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Geospatial Data Science Techniques and Applications - ISBN 9781138626447

Geospatial Data Science Techniques and Applications

ISBN 9781138626447

Autor: Hassan A. Karimi

Wydawca: CRC Press

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Dostępność: Wysyłka w ciągu 2-3 dni

Cena: 505,05 zł






Hassan A. Karimi



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Data science has recently gained much attention for a number of reasons, and among them is Big Data. Scientists (from almost all disciplines including physics, chemistry, biology, sociology, among others) and engineers (from all fields including civil, environmental, chemical, mechanical, among others) are faced with challenges posed by data volume, variety, and velocity, or Big Data. This book is designed to highlight the unique characteristics of geospatial data, demonstrate the need to different approaches and techniques for obtaining new knowledge from raw geospatial data, and present select state-of-the-art geospatial data science techniques and how they are applied to various geoscience problems.

Author Biography: Prof. Hassan A. Karimi is a Professor and the Director of the Geoinformatics Laboratory in the School of Information Sciences at the University of Pittsburgh. He holds a PhD in Geomatics Engineering (University of Calgary), an MS in Computer Science (University of Calgary), and a BS in Computer Science (University of New Brunswick). Prof. Kaimi's research interests include computational geometry, geospatial big data, distributed/parallel computing, mobile computing, navigation, and location-based services. In his research Prof. Karimi seeks to exploit the rich interdependence between the theory and practice. Prof. Karimi's research in geoinformatics has resulted in numerous publications in peer-reviewed journals and conference proceedings, as well as in many workshops and presentations at national and international forums. He has published the following books: Indoor Wayfinding and Navigation (sole editor), published by Taylor & Francis (2015); Big Data: Techniques and Technologies in Geoinformatics (sole editor), published by Taylor & Francis (2014); Advanced Location-Based Technologies and Services (sole editor), published by Taylor & Francis (2013); Universal Navigation on Smartphones (sole author), published by Springer (2011); CAD and GIS Integration (lead editor), published by Taylor & Francis (2010); Handbook of Research on Geoinformatics (sole editor), published by IGI (2009); and Telegeoinformatics: Location-Based Computing and Services (lead editor), published by Taylor & Francis (2004). Dr. Bobak Karimi is a Visiting Assistant Professor at Colorado College in Colorado Springs. He received a BS and PhD in Geology from the University of Pittsburgh. Dr. Karimi's research interests include remote sensing and GIS techniques applied to solve structural and tectonic problems, numerical modeling to imitate known stress/strain tests, validation of remote and modeling work by field analysis, and geophysical methods applied to increase breadth of knowledge for regional tectonic assessments. His research findings have appeared in a myriad of publications ranging in topic from tectonics, energy resources, geohazards, and CO2 storage. Dr. Karimi has presented his research at many University colloquia, national, and regional conferences, and has published several papers across the range of topics where his expertise has been applied. His more recent research is focused on unraveling the more complex details of Appalachian tectonics.

1. Geospatial Data Science: A Transdisciplinary Approach [Emre Eftelioglu, Reem Y. Ali, Xun Tang, Yiqun Xie, Yan Li, and Shashi Shekhar] 2. Geocoding Fundamentals and Associated Challenges [Claudio Owusu, Yu Lan, Minrui Zheng, Wenwu Tang, and Eric Delmelle] 3. Deep Learning with Satellite Images and Volunteered Geographic Information [Jiaoyan Chen and Alexander Zipf] 4. Visual Analysis of Floating Car Data [Linfang Ding, Jukka M. Krisp, and Liqiu Meng] 5. Recognizing Patterns in Geospatial Data Using Persistent Homology: A Study of Geologic Fractures [Kathryn A. Bryant and Bobak Karimi] 6. LiDAR for Marine Applications [Ajoy Kumar and Nathan Murry] 7. Spatiotemporal Point Pattern Analysis Using Ripley's K Function [Alexander Hohl, Minrui Zheng, Wenwu Tang, Eric Delmelle, and Irene Casas] 8. Geospatial Data Science Approaches for Transport Demand Modeling [Zahra Navidi, Rahul Deb Das, and Stephan Winter] 9. Geography of Social Media in Public Response to Policy-Based Topics [Xinyue Ye, Shengwen Li, Adiyana Sharag-Eldin, Ming-Hsiang Tsou, and Brian Spitzberg] 10. Geospatial Data Streams [Zdravko Galic]


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