@article{ART003354092},
author={Kyoungmin Kim and Chang Seo Il},
title={Statistical Environmental Noise Mapping Based on Measured Noise Data},
journal={Journal of Environmental Impact Assessment},
issn={1225-7184},
year={2026},
volume={35},
number={3},
pages={245-255}
TY - JOUR
AU - Kyoungmin Kim
AU - Chang Seo Il
TI - Statistical Environmental Noise Mapping Based on Measured Noise Data
JO - Journal of Environmental Impact Assessment
PY - 2026
VL - 35
IS - 3
PB - Korean Society Of Environmental Impact Assessment
SP - 245
EP - 255
SN - 1225-7184
AB - This study aims to develop a machine learning-based statistical environmental noise prediction model for predicting and monitoring the spatial variability of noise exposure. To this end, measured noise data collected from the S-DoT monitoring network in Seoul were combined with surrounding urban components, including traffic, buildings, land, vegetation, and population, aggregated across multiple buffer radius. The developed model was then applied to the entire area of Seoul to conduct statistical environmental noise mapping and to propose its potential applications.
The results showed that the Random Forest nonlinear regression model achieved the best predictive performance when urban component variables within a 40m buffer radius were used for 973 S-DoT monitoring sites. Based on 5-fold cross-validation, approximately 70% of the predicted noise levels were within ±5dB of the measured noise levels. In addition, SHAP analysis identified building density, represented by the Ground Space Index (GSI), and land cover variables, particularly residential and road land cover, as the most influential urban components affecting predicted noise levels. This study demonstrates the potential for developing statistical environmental noise maps using noise monitoring network data. The results can be used to identify areas requiring urban noise monitoring and to support the prioritization of noise reduction and management measures.
KW - S-DoT;Measured Noise Data;Statistical Noise Map;Random Forest;SHAP;Environmental Noise
DO -
UR -
ER -
Kyoungmin Kim and Chang Seo Il. (2026). Statistical Environmental Noise Mapping Based on Measured Noise Data. Journal of Environmental Impact Assessment, 35(3), 245-255.
Kyoungmin Kim and Chang Seo Il. 2026, "Statistical Environmental Noise Mapping Based on Measured Noise Data", Journal of Environmental Impact Assessment, vol.35, no.3 pp.245-255.
Kyoungmin Kim, Chang Seo Il "Statistical Environmental Noise Mapping Based on Measured Noise Data" Journal of Environmental Impact Assessment 35.3 pp.245-255 (2026) : 245.
Kyoungmin Kim, Chang Seo Il. Statistical Environmental Noise Mapping Based on Measured Noise Data. 2026; 35(3), 245-255.
Kyoungmin Kim and Chang Seo Il. "Statistical Environmental Noise Mapping Based on Measured Noise Data" Journal of Environmental Impact Assessment 35, no.3 (2026) : 245-255.
Kyoungmin Kim; Chang Seo Il. Statistical Environmental Noise Mapping Based on Measured Noise Data. Journal of Environmental Impact Assessment, 35(3), 245-255.
Kyoungmin Kim; Chang Seo Il. Statistical Environmental Noise Mapping Based on Measured Noise Data. Journal of Environmental Impact Assessment. 2026; 35(3) 245-255.
Kyoungmin Kim, Chang Seo Il. Statistical Environmental Noise Mapping Based on Measured Noise Data. 2026; 35(3), 245-255.
Kyoungmin Kim and Chang Seo Il. "Statistical Environmental Noise Mapping Based on Measured Noise Data" Journal of Environmental Impact Assessment 35, no.3 (2026) : 245-255.
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