Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

A Graph-Based Spatiotemporal Data Framework for 4D Natural Phenomena Representation and Quantification–An Example of Dust Events

Bibliographic Data

ID22034109
AuthorsManzhu Yu (0000-0001-6769-7517, Pennsylvania State University, corresponding author)
Year2020
Volume9
Issue2
Pages127
Publication date2020-02-22
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi9020127
OpenAlexW3007205260
LanguageEN
Citations received1
References cited38

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

Data mining · Geography · Graph · Natural phenomenon · Physics · Computer Science · Data Management and Algorithms · Geographic Information Systems Studies · Human Mobility and Location-Based Analysis · Theoretical Computer Science

  • Pyramidal Framework

    Open Access•Cyril Carré, Younes Hamdani•ISPRS International Journal of…•2021

  • A Space–Time Permutation Scan Statistic for Disease Outbreak Detection

    Open Access•Martin Kulldorff, Richard Heffernan et al.•PLoS Medicine•2005

  • Dust Storms and Their Impact on Ocean and Human Health

    Open Access•DaleW Griffin, ChristinaA Kellogg•EcoHealth•2004

  • A Framework For Temporal Geographic Information

    GAIL LANGRAN, Nicholas R Chrisman et al.•Cartographica The International…•1988

  • Representing Complex Geographic Phenomena in GIS

    May Yuan•Cartography and Geographic…•2001

  • Space–Time Analysis

    Li An, An Li et al.•Annals of the Association of…•2015

Citations per year0.2
Citation span2021 - 2021 (1)
Highly citedNo

Tools

Open DOISci-HubOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae