Towards better visualizations of urban sound environments: insights from interviews

• URL: http://arxiv.org/abs/2407.16889v1
• Date: Tue, 11 Jun 2024 07:39:48 GMT
• Title: Towards better visualizations of urban sound environments: insights from interviews
• Authors: Modan Tailleur, Pierre Aumond, Vincent Tourre, Mathieu Lagrange,
• Abstract summary: We analyze the need for the representations of sound sources, by identifying the urban stakeholders for whom such representations are assumed to be of importance. Three distinct use of sound source representations emerged in this study: noise-related complaints for industrials and specialized citizens, soundscape quality assessment for citizens, and guidance for urban planners. Findings reveal diverse perspectives for the use of visualizations, which should use indicators adapted to the target audience, and enable data accessibility.
• Score: 1.2599533416395765
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Urban noise maps and noise visualizations traditionally provide macroscopic representations of noise levels across cities. However, those representations fail at accurately gauging the sound perception associated with these sound environments, as perception highly depends on the sound sources involved. This paper aims at analyzing the need for the representations of sound sources, by identifying the urban stakeholders for whom such representations are assumed to be of importance. Through spoken interviews with various urban stakeholders, we have gained insight into current practices, the strengths and weaknesses of existing tools and the relevance of incorporating sound sources into existing urban sound environment representations. Three distinct use of sound source representations emerged in this study: 1) noise-related complaints for industrials and specialized citizens, 2) soundscape quality assessment for citizens, and 3) guidance for urban planners. Findings also reveal diverse perspectives for the use of visualizations, which should use indicators adapted to the target audience, and enable data accessibility.

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