Federal Railways Office receives backing from Disy for nationwide noise measurement project
In the ongoing fifth round of the nationwide railway noise mapping project in Germany, Disy Informationssysteme GmbH continues to spearhead the data processing efforts. The EU-wide tender for this project was won by a consortium led by Disy, which includes partners SoundPLAN and AFRY.
The project's aim remains to assess environmental noise and plan measures to reduce noise based on this assessment, as mandated by the EU Environmental Noise Directive (2002/49/EG). This directive requires an update of noise maps every five years.
Disy brings its unique experience in Germany in the automated processing of railway data for railway noise mapping. The company's strength lies in creating a valid foundation for noise calculation and subsequent noise action planning. The Disy Spatial Workbench is the heart of the system, automating and quality-assuring all processes.
SoundPLAN brings strategies and computing capacity for efficient noise mapping to the project. They focus on the digital terrain model and route purification, while AFRY ensures engineering quality by validating the results from an engineering perspective, leveraging their long-standing experience.
Together, they will process up to 52,000 kilometers of track for the project. The Deutsche Bahn AG (DB Netz AG) is responsible for the technical implementation of data processing in this project.
Torsten Brauer, Senior Consultant for Traffic at Disy, stated that the great challenge lies in the complex railway data landscape. Four central factors ensure data quality in round 5: complex traffic route preparation steps, data combination for the acoustic model, collaboration with project partners, and the central infrastructure provided by Disy.
The project's process balances automation and quality control. The project's results, based on the EU Environmental Noise Directive, will be published no later than June 30, 2027, on the Geoportal of the Federal Railway Authority. The partners in this consortium are committed to ensuring a stable, traceable, and quality-assured data model from track axes and various railway data.
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