A Green Soundscape Index (GSI): The potential of assessing the perceived balance between natural sound and traffic noise.

Urban soundscapes are dynamic and complex multivariable environmental systems. Soundscapes can be organized into three main entities containing the multiple variables: Experienced Environment (EE), Acoustic Environment (AE), and Extra-Acoustic Environment (XE). This work applies a multidimensional and synchronic data-collecting methodology at eight urban environments in the city of Córdoba, Argentina. The EE was assessed by means of surveys, the AE by acoustic measurements and audio recordings, and the XE by photos, video, and complementary sources. In total, 39 measurement locations were considered, where data corresponding to 61 AE and 203 EE were collected. Multivariate analysis and GIS techniques were used for data processing. The types of sound sources perceived, and their extents make up part of the collected variables that belong to the EE, i.e. traffic, people, natural sounds, and others. Sources explaining most of the variance were traffic noise and natural sounds. Thus, a Green Soundscape Index (GSI) is defined here as the ratio of the perceived extents of natural sounds to traffic noise. Collected data were divided into three ranges according to GSI value: 1) perceptual predominance of traffic noise, 2) balanced perception, and 3) perceptual predominance of natural sounds. For each group, three additional variables from the EE and three from the AE were applied, which reported significant differences, especially between ranges 1 and 2 with 3. These results confirm the key role of perceiving natural sounds in a town environment and also support the proposal of a GSI as a valuable indicator to classify urban soundscapes. In addition, the collected GSI-related data significantly helps to assess the overall soundscape. It is noted that this proposed simple perceptual index not only allows one to assess and classify urban soundscapes but also contributes greatly toward a technique for separating environmental sound sources.

A comprehensive methodology for the multidimensional and synchronic data collecting in soundscape.

The soundscape paradigm is comprised of complex living systems where individuals interact moment-by-moment among one another and with the physical environment. The real environments provide promising conditions to reveal deep soundscape behavior, including the multiple components involved and their interrelations as a whole. However, measuring and analyzing the numerous simultaneous variables of soundscape represents a challenge that is not completely understood. This work proposes and applies a comprehensive methodology for multidimensional and synchronic data collection in soundscape. The soundscape variables were organized into three main entities: experienced environment, acoustic environment, and extra-acoustic environment, containing, in turn, subgroups of variables called components. The variables contained in these components were acquired through synchronic field techniques that include surveys, acoustic measurements, audio recordings, photography, and video. The proposed methodology was tested, optimized, and applied in diverse open environments, including squares, parks, fountains, university campuses, streets, and pedestrian areas. The systematization of this comprehensive methodology provides a framework for soundscape research, a support for urban and environment management, and a preliminary procedure for standardization in soundscape data collecting.