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.

This work combines research and empirical evidence on the economic costs of disasters with theoretical approaches. It provides new insights on how to assess and manage the costs and impacts of disaster prevention, mitigation, recovery and adaption, and much more.

This is the first English language book to systematically introduce basic theories, methods and applications of disaster risk science from the angle of different subjects including disaster science, emergency technology and risk management. Viewed from basic theories, disaster risk science consists of disaster system, formation mechanism and process, covering 3 chapters in this book. From the perspective of technical methods, disaster risk science includes measurement and assessment of disasters, mapping and zoning of disaster risk, covering 4 chapters in this book. From the angle of application practices, disaster risk science contains disaster management, emergency response and integrated disaster risk paradigm, covering 3 chapters in the book. The book can be a good reference for researchers, students, and practitioners in the field of disaster risk science and natural disaster risk management for more actively participating in and supporting the development of "disaster risk science".