Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/46563
Title: A Graph-based Technique for Higher Order Topological Data Structure Visualisation
Authors: de Almeida, J.-P. 
Morley, J.G. 
Dowman, I.J. 
Orientador: Morley, J.G.
Dowman, I.J.
Keywords: Visualisation; Topology; Graph theory
Issue Date: Apr-2005
Publisher: University of Glasgow
Project: FCT SFRH/BD/9909/2002 - PhD in Geomatic Engineering (UCL) 
Serial title, monograph or event: GISRUK 2005 - 13th Annual GIS Research UK
Place of publication or event: University of Glasgow, Escócia, Reino Unido
Abstract: Interpretation and analysis of spatial phenomena is a highly time consuming and laborious task in several fietds of the Geomatics world (Anders et al., 1999). That is why the automation of those tasks is especially needed in areas such as Geographical Information Science (GlScience). Carrying out these tasks in the context of an urban scene is particulariy challenging given its complexity: relatively small component elements and itt"it g"nrially complei spatial pattern (Eyton, 1993, and Barr & Barnsley, 1996, both cited in Barnsley and Barr, 1997). Topology is a particularly important research area in the field of GlScience, for it is a central àefining feature of a geographical information system (GIS). But, as far as topological relàtionships between spatial objects are concerned, "generally speaking .ottt.Àporary desktop bIS packages do not support further information beyond the first level oi adjâcency" (Theobald, 2001). Therefore, this research project focused on scene analysis bi buiiding up a technique for the better understanding of topological relationships between vector-based GIS objects, beyond the fnst level of adjacency. Another initial interest was to investigate the possible use of graph theory for this purpose. To date, this mathematical framework has been used in different applications in a wide range of fields to represent connections and relationships between spatial entities. Several u,rtùo6 (including Laurini and Thompson, 1992) have maintained that "this particular tool is extremely valuable and efficient in storing and describing the spatial structure of geographicil entities and their spatial arrangement". Theobald (2001) added that "concepts àf gruptt theory allow us to extend the standard notion of adjacency". The aim of retrieving structured information translated into more meaningful homogeneous regions, for instancJ fro* an initial unstructured data set, may be achieved by identifuing mJaningful structures within the initial random collection of objects and by understanding the spatial arrangement between them. We believe that applying graph theory and carrying out graph analysis may accomplish this.
Description: Esta publicação foi agraciada com o prémio GISRUK 2005 “Whittles Publishing” Best Paper Award.
URI: http://hdl.handle.net/10316/46563
Rights: openAccess
Appears in Collections:I&D INESCC - Artigos e Resumos em Livros de Actas

Files in This Item:
File Description SizeFormat
GISRUK2005_BestPaperPrize.pdf4.42 MBAdobe PDFView/Open
Show full item record

Page view(s)

100
checked on Sep 18, 2019

Download(s) 50

203
checked on Sep 18, 2019

Google ScholarTM

Check


This item is licensed under a Creative Commons License Creative Commons