Predicting traffic noise using land-use regression-a scalable approach.

ABSTRACT:

Background

In modern societies, noise is ubiquitous. It is an annoyance and can have a negative impact on human health as well as on the environment. Despite increasing evidence of its negative impacts, spatial knowledge about noise distribution remains limited. Up to now, noise mapping is frequently inhibited by the necessary resources and therefore limited to selected areas.

Objective

Based on the assumption, that prevalent noise is determined by the arrangement of sources and the surrounding environment in which the sound propagates, we build a geostatistical model representing these parameters. Aiming for a large-scale noise mapping approach, we utilize publicly available data, context-aware feature engineering and a linear land-use regression (LUR) model.

Methods

SUBMITTER: Staab J 

PROVIDER: S-EPMC8920888 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature