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Senior Scientist or Principal Investigator
01 December 2018 - 30 August 2021
University Educator/Researcher
01 March 2018 - 01 December 2018
Post Doctoral Researcher
01 March 2017 - 01 March 2018
Statistical models that can generate a road-traffic noise map for a city or area where only elementary urban design factors are determined, and where no concrete urban morphology, including buildings and roads, is given, can provide basic but essential information for developing a quiet and sustainable city. Long-term cost-effective measures for a quiet urban area can be considered at early city planning stages by using the statistical road-traffic noise map. An artificial neural network (ANN) and an ordinary least squares (OLS) model were developed by utilizing data on urban form indicators, based on a 3D urban model and road-traffic noise levels from a normal noise map of city A (Gwangju). The developed ANN and OLS models were applied to city B (Cheongju), and the resultant statistical noise map of city B was compared to an existing normal road-traffic noise map of city B. The urban form indicators that showed multi-collinearity were excluded by the OLS model, and among the remaining urban forms, road-related urban form indicators such as traffic volume and road area density were found to be important variables to predict the road-traffic noise level and to design a quiet city. Comparisons of the statistical ANN and OLS noise maps with the normal noise map showed that the OLS model tends to under-estimate road-traffic noise levels, and the ANN model tends to over-estimate them.
Phillip Kim; Hunjae Ryu; Jong-June Jeon; Seo Chang. Statistical Road-Traffic Noise Mapping based on Elementary Urban Forms in Two Cities of South Korea. Sustainability 2021, 13, 2365 .
AMA StylePhillip Kim, Hunjae Ryu, Jong-June Jeon, Seo Chang. Statistical Road-Traffic Noise Mapping based on Elementary Urban Forms in Two Cities of South Korea. Sustainability. 2021; 13 (4):2365.
Chicago/Turabian StylePhillip Kim; Hunjae Ryu; Jong-June Jeon; Seo Chang. 2021. "Statistical Road-Traffic Noise Mapping based on Elementary Urban Forms in Two Cities of South Korea." Sustainability 13, no. 4: 2365.
Road-traffic noise is a critical factor that affects the life and health environments of urban inhabitants. In Korea, noise maps of cities created by commercial noise mapping software are used to manage road-traffic noise. This makes the management of noisy environments easy, but in the case of metropolitan cities, the creation of noise maps is time-consuming and costly. In this study, the relationship between road-traffic noise and urban form indicators (i.e., population, roads, buildings, and land use), showing the characteristics of a city, were analyzed to predict the road-traffic noise level using a statistical model. The road-traffic noise level predicted by the artificial neural network method was compared to that using the ordinary least squares method: The adjusted coefficient of determination (R2) of the former method was 0.5, while that of the latter model was 0.44. Furthermore, the floor space index was used as the urban form indicator, which has the largest effect on the road-traffic noise level.
Phillip Kim; Hunjae Ryu; Jong June Jeon; Seo Il Chang. Artificial Neural Network Model Development based on Road-traffic Noise and Urban Form Indicators. Transactions of the Korean Society for Noise and Vibration Engineering 2019, 29, 577 -583.
AMA StylePhillip Kim, Hunjae Ryu, Jong June Jeon, Seo Il Chang. Artificial Neural Network Model Development based on Road-traffic Noise and Urban Form Indicators. Transactions of the Korean Society for Noise and Vibration Engineering. 2019; 29 (5):577-583.
Chicago/Turabian StylePhillip Kim; Hunjae Ryu; Jong June Jeon; Seo Il Chang. 2019. "Artificial Neural Network Model Development based on Road-traffic Noise and Urban Form Indicators." Transactions of the Korean Society for Noise and Vibration Engineering 29, no. 5: 577-583.
Most of the national parks in South Korea are exposed to noise pollution caused by urban noise from adjacent cities. Especially, the road-traffic noise from the roads passing through or surrounding the parks has increased the exposure. In addition, the military and tele-communication facilities located in ecologically sensitive highlands are noise sources and affect nearby ecosystems. Therefore, it is important to preserve and maintain a comfortable sound environment to ensure the quality of the park trails for visitors and the habitat of animals and plants. The purpose of this study is to map a sound environment of national parks in South Korea and to classify sound grades of park trails. The park trails were categorized into 5 different groups based on acoustic factors such as noise level, loudness, sharpness, roughness, and tonality, and environmental factors such as land-use, ground coverage, vegetation type, and relative location which can be obtained from biotope map and GIS DB. This classification was based on factor analysis and cluster analysis. It is expected that this sound grade classification of the national park trails meets the right of visitors to know the sound environment, and that the managers of national parks can use it as a guideline to create a positive sound environment.
Hunjae Ryu; Kyong Seok Ki; Jisu Yoo; Seo I. Chang; Bo-Hyun Kim. Sound grade classification with sound mapping of national park trails in South Korea. The Journal of the Acoustical Society of America 2018, 144, 1931 -1931.
AMA StyleHunjae Ryu, Kyong Seok Ki, Jisu Yoo, Seo I. Chang, Bo-Hyun Kim. Sound grade classification with sound mapping of national park trails in South Korea. The Journal of the Acoustical Society of America. 2018; 144 (3):1931-1931.
Chicago/Turabian StyleHunjae Ryu; Kyong Seok Ki; Jisu Yoo; Seo I. Chang; Bo-Hyun Kim. 2018. "Sound grade classification with sound mapping of national park trails in South Korea." The Journal of the Acoustical Society of America 144, no. 3: 1931-1931.
Namsan is a 262 m high mountain located in the center of Seoul. Its easy accessibility and tourist attractions such as a cable car and a tall tower on the top allure native and foreign people. It functions as a park rather than a mountain and has a 7.5 km promenade around it with a moderate slope where even the old and the weak enjoy walking. Some parts of the promenade are surrounded by trees and flowing waters but other parts are influenced by shuttle buses, roundabout road-traffic and various machines etc. Noise maps for the sources were generated to find the spatial distribution of the noise over the mountain including the promenade. By observation along the promenade, natural sound including mainly birdsong and water streaming sound were identified and sound maps were generated. To collect individual responses from 4 acousticians and 6 non-acoustic people about an on-site questionnaire of the sound environment along the promenade, a total of 37 spots were selected apart from each other by approximately 200 m. The responses were used to generate soundscape maps. Separate and combined analyses of the three acoustic maps were performed to propose some measures to improve sound quality of the promenade.
Jisu Yoo; Kyong Seok Ki; Hunjae Ryu; Ji Suk Kim; Seo I. Chang. Soundscape approach integrating noise mapping in Namsan Promenade. The Journal of the Acoustical Society of America 2018, 144, 1931 -1931.
AMA StyleJisu Yoo, Kyong Seok Ki, Hunjae Ryu, Ji Suk Kim, Seo I. Chang. Soundscape approach integrating noise mapping in Namsan Promenade. The Journal of the Acoustical Society of America. 2018; 144 (3):1931-1931.
Chicago/Turabian StyleJisu Yoo; Kyong Seok Ki; Hunjae Ryu; Ji Suk Kim; Seo I. Chang. 2018. "Soundscape approach integrating noise mapping in Namsan Promenade." The Journal of the Acoustical Society of America 144, no. 3: 1931-1931.
The purpose of this study is to present a statistical model which can predict the noise level of road-traffic in urban area. A spatial statistical model which can take into account spatial dependency on geographically neighboring areas is constructed from a noise map of a city in South Korea. A system of 250m×250m grid cells is placed on the city of Cheongju, South Korea, and the noise level and urban form indicators are averaged over each cell. The population-weighted mean of the noise level is subsequently regressed on the average urban form by adopting the spatial autoregressive model (SAR) and the spatial error model (SEM), as well as an ordinary least squares (OLS) model. Direct and indirect impacts are analyzed for a valid interpretation of the spatial statistical models. Factors such as GSI, FSI, traffic volume, traffic speed, road area density, and the fraction of industrial area turn out to have significant impacts on the noise level
Hunjae Ryu; In Kwon Park; Bum Seok Chun; Seo Il Chang. Spatial statistical analysis of the effects of urban form indicators on road-traffic noise exposure of a city in South Korea. Applied Acoustics 2017, 115, 93 -100.
AMA StyleHunjae Ryu, In Kwon Park, Bum Seok Chun, Seo Il Chang. Spatial statistical analysis of the effects of urban form indicators on road-traffic noise exposure of a city in South Korea. Applied Acoustics. 2017; 115 ():93-100.
Chicago/Turabian StyleHunjae Ryu; In Kwon Park; Bum Seok Chun; Seo Il Chang. 2017. "Spatial statistical analysis of the effects of urban form indicators on road-traffic noise exposure of a city in South Korea." Applied Acoustics 115, no. : 93-100.
Hunjae Ryu; Bum Seok Chun; In Kwon Park; Seo Il Chang. Road Traffic Noise Simulation for Small-scale Urban Form Alteration Using Spatial Statistical Model. Transactions of the Korean Society for Noise and Vibration Engineering 2015, 25, 284 -290.
AMA StyleHunjae Ryu, Bum Seok Chun, In Kwon Park, Seo Il Chang. Road Traffic Noise Simulation for Small-scale Urban Form Alteration Using Spatial Statistical Model. Transactions of the Korean Society for Noise and Vibration Engineering. 2015; 25 (4):284-290.
Chicago/Turabian StyleHunjae Ryu; Bum Seok Chun; In Kwon Park; Seo Il Chang. 2015. "Road Traffic Noise Simulation for Small-scale Urban Form Alteration Using Spatial Statistical Model." Transactions of the Korean Society for Noise and Vibration Engineering 25, no. 4: 284-290.
Hunjae Ryu; In Kwon Park; Seo Il Chang; Bum Seok Chun. The Spatial Statistical Relationships between Road-traffic Noise and Urban Components Including Population, Building, Road-traffic and Land-use. Transactions of the Korean Society for Noise and Vibration Engineering 2014, 24, 348 -356.
AMA StyleHunjae Ryu, In Kwon Park, Seo Il Chang, Bum Seok Chun. The Spatial Statistical Relationships between Road-traffic Noise and Urban Components Including Population, Building, Road-traffic and Land-use. Transactions of the Korean Society for Noise and Vibration Engineering. 2014; 24 (4):348-356.
Chicago/Turabian StyleHunjae Ryu; In Kwon Park; Seo Il Chang; Bum Seok Chun. 2014. "The Spatial Statistical Relationships between Road-traffic Noise and Urban Components Including Population, Building, Road-traffic and Land-use." Transactions of the Korean Society for Noise and Vibration Engineering 24, no. 4: 348-356.
Hun Jae Ryu; Joon Hee Ko; Seo Il Chang; Byung Chan Lee. A Study on Sampling Techniques to Assure the Representativeness of Short-term Equivalent Noise Level. Transactions of the Korean Society for Noise and Vibration Engineering 2012, 22, 1213 -1219.
AMA StyleHun Jae Ryu, Joon Hee Ko, Seo Il Chang, Byung Chan Lee. A Study on Sampling Techniques to Assure the Representativeness of Short-term Equivalent Noise Level. Transactions of the Korean Society for Noise and Vibration Engineering. 2012; 22 (12):1213-1219.
Chicago/Turabian StyleHun Jae Ryu; Joon Hee Ko; Seo Il Chang; Byung Chan Lee. 2012. "A Study on Sampling Techniques to Assure the Representativeness of Short-term Equivalent Noise Level." Transactions of the Korean Society for Noise and Vibration Engineering 22, no. 12: 1213-1219.