Spatiotemporal Analytics of Environmental Sounds and Influencing Factors Based on Urban Sensor Network Data

Urban construction has accelerated the deterioration of the urban sound environment, which has constrained urban development and harmed people's health. This study aims to explore the spatiotemporal patterns of environmental sound and determine the influencing factors on the spatial differentiation of sound, thus supporting sustainable urban planning and decision-making. Fine-grained sound data are used in most urban sound-related research, but such data are difficult to obtain. For this problem, this study analyzed sound trends using Array of Things (AoT) sensing data. Additionally, this study explored the influences on the spatial differentiation of sound using GeoDetector (version number: 1.0-4), thus addressing the limitation of previous studies that neglected to explore the influences on spatial heterogeneity. Our experimental results showed that sound levels in different areas of Chicago fluctuated irregularly over time. During the morning peak on weekdays: the four southern areas of Chicago have a high-high sound gathering mode, and the remaining areas are mostly randomly distributed; the sound level of a certain area has a significant negative correlation with population density, park area, and density of bike route; park area and population density are the main factors affecting the spatial heterogeneity of Chicago's sound; and population density and park area play an essential role in factor interaction. This study has some theoretical significance and practical value. Residents can choose areas with lower noise for leisure activities according to the noise map of this study. While planning urban development, urban planners should pay attention to the single and interactive effects of factors in the city, such as parks, road network structures, and points of interest, on the urban sound environment. Researchers can build on this study to conduct studies on larger time scales.