Share Email Print

Proceedings Paper

Modeling spatial uncertainties in geospatial data fusion and mining
Author(s): Boris Kovalerchuk; Leonid Perlovsky; Michael Kovalerchuk
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Geospatial data analysis relies on Spatial Data Fusion and Mining (SDFM), which heavily depend on topology and geometry of spatial objects. Capturing and representing geometric characteristics such as orientation, shape, proximity, similarity, and their measurement are of the highest interest in SDFM. Representation of uncertain and dynamically changing topological structure of spatial objects including social and communication networks, roads and waterways under the influence of noise, obstacles, temporary loss of communication, and other factors. is another challenge. Spatial distribution of the dynamic network is a complex and dynamic mixture of its topology and geometry. Historically, separation of topology and geometry in mathematics was motivated by the need to separate the invariant part of the spatial distribution (topology) from the less invariant part (geometry). The geometric characteristics such as orientation, shape, and proximity are not invariant. This separation between geometry and topology was done under the assumption that the topological structure is certain and does not change over time. New challenges to deal with the dynamic and uncertain topological structure require a reexamination of this fundamental assumption. In the previous work we proposed a dynamic logic methodology for capturing, representing, and recording uncertain and dynamic topology and geometry jointly for spatial data fusion and mining. This work presents a further elaboration and formalization of this methodology as well as its application for modeling vector-to-vector and raster-to-vector conflation/registration problems and automated feature extraction from the imagery.

Paper Details

Date Published: 21 May 2012
PDF: 10 pages
Proc. SPIE 8396, Geospatial InfoFusion II, 83960N (21 May 2012); doi: 10.1117/12.920878
Show Author Affiliations
Boris Kovalerchuk, Central Washington Univ. (United States)
Leonid Perlovsky, Harvard Univ. (United States)
Michael Kovalerchuk, BKF Systems (United States)

Published in SPIE Proceedings Vol. 8396:
Geospatial InfoFusion II
Matthew F. Pellechia; Richard J. Sorensen; Shiloh L. Dockstader; Kannappan Palaniappan; Xuan Liu, Editor(s)

© SPIE. Terms of Use
Back to Top