Spatial Interpolation contribution to noise maps uncertainty

Abstract

Noise maps results are usually presented as contour graphs or isophone curves, which describe the sound levels as functions of spatial location. These maps are added to Geographic Information Systems (GIS), allowing sound level evaluation as a function of the continuous coordinates x and y, for a given height above ground. Although the outcome of the system is a continuous variable, the calculations that allow its evaluation are obtained in discrete points that form a calculation grid, which is created by the application of spatial sampling techniques. Using spatial interpolation tools, values are assigned to the locations in which measures or calculations have not been performed. The application of sampling and interpolation techniques (the type of grid, its density, the interpolation algorithms…) contributes to the uncertainty of the results. This paper describes a calculation method to quantify the uncertainty associated to the spatial sampling and interpolation process. We also propose a revision of the classical meaning of noise mapping uncertainty, taking into account the final application of the results.