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Over the past decade, extreme natural disasters have imposed escalating human and economic tolls. Advances in data-driven artificial intelligence (AI) now offer the potential to extend forecast lead times and improve predictive accuracy, while innovations in unmanned aerial vehicles (UAVs) and robotics can bolster our capacity to mitigate and respond. By harnessing these technologies, it is reasonable to expect that humanity will develop the tools needed to prevent-or at least dramatically reduce-the impact of future natural disasters. Predicting, Preventing, and Mitigating Natural Disasters Through Advanced Technologies confronts the most destructive natural phenomena by systematically reviewing today's state-of-the-art predictive and preventive technologies. Each chapter provides an in-depth analysis of a specific hazard, examining how data-driven forecasting models, early-warning systems, and emerging drone and robotics-based interventions currently function, where they fall short, and what incremental advances could sharpen our ability to anticipate and avert catastrophe. Covering topics such as disaster risk reduction, cyclone readiness evaluation, and landslide susceptibility mapping, this book is an excellent resource for researchers and graduate students, disaster management engineers and technologists, policymakers and planners, non-profit and aid organizations, and more.
