Temporal Resolution
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Temporal Indexing
knowledge discovery in databases, research in spatiotemporal modeling and visualization has attracted much attention in GIScience. Computational models in geography, traditionally Monte Carlo simulation and Markov chain, have been rapidly expanded in recent years to cellular automata, agent-based modeling, and evolutionary algorithms [15]. In summary, research in temporal GIS and applications has grown over the last two decades. Many fundamental concepts about time and time properties have been discussed in depth in both GIScience and computer science literature. Significant progress has been made in conceptual development as well as in case studies in different application domains. Research emphases have shifted from the space-centered map paradigm to ways of integrating space and time for a richer representation of geographic dynamics. The many challenges and opportunities ahead call for improved communication, more robust theoretical and reasoning frameworks, and more powerful and friendly methods for information query, analysis, modeling and visualization.
11. Frank, A., Grumbach, S., Guting, R.H., Jensen, C.S., Koubarakis, M., Lorentzos, N., Manolopoulos, Y., Nardelli, E., Pernici, B., H.-J. Schek, Scholl, M., Sellis, T., Theodoulidis, B., Widmayer, P.: Chorochronos: a research network for spatiotemporal database systems. SIGMOD Rec. 28, 12–21 (1999) 12. Hornsby, K., Egenhofer, M.J.: Modeling moving objects over multiple granularities. Ann. Math. Artificial Intell. 36, 177–194 (2002) 13. Yuan, M., McIntosh, J.: A typology of spatiotemporal information queries. In: Shaw, K., Ladner, R., Abdelguerfi, M. (eds.) Mining Spatiotemporal Information Systems. Kluwer, Norwell, Massachusetts, USA (2002) 14. Miller, H.: Modeling accessiblity using space-time prism concepts within a GIS. Int. J.~Geogr. Inf. Syst. 5, 287–301 (1991) 15. Torrens, P.M.: Simulating sprawl. Ann. Assoc. Am. Geogr. 96, 248–275 (2006)
Cross References
Exploratory Visualization
Temporal Indexing Indexing and Mining Time Series Data
Temporal Ordered Space Matrix
Geographic Dynamics, Visualization And Modeling
Recommended Reading 1. Langran, G.: Time in geographic information systems. Taylor and Francis, London (1992) 2. Christakos, G., Bogaert, P., Serre, M.: Temporal GIS: Advanced Functions for Field-Based Applications. Springer, New York (2002) 3. Egenhofer, M.J., Golledge, R.G. (eds.): Spatial and Temporal Reasoning in Geographic Information Systems. Oxford University Press, New York (1998) 4. Frank, A.U.: Ontology for spatio-temporal databases. In: Koubarakis, M., Sellis, T.K., Frank, A.U. (eds.) Spatiotemporal Databases: the Chorochronos Approach, pp. 9–77. SpringerVerlag, Berlin (2003) 5. O’Sullivan, D.: Geogrpahical information science: time changes everything. Prog. Hum. Geogr. 29, 749–756 (2005) 6. Yuan, M.: Use of a three-domain repesentation to enhance GIS support for complex spatiotemporal queries. Trans. GIS 3, 137–159 (1999) 7. Peuquet, D.J., Duan, N.: An event-based spatiotemporal data model (ESTDM) for
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