Discussion

The low correlation showed in the scatterplot is mainly due to the repartition of the observation. They are gathered around a middle ground and this clustering influences heavily the regression line. The slightly positive relationship however, is a good sign that we are heading in the same direction. It shows that we are in a situation where there is a trend suggesting that there is a relationship between our variables, but the scatter plot shows correlation too weak to assert it definitively.
The co-location map, however, shows a really clear separation of the quantiles between the different parts of the city. The eastern part, mainly composed of smaller, less dense villages is clearly a different entity than the densely populated and built center. The human activity, which is the underlying indicator that is measured through the noise follows this trend well. It is interesting to note the pattern of how the red squares are distributed. We can see that they often follow straight lines, indicating big roads with a lot of traffic. The roads tend to heat up and radiate a lot due to the flow of vehicles and this is shown in the data.
The data also shows that day noise is a good enough indicator of the human activity. As expected, areas with high density of population, businesses, traffic and buildings are mostly clustered at the center of the town, where the noise during the day is the highest. That leads to the conclusion that, while activity itself is hard to quantify, the noise it produces can be a good indicator of how it is laid out in an urban area. 

Conclusion