Can acoustic indices reflect the characteristics of public recreational behavioral in urban green spaces?
Creators: name: Fu, Weicong
name: Ran, Chengyu
name: Huang, Jingkai
name: Chen, Zhu
name: Fan, Shiyuan
name: Fang, Wenqiang
name: Ye, Miaojun
name: Dong, Jiaying
name: Yao, Xiong
name: Chen, Ziru
Publisher: name: Amsterdam [u.a.] : Elsevier Science
Year: 2023
Subjects: subject: Acoustic index
subject: Recreational behavior
subject: Soundscape
subject: Spatial and temporal variation
subject: Dewey Decimal Classification::500 | Naturwissenschaften::570 | Biowissenschaften, Biologie
subject: Dewey Decimal Classification::600 | Technik::630 | Landwirtschaft, Veterinärmedizin

description: Acoustic indicators serve as an effective means of assessing the quality of urban green space soundscape. The informative, easy accessibility and non-invasive nature of acoustic monitoring renders it an excellent tool for studying the interaction among the natural environment, wildlife, and human activities. Urban green space is essential in the urban ecosystem and constitutes the primary location for public outdoor recreation. However, the existing methods for monitoring public recreational behavior, such as on-site observation, drone observation, or questionnaire interviews, require significant labor or professional expertise. All of these methods have their limitations, so there is still much to be researched in the acoustic indices and recreational behavior. As a result, the potential for using acoustic characteristics to monitor public recreational behavior remains underexplored. To address this gap, this study investigates the potential of 5 widely used acoustic indices and acoustic intensity for monitoring public recreational behavior: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Richness (AR), Normalized Difference Soundscape Index (NDSI), and Power Spectral Density (PSD). Data were collected from 35 monitoring points in urban green spaces during the opening hours (6:00–22:00) to analyze the relationship between these indices and public recreational behavior. The findings indicate that (1) ACI, ADI, and AR daily exhibited multi-peak daily variation characteristics similar to those of public recreational behavior, displaying a “W” shape, while NDSI exhibits opposite variation characteristics; (2) the spatial variation characteristics of ACI, ADI, and AR change in response to the green space, and these changes align with public recreational behavior; (3) the correlation analysis and generalized linear mixed model construction further demonstrate that acoustic indices are effective in capturing the dynamic activities of visitor behavior; and (4) PSD undergoes significant temporal dynamic changes along the frequency gradient, with different frequency intervals reflecting the activity information of different recreational behaviors. In conclusion, this research highlights the effectiveness of using acoustic indices to analyze both the spatial and temporal variation characteristics of public recreational behavior in urban green spaces. The results can provide valuable data support for the enhancement and renovation of urban green spaces.