文章基本信息

标题：A Graph-Based Spatiotemporal Data Framework for 4D Natural Phenomena Representation and Quantification–An Example of Dust Events
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作者：Manzhu Yu
期刊名称：ISPRS International Journal of Geo-Information
电子版ISSN：2220-9964
出版年度：2020
卷号：9
期号：2
页码：127
DOI：10.3390/ijgi9020127
语种：English
出版社：MDPI AG
摘要：Natural phenomena are intrinsically spatiotemporal and often highly dynamic. The increasing availability of simulation and observation datasets has provided us a great opportunity to better capture and understand the complexity and dynamics of natural phenomena. Challenges are posed by the formalization of the representation of such phenomena in terms of their non-rigid boundaries and the quantification of event dynamics over space and time. The objectives of this research are to (1) conceptually represent the natural phenomenon as an event, and (2) quantify the dynamic movements and evolutions of events using a graph-based approach. This proposed data framework is applied to a dust simulation dataset to represent the 4D dynamic dust events. Dust events are identified, and movements are tracked to reconstruct dust events in the Northern Africa region from December 2013 to November 2014. Quantified dynamics of different dust events are demonstrated and verified to be in alignment with observations.