Urban soundscape maps modelled with geo-referenced data

Abstract

Abstract:The noise maps that are currently proposed as part of the EU Directive are based on the calculation of the Lday, Levening and Lnight. These levels are calculated from emission and propagation models that are expensive in time. These noise maps are criticized for being distant from the perception of city users. Thus, calculation models of sound quality have been proposed, for being closer to city users' perception. They are either based on perceptual variables, or on acoustic measurements, or on georeferenced data, the latter being often already integrated into the Geographic Information Systems of most French metropolises. Considering 89 Parisian situations, this article proposes to compare the sound quality really perceived, with those from models using geo-referenced data. It also looks at the modeling of perceptual variables that influence the sound quality, such as perceived loudness, the perceived time ratio of traffic, voices and birds. To do this, such geo-referenced data as road traffic, the presence of gardens, food shops, restaurants, bars, schools, markets, are transformed into core densities. Being quick and easy to calculate, these densities predict effectively sound quality in the urban public space. Visualization of urban soundscape maps are proposed in this paper.

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

“…As [31] mention, one possible reason is the absence of objective data to generate such maps compared to noise maps. Previous works in this field refer to the spatial representation of loudness and soundscape quality [26,32], or the soundscape ecology in parks [27] and rural areas [38]. As expected, the majority of these studies are disconnected from the planning process or present the potential to be integrated in this field.…”

“…In particular, previous studies for mapping the variability of sound sources [14,30,31] and use various geostatistical and non-geostatistical mapping techniques. A few studies have dealt with the representation of psychoacoustic parameters [26,32] such as loudness, sharpness or pleasantness in the urban environments. However, very few studies [24,33] have dealt with the overall assessment of the sound environment as a holistic process and in cooperation with the local planning authorities or City Councils.…”

“…Nonetheless, for ur- ban environments a categorization that can be more representative is closer to the taxonomy of human, natural and technological sources previously used in other studies as well [32,41,42].…”

Road traffic sound level estimation from realistic urban sound mixtures by Non-negative Matrix Factorization

“…Consequently, in the case where the location or the type of sound environments the sensors are monitoring cannot 670 be identified (for instance within a mobile measurement framework), TI-NMF appears to be the most appropriate method. If the sound environment can be identified through a prior analysis, or based on positioning data [57,58], it should be possible to adapt the estimation pro-675 cedure by selecting the most efficient approach in order to further reduce the error in the estimated road traffic sound levels.…”

Estimation of the Perceived Time of Presence of Sources in Urban Acoustic Environments Using Deep Learning Techniques

“…The dominance is built on coupled notions of time and volume, while the time of presence is more easily linked to the physical activity of sources. In a more holistic approach of soundscape quality evaluation, the time of presence should thus be easier to identify from acoustic monitoring measurements and would provide more complete information on the content of polyphonic urban environments [26].…”