Reliability of smart noise pollution map

Abstract The problem of noise pollution in Baghdad, the capital city Iraq, is getting worse every day as a result increased volume traffic. This presents considerable risk, particularly on main roads that connect densely populated neighborhoods such Al-Sadr City district with central capital. In order to inform decision-makers urban development and environmental policy about high values require remediation regulation, maps are produced. However, two fundamental problems generally faced creating more reliable map shortest possible time: excessive time requirements for measuring determining method creation. Therefore, role geographic information system (GIS) software producing evident due difficulty increasing spatial density measurements integrating them information. Hence, an appropriate interpolation required. this article, Moran’s I index was calculated assess autocorrelation measured traffic points. A comparison made between Smart Map Plugin ordinary kriging (OK) inverse distance weighting (IDW) deterministic determine best entrance exit City. were modeled using best-performing method. Furthermore, predictive raster data displayed context starting point reference identifying understanding levels selected study area. locations points determined organized homogeneous manner, where opposite each other, consecutive road 100 m. Traffic carried out at SVAN977 sound vibration analyzer. At measurement point, three (LAeq, Max, Min) obtained during peak times, 7–9 AM, 12–2 PM, 4–6 PM. QGIS used compare methods, its strength lying use plugins facilitate analysis, processing tools, algorithms. provided facilities choose semi-variogram OK root mean square error methods most suitable results indicated outperformed IDW method, distribution pattern homogeneity affect accuracy interpolation. Moreover, based analysis attributes Min), performance found be better than when value high.