The criteria maps were overlaid based upon the assigned weight to derive final noise intensity in which the noise pollution prone areas of the District 14 are specified. The red spots on the map indicate highways and main streets with high noise pollution potentials. At final step, sensitivity analysis was performed to test how sensitive the output noise pollution map is against
variations in the weight of input maps. In this research, dynamic sensitivity analysis was used by expert choice software to detect sensitivity of the proposed model ageist different criteria. The obtained results indicated that ‘‘passages’’, compared to the other criteria, has the greatest impact on the model output.