Work

Mapping Noise Pollution Using Modelled and Crowdsourced Urban Noise Data

Year: 2025

Type: article

Abstract: ABSTRACT Transport‐generated noise pollution significantly burdens population health. Quantifying noise distribution and identifying areas with elevated noise levels is crucial for designing effective policy measures. We apply the CNOSSOS‐EU numerical transport noise model to Pōneke Wellington, mapping traffic‐induced noise exposure with good spatial coverage from public data. Crowdsourced noise data (CND) maps all noise sources and we spatially compare results. While unsuitable as a standalone method, CND highlights the impact of missing noise sources and offers a limited but promising validation tool for modelled data when alternatives are lacking.

Source: New Zealand Geographer

DOI: 10.1111/nzg.70002

Authors: Allan Schori, Mairéad de Róiste, Mirjam Schindler

Institution: Victoria University of Wellington

Language: English

Topic: Noise Effects and Management

Subfield: Speech and Hearing

Field: Health Professions

Domain: Health Sciences

SDG: Sustainable cities and communities

Open Access status: hybrid

Estimated APC paid: $2,900