Abstract
Humans tend to interpret a temporal series of geographical spatial data in terms of geographical processes. They also often ascribe certain properties to processes (e.g. a process may be said to accelerate). Given a spatial region of observation, distinct properties may be observed in different subregions and at different times, which causes difficulties for humans to identify them. The conceptualisation of geographical features and their correlation with geographical phenomena may provide a human like approach to analyse large spatio-temporal datasets. This paper presents a representational model and a reasoning mechanism to analyse evolving geographical features and their relationship to geographical processes. The proposed approach comprises methods of relating occurrences of geographical events to geographical processes which is said to proceed over time. We introduce an initial set of properties which can be associated with several geographical processes. We consider this as a first step towards a more general model for representing and reasoning about geographical processes.
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References
Batty, M.: Geocomputation Using Cellular Automata. Geocomputation, 95–126 (2000)
Clarke, C.K., Brass, A.J., Riggan, J.P.: A Cellular Automaton Model of Wildfire Propagation and Extinction. Photogrammetric Engineering and Remote Sensing 60(11), 1355–1367 (1994)
Claramunt, C., Parent, C., Thériault, M.: Design patterns for spatiotemporal processes. Searching for Semantics: Data Mining, Reverse Engineering, 415–428 (1997)
Claramunt, C., Theriault, M.: Toward semantics for modelling spatio-temporal processes within GIS. In: Advances in GIS Research I, pp. 27–43 (1996)
Claramunt, C., Thriault, M., Parent, C.: A qualitative representation of evolving spatial entities in two-dimensional spaces. In: Innovations in GIS V, pp. 119–129 (1997)
Cohn, A.G., Bennett, B., Gooday, J., Gotts, N.: RCC: a calculus for region-based qualitative spatial reasoning. GeoInformatica 1, 275–316 (1997)
Crooks, A.: Exploring cities using agent-based models and GIS. In: Proceedings of the Agent 2006 Conference on Social Agents: Results and Prospects, Citeseer (2006)
Devaraju, A., Kuhn, W.: A Process-Centric ontological approach for integrating Geo-Sensor data. In: 6th International Conference on Formal Ontology in Information Systems, FOIS 2010 (2010)
Erol, K., Levy, R., Wentworth, J.: Application of agent technology to traffic simulation. In: Complex Systems, Intelligent Systems and Interfaces, Nimes, France (May 1998)
Frank, A.U., Campari, I., Formentini, U. (eds.): GIS 1992. LNCS, vol. 639. Springer, Heidelberg (1992)
Galton, A.: Desiderata for a spatio-temporal geo-ontology. Spatial Information Theory, 1–12 (2003)
Galton, A.: Experience and history: Processes and their relation to events. Journal of Logic and Computation 18(3), 323–340 (2007)
Galton, A.: A formal theory of objects and fields. In: Montello, D.R. (ed.) COSIT 2001. LNCS, vol. 2205, pp. 458–473. Springer, Heidelberg (2001)
Galton, A.: Spatial and temporal knowledge representation. Earth Science Informatics 2(3), 169–187 (2009)
Grenon, P., Smith, B.: SNAP and SPAN: towards dynamic spatial ontology. Spatial Cognition & Computation, 69–104 (2004)
Hornsby, K., Egenhofer, M.J.: Identity-based change: A foundation for spatio-temporal knowledge representation. International Journal of Geographical Information Science 14, 207–224 (2000)
Ohgai, A., Gohnai, Y., Watanabe, K.: Cellular automata modeling of fire spread in built-up areas–A tool to aid community-based planning for disaster mitigation. Computers, Environment and Urban Systems 31(4), 441–460 (2007)
Parker, D.C., Manson, S.M., Janssen, M.A., Hoffmann, M.J., Deadman, P.: Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93(2), 314–337 (2003)
Randell, D.A., Cui, Z., Cohn, A.G.: A spatial logic based on regions and connection. In: KR 1992, pp. 165–176 (1992)
Shimabukuro, Y., Duarte, V., Anderson, L., Valeriano, D., Arai, E., de Freitas, R., Rudorff, B., Moreira, M.: Near real time detection of deforestation in the Brazilian Amazon using MODIS imagery. Revista Ambiente & Água-An Interdisciplinary Journal of Applied Science 1(1) (2006)
Wainwright, J.: Can modelling enable us to understand the rôle of humans in landscape evolution?. Geoforum 39(2), 659–674 (2008)
Walter, V.: Object-based classification of remote sensing data for change detection. ISPRS Journal of Photogrammetry and Remote Sensing 58(3-4), 225–238 (2004)
White, R., Engelen, G.: Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A 25(8), 1175–1199 (1993)
Wolter, F., Zakharyaschev, M.: Spatio-temporal representation and reasoning based on rcc-8. In: Proceedings of the Seventh Conference on Principles of Knowledge Representation and Reasoning, KR 2000, pp. 3–14. Morgan Kaufmann, San Francisco (2000)
Worboys, M., Hornsby, K.: From objects to events: GEM, the geospatial event model. In: Egenhofer, M.J., Freksa, C., Miller, H.J. (eds.) GIScience 2004. LNCS, vol. 3234, pp. 327–343. Springer, Heidelberg (2004)
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Campelo, C.E.C., Bennett, B., Dimitrova, V. (2011). Identifying Geographical Processes from Time-Stamped Data. In: Claramunt, C., Levashkin, S., Bertolotto, M. (eds) GeoSpatial Semantics. GeoS 2011. Lecture Notes in Computer Science, vol 6631. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20630-6_5
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DOI: https://doi.org/10.1007/978-3-642-20630-6_5
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