Abstract
Technological tools allow the generation of large volumes of data. For example satellite images aid in the study of spatio-temporal phenomena in a range of several disciplines, e.g. environment and health. Thus, remote-sensing experts must handle various and complex image sets for their interpretations. Additionally, the GIS community has heavily worked on describing spatio-temporal features, and standard specifications nowadays provide design foundations for GIS software and spatial databases. We argue that this spatio-temporal knowledge and expertise would provide invaluable support for the field of image interpretation. As a result, we propose a high level conceptual framework, based on existing and standardized approaches, offering enough modularity and adaptability for representing the various dimensions of spatio-temporal knowledge.
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Pierkot, C. (2012). A Geographic Standards Based Metamodel to Formalize Spatio-temporal Knowledge in Remote Sensing Applications. 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_36
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DOI: https://doi.org/10.1007/978-3-642-33999-8_36
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