ABSTRACT
Extreme events such as urban floods are dynamic in nature, i.e. they evolve with time. The spatiotemporal analysis of such disastrous events is important for understanding the resiliency of an urban system during these events. Remote Sensing (RS) data is one of the crucial earth observation (EO) data sources that can facilitate such spatiotemporal analysis due to its wide spatial coverage and high temporal availability. In this paper, we propose a discrete mereotopology (DM) based approach to enable representation and querying of spatiotemporal information from a series of multitemporal RS images that are acquired during a flood disaster event. We represent this spatiotemporal information using a semantic model called Dynamic Flood Ontology (DFO). To establish the effectiveness and applicability of the proposed approach, spatiotemporal queries relevant during an urban flood scenario such as, show me road segments that were partially flooded during the time interval t1 have been demonstrated with promising results.
- James F Allen. 1990. Maintaining knowledge about temporal intervals. In Readings in qualitative reasoning about physical systems. Elsevier, 361--372.Google ScholarDigital Library
- Alessandro Artale and Enrico Franconi. 2000. A survey of temporal extensions of description logics. Annals of Mathematics and Artificial Intelligence 30, 1-4 (2000), 171--210.Google ScholarDigital Library
- Sotiris Batsakis and Euripides GM Petrakis. 2010. SOWL: spatiotemporal representation, reasoning and querying over the semantic web. In Proceedings of the 6th International Conference on Semantic Systems. ACM, 15.Google ScholarDigital Library
- M. Datcu, H. Daschiel, A. Pelizzari, M. Quartulli, A. Galoppo, A. Colapicchioni, M. Pastori, K. Seidel, P. G. Marchetti, and S. D'Elia. 2003. Information mining in remote sensing image archives: system concepts. IEEE Transactions on Geoscience and Remote Sensing 41, 12 (Dec 2003), 2923--2936. https://doi.org/10.1109/TGRS.2003.817197Google ScholarCross Ref
- Antony Galton. 1999. The mereotopology of discrete space. In International Conference on Spatial Information Theory. Springer, 251--266.Google ScholarCross Ref
- W3C Working Group. 2006. Defining N-ary Relations on the Semantic Web. https://www.w3.org/TR/swbp-n-aryRelations/Google Scholar
- Thomas R Gruber. 1993. A translation approach to portable ontology specifications. Knowledge acquisition 5, 2 (1993), 199--220.Google Scholar
- Claudio Gutierrez, Carlos A Hurtado, and Alejandro Vaisman. 2007. Introducing time into RDF. IEEE Transactions on Knowledge and Data Engineering 19, 2 (2007).Google ScholarDigital Library
- Benjamin Harbelot, Helbert Arenas, and Christophe Cruz. 2015. LC3: A spatiotemporal and semantic model for knowledge discovery from geospatial datasets. Web Semantics: Science, Services and Agents on the World Wide Web 35 (2015), 3--24.Google ScholarDigital Library
- Michel CA Klein and Dieter Fensel. 2001. Ontology versioning on the Semantic Web.. In SWWS. 75--91.Google Scholar
- Kuldeep R Kurte, Surya S Durbha, Roger L King, Nicolas H Younan, and Abhishek V Potnis. 2017. A spatiotemporal ontological model for flood disaster monitoring. In Geoscience and Remote Sensing Symposium (IGARSS), 2017 IEEE International. IEEE, 5213--5216.Google Scholar
- K. R. Kurte, S. S. Durbha, R. L. King, N. H. Younan, and R. Vatsavai. 2017. Semantics-Enabled Framework for Spatial Image Information Mining of Linked Earth Observation Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10, 1 (Jan 2017), 29--44. https://doi.org/10.1109/JSTARS.2016.2547992Google ScholarCross Ref
- Carsten Lutz, Frank Wolter, and Michael Zakharyaschev. 2008. Temporal description logics: A survey. In Temporal Representation and Reasoning, 2008. TIME'08. 15th International Symposium on. IEEE, 3--14.Google ScholarDigital Library
- David A Randell, Zhan Cui, and Anthony G Cohn. 1992. A spatial logic based on regions and connection. KR 92 (1992), 165--176.Google ScholarDigital Library
- David A Randell, Gabriel Landini, and Antony Galton. 2013. Discrete mereotopology for spatial reasoning in automated histological image analysis. IEEE transactions on pattern analysis and machine intelligence 35, 3 (2013), 568--581.Google Scholar
- W3C Recommendation. 2012. OWL 2 Web Ontology Language Document Overview (Second Edition). https://www.w3.org/TR/owl2-overview/Google Scholar
- W3C Recommendation. 2017. Time Ontology in OWL. https://www.w3.org/TR/owl-time/Google Scholar
- Chi-Ren Shyu, Matt Klaric, Grant J Scott, Adrian S Barb, Curt H Davis, and Kannappan Palaniappan. 2007. GeoIRIS: Geospatial information retrieval and indexing system---Content mining, semantics modeling, and complex queries. IEEE Transactions on geoscience and remote sensing 45, 4 (2007), 839--852.Google ScholarCross Ref
- Theodore Sider. 1997. Four-dimensionalism. The Philosophical Review 106, 2 (1997), 197--231.Google ScholarCross Ref
- Jonas Tappolet and Abraham Bernstein. 2009. Applied temporal RDF: Efficient temporal querying of RDF data with SPARQL. In European Semantic Web Conference. Springer, 308--322.Google ScholarDigital Library
- Kenneth W Tobin, Budhendra L Bhaduri, Eddie A Bright, Anil Cheriyadat, Thomas P Karnowski, Paul J Palathingal, Thomas E Potok, and Jeffery R Price. 2006. Automated feature generation in large-scale geospatial libraries for content-based indexing. Photogrammetric Engineering & Remote Sensing 72, 5 (2006), 531--540.Google ScholarCross Ref
- Chris Welty, Richard Fikes, and Selene Makarios. 2006. A reusable ontology for fluents in OWL. In FOIS, Vol. 150. 226--236.Google ScholarDigital Library
Index Terms
- Semantics-enabled Spatio-Temporal Modeling of Earth Observation Data: An application to Flood Monitoring
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