Abstract
Humans tend to interpret a temporal series of geographical spatial data in terms of geographical processes. They also often ascribe certain properties to processes (e.g. a process may be said to accelerate). Given a spatial region of observation, distinct properties may be observed in different subregions and at different times, which causes difficulties for humans to identify them. The conceptualisation of geographical features and their correlation with geographical phenomena may provide a human like approach to analyse large spatio-temporal datasets. This paper presents a representational model and a reasoning mechanism to analyse evolving geographical features and their relationship to geographical processes. The proposed approach comprises methods of relating occurrences of geographical events to geographical processes which is said to proceed over time. We introduce an initial set of properties which can be associated with several geographical processes. We consider this as a first step towards a more general model for representing and reasoning about geographical processes.
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Campelo, C.E.C., Bennett, B., Dimitrova, V. (2011). Identifying Geographical Processes from Time-Stamped Data. In: Claramunt, C., Levashkin, S., Bertolotto, M. (eds) GeoSpatial Semantics. GeoS 2011. Lecture Notes in Computer Science, vol 6631. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20630-6_5
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DOI: https://doi.org/10.1007/978-3-642-20630-6_5
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