Analytical Data Transformations in Space–Time Region: Three Stories of Space–Time Cube

In this era of abundant space–time geographic information systems (GIS) data, one challenge in GIScience is to adapt and improve current GIS environments to facilitate new ways of space–time thinking and to fully exploit the information in these data. This article focuses on the use of spatiotemporal data transformations using the construct of a space–time cube, which is a space–time coordinate space with geographical horizontal axes and a temporal vertical axis. I have chosen three examples in which the concept of space–time cubes is applied to different themes and on different scales to illustrate how diverse subjects can be interpreted with space–time analysis and transformations of space–time data. The transformation functions, such as space–time overlays, interpolation, and surface operations, can be understood as natural extensions of popular analytical operations already present in current GIS and should be intrinsic in the next generation of GIS to handle the dense space–time information that is available to us.