Cao, X;
Meng, Q;
Kang, J;
(2020)
Red Soundscape Index (RSI): An index with the potential to assess soundscape quality.
In:
INTER-NOISE and NOISE-CON Congress and Conference Proceedings.
(pp. pp. 3527-3539).
Institute of Noise Control Engineering
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Abstract
It is not enough to define urban soundscape just using the green soundscape index (GSI), which is the ratio of the perception of natural sounds to the perception of traffic noises. Therefore, in the present study, red soundscape index (RSI), defined as the ratio of perception of natural sounds to perception of human sounds, was introduced. The data for calculating RSI were collected from sound environment measurements and a questionnaire-based survey in seven urban parks in Harbin city, China. The results revealed the following: (1) RSI was correlated with the overall soundscape quality; (2) RSI was correlated with the maximum and minimum instantaneous sound pressure levels and with equivalent sound pressure levels; and (3) The urban sound environment as well as sound quality can be classified by RSI. It was confirmed that RSI could be used as a supplement to GSI in urban soundscape planning.
| Type: | Proceedings paper |
|---|---|
| Title: | Red Soundscape Index (RSI): An index with the potential to assess soundscape quality |
| Event: | International Congress on Noise Control Engineering, INTER-NOISE 2020 |
| ISBN-13: | 9788994021362 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://www.ingentaconnect.com/content/ince/incecp... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10123422 |
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