New methods of data collection, in particular the wide range of sensors and sensor networks that are being constructed, with the ability to collect real-time data streams, provide a driver for an appropriate underlying theory for information related to dynamic geographic phenomena. This paper investigates the underlying processes by which entities with both spatial and aspatial components may evolve and change through time, and how the spatial and aspatial dimensions participate separately and together in such an evolution. The overall structure that we propose is that of attributed locations in space-time. After motivation and a survey of relevant background work, the paper introduces a formal framework and presents a case study that applies it to a detailed example. The focus is the impact of spatial change on attribute change, but also considered is the converse process. We conclude by discussing the relevance of this work to the extraction of dynamic objects and their changes from sequences of temporal snapshots of static scenes.
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