Abstract
Due to increasing amount of spatio-temporal data collected from various applications, spatio-temporal data mining has become a demanding and challenging research field requiring development of novel algorithms and techniques for successful analysis of large spatio-temporal databases. In this study, we propose a spatio-temporal mining technique and apply it on meteorological data, which has been collected from various weather stations in Turkey. In addition, we introduce one more mining level on the extracted patterns in order to discover general trends with respect to spatial changes. Generated patterns are investigated under different temporal ranges, in order to monitor the change of the events with respect to temporal changes.
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Goler, I., Senkul, P., Yazici, A. (2011). Spatio-Temporal Pattern and Trend Extraction on Turkish Meteorological Data. In: Gelenbe, E., Lent, R., Sakellari, G. (eds) Computer and Information Sciences II. Springer, London. https://doi.org/10.1007/978-1-4471-2155-8_64
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DOI: https://doi.org/10.1007/978-1-4471-2155-8_64
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