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

Staab, Jeroen and Schady, Arthur and Wolf, Kathrin and Lakes, Tobia and Taubenböck, Hannes (2021) Predicting traffic noise – a scalable approach using land-use regression. In: 13th ICBEN Congress on Noise as a Public Health Problem. 13th ICBEN Congress on Noise as a Public Health Problem, 14.-17. Jun. 2021, Stockholm, Schweden.

Full text not available from this repository.

Abstract

Notable noise mapping obligations exist in the European Union. However, they are limited to designated areas such as large agglomerations and main traffic infrastructures and therefore exclude certain populations from exposure assessments and consecutive noise action planning. Existing maps are not spatially congruent to epidemiological cohorts like the German National Cohort (NAKO). As noise mapping is frequently confined by the necessary resources and data, we searched for economic alternatives for area-wide noise mapping making use of spaceborne earth observations. Using remote sensing methods, we built a geostatistical model embracing the arrangement of sources of noise and the surrounding environment in which the sound propagates. In our experimental set-up, we relied on publicly available noise data, context-aware feature engineering and a machine learning model. Eventually, the scalable approach explained 78% of the variations and can be deployed for predictions at a high spatial granularity of 10x10 meters. With it, we aim to spatially close the blank spots in existing noise maps allowing to assess noise exposure beyond already mapped urban populations in suburban and rural areas as well.

Item URL in elib:https://elib.dlr.de/142601/
Document Type:Conference or Workshop Item (Speech)
Title:Predicting traffic noise – a scalable approach using land-use regression
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Staab, JeroenJeroen.Staab (at) dlr.dehttps://orcid.org/0000-0002-7342-4440
Schady, ArthurDLR, IPAhttps://orcid.org/0000-0002-3078-9546
Wolf, KathrinInstitute of Epidemiology, Helmholtz Zentrum München-German Research Centre for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, GermanyUNSPECIFIED
Lakes, TobiaHU BerlinUNSPECIFIED
Taubenböck, HannesHannes.Taubenboeck (at) dlr.deUNSPECIFIED
Date:15 June 2021
Journal or Publication Title:13th ICBEN Congress on Noise as a Public Health Problem
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Urban; Traffic Noise; Land Use Regression; Linear Model; Cross Validation; Environmental Justice
Event Title:13th ICBEN Congress on Noise as a Public Health Problem
Event Location:Stockholm, Schweden
Event Type:international Conference
Event Dates:14.-17. Jun. 2021
Organizer:International Commission on Biological Effects of Noise (ICBEN)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research, R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Institute of Atmospheric Physics > Transport Meteorology
Deposited By: Staab, Jeroen
Deposited On:07 Jul 2021 15:01
Last Modified:07 Jul 2021 15:01

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