Computational Movement Analysis (Paperback, 2014 ed.)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	September 2014
First published:	2014
Authors:	Patrick Laube
Dimensions:	235 x 155 x 6mm (L x W x T)
Format:	Paperback
Pages:	87
Edition:	2014 ed.
ISBN-13:	978-3-319-10267-2
Categories:	Books > Business & Economics > Economics > Political economy Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing Books > Professional & Technical > Energy technology & engineering > Electrical engineering > Power generation & distribution Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	3-319-10267-2
Barcode:	9783319102672

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