Social Sensing and Big Data Computing for Disaster Management (PDF)
Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management.
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Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management.
Qunying Huang is Associate Professor in the Department of Geography at the University of Wisconsin-Madison, USA. Her fields of expertise include spatial computing, spatial data mining, and spatial data analytics. Dr. Huang's research bridges the gap between computer and information science (CIScience) and GIScience by generating new computational algorithms and methods to make sense of complex big spatial datasets obtained from both the physical sensing (e.g. remote sensing) and social (e.g. social media) sensing networks. The problem domains of her research are related to natural hazards and human mobility.
Christopher T. Emrich is Endowed Associate Professor of Environmental Science and Public Administration within the School of Public Administration and a founding member of the newly formed National Center for Integrated Coastal Research at the University of Central Florida (UCF Coastal), USA. His research/practical service includes applying geospatial technologies to emergency management planning and practice, long-term disaster recovery, and the intersection of social vulnerability and community resilience in the face of catastrophe.
- 2020, 1. Auflage, 204 Seiten, Englisch
- Herausgegeben: Zhenlong Li, Qunying Huang, Christopher T. Emrich
- Verlag: Taylor & Francis
- ISBN-10: 1000261492
- ISBN-13: 9781000261493
- Erscheinungsdatum: 17.12.2020
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- Größe: 19 MB
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