Document Type: Review Article
Faculty of Engineering, Departments of Electromechanical, Civil, and Biomedical Engineering. Autonomous University of Queretaro, Campus San Juan del Rio, Moctezuma 249, Col. San Cayetano, 76807, San Juan del Rio, Queretaro, Mexico
Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43220, U.S.A
This article presents a state-of-the-art review of different methods, signal and image processing techniques, and statistical analyses used for prediction and assessment of natural disasters including earthquakes, tsunamis, volcanic eruptions, hurricanes, tornadoes, and floods. Application of the big data paradigm to the aforementioned natural disasters is also discussed. The research for increasingly more sophisticated computational models will continue to achieve more accurate predictions of various natural disasters.