Paper Info
Title
An evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS
Abstract
AbstractOne solution to the integration of additional characteristics, e.g. time and scale, into geographic information system GIS datasets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. Previous work has been mostly limited to higher-dimensional rasters and hierarchies of trees, which grow exponentially with the dimension. As representations with limited topological relationships quickly become intractable in higher dimensions, a topological vector approach seems most suitable for this purpose, requiring the use of higher-dimensional topological data structures. We therefore present in this paper an evaluation and classification of the possible data structures for an nD GIS, including how they can be implemented to support real-world data aspects, such as holes, disconnected components and attributes, as well as practical issues that affect their feasibility, like the availability of algorithms, libraries and software.
Year
DOI
Venue
2015
10.1080/13658816.2014.999683
Periodicals
Keywords
Field
DocType
data structures, nD GIS, topology, multidimensional GIS
Data mining,Data structure,Geographic information system,Computer science,Theoretical computer science,Software,Artificial intelligence,Enterprise GIS,Hierarchy,Machine learning,Topological data structures
Journal
Volume
Issue
ISSN
29
5
1365-8816
Citations 
PageRank 
References 
6
0.44
38
Authors
3
Name
Order
Citations
PageRank
Ken Arroyo Ohori1468.14
Hugo Ledoux223122.27
Jantien E. Stoter320022.20