Introducing spatiotemporal data
Spatiotemporal data is geospatial data that contains a time series element. Time series analysis shows how features evolve over time within a space. It can be used in a variety of contexts but is most frequently used in sociological, demographic, environmental, and meteorology/climate studies. For example, you might analyze rainfall data in a city for a period of time. It can also be used to visualize population shifts in a country. Time series data allows for trend analysis or giving data a broader context.
The following figure shows a jogger’s workout visualized from Garmin GPX data with each point on the line representing the runner at a different location along the route over time. The speed at each given time is also attached to each point.
Figure 2.8 – A spatiotemporal data example showing speed over time on a road
The following graph shows the speed values from this dataset over time:
