Tapping urban and soundscape heritage in urban forests contributes to the conservation and utility of cultural heritage. However, urban heritage and soundscapes might be damaged by urban renewal and geological changes. Poems describing urban and soundscape heritage have been poorly researched due to the obscurity, fragmentation, and inaccessibility of historical materials. This study explores the tendencies of ancient poets toward poetized locales and soundscapes and investigates the present conservation of cultural heritage. This study uses historical sensing to assess the spatial information and auditory sensations about cultural heritage in poems through manual collation. Most of the sites in the poems are currently distributed in urban green spaces with good greenery conditions. These sites are mostly located in the downtown area (38.1%) and outskirts (38.1%) of Fuzhou and are well-preserved urban heritage sites. Generally, the poets preferred to describe birds chirping and visited sites with high forest coverage, such as mountains. The methodology of this study can provide a reference for other research on urban and soundscape heritage, helping with the excavation of natural culture and historical resource conservation in cities.

Natural soundscape is considered a dominant type of hearing in forested areas and contributes to health and recovery effects from exposure to the biophilic outdoor environment. This study focuses on the different forest structures, and aims to explore the relationship between perceived soundscape and acoustical parameters, observe physiological indicators, and model the physiological restorative role of soundscape. Questionnaires and measuring equipment were used to gather psychophysical and physiological information at 20 observation sites in urban forested areas. Back-propagation neural network techniques were conducted to determine the forecasting model from psychophysical to physiological parameters. Our results suggested that L_Aeq and L₁₀ are important factors that influence questionnaire responses. Our findings also showed that electromyogram (EMG) signals were the most obvious and sensitive in physiological parameters. Additionally, we found that L_10–90 played the most important role among all physical parameters in the physiological restorativeness soundscape model. This can facilitate the understanding of the physiological restorative role of soundscape in different forest structures when proposing suitable forest-based health care strategies.

The effect of urban green spaces on traffic noise reduction has been extensively studied at the level of single vegetation, hedges, etc., but there is a lack of corresponding studies at the scale of spatial patterns of urban green spaces. Therefore, this study aims to analyze the relationship between the spatial pattern of urban green space and the change in green space’s noise reduction capacity. Through the morphology spatial pattern analysis method, this analysis divides the urban green space in the Fuzhou high-tech zone into seven types of elements with different ecological definitions and simulates the noise condition of the urban environment with the presence of green space as well as without the presence of green space by computer simulation, calculates the distribution map of the noise reduction produced by the urban green space, and analyzes the correlation between the seven types of green space elements and the noise reduction with the geographically weighted regression modeling analysis. The study finds that (1) Urban green space patterns can significantly affect the net noise reduction of green space. Areas with high green coverage can produce a stronger green space noise reduction effect. (2) More complex green space shapes and more fragmented urban green space can produce higher noise reduction. (3) The green space close to the source of noise can exert a stronger noise reduction effect. Therefore, in the process of planning and design, from the perspective of improving the urban acoustic environment, the configuration of high-quality green spaces in areas with higher levels of noise pollution should be given priority, which may have better noise reduction effects.

Kulangsu is a famous scenic area in China and a World Heritage Site. It is important to obtain knowledge with regard to the status of soundscape and landscape resources and their interrelationships in Kulangsu before it became a World Heritage. The objective of this study was to explore the spatial dependency of the soundscapes in Kulangsu, based on the spatiotemporal dynamics of soundscape and landscape perceptions, including perceived sound sources, soundscape quality, and landscape satisfaction degree, and the spatial landscape characteristics, including the distance to green spaces, normalized difference vegetation index, and landscape spatial patterns. The results showed that perception of soundscape and landscape were observed in significant spatiotemporal dynamics, and the dominance of biological sounds in all sampling periods and human sounds in the evening indicated that Kulangsu scenic area had a good natural environment and a developed night-time economy, respectively. The green spaces and commercial lands may contribute to both the soundscape pleasantness and eventfulness. Moreover, the soundscape quality was dependent on the sound dominant degree and landscape satisfaction degree but not on the landscape characteristics. The GWR model had better goodness of fit than the OLS model, and possible non-linear relationships were found between the soundscape pleasantness and the variables of perceived sound sources and landscape satisfaction degree. The GWR models with spatial stationarity were found to be more effective in understanding the spatial dependence of soundscapes. In particular, the data applied should ideally include a complete temporal dimension to obtain a relatively high fitting accuracy of the model. These findings can provide useful data support and references for future planning and design practices, and management strategies for the soundscape resources in scenic areas and World Heritage Sites.