Mapping Temporal Patterns in Data

CartoDB's Torque library often seems to be used just to show lots of activity on a map. For example, lots of the Torque powered maps of Twitter data seem to be designed only to prove that lots of people use Twitter.

However the Torque library is a powerful tool and when used well it is able to clearly visualize temporal and geographical patterns in huge data-sets. A good example of this is a new map from The Strait Times which shows the patterns of air pollution in Sumatra, Peninsular Malaysia and Borneo since November 2000.

The map uses data from Nasa's EODIS database to show the monthly distribution of air pollution hot-spots since 2000. When you play the map you can clearly see a pattern of high pollution levels during the dry season every year, between June and September. One of the causes of this high level of pollution is forest and plantation fires during the dry season.

The Regional Air Pollution Map therefore seems to prove a link between the dry season and high pollution levels. It also allows the authorities to clearly identify the areas affected by these dangerous levels of pollution every year.