Editors:
- Provides timely discussions on how cutting-edge technologies of data collection, management, processing, and analysis change trends in complexity science approaches in geospatial sciences
- Introduces the-state-of-the-art frameworks/methodologies to leverage advanced computational infrastructure to improve modeling, simulation, and data analysis
- Introduces novel analysis/visualization methods for new types of geospatial big data
- Shows how such advanced technologies and frameworks can be adapted to various application domains across natural and human phenomena
Part of the book series: Advances in Geographic Information Science (AGIS)
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Table of contents (7 papers)
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Front Matter
About this book
This book contains a selection of papers presented during a special workshop on Complexity Science organized as part of the 9th International Conference on GIScience 2016. Expert researchers in the areas of Agent-Based Modeling, Complexity Theory, Network Theory, Big Data, and emerging methods of Analysis and Visualization for new types of data explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.
Editors and Affiliations
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Laboratoire de Géosimulation Environnementale, Department of Geography, Université de Montréal, Montreal, Canada
Liliana Perez
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Department of Geography, Pennsylvania State University, University Park, USA
Eun-Kyeong Kim
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Department of Geography, School of Environment, McGill University, Montreal, Canada
Raja Sengupta
About the editors
Liliana Perez is an Assistant Professor at the Department of Geography and director of the Laboratory of Environmental Geosimulation (LEDGE), University of Montreal, Canada. Liliana is interested in advancing GIScience methods applied to ecology, by developing modelling approaches to simulate ecological complexities in order to understand their behavior and dynamics as well as to use them as a starting point to begin planning and preparing management strategies in face of climate change. She has developed and implemented a series of simulation tools focusing on forestry, landscape ecology, biodiversity and climate change.
Eun-Kyeong Kim is a Ph.D. candidate in the GeoVISTA Center in the Department of Geography at the Pennsylvania State University. Eun-Kyeong’s research attempts to advance spatiotemporal data analysis methodologies by integrating methods from statistical physics and complexity science. She also has an interest in geospatial big data visualization with advanced technologies. She has served NSF-sponsored Big Data Education project as a graduate researcher, and is a co-author of big data analytics online textbook.
Raja Sengupta is Associate Professor, Geography and School of Environment at McGill University. Dr. Sengupta is interested in research on both Artificial Life and Software Agents, and applying GIScience to environmental management issues and water resources management. He was an editorial board member for the journal Transactions in GIS (2011-2016) and is currently an editorial board member for Water International.
Bibliographic Information
Book Title: Agent-Based Models and Complexity Science in the Age of Geospatial Big Data
Book Subtitle: Selected Papers from a workshop on Agent-Based Models and Complexity Science (GIScience 2016)
Editors: Liliana Perez, Eun-Kyeong Kim, Raja Sengupta
Series Title: Advances in Geographic Information Science
DOI: https://doi.org/10.1007/978-3-319-65993-0
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer International Publishing AG 2018
Hardcover ISBN: 978-3-319-65992-3Published: 21 October 2017
Softcover ISBN: 978-3-319-88146-1Published: 25 August 2018
eBook ISBN: 978-3-319-65993-0Published: 17 October 2017
Series ISSN: 1867-2434
Series E-ISSN: 1867-2442
Edition Number: 1
Number of Pages: XI, 102
Number of Illustrations: 4 b/w illustrations, 22 illustrations in colour
Topics: Geographical Information Systems/Cartography, Simulation and Modeling, Big Data/Analytics, Big Data, Algorithm Analysis and Problem Complexity