Computational Movement Analysis
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Computational Movement Analysis
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.
Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques
"This book provides information regarding state-of-the-art research outcomes and cutting-edge technology on various aspects of the human movement"--Provided by publisher.
Advancing Geographic Information Science: The Past and Next Twenty Years
This book is the result of invited and competitive submissions to a 2015 academic institute on Advancing Geographic Information Science: The Past and Next Twenty Years. A core goal of the institute was to review the research challenges of the past twenty years and discuss emerging challenges of the next twenty.