Modelling Geographic Relationships in Automated Environments

Abstract

Automated processes such as cartographic generalisation require formal abstraction of the geographic space in order to analyse, process and transform it. Spatial relations are key to understanding geographic space and their modelling is a critical issue. This chapter reports on existing classifications and modelling frameworks for spatial relations. A generic model is proposed for building an ontology of spatial relations for automatic processes such as generalisation or ondemand mapping, with a focus on so-called multiple representation relations. Propositions to use such ontology in an automated environment are reported. The three use cases of the chapter describe recent research that uses relations modelling. The first use case is the extension of CityGML with relations for 3D city models. The second use case presents the use of spatial relations for automatic spatial analysis, and particularly the grouping of natural features such as lakes or islands. Finally, the third use case is a data migration model guided by relations that govern the positioning of thematic data upon changing reference data.

Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda

“…In our case, we decided to extract the locations of crossroads to make them explicit in the map with a point symbol. Interestingly, this necessity to make spatial relations explicit matches practices in map generalization where the important spatial relations are made explicit to preserve them [37]. In this experiment, the spatial relation detection was limited to crossroads (that will be depicted by symbols), and to tree-lined streets, in order to preserve the position of vegetation patches along a street.…”

Automatic (Tactile) Map Generation—A Systematic Literature Review

“…The CartACom model relies on communicating agents and was designed to handle unstructured geographic spaces with no clear borders between groups of objects [56]. Spatial relations between objects are of high importance in this model [57]. The model introduces relational constraints managing relations between two agents.…”

A Review of Geospatial Semantic Information Modeling and Elicitation Approaches

“…The ontology is developed in first-order logic to support the detailed ontological Ontologies at different levels of generality are also built to formalize and support reasoning over cartographic knowledge. Earlier works mostly focused on the formalization of the cartographic generalization process [73] classifying cartographic features, spatial relations, and relational constraints to be observed by the generalization process. Gould and Mackaness [74] also include generalization algorithms in their ontology in order to have a knowledge base that could be used in an automated system.…”