Abstract
Although information theory is primarily concerned with the transmission of information it can be also applied to the quantification of the intrinsic information that emerges from a given physical system. Over the past years, principles of information theory have been applied to many environmental and ecological studies. However, it still appears that the initial concept of entropy as identified by Shannon’s initial contribution cannot be directly applied to evolving geographical systems. The research introduced in this paper suggests an extension of the concept of entropy to the spatial and temporal dimensions, by taking into account the distribution of entities in space and time. We propose a series of entropy measures that together form a set of complementary indices to evaluate the distribution of entities, events and categories in space and time. The whole approach is exemplified by several illustrative configurations.
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Claramunt, C. (2012). Towards a Spatio-temporal Form of Entropy. In: Castano, S., Vassiliadis, P., Lakshmanan, L.V., Lee, M.L. (eds) Advances in Conceptual Modeling. ER 2012. Lecture Notes in Computer Science, vol 7518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33999-8_28
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DOI: https://doi.org/10.1007/978-3-642-33999-8_28
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