A graph-based spatiotemporal data framework for 4D natural phenomena representation and quantification-an example of dust events

摘要: Natural phenomena are intrinsically spatiotemporal and often highly dynamic. The increasing availability of simulation observation datasets has provided us a great opportunity to better capture understand the complexity dynamics natural phenomena. Challenges posed by formalization representation such in terms their non-rigid boundaries quantification event over space time. objectives this research (1) conceptually represent phenomenon as an event, (2) quantify dynamic movements evolutions events using graph-based approach. This proposed data framework is applied dust dataset 4D events. Dust identified, tracked reconstruct Northern Africa region from December 2013 November 2014. Quantified different demonstrated verified be alignment with observations.