Region-wide environmental noise monitoring in Flanders through Citizen Science : protocol to integrate surveys and measurements

Within the Program for Innovation Procurement, the Flemish government is investing in innovative methods to answer numerous societal challenges. With support of this program the Department of Environment will develop a region-wide noise monitoring protocol in a two year project, started in April 202...

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Hauptverfasser: Dekoninck, Luc, Thomas, Pieter, Botteldooren, Dick, Van Laer, Jef, Duerinckx, Annelies, Van Campenhout, Karen, Verlaek, Mart, Van Haver, Philippe, Geens, Rudi, Van Renterghem, Timothy
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Within the Program for Innovation Procurement, the Flemish government is investing in innovative methods to answer numerous societal challenges. With support of this program the Department of Environment will develop a region-wide noise monitoring protocol in a two year project, started in April 2023. To achieve this, Ghent University partnered up with Scivil, the knowledge center for Citizen Science in Flanders. The noise monitoring question fits in an environmental noise indicator evaluation designed by the Ghent University in 2019-2020. This manuscript gives an overview of the project outline. We discuss the goals, the methodology, the technical implementation and the dataflow. We explain the strategy to include citizens to achieve both the societal and the scientific goals. Since this is a government funded project, the societal aspects have priority. The first component is the technology: hardware, quality, calibration, noise surveys, event classification, privacy and data storage. The second component is the citizen engagement: how to achieve the data collection at a reasonable cost? The third component is the sampling strategy: how to reach an unbiased dataset for multiple variables: spatial characteristics, sources and population? The last component deals with applications: trends in population exposure and perception. This protocol will provide matched exposure and perception data at an unprecedented scale.
ISSN:2221-3767
3005-7124