Modelling higher dimensional data for GIS using generalised maps

Authors:
Ken Arroyo Ohori;Hugo Ledoux;Jantien Stoter
Affiliations:
Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands
Venue:
ICCSA'13 Proceedings of the 13th international conference on Computational Science and Its Applications - Volume 1
Year:
2013

Citing 13
Cited 1

Elementary set operations with d-dimensional polyhedra

Proceedings on International Workshop on Computational Geometry on Computational Geometry and its Applications
Introduction to Solid Modeling

Introduction to Solid Modeling
Representing geometric structures in d dimensions: topology and order

SCG '89 Proceedings of the fifth annual symposium on Computational geometry
Topological models for boundary representation: a comparison with n-dimensional generalized maps

Computer-Aided Design - Beyond solid modelling
Geographical data modeling

Computers & Geosciences - Special issue on GIS design models
Spatial concepts, geometric data models, and geometric data structures

Computers & Geosciences - Special issue on GIS design models
Good orders for incremental (re)construction

SCG '97 Proceedings of the thirteenth annual symposium on Computational geometry
Sweep algorithms for constructing higher-dimensional constrained Delaunay triangulations

Proceedings of the sixteenth annual symposium on Computational geometry
A Quasi-Four Dimensional Database for the Built Environment

DEM '01 Proceedings of the First International Symposium on Digital Earth Moving
General-Dimensional Constrained Delaunay and Constrained Regular Triangulations, I: Combinatorial Properties

Discrete & Computational Geometry
A simplex-based approach to implement dimension independent spatial analyses

Computers & Geosciences
5D data modelling: full integration of 2D/3D space, time and scale dimensions

GIScience'10 Proceedings of the 6th international conference on Geographic information science
Representing topological relationships for spatiotemporal objects

Geoinformatica

Using extrusion to generate higher-dimensional GIS datasets

Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Real-world phenomena have traditionally been modelled in 2D/3D GIS. However, powerful insights can be gained by integrating additional non-spatial dimensions, such as time and scale. While this integration to form higher-dimensional objects is theoretically sound, its implementation is problematic since the data models used in GIS are not appropriate. In this paper, we present our research on one possible data model/structure to represent higher-dimensional GIS datasets: generalised maps. It is formally defined, but is not directly applicable for the specific needs of GIS data, e.g. support for geometry, overlapping and disconnected regions, holes, complex handling of attributes, etc. We review the properties of generalised maps, discuss needs to be modified for higher-dimensional GIS, and describe the modifications and extensions that we have made to generalised maps. We conclude with where this research fits within our long term goal of a higher dimensional GIS, and present an outlook on future research.