A Spatial Data Infrastructure for Environmental Noise Data in Europe

Area of Science:

• Environmental Science
• Geoinformatics
• Public Health

Background:

• Urbanization increases environmental noise, necessitating better data for impact assessment.
• Current data utilization and reporting for noise pollution are fragmented across Europe.
• Spatial data infrastructures offer potential solutions for harmonized environmental data management.

Purpose of the Study:

• To analyze how European spatial data infrastructures enhance environmental noise data utilization and reporting.
• To demonstrate the benefits of the INSPIRE and END frameworks for noise data management.
• To showcase improved interoperability and data sharing for noise pollution assessment and mitigation.

Main Methods:

• Analysis of existing spatial data infrastructures in Europe, focusing on INSPIRE and END.
• Examination of data management principles for environmental noise data.
• Description of a use case involving cross-border noise data harmonization.

Main Results:

• INSPIRE and END principles facilitate better environmental noise data management and understanding.
• Shared, harmonized spatial data improves noise mapping and action plan development.
• Decentralized e-reporting infrastructure enhances data flow and integration with other domains.

Conclusions:

• Implementing INSPIRE and END principles significantly improves pan-European noise data management and reporting.
• Spatial data infrastructures are crucial for effective environmental noise assessment and mitigation strategies.
• Interoperable and harmonized noise data supports integrated environmental monitoring and policy development.