Mapping the Sound Environment of Andorra and Escaldes-Engordany by Means of a 3D City Model Platform

Rosa Ma Alsina-Pagès,Robert Garcia Almazan,Marc Pons,Marc Vilella

doi:10.3390/urbansci3030089

Rosa Ma Alsina-Pagès, Robert Garcia Almazan + Show 2 more

Open Access

https://doi.org/10.3390/urbansci3030089

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Journal: Urban Science	Publication Date: Aug 9, 2019
Citations: 1	License type: CC BY 4.0

Affiliation: Ramon Llull University, University of Andorra

Abstract

In the new paradigm of the smart cities world, public opinion is one of the most important issues in the new conception of urban space and its corresponding regulations. The data collection in terms of environmental noise cannot only be related to the value of the equivalent noise level L A e q of the places of interest. According to WHO reports, the different types of noise (traffic, anthropomorphic, industrial, and others) have different effects on citizens; the focus of this study is to use the identification of noise sources and their single impacts on background urban noise to develop a visualization tool that can represent all this information in real time. This work used a 3D model platform to visualize the acoustic measurements recorded at three strategic positions over the country by means of a sound map. This was a pilot project in terms of noise source identification. The visualization method presented in this work supports the understanding of the data collected and helps the space-time interpretation of the events. In the study of soundscape, it is essential not only to have the information of the events that have occurred, but also to have the relations established between them and their location. The platform visualizes the measured noise and differentiates four types of noise, the equivalent acoustic level measured and the salience of the event with respect to background noise by means of the calculation of SNR (Signal-to-Noise), providing better data both in terms of quantity and quality and allowing policy-makers to make better-informed decisions on how to minimize the impact of environmental noise on people.

Highlights

While the rise of Big Data is transforming both industry and academia, some of the challenges that have appeared as part of this new paradigm have become full research lines themselves
An easy-to-understand showcase of complex information [1] may be remarkably useful for policy-makers who are responsible for developing and implementing policies and regulations, as well as among the citizenship in terms of raising awareness and engaging the community
We describe how raw acoustic data were labeled to identify the different types of noise events that occurred in the three pilot locations, and we describe the four groups of noise events designed for the noise mapping in the 3D city platform

Summary

Introduction

While the rise of Big Data is transforming both industry and academia, some of the challenges that have appeared as part of this new paradigm have become full research lines themselves. The data consumer profile is evolving as well and is increasingly demanding access to a greater volume of data, which is more diverse in content. Data democratization is unveiling the need to develop new visualization tools, suitable for users with less expertise in data interpretation or a non-technical background. In this context, an easy-to-understand showcase of complex information [1] may be remarkably useful for policy-makers who are responsible for developing and implementing policies and regulations, as well as among the citizenship in terms of raising awareness and engaging the community.

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