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Book Cover
Author Laube, Patrick, author

Title Computational movement analysis / Patrick Laube
Published Cham : Springer, 2014
Online access available from:
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Description 1 online resource (xiii, 87 pages) : illustrations
Series SpringerBriefs in Computer Science, 2191-5768
SpringerBriefs in computer science. 2191-5768
Contents Introduction -- Movement spaces and movement traces -- Movement mining -- Decentralized movement analysis -- Grand challenges in Computational Movement Analysis
Summary This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research
Bibliography Includes bibliographical references
Notes Online resource; title from PDF title page (SpringerLink, viewed September 17, 2014)
Subject Data mining.
Geospatial data.
Geographic information systems.
Form Electronic book
ISBN 9783319102689 (electronic bk.)
3319102680 (electronic bk.)
3319102672 (print)
9783319102672 (print)