On the problem of adjacency relations in the Spatial Aggregation approach
by
L. Ironi, S. Tentoni
Proc. of 17th International Workshop on Qualitative Reasoning , Brasilia, 20-22 August, 2003, 111-118.
ABSTRACT
Spatial Aggregation (SA) is a computational approach to the
analysis of large spatial data sets. It differs from other tools for data
analysis for its hierarchical strategy in aggregating spatial objects at
higher and higher levels until the behavioral and structural
information about the underlying physical phenomenon, that is required for
performing a specific task, is extracted from the data set.
This characteristic makes SA an interesting and versatile framework
for the development of tools for automated
reasoning about physical phenomena spatially represented. The SA approach has been
successfully applied to different domains and tasks; but, its soundness
strictly depends on the definitions of spatial adjacency relations at different levels of abstraction.
The definitions given by Zhao and Huang
may reveal to be not fully sound when performing the contouring task.
In such a context, the found
drawbacks are at least twofold: (1) metric-based adjacency relations are too difficult to be optimally defined, and aggregation may fail to extract isocurves;
(2) the soundness of neighborhood relations depends on the density of the isopoint set, and aggregation may fail to extract physical structures as isopoint contiguity may be lost. This paper illustrates the problems above, and presents new definitions and algorithms for their solutions.
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Liliana Ironi
2003