Methods 

In order to obtain the results needed to do the study, both QGIS and GeoDa softwares were used following the respective "QGIS User Guide"\cite{nokey_13188} and "GeoDa User Guide" \cite{nokey_9ebde}
The data needed for the analysis was obtained from four RVB satellite images encompassing the municipality of Vernier, two raster layers with the sound levels around the municipality of interest, and one vector layer defining the boundaries of Vernier. All this content was imported to QGIS. A Virtual Raster Catalogue was then created to merge the four RVB images. Using the style properties of the catalog, both Red and Blue bands were removed so that only the green band remained visible. This allowed to keep only the reflectance information of the area, which is important to detect the vegetation. 
After that a 50x50m grid was created with its extent around the limits of the municipality of Vernier. With this grid all information contained in the green band raster and the day and night rasters was gathered in one single attribute table: levels of sound during day and night and of greenness in the area selected. This task was performed using the zonal statistical tool. 
Then, the main tool of analysis was created, namely selecting only the cells confined within the boundaries of the municipality to extract precisely the information of interest. This operation was made possible with the "Spatial Query" tool available in QGIS.
In GeoDa this finer grid was exploited to extract both box maps and scatter plots. Those allow to establish comparisons between the different values of greenness and sound. They are also of interest to verify the spatial correlation between the levels of vegetation and noise, which allow for the verification of the hypothesis.
Anselin, L. GeoDa™ 0.9 User’s Guide. 2003.

Results 

The average values of each dataset for the commune of Vernier are shown in table \ref{350700}. There is quite a high range of values for the vegetation indicator, while the sound values for both day and night vary less. The data obtained during nighttime shows lower values as during daytime.