# Towards Urban Sustainability: Developing Noise Prediction Model in an Informal Setting
## 3 Results  
Table 3 shows the descriptive statistics of the noise levels by land use types. The mean noise level of the area is generally high and greater than permissible level for dwelling places [11]. The mean noise level recorded was highest in high density residential and commercial areas and lowest in educational areas. The lowest mean value recorded in the educational area is be attributed to higher tree density in the area as trees is known to absorb a lot of noise. The highest noise level areas were high density residential, commercial, and industrial clusters. Noise pollution levels were regressed with the parameters to see how they (the variables used) explained noise level. The result of spatial regression analysis is presented in Table 4 which indicates that relationships between noise level and determinants of noise pollution is very significant for mean daily, morning, afternoon, and evening because for each of the four the \(p\)-values were less than 0.05. However, the individuals \(p\)-values show that population density is the most significant factor by having \(p=0.01\) and 0.033 \begin{table}
\begin{tabular}{c c} \hline \hline
**Land Use Type** & **Code** \\ \hline Administrative/Open & 1 \\ Educational & 2 \\ Low Density Res. & 3 \\ Medium Density Res. & 4 \\ High Density Res. & 5 \\ Industrial & 6 \\ Commercial & 7 \\
**Distance from main road (km)** & **Code** \\ \(<\)0.25 & 0.70 \\
0.025 to 0.5 & 0.20 \\
0.6–1.0 & 0.050 \\
1.0–2.0 & 0.045 \\
2.0–4.0 & 0.005 \\ \(>\)4.0 & 0.000 \\
**Population Density** & **Code** \\
0.0–2500 & 0.10 \\
2501–6262 & 0.20 \\
6263–20,666 & 0.30 \\
20,667–40,705 & 0.40 \\
40,706–79,846 & 0.50 \\
**Land Cover** & **NDVI value** \\
**Traffic Volume** & **Absolute Volume data** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Variable Used and Their Ranking for the Modelling. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Land Use** & **Mean** & **Stdv** & **N** & **CV (\%)** &
\begin{tabular}{c} **Maximum Permissible Sound** \\ **Level by WHO/NESREA** \\ \end{tabular} \\ \hline Commercial & 65.5 & 11.20 & 750,699 & 17.1 & 55 \\ Educational & 51.28 & 7.33 & 79,180 & 14.3 & 45 \\ Industrial & 64.66 & 12.00 & 353,881 & 18.6 & 60 \\ Institutional & 63.18 & 12.95 & 75,936 & 20.5 & 45 \\ High Density & 66.99 & 14.42 & 599,992 & 21.5 & 50 \\ Residential & 58.07 & 12.52 & 161,115 & 21.6 & 50 \\ Medium Density & 58.01 & 13.22 & 766,972 & 22.8 & 50 \\ Residential & 60.07 & 11.77 & 143,871 & 19.6 & 50 \\ Recreational & 63.51 & 12.78 & 48,752 & 20.1 & 45 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: General Distribution of Noise Land use type in dB(A). for afternoon and evening, respectively. Land cover, which has to do with greening and tree cover, is equally significant at 95% confidence level for morning and afternoon; and is probably significant in evening. A significant relationship was found between noise level and the set of explanatory variables given a multiple correlation coefficient (multiple \(R\)) of 48.7% and coefficient of determination (\(R^{2}\)) of 23.7% (Table 5). This indicates that the set of variables in the equation can predict approximately 49% of the noise level (dependent variable) assuming that intercepts were included in the equation and can explain up to 24% of the noise level variation assuming noise variables relation to be non-linear. The adjusted \(R^{2}\) is said to clear the issues that arise from addition of a new variable. Any addition of an independent variable will have a positive effect on the coefficient of determination. Individually, the variables differ in their contribution to noise level. The most significant variables are land use type, traffic volume, and land cover (Table 6). The model substitute is:  
\[NL=64.061+\big{[}(-19.599\times\text{Land cover})+)-0.259\times\text{Distance to road})+\]  
\[(4.017\times\text{Population density})+(3.210\times\text{ Housing subdivision})+\]  
\[(1.652\times Land\text{ }use)+(-0.002\times\text{Traffic volume})\big{]}\pm 4.58\]