Geological Disaster Monitoring Based on Sensor Networks

Preface.- Introduction.- Application of Dense Offshore Tsunami Observations from Ocean Bottom Pressure Gauges (OBPGs) for Tsunami Research and Early Warnings.- Remote Sensing for Natural or Man-made Disasters and Environmental Changes.- Classification of Post-Earthquake High Resolution Images using Adaptive Dynamic Region Merging and Gravitational Self-Organizing Maps.- A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management.- Modelling of Earthquake Hazard and Secondary Effects for Loss Assessment in Marmara (Turkey).- Unmanned Aerial Vehicles for Disaster Management.- Human Detection based on Radar Sensor Network in Natural Disaster.- Real-time Wind Velocity Monitoring based on Acoustic Tomography.- Intelligent Sub-meter Localization Based on OFDM Modulation Signal.- Conclusions and Final Comments.

Tariq S Durrani received his M.Sc. and Ph.D. degrees from the University of Southampton, UK in 1967 and 1970 respectively. After postdoctoral research at Southampton, he joined the University of Strathclyde, Glasgow, as a lecturer in 1976, and was appointed Professor of Signal Processing in 1982. He was Head of the Electronic and Electrical Engineering Department from 1982 to 1986, and Deputy Principal from 2000 to2006. Currently, he is a research professor at the department.

His research interests are in the areas of communications signal/image processing, technology management and higher education management. He is a fellow of the Royal Society of Edinburgh, the Royal Academy of Engineering, the IEEE, the IET and The Word Academy of Sciences, and a Foreign Member of the US National Academy of Engineering. He was awarded the OBE in December 2002 for services to higher education and electronics research.

Wei Wang is a Professor in the College of Electronic and Communication Engineering at Tianjin Normal University, China. He received his Ph.D. degree in Measuring Technology and Instruments from Tianjin University. He was a visiting scholar at the University of Texas at Arlington from September 2011 to February 2012. His research interests are data stream mining technology in sensor networks, including feature extraction and selection, small sample classification, and multi-class identification from sensor network data streams. He has published more than thirty papers in international journals and conferences. Sheila Forbes obtained her MBA degree from the University of Strathclyde Graduate Business School, UK in 1993 and is an honorary administration officer in the Department of Electronic and Electrical Engineering at the University of Strathclyde, Glasgow, UK. Her research interests include management of technology, innovation, engineering management and triple helix activities. She has co-authored twenty-five research publications and has