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Exploring movement – similarity analysis of moving objects


Dodge, S; Weibel, Robert; Laube, P (2009). Exploring movement – similarity analysis of moving objects. SIGSPATIAL Special, 1(3):11-16.

Abstract

Extracting knowledge about the movement of different types of mobile agents (e.g. human, animals, vehicles) and dynamic
phenomena (e.g. hurricanes) requires new exploratory data
analysis methods for massive movement datasets. Different types of moving objects share similarities but also express differences in terms of their dynamic behavior and the nature of their movement. Extracting such similarities can significantly contribute to the prediction, modeling and simulation dynamic phenomena. Therefore, with the development of a quantitative methodology this research intends to investigate and explore similarities in the
dynamics of moving objects by using methods of GIScience in
knowledge discovery. This paper presents a summary of the
ongoing Ph.D. research project.

Abstract

Extracting knowledge about the movement of different types of mobile agents (e.g. human, animals, vehicles) and dynamic
phenomena (e.g. hurricanes) requires new exploratory data
analysis methods for massive movement datasets. Different types of moving objects share similarities but also express differences in terms of their dynamic behavior and the nature of their movement. Extracting such similarities can significantly contribute to the prediction, modeling and simulation dynamic phenomena. Therefore, with the development of a quantitative methodology this research intends to investigate and explore similarities in the
dynamics of moving objects by using methods of GIScience in
knowledge discovery. This paper presents a summary of the
ongoing Ph.D. research project.

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Additional indexing

Item Type:Journal Article, not refereed, further contribution
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2009
Deposited On:21 Jan 2010 20:55
Last Modified:05 Apr 2016 13:37
Publisher:Association for Computing Machinery
ISSN:1946-7729
Free access at:Related URL. An embargo period may apply.
Official URL:http://portal.acm.org/citation.cfm?doid=1645424.1645427
Related URLs:http://www.sigspatial.org/sigspatial-special-issues/SIGSPATIALSpecialVol1Num3Nov09.pdf/view (Publisher)

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