Geographical Process Representation: Issues and Challenges

Introduction

In recent years, there has been an increasing awareness of the importance of ontologies as an effective resource for representing knowledge in the geographical domain, providing a precise conceptualisation of the entities present in geographic space and the relationships between them (Winter, 2001; Egenhofer & Hirtle, 2005). Coupled with this, substantial efforts have been made by many scientists in Geographical Information (GI) Science community to include time and the representation of dynamic geographic phenomena as elemental constituents of GI science (Peuquet, 2001, 2002). The development of a universal semantic reference system of geographic space is an intricate research challenge which raises numerous issues. This chapter presents a perspective on these issues by examining what has been and is currently being done towards the development of a comprehensive ontology of geographical processes.

Geographers have been also making notable contributions in the field of geostatistics, and have been producing an increasing amount of useful data related to a variety of fields (e.g., hydrology, geology, climate, urban planning, logistics, and epidemiology). Furthermore, the advance in remote sensing techniques, geo-sensor networks and other areas of computer science has been contributing for the production of effective mechanisms for generating spatio-temporal geographic data. Nevertheless, such data shall be fully exploited only when we provide intelligent ways to enrich these data semantically. This chapter surveys the object-based and the field-based views of spatio-temporal data representation and gives an insight about the challenges for the development of a comprehensive ontology of dynamic geographic phenomena which is able to manipulate both views.

In GI Science, some research has been presented as an approach to handling dynamic geographic phenomena. Nonetheless, the development of such systems has been frequently limited to a particular area of application (e.g., meteorology, traffic studies and population studies) and usually with the purpose of simulation and prediction. Examples can be found in Parker, Manson, Janssen, Hoffmann, and Deadman (2003), and White and Engelen (1993). In the field of Knowledge Representation, spatio-temporal reasoning (Frank, Campari, & Formentini, 2000) and reasoning about spatio-temporal changes (Hornsby & Egenhofer, 2000) have been investigated. Theories involving objects, events, states, and process have also become of interest (Galton, 2007; Grenon & Smith, 2004). We examine existing models to deal with space, time, event and process and point out important aspects which should be considered for building a universal ontology of geographical process.

A characteristic of geographical information is that it may be affected by vagueness, leading to additional representational difficulties (Bennett, 2010). Different methods have been proposed to handle vagueness in geography, such as Fuzzy Logic (Zadeh, 1965, 1968) and Supervaluation Theory (Fine, 1975). In addition, ontologies have emerged as a suitable resource for identifying, classifying and reasoning about vague geographical features, as demonstrated in Bennett, Mallenby, and Third (2007, 2008). In this chapter we draw special attention to the phenomenon of vagueness and how it affects modelling of geographical processes. Different approaches to handling vagueness in geography shall be surveyed and a discussion is given about the issues which arise in applying them to a spatio-temporal geo-ontology.