Multiple Linear Regression Approach To Predicting Noise Pollution Levels and Their Spatial Patterns For The Tarkwa Mining Community Of Ghana
Journal Title: American journal of Engineering Research - Year 2018, Vol 7, Issue 7
Abstract
Predicting and preventing intraurban noise pollution in our communities are very challenging for urban planning, epidemiological studies and environmental management; especially in the developing world. Most existing noise-predicting models are limited in providing changes in noise levels during intraurban development and the corresponding noise pollution. In this study, noise levels were measured at 50 purposedesigned monitoring stations and then a land-use regression model was developed for the intraurban noise prediction applying the multiple linear regression (MLR) approach. The measured and the predicted noise levels were compared; and then further compared with noise estimates from a standard noise model, Lyons empirical model. The results from the developed MLR model did not show any significant differences in the patterns as compared with those of the Lyons Empirical model. The model performance indicators showed a standard deviation of 1.585, high correlation (r) of 0.98, R2 of 0.961 and RMSE of 1.569. The resulting maps showed a heterogeneous distribution of the noise pollution levels in the community. This confirms the usefulness of the method for assessing the spatial pattern of noise pollution in a community. Thus, making it a useful tool for urban planning, epidemiological studies and environmental management.
Authors and Affiliations
Baffoe1 , P. E. , Duker2 , A. A
Keywords
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