Space-time dynamics is closely related to the concepts of change and process, which are inherent to our real-world world. Space-time dynamics is especially manifested when we move from a static to a dynamic representation of phenomena. Various processes taking place at different spatial and temporal scales interact with each other and lead to changes in the phenomena being modelled.
There are many different approaches to conceptualizing and understanding space-time dynamics in order to understand or predict phenomena in heterogeneous application domains ranging from human activities and urban sprawl to disease spread and traffic flow. An example is the time geography approach and its variants, such as the spatiotemporal prism, to model and understand human physical activities that occur in and are simultaneously constrained by space and time. These interactions produce space–time prisms that simultaneously situate individuals locally in physical space. Other techniques such as cellular automata also model human and physical activity in space and time, to simulate space–time and associated constraints to individual human activities.
While the above examples are primarily oriented towards human activities, such as urban transport and mobility, these theoretical approaches have the potential to investigate and understand interactions between humans and the environment, recognizing the importance of individual human activities together with the geographic-environmental context applied to multiple scenarios, such as climatology, physical geography, and natural disasters. For the latter, for example, modelling and simulating human responses to floods or hurricanes can lead to more efficient and effective emergency plans.