This study proposed a plan for implementing a pleasant and healthy indoor landscape in subway station space. To this end, it established a 3D landscape model of the subway interior by reviewing previous studies on indoor landscape and the greenness index of indoor spaces. Moreo-ver, it investigated and analyzed psychophysiological responses of users to environmental indoor landscape design in subway station space. Subway stations were classified as underground subway stations and ground subway stations according to the presence of natural light inflow. The greenness index of indoor spaces was also divided into four types of 0%, 10%, 15%, and 20%. Through this process, eight 3D landscape models of the subway interior were implemented. In addition, this study investigated psychophysiological responses of 60 male and female adults in their 20s and 30s using the models implemented. The investigation result was analyzed based on a frequency analy-sis, the χ2 test, T-test, one-way analysis of variance, and multidimensional scaling, which were per-formed in SPSS Statistics 25. The results of this study can be summarized as follows. First, physiological responses of research subjects were analyzed based on their prefrontal α wave asymmetric values. The analytic result showed that the environment where interior landscape was adopted pro-duced more positive effects than the environment where interior landscape was not adopted. Sec-ond, psychological responses of research subjects were examined based on their greenness index preference, awareness of interior landscape area, attention restoration effect, and space images. The analytic result indicated that, among eight 3D landscape models of the subway interior, they preferred the model with the greenness index of 15% for underground subway stations. In addition, they preferred the model with the greenness index of 10% the most for ground subway stations.
CITATION STYLE
Kim, W. J., & Lee, T. K. (2021). Psychophysiological response according to the greenness index of subway station space. Sensors, 21(13). https://doi.org/10.3390/s21134360
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