title: Noise pollution mapping approach and accuracy on landscape scales.
abstract: Noise mapping allows the characterization of environmental variables, such as noise pollution or soundscape, depending on the task. Strategic noise mapping (as per Directive 2002/49/EC, 2002) is a tool intended for the assessment of noise pollution at the European level every five years. These maps are based on common methods and procedures intended for human exposure assessment in the European Union that could be also be adapted for assessing environmental noise pollution in natural parks. However, given the size of such areas, there could be an alternative approach to soundscape characterization rather than using human noise exposure procedures. It is possible to optimize the size of the mapping grid used for such work by taking into account the attributes of the area to be studied and the desired outcome. This would then optimize the mapping time and the cost. This type of optimization is important in noise assessment as well as in the study of other environmental variables. This study compares 15 models, using different grid sizes, to assess the accuracy of the noise mapping of the road traffic noise at a landscape scale, with respect to noise and landscape indicators. In a study area located in the Manzanares High River Basin Regional Park in Spain, different accuracy levels (Kappa index values from 0.725 to 0.987) were obtained depending on the terrain and noise source properties. The time taken for the calculations and the noise mapping accuracy results reveal the potential for setting the map resolution in line with decision-makers' criteria and budget considerations.
authors: Departamento de Proyectos y Planificación Rural, Universidad Politécnica de Madrid, EUIT Forestal, C. Ramiro de Maeztu s/n, 28040 Madrid, Spain. carlos.iglesias@upm.es
authors: Carlos
authors: C
authors: Iglesias Merchan
authors: Luis
authors: L
authors: Diaz-Balteiro
mesh_terms: D004784:Environmental Monitoring / Q000379:methods*; D040362:Geographic Information Systems; D008962:Models, Theoretical; D009622:Noise; D013030:Spain