Faming Huang

Sansar Raj Meena

Jingjing Meng

This Research Topic is Volume III of a series. The previous volume can be found here: Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods - Volume II and Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods Natural and engineering disasters, which include landslides, rock fall, rainstorm, dam failure, floods, earthquakes, road and building disasters and wildfires, appear as results of the progressive or extreme evolution of climatic, tectonic and geomorphological processes and human engineering activities. It is significant to explore the failure mechanism and carry out spatial modeling of these engineering and natural disasters due to their serious harm to the safety of people's lives and property. The data-based methods, including advanced and successful remote sensing, geographic information systems, machine learning and numerical simulation techniques methods, are promising tools to analyze these complex disasters. Machine Learning models such as neurofuzzy logic, decision tree, artificial neural network, deep learning and evolutionary algorithms are characterized by their abilities to produce knowledge and discover hidden and unknown patterns and trends from large databases, whereas remote sensing and Geographic Information Systems appear as significant technology equipped with tools for data manipulation and advanced mathematical modeling. What is more, the numerical simulation can also be acknowledged as advanced technologies for discovering hidden failure mechanism of disasters. The main objective of this Research Topic is to provide a scientific forum for advancing the successful implementation of Machine Learning (ML) and numerical simulation techniques in operation rules, failure mechanism, spatial and time series prediction, susceptibility mapping, hazard assessment, vulnerability modeling, risk assessment and early warning of complex natural and engineering disasters.

Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-Based Methods,volume III

Chong Xu

Liam Taylor

Xiangli He

Wenwen Qi

Qi Yao

Wentao Yang 

At present, the intensification of global climate and environmental change has led to frequent occurrence of natural hazards. Various types of natural hazards always overlap and interact, or occur in a chain reaction, with a wide range of impacts and a long period of time, resulting in serious disaster losses. Typically, major earthquakes and geological hazards, extreme meteorological hazards, large-scale floods and droughts, marine disasters, and forest and grassland fires, as well as their compound and chained hazards are among the key factors affecting human life safety and world economic development. To better our understanding of disaster prevention, mitigation, and relief, it is thus pivotal to facilitate advanced perception, intelligent early warning, accurate prevention, and efficient rescue of natural hazards. This Research Topic aims to collect both Original Research and Review articles addressing the state-of-the-art advances of theories and methodologies in all types of natural hazards. Studies underlining the compound and chained relationship between different hazards are in particular welcomed. Potential themes include, but are not limited to: • Mechanisms of formation, evolution, and disaster process of multiple natural hazards as well as their compound and chained natural hazards • Model and scenario development regarding whole process control, chain breaking of key nodes, and precise prevention of major natural hazard chains • Methods and applications on detection, identification, database establishment, and spatiotemporal evolution law analysis of natural hazard sources • Technologies on intelligent early warning and refined risk assessment of compound and chained natural hazards. • Rescue equipment and investigation of post-disaster community reconstruction

Prevention, Mitigation, and Relief of Compound and Chained Natural Hazards

Sansar Raj Meena

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