URBAN ICONIC SOUNDSCAPE EVALUATION BASED ON MEMORY - Dwi Tassia, Ranti
Open public space plays an important role in urban community activities, as a place of recreation and gathering which generally reflects the value of art, culture, and history of the city. Activities in the environment give rise to a diversity of sound sources that are not always considered disturbing, instead, they can represent the uniqueness of a location or region. For this reason, the approach in evaluating the sonic environment of a location is not only based on noise measurement but also involves human factors to understand the acoustic environment. An approach that involve human perception, sonic environment, sound source, and its context known as soundscape. One method to evaluate the soundscape is a memory-based. Generally this method is evaluated using an interview protocol to collect soundcape data and applied to a familiar environment. However, this interview protocol has limitations in generalizing perceptions from respondents, because it is vulnerable to individual interpretations of researchers. Therefore, this study aims to determine the extent to which memory-based methods can be applied to collect soundscape data in iconic urban environments. This method was evaluated using an online questionnaire consist of open questions and rating of semantic scales which compared to in-situ experiment. In addition, experiments in the laboratory through a soundscape composition are applied to collect data. This provides benefits for wider data distribution without having to be in the actual environment. The results of the evaluation were analyzed by applying verbal analysis (description of word occurance and semantic categorization) and semantic scale analysis (soundscape dimensions, semantic clustering, and semantic scale assessment), and analysis based on the soundscape composition method consisting of actual composition and preference composition with the help of an acoustic simulator. Analysis of the soundscape composition in the form of sound object selection, sound level, and perceptual assessment between the composition of the actual conditions and preferences of the sonic environment. In addition, a model to predict soundscape perceptions related to the dimensions of comfort, dynamics, and communication will be applied using logistic regression analysis.