PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (5): 779-791.doi: 10.18306/dlkxjz.2020.05.007

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Impact of greenspace exposure on residents’ mental health: A case study of Nanjing City

LI Zhixuan, HE Zhongyu*(), ZHANG Yiming, JIN Shuangshuang, WANG Xuemei, ZHU Jie, LIU Shicen   

  1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
  • Received:2019-04-11 Revised:2019-07-18 Online:2020-05-28 Published:2020-07-28
  • Contact: HE Zhongyu
  • Supported by:
    National Natural Science Foundation of China(51678288)


The impact of greenspace exposure on mental health has long been the focus of scholars in different fields in China and internationally. Most studies are based on a single individual perspective, such as activity time, range of activities, and so on, or a single environmental perspective, such as the number of green spaces, green space accessibility, among others. Few studies have measured individuals' perception of the environment from the perspective of the interaction between the individuals and the environment. This study constructed a conceptual framework for the impact of green environment exposure on mental health based on considerations of residents' visual perception and spatiotemporal activities. In addition, this study also proposed a green visual exposure measurement method based on green view index and individual spatiotemporal activity, and estimated the green rate using convolutional neural network model and machine learning. This study took Nanjing City as an empirical research object, and used structural equation modeling to compare and analyze the differences in the impact of green rate, green view index, and total green visual exposure on mental health. In addition to observing the direct influences, environmental perception, physical activity, and sense of belongingness were selected as mediating variables to analyze the pathways of different indicators that affect mental health. The results show that the three greenspace exposure measurement indicators have a significant correlation with mental health, but the degree of influence and pathway are different. It is important to establish a more comprehensive green environment exposure evaluation index system. Subjective built-up environment perception can be used as a mediator of the impact of green view index and total green visual exposure on mental health. Physical activity only serves as a mediator of the impact of the total amount of green visual exposureon mental health. This study expands the research framework of the impact of greenspace exposure on mental health, and has important reference value for the planning and management of urban greenspace system.

Key words: environmental exposure, green visual exposure, green view index, mental health, machine learning, Nanjing City