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.

Soundscapes are important resources and contribute to high-quality visiting experiences in scenic areas. Based on a public investigation of 195 interviewees in the Kulangsu scenic area, this study aimed to explore the relationships between the harmonious degree of sound sources (SHD) and visiting experience indicators, in terms of soundscape perception, as well as the satisfaction degree of visual landscape and comprehensive impression. The results suggested that the dominating positions of human sounds did not totally suppress the perception of natural sounds such as birdsong and sea waves in the scenic area. Natural sound sources also showed a higher harmonious degree than other artificial sounds. Significant relationships existed between the SHD of most sound sources and the visiting experience indicators. Natural sounds were closely related to pleasant and comfortable soundscape perception, while mechanical sound sources were mainly related to eventful and varied soundscapes. The close relationships between certain sound sources and the satisfaction degree of the visual landscape and comprehensive impression evaluation indicated the effectiveness of audio-visual and even multi-sensory approaches to enhance visiting experience. The structural equation model further revealed that (1) natural sound was the most influential sound source of soundscape and visual landscape perception; (2) human sounds and mechanical sounds all showed significant positive effects on soundscape perception; and (3) indirect relationships could exist in the SHD of sound sources with comprehensive impression evaluation. The results can facilitate targeted soundscape and landscape management and landsense creation with the aim of improving visiting experience.

Natural soundscape quality (NSQ) has been recognized as an essential cultural ecosystem service that contributes significantly to human health and well-being. It also stands as an indispensable component of environmental quality, especially for landscape aesthetic quality. However, an assessment tool for NSQ in landscape planning and environmental impact assessments is still absent. Therefore, this paper aims to address this gap by proposing an indicator-based model for assessing and quantifying NSQ in the Geographic Information System. The model characterizes NSQ based on Calmness and Vibrancy, and employs several indicators, sub-indicators, and respective metrics as proxies to quantify and map them spatially. The evaluation criteria of the model correspond to the general public's preferences for soundscape features. The case study results in Springe municipality, Germany, show that the relative values of NSQ are high in green spaces, including forests, grasslands, and shrublands, whereas they are low in open farmlands. The multiple natural sounds yield higher NSQ scores than the individual ones. The same soundscape compositions in forests and in urban parks exhibit higher NSQ scores than in other land cover types. In addition, the shares of relative values show similar distribution patterns among Calmness, Vibrancy, and NSQ according to land cover types and soundscape compositions. The evaluation results align with public values and preferences for soundscape features. Unlike subjectivist approaches, our user-independent methodology is easily transferable and reproducible. The results are comparable and communicable among the assessed areas. These endow the indicator-based model with the potential to be applied at various planning and management scales. The findings can help to incorporate soundscape evaluation into landscape planning and management systems, supporting sustainable landscape development, and providing valuable information for policy-, plan- and decision-making.

The physical environment of urban public facilities is an important driver for public health and work efficiency. Unfortunately, citizens are exposed to negative physical environments because of inappropriate spatial forms in urban growth boundaries. This study aims to explore psychophysical drivers and their spatial distribution in campus city community life circles during the COVID-19 pandemic. Questionnaires and measuring equipment were used to gather psychophysical information in a 15 min campus city community life circle in Fuzhou, China. To this end, acoustic, light and thermal environments were used to map spatial distributions. We then explored relationships between spatial form and psychophysical parameters. The study results show that the distance to road (DTR), green area ratio (GR) and street width (SW) are all potential spatial drivers for psychophysical information. Furthermore, the acoustical, light and thermal environments provide interactions for the public understanding of the environment. These findings contribute to the understanding and evaluation of psychophysical drivers, spurring regional industry in community life circles and contributing to developing suitable plans and industrial distribution in urban areas.

Soundscape quality in green spaces of residential areas directly contributes to residents’ quality of life. It has close relationships with landscape characteristics, which should be considered in landscape planning and design processes in residential areas. Accordingly, this study proposed a new perspective on the interrelationships between soundscape perception and landscape pattern on multi-scale, based on a case study of 30 residential green spaces in Fuzhou, China. Percentage of Landscape (PLAND), Patch Density (PD), Landscape Shape Index (LSI), and Patch cohesion index (COHESION) were utilized to represent the landscape pattern of vegetation, buildings, and roads in the residential areas. Soundscape perception was interpreted using the sound dominant degree (SDD) of sound sources and overall soundscape quality. The examined spatial scales range from 20 m to 180 m, with concentric circles spaced 20 m apart for each sampling point. Correlation analyses indicated that most landscape indices of vegetation and buildings were correlated with these soundscape perception indicators, while limited landscape indices of roads were associated with them. Based on the multi-scale landscape indices, multiple linear regression models for the SDD of sound sources and overall soundscape quality were established, confirming that the scale effect of landscape patterns can affect soundscape perception. Expressly, results indicated that these models were chiefly influenced by the landscape indices at a scale less than 120 m, but the scale effect of landscape pattern on the SDD of birdsong, pleasantness, and quietness was not so evident. Furthermore, we found that the number of explanatory variables may somewhat affect the model performance. The overall interpretability of these landscape indices for the SDD of sound sources was better than that of overall soundscape quality, implying the complexity of the latter. This study offers a fresh insight into the relationship between landscapes and soundscapes at varying scales. The findings can provide useful information for the promotion strategies of landscapes and soundscapes, especially in residential green spaces.