Invited perspectives: How machine learning will change flood risk and impact assessment

• Published in: Natural hazards and earth system sciences Vol. 20; no. 4; pp. 1149 - 1161
• Main Authors: Wagenaar, Dennis, Curran, Alex, Balbi, Mariano, Bhardwaj, Alok, Soden, Robert, Hartato, Emir, Mestav Sarica, Gizem, Ruangpan, Laddaporn, Molinario, Giuseppe, Lallemant, David
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 29.04.2020; Copernicus Publications
• Subjects: Algorithms; Computation; Data; Data collection; Data mining; Digital media; Disaster planning; Emergency preparedness; Emergency response; Environmental risk; Ethical standards; Ethics; Flood damage; Flood relief; Flood risk; Floods; Flow velocity; Hydrodynamics; International organizations; Learning algorithms; Machine learning; Mitigation; Neural networks; Observation methods; Power (Philosophy); Prejudice; Recovery plans; Remote sensing; Risk assessment; Rural areas; Social media; Storm damage; Time; Trends

Increasing amounts of data, together with more computing power and better machine learning algorithms to analyse the data, are causing changes in almost every aspect of our lives. This trend is expected to continue as more data keep becoming available, computing power keeps improving and machine lea...