## 3 Characterizing Public Transportation System
### Results and Discussion
#### 3.3.4 Spatiotemporal Analysis of Transactions  
Spatial and temporal dimensions of smartcard transactions can be combined to gain insights that might not arise when studying each dimension independently. Figure 8 shows an aggregated visualization of the spatiotemporal distribution of sales in Montevideo. Each transaction occurring at a given pixel in the image is categorized according to its time stamp. Then, the color of the pixel is set considering the amount of transactions on each category. The color mapping, which is detailed in the visualization, corresponds to: red (0:00), yellow (4:00), green (8:00), cyan (12:00), blue (16:00), and purple (20:00). An interactive version of the visualization is available at www.fing.edu.uy/~renzom/msc.  
Figure 7: Histogram of sales with smart cards at different times of the day.  
The city center has most transactions taking place between noon and the afternoon, which might be explained by the fact that many offices and public entities are located in this area. Consequently, most transactions correspond to people commuting back to their homes by the end of the office-hours. A clear difference can also be noticed between areas near the coast and areas farther away. The majority of transactions in areas farther away from the coast occur earlier in the day than those near the coast. This might be explained by people commuting early in the day from these areas to workplaces located closer to the city center. It is worth noting that, as outlined in Section 3.1, areas farther away from the coast are usually more vulnerable from a socioeconomic point of view.  
Figures 9 and 10 show choropleth maps of the number of transactions occurring in each census tract in the morning and evening, respectively.  
In the morning, those areas farther away from the city center and the coastline have higher smart card transaction activity early (6:00-7:00) than those near the coast. Transaction activity in the  
Figure 8: Spatiotemporal distribution of trips in Montevideo.  
Figure 9: Choropleth map of smart card transactions in the morning.  
city center and near the coastline intensities an hour later. Between 7:00 and 8:00 large amounts of transactions occur in most areas of Montevideo. A few census tracts show a specially large number of transactions. These areas correspond to the location of bus terminals, where several bus lines converge and many transfers between bus lines occur.  
In the evening, a large number of transactions occur in the city center. This is explained by people returning to their homes from workplaces in the city center at the end of office hours (18:00-19:00). Between 21:00 and 22:00 the amount of sales in the whole territory significantly drops. The areas with some remaining transaction activity are, once again, those located farther away from the city center and the coastline. This might be explained by people living in poorly connected areas taking longer to commute back to their homes by the end of the working day or also due to citizens working during night shifts and commuting to their workplace.  
Spatiotemporal analysis can be combined with the population and socioeconomic description. Areas with transactions occurring early in the morning/late at night are also more vulnerable from a socioeconomic point of view, as outlined in Section 3.1. This study helps understanding the variation of mobility patterns for citizens with different socioeconomic levels [22].