Defining a model for the representation and the analysis of spatio-temporal dynamics remains an open domain in geographical information sciences. In this article we investigate a spatio-temporal graph-based model dedicated to managing and extracting sets of geographical entities related in space and time. The approach is based on spatial and temporal local relations between neighboring entities during consecutive times. The model allows us to extract sets of connected entities distant in time and space over long periods and large spaces. From GIS concepts and qualitative reasoning on space and time, we combine the graph model with a dedicated spatial database. It includes information on geometry and geomorphometric parameters, and on spatial and temporal relations. This allows us to extend classical measurements of spatial parameters, with comparisons of entities linked by complex relations in space and time. As a case study, we show how the model suggests an efficient representation of dunes dynamics on a nautical chart for safe navigation. Acknowledgements: This work was supported and founded by the GIS europôleMer. We have greatly benefited from constructive comments and suggestions from anonymous referees. We also thank Christophe Claramunt and Yvon Benoist for carefully reading the manuscript. bs_bs_banner Research ArticleTransactions in GIS, 2013, 17(5): 742-762 2001). Entities should not be considered as basic primitives of cartographical representations, but rather as geometric elements with spatial attributes (shape and location) that evolve in time. With regard to time, the distinction between linearity and cyclicity, or between events and processes, has led to numerous concepts and approaches to establish a model (. For practical reasons it is usually necessary to use a discrete measurement of time with a distinction between instants (point-base) and intervals (Allen 1984, Freksa 1992b, Galton 2000. An instant localizes a unique measurement of time, whereas an interval defines two measurements, one for the start of the phenomenon and a second for its end (Langran 1992). The last component in spatio-temporal theory in GIS concerns the relations between entities. To relate entities, GIS approaches mainly specify spatial relationships with the use of a topological model and spatial algebra. In addition to quantitative measurements (metric relations), the field of GIS research suggests several models in the area of qualitative spatial reasoning, with concepts of neighborhood, connection, or cardinal direction relations (Frank 1991, Egenhofer and Al-Taha 1992, Langran 1992, Randell et al. 1992. Sriti et al. (2005) introduce a distinction between the spatial neighborhood and the spatio-temporal neighborhood. The first one (i.e. "spatial relations") concerns relations between entities present at the same time, whereas "spatio-temporal relations" concerns relations between entities identified at two consecutive times. The concept of relation is also defined by the notion of filiation. This concerns the way e...
Abstract. We present a novel approach to modelling the evolution of spatial entities over time by using bigraphs. We use the links in a bigraph to represent the sharing of a common ancestor and the places in a bigraph to represent spatial nesting as usual. We provide bigraphical reaction rules that are able to model situations such as two crowds of people merging together while still keeping track of the resulting crowd's historical links.
This paper introduces a prospective study of the potential of spatio-temporal graphs (ST-graphs) and knowledge graphs (K-graphs) for the modelling of geographical phenomena. While the integration of time within GIS has long been a domain of major interest, alternative modelling and data manipulation approaches derived from graph and knowledge-based principles provide many opportunities for many application domains. We first survey graph principles and how they have been applied to GIS and a few representative domains to date. A comprehensive analysis of the principles behind K-graphs, respective data representation and manipulation capabilities is discussed. The perspectives offered by a close integration of ST-graphs and K-graphs are explored. The whole approach is illustrated and discussed in the context of maritime transportation.
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