In order to minimize the duration of acoustic measurements and to characterize homogeneous areas from a temporal point of view, a series of six location measurements was carried out continuously during three months in Paris. Around fifty thousand samples of 5-min, 10-min, 15-min, 20-min, 30-min, and 1-h duration measurements were extracted for each location. Each sample is characterized by eleven energy indicators and ten event descriptors. In this paper, analysis of a crossroad location is detailed. Through hierarchical ascendant classification and artificial neural networks classification, it is shown that four homogeneous periods can be detected: two during the night, one during the day, and one transition corresponding either to the awakening or to the moment when the city falls asleep. 10-min measurements are necessary to discriminate these time periods at the crossroad location. At the end of the paper, a comparison with the other locations shows that minimum duration states in between 10 and 20 min. The homogeneous periods are connected to the human activities and depend on the location. Energy indicators such as LAeq, LA10, or LA90 and event indicators are necessary to characterize the different clusters.