A university campus is a complex environment, as it comprises many areas, each with distinctive acoustic characteristics. There are zones where a quiet environment is crucial for work and study, parking lots and internal road networks, as well as vibrant spaces where students and personnel stay during leisure time. Thus, university campuses clearly offer a remarkable opportunity for the evaluation of soundscape analysis tools and the exploration of new methodologies for assessing and mapping soundscapes. In this work, the Fisciano campus of the University of Salerno (Italy) has been depicted as a case study. Specifically, the outcomes of a soundwalk conducted following ISO/TS 12913 standards will be presented, together with data gathered through crowd-sourcing during NoiseCapture parties. The data from NoiseCapture parties have been used to test and validate an innovative methodology based on an inverse distance weighting interpolation to produce soundscapes' attributes maps, using the mean pleasantness as an example and exploring the relative influence of the maximum distance used to characterize an homogeneous sound environment to build the maps themselves. The results will offer valuable insights into the proposed methodology.
Soundscape maps of pleasantness in a university campus by crowd-sourced measurements interpolation
Mascolo A.;Rossi D.;Grimaldi M.;Guarnaccia C.
2024-01-01
Abstract
A university campus is a complex environment, as it comprises many areas, each with distinctive acoustic characteristics. There are zones where a quiet environment is crucial for work and study, parking lots and internal road networks, as well as vibrant spaces where students and personnel stay during leisure time. Thus, university campuses clearly offer a remarkable opportunity for the evaluation of soundscape analysis tools and the exploration of new methodologies for assessing and mapping soundscapes. In this work, the Fisciano campus of the University of Salerno (Italy) has been depicted as a case study. Specifically, the outcomes of a soundwalk conducted following ISO/TS 12913 standards will be presented, together with data gathered through crowd-sourcing during NoiseCapture parties. The data from NoiseCapture parties have been used to test and validate an innovative methodology based on an inverse distance weighting interpolation to produce soundscapes' attributes maps, using the mean pleasantness as an example and exploring the relative influence of the maximum distance used to characterize an homogeneous sound environment to build the maps themselves. The results will offer valuable insights into the proposed methodology.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
