ArticleJournal of exposure science & environmental epidemiology2015
Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities.
Article in Journal of exposure science & environmental epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Modelling the urban acoustic environment using land use-based gradient boosting.Journal of exposure science & environmental epidemiology · 2026Article
- Integrating noise as a risk factor in studies of Alzheimer's disease and dementia: Guidance for epidemiologic research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Intersections as Hot Spots: Assessing the Contribution of Localized Nontailpipe Emissions and Noise on the Association Between Traffic and Children's Lung Function.Research report (Health Effects Institute) · 2026Article
- Systematic measurement and machine learning-based profile characterization of community noise in a medium-large city in the United States.Journal of exposure science & environmental epidemiology · 2026Article
- The impact of spatial distribution of noise pollution from music recreation facilities and residents' perceptions in Chongqing municipality.Scientific reports · 2025Article
- Moving beyond the noise: geospatial modelling of urban sound environments in a sub-Saharan African city.Scientific reports · 2025Article
- Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.Journal of exposure science & environmental epidemiology · 2024Article
- Spatial modelling and inequalities of environmental noise in Accra, Ghana.Environmental research · 2022Article
- Article
- What Is the Role of Night-Time Noise Exposure in Childhood Allergic Disease?International journal of environmental research and public health · 2022Article
- Space-time characterization of community noise and sound sources in Accra, Ghana.Scientific reports · 2021Article
- Article
- Predicting Fine Spatial Scale Traffic Noise Using Mobile Measurements and Machine Learning.Environmental science & technology · 2020Article
- Article
- Noise Disturbances and Calls for Police Service in València (Spain): A Logistic Model with Spatial and Temporal Effects.International journal of environmental research and public health · 2019Article
- Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system.Environmental monitoring and assessment · 2019Article
- Noise estimation model development using high-resolution transportation and land use regression.Journal of exposure science & environmental epidemiology · 2018Article
- Road Traffic Noise, Air Pollutants, and the Prevalence of Cardiovascular Disease in Taichung, Taiwan.International journal of environmental research and public health · 2018Article
- Lower Noise Annoyance Associated with GIS-Derived Greenspace: Pathways through Perceived Greenspace and Residential Noise.International journal of environmental research and public health · 2018Article
- Spatial and temporal determinants of A-weighted and frequency specific sound levels-An elastic net approach.Environmental research · 2017Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a "GIS-only" model, which considered only predictor variables derived with Geographic Information Systems; and (b) a "Best" model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R(2)) was 0.66-0.87 for "GIS-only" models, and 0.70-0.89 for "Best" models. Short-term noise measurements showed a high correlation (r=0.62-0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.
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