| Session Details | |
| Section | IG - Interdisciplinary Geosciences |
| Session Title | Advanced Remote Sensing and Big Data Analysis for Disaster Risk Reduction |
| Main Convener | Dr. Young-Joo Kwak (International Centre for Water Hazard and Risk Management (ICHARM)/ UNESCO, Japan) |
| Co-convener(s) | Prof. A.W. Jayawardena (The University of Hong Kong, Hong Kong SAR) Prof. Biswajeet Pradhan (University of Technology Sydney, Australia) Dr. Sang-Ho Yun (NASA Jet Propulsion Laboratory, United States) |
| Session Description | In recent years, the world has witnessed an unusually large number of disasters, some natural and some caused by human interference. The more recent ones include the earthquake in Mexico, typhoons of varying intensities that have affected the Caribbean, the United States and some regions in Southeast Asia, forest fires in Canada, Spain, Portugal and volcanic eruptions in Indonesia. Thus, there is an urgent need to minimize the risks associated with such disasters the occurrences of which in many instances are not preventable. Early warning of impending disasters is one way of minimizing the associated risks. All types of early warning systems depend on some kind of model that is capable of forecasting what is likely to happen before it happens. Despite the availability of a plethora of such models, their usefulness heavily depends on how and whether the models can be calibrated and tested to a high degree of reliability. In this context, high quality data is extremely important. Big data handling including capturing, storing, analyzing, and interpreting is currently a hot topic in many fields. Remote sensing appears to be the way forward to big data analysis. The objective of this session is to introduce papers focused on both remote sensing fundamentals and the use of remotely sensed data preferably within the framework of ‘big data analysis’ with the goal of issuing early warnings. Emphasis will be on water-related disasters and their relationships to the hydrological cycle. Presentations on new approaches to minimize risks associated with natural disasters such as floods, tropical cyclones, storm surges, tsunamis, earthquakes, landslides, wild fires are sought and welcome. Examples of land surface dynamics, numerical simulation, and social applications between near-real time observations and long-term trends as well as topics that promote investments in disaster risk management are also welcome. |