Measurement network for urban noise assessment: Comparison of mobile measurements and spatial interpolation approaches

Abstract

This paper investigates the relevance of different interpolation techniques to improve the spatial resolution of urban noise maps, in complement to measurements achieved at fixed stations. Interpolation techniques based on mobile measurements are compared to usual spatial interpolations techniques, namely Inverse Distance Weighting and Kriging. The analyses rely on a measurement campaign, which consisted of nearly 8 hours of georeferenced mobile noise measurements performed at random moments of the day, conducted simultaneously with continuous measurements collected at five fixed stations located on the inner city of Gent, Belgium.Firstly, a procedure is proposed to build a noise map with a high spatial resolution (one point every 5m). The procedure relies on both mobile and fixed measurements: the mobile 2 measurements are used to capture spatial variations on the network, and the measurements at fixed stations are used to capture the temporal variations. The map produced is then used as reference to compare the interpolation techniques based on a significantly more sparse measurement set.The spatial interpolation techniques tested fail in predicting accurately the noise level variations within streets. The explanation given is that they do not offer a sufficient covering of the network, and assume spatial variations which are not coherent with traffic dynamics or street configurations. Inversely, mobile measurements cover the entire network. As a result, they allow a more accurate prediction of noise levels even if very short samples are used, provided that the procedure used to estimate noise levels includes a spatial aggregation, which aims at smoothing the high spatial variations inevitable with short samples. Moreover, mobile measurements can advantageously be used to optimize, through a genetic algorithm, the locations where to install fixed stations, promising an efficient noise monitoring at reduced operational costs.

Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities

“…The most crucial include the size of the area, the number of points measured as well as their spatial distribution and the way of selecting them (a priori, on site). Although the use of spatial interpolation methods has not been always successful in the prediction of noise levels [25] it has been shown that they can be useful for mapping soundscape quality or particular perceptual attributes in the urban context [24,26]. Definitely the proper soundscape data collection method should be applied according to the scope of the study.…”

“…What can be taken for sure is that almost in all cases different interpolation methods will produce different results [23]. Since there are no hard and fast rules for soundscape mapping, previous studies have used several interpolation algorithms such as: Kriging [24,25] Inverse Distance Weighted (IDW) [26] or Spline [27].…”

Noise mapping based on participative measurements

“…The main advantages of mobile measurements for the purpose of refining the spatial resolution of noise maps are discussed in [22]. Compared to fixed stations coupled with classical interpolation methods (e.g.…”

“…A finer spatial granularity can be obtained experimentally through mobile measurements [22]. In-transit measurements consists in recording noise levels along a journey and involve two main devices: an acoustic sensor (a sonometer usually) and a global positioning system (GPS).…”

Seasonal Change and Spatial Distribution of Traffic Noise in Seferihisar, Turkey

“…Some studies compared the methods which are used to prepare noise maps. These studies focused on the advantages and disadvantages of above mentioned methods with the help of sample implementations (Can et al, 2014;Harman et al, 2016). In the literature, there are various studies that special techniques applications of GIS have been employed to map, monitor and model noise (Akintuyi et al, 2014).…”