Transforming Noise Control Stations into Soundscape Resource Monitoring Networks: An Adaptive Location Recommendation

Strategic environmental monitoring is crucial for maintaining urban health. Despite ranking among the top environmental risks, noise and its management primarily focus on pollution control, neglecting the health- and biorelated information inherent in soundscapes. For holistic urban sound environment monitoring and strategic governance, this study investigated the complexity of urban social-ecological systems (SES) and compiled 27 variables accordingly, including two sound environment-related indicators, to characterize diverse acoustic conditions across SES. The monitoring sites are expected to provide an adequate representative capacity of these various conditions derived from SES complexity, for which we defined a multigranularity clustering coverage score metric. Concurrently, a total of four criteria─coverage score of representativeness, cost efficiency, population coverage, and noise-sensitive areas─are incorporated into the grid-based location optimization algorithm to generate recommended sites. Results from a case city demonstrate that our method can increase 39.5% of global representativeness by the 10 recommended sites, whose individual representativeness was further evaluated to determine coverage range and levels. Notably, many of the recommended sites are in urban green spaces, which tend to host richer natural soundscapes, highlighting the potential for transforming the rationale of sound environment management from noise control to soundscape resource management.