Open AccessCrowdsourcing Data for the Elaboration of Noise Maps: a Methodological Proposal
Author(s) -
Gabriella Graziuso,
Michele Grimaldi,
Simona Mancini,
J. Quartieri,
Cláudio Guarnaccia
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1603/1/012030
Subject(s) - computer science , noise pollution , crowdsourcing , upload , noise (video) , environmental noise , global positioning system , data collection , data science , elaboration , data acquisition , recreation , artificial intelligence , world wide web , telecommunications , sound (geography) , noise reduction , philosophy , statistics , mathematics , geomorphology , geology , humanities , law , political science , image (mathematics) , operating system
In recent decades, the awareness that noise pollution caused by traffic, industry and recreational activities constitutes one of the main environmental problems is growing. In order to control the environmental noise, many regulations propose the creation of noise maps according to standard procedures that involves the data acquisition, analysis and elaboration. In this paper, crowdsourcing noise data collection is described. It involves volunteers that can record sound pressure levels thanks to specific applications on their mobile devices, such as the “NoiseCapture” app developed in France by CNRS and IFSTTAR, and upload the measurement, with their GPS location data, on a continuously updated map. This approach mainly contributes to citizens’ greater awareness about noise pollution in an urban area. Beside this mode of data acquisition, the paper focuses on the analysis of the acquired data with the kernel density estimation technique, implemented in a GIS environment. The results allows the elaboration of sound density maps, defined from the spatial and temporal point of view, that can support the appropriate mitigation actions.