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" Geological disaster monitoring based on sensor networks / "
Tariq S. Durrani, Wei Wang, Sheila M. Forbes, editors.
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BL
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| Record Number
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889780
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| Title & Author
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Geological disaster monitoring based on sensor networks /\ Tariq S. Durrani, Wei Wang, Sheila M. Forbes, editors.
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| Publication Statement
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Singapore :: Springer,, [2019]
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| Series Statement
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Springer natural hazards,
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| Page. NO
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1 online resource
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| ISBN
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9789811309922
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: 9811309922
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9789811309915
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9811309914
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Intro; Contents; 1 Introduction; Abstract; 2 Application of Dense Offshore Tsunami Observations from Ocean Bottom Pressure Gauges (OBPGs) for Tsunami Research and Early Warnings; Abstract; 1 Introduction and Background; 2 Data and Different Types of OBS Pressure Gauges; 3 Methodology; 4 Case Study One: The 2012 Haida Gwaii Tsunami, Offshore Canada; 5 Case Study Two: The 2009 Dusky Sound Tsunami, Offshore New Zealand; 6 Conclusions; Acknowledgements; References; 3 Remote Sensing for Natural or Man-Made Disasters and Environmental Changes; Abstract; 1 Introduction; 2 St. Lucia Case Study
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2.2 System Components3 UAV for Emergency Communication; 3.1 UAV as a Communication Relay; 3.2 Bridging Communication Through Multiple UAVs; 3.3 Bridging Communication to Connect Disjoint Group of Segments; 3.4 Real-Time UAV-Assisted Disaster Management; 3.5 Results and Discussion from Real-time Testbed Experiments; 3.6 Summary; 4 UAV Based Disaster Management; 4.1 Early Warning Systems; 4.2 Emergency Communication; 4.3 Search and Rescue; 4.4 Information Gathering; 4.5 Logistics; 5 Design Challenges and Consideration; 5.1 Characteristics of UAV Networks
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3 Papanice Case Study4 Sendai Case Study; 5 Discussion and Conclusions; Acknowledgements; References; 4 Classification of Post-earthquake High Resolution Image Using Adaptive Dynamic Region Merging and Gravitational Self-Organizing Maps; Abstract; 1 Introduction; 2 Methodology; 2.1 Feature Extraction; 2.2 Adaptive Region Descriptor; 2.3 Dynamic Region Merging; 2.4 gSOM Clustering; 2.5 Clustering Ensemble; 3 Experiments; 3.1 Survey Area and Data Description; 3.2 Experiment Setups; 3.2.1 ADRM Segmentation Evaluation; 3.2.2 gSOM Classification Evaluation; 4 Conclusion; Acknowledgments
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3.3 Research Recommendations/Future Directions4 Conclusion; Acknowledgements; References; 6 Modelling of Earthquake Hazard and Secondary Effects for Loss Assessment in Marmara (Turkey); Abstract; 1 Introduction; 2 Methodology; 2.1 Geological and Tectonic Setting; 2.2 PSHA Input Parameters; 2.3 Attenuation Equation; 2.4 Time-Dependent (Renewal) Model; 3 Results and Discussion; 4 Secondary Effects-Liquefaction; 5 Conclusions; Acknowledgements; References; 7 Unmanned Aerial Vehicles for Disaster Management; Abstract; 1 Introduction; 2 UAV Networking Technologies; 2.1 Network Architecture
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| Abstract
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This book presents the outcomes of the workshop sponsored by the National Natural Sciences Foundation of China and the UK Newton Fund, British Council Researcher Links. The Workshop was held in Harbin, China, from 14 to 17 July 2017, and brought together some thirty young (postdoctoral) researchers from China and the UK specializing in geosciences, sensor signal networks and their applications to natural disaster recovery. The Workshop presentations covered the state of the art in the area of disaster recovery and blended wireless sensor systems that act as early warning systems to mitigate the consequences of disasters and function as post-disaster recovery vehicles. This book promotes knowledge transfer and helps readers explore and identify research opportunities by highlighting research outcomes in the internationally relevant area of disaster recovery and mitigation.
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| Subject
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Natural disasters.
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Sensor networks.
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Natural disasters.
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SCIENCE-- Earth Sciences-- Geography.
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SCIENCE-- Earth Sciences-- Geology.
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Sensor networks.
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| Dewey Classification
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551
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| LC Classification
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GB5014
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| Added Entry
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Durrani, Tariq S.
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Forbes, Sheila M.
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Wang, Wei
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