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Acoustic, Visual and Spatial Indicators for the Description of the Soundscape of Waterfront Areas with and without Road Traffic Flow

View Article: PubMed Central - PubMed

ABSTRACT

High flows of road traffic noise in urban agglomerations can negatively affect the livability of squares and parks located at the neighborhood, district and city levels, therefore pushing anyone who wants to enjoy calmer, quieter areas to move to non-urban parks. Due to the distances between these areas, it is not possible to go as regularly as would be necessary to satisfy any needs. Even if cities are densely populated, the presence of a sea or riverfront offers the possibility of large restorative places, or at least with potential features for being the natural core of an urban nucleus after a renewal intervention. This study evaluates the soundscape of the Naples waterfront, presenting an overview of the most significant visual, acoustic and spatial factors related to the pedestrian areas, as well as areas open to road traffic and others where the road traffic is limited. The factors were chosen with feature selection methods and artificial neural networks. The results show how certain factors, such as the perimeter between the water and promenade, the visibility of the sea or the density of green areas, can affect the perception of the soundscape quality in the areas with road traffic. In the pedestrian areas, acoustic factors, such as loudness or the A-weighted sound level exceeded for 10% of the measurement duration (LA10), influence the perceived quality of the soundscape.

No MeSH data available.


Inferred mRMR network topology of the soundscape quality (SQQ) for the pedestrian areas. The variables selected were “percentage of generic buildings in the aerial photograph within a distance of 100 m” (CP_Building_100), spatial metric “proximity” calculated for the land use “food services” (PROX_MN_Food), spatial metric “split” calculated for the land use “singular buildings” (SPLIT_Singular), sound pressure level exceeded 50% of time (LA50), A-weighted equivalent sound pressure level (LAeq), roughness (R), loudness(N5) and sound pressure level exceeded 10% of time.
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ijerph-13-00934-f010: Inferred mRMR network topology of the soundscape quality (SQQ) for the pedestrian areas. The variables selected were “percentage of generic buildings in the aerial photograph within a distance of 100 m” (CP_Building_100), spatial metric “proximity” calculated for the land use “food services” (PROX_MN_Food), spatial metric “split” calculated for the land use “singular buildings” (SPLIT_Singular), sound pressure level exceeded 50% of time (LA50), A-weighted equivalent sound pressure level (LAeq), roughness (R), loudness(N5) and sound pressure level exceeded 10% of time.

Mentions: Figure 10 shows the variables selected by the mRMR method for the pedestrian areas. The mean concordance index calculated from the variables selected in the pedestrian areas is C = 0.56 (C > 0.5). Therefore, the set of variables selected can be accepted.


Acoustic, Visual and Spatial Indicators for the Description of the Soundscape of Waterfront Areas with and without Road Traffic Flow
Inferred mRMR network topology of the soundscape quality (SQQ) for the pedestrian areas. The variables selected were “percentage of generic buildings in the aerial photograph within a distance of 100 m” (CP_Building_100), spatial metric “proximity” calculated for the land use “food services” (PROX_MN_Food), spatial metric “split” calculated for the land use “singular buildings” (SPLIT_Singular), sound pressure level exceeded 50% of time (LA50), A-weighted equivalent sound pressure level (LAeq), roughness (R), loudness(N5) and sound pressure level exceeded 10% of time.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036766&req=5

ijerph-13-00934-f010: Inferred mRMR network topology of the soundscape quality (SQQ) for the pedestrian areas. The variables selected were “percentage of generic buildings in the aerial photograph within a distance of 100 m” (CP_Building_100), spatial metric “proximity” calculated for the land use “food services” (PROX_MN_Food), spatial metric “split” calculated for the land use “singular buildings” (SPLIT_Singular), sound pressure level exceeded 50% of time (LA50), A-weighted equivalent sound pressure level (LAeq), roughness (R), loudness(N5) and sound pressure level exceeded 10% of time.
Mentions: Figure 10 shows the variables selected by the mRMR method for the pedestrian areas. The mean concordance index calculated from the variables selected in the pedestrian areas is C = 0.56 (C > 0.5). Therefore, the set of variables selected can be accepted.

View Article: PubMed Central - PubMed

ABSTRACT

High flows of road traffic noise in urban agglomerations can negatively affect the livability of squares and parks located at the neighborhood, district and city levels, therefore pushing anyone who wants to enjoy calmer, quieter areas to move to non-urban parks. Due to the distances between these areas, it is not possible to go as regularly as would be necessary to satisfy any needs. Even if cities are densely populated, the presence of a sea or riverfront offers the possibility of large restorative places, or at least with potential features for being the natural core of an urban nucleus after a renewal intervention. This study evaluates the soundscape of the Naples waterfront, presenting an overview of the most significant visual, acoustic and spatial factors related to the pedestrian areas, as well as areas open to road traffic and others where the road traffic is limited. The factors were chosen with feature selection methods and artificial neural networks. The results show how certain factors, such as the perimeter between the water and promenade, the visibility of the sea or the density of green areas, can affect the perception of the soundscape quality in the areas with road traffic. In the pedestrian areas, acoustic factors, such as loudness or the A-weighted sound level exceeded for 10% of the measurement duration (LA10), influence the perceived quality of the soundscape.

No MeSH data available.