edoc

Noise estimation model development using high-resolution transportation and land use regression

Harouvi, Omer and Ben-Elia, Eran and Factor, Roni and de Hoogh, Kees and Kloog, Itai. (2018) Noise estimation model development using high-resolution transportation and land use regression. Journal of exposure science and environmental epidemiology, 28 (6). pp. 559-567.

Full text not available from this repository.

Official URL: https://edoc.unibas.ch/66920/

Downloads: Statistics Overview

Abstract

Noise pollution is a common phenomenon of the 21st century. Noise prediction models tend to estimate noise levels mainly from road traffic sources (such as cars, public transportation etc.). This paper describes the adoption of land use regression (LUR) modeling methodology to assess noise pollution in two periods of the day (rush hour and off-peak), in two major cities in Israel (Tel Aviv and Beer Sheva). For both rush hour and off-peak times, 20 min short term measurements were used to develop a LUR noise estimation model. We used GIS-based predictors alongside commonly used traffic predictors. The findings show good fits for our model, with rush hour "out of sample" ten folds cross-validated R² of 0.79 (Tel Aviv) and 0.52 (Beer Sheva). The Tel Aviv model performance was also tested with independent monitoring data in an adjacent city (Bat Yam), presenting a good performance as well (R² of 0.93). The findings demonstrate the viability of using a LUR approach for applying high-resolution spatial data to estimate and map noise pollution for environmental noise assessment.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Environmental Exposures and Health > Physical Hazards and Health (Röösli)
UniBasel Contributors:de Hoogh, Kees
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Nature Publishing Group
ISSN:1559-0631
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:17 Dec 2018 08:24
Deposited On:17 Dec 2018 08:24

Repository Staff Only: item control page