the range was increased by interpolating the stand characteristics of another 12 urban forest parks. Visitors smiled more in parks in regions with a high population or a large built-up area, where trees had strong trunks and dense canopies. People who displayed sad faces were more likely to visit parks located in regions of hilly mountains or farmlands, where soils had a greater total nitrogen concentration and organic matter. Our study illustrates a successful case in using data from a local tree inventory to predict stand characteristics of forest parks that attracted frequent visits.

Keywords: mental well-being; urbanization; sentiments of urban forest visitors; spatial interpolation; tree inventory (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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