Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

Machine learning (ML) is a collection of methods used to develop understanding and
predictive capability by learning relationships embedded in data. ML methods are becoming …

As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …

Within the paradigm of smart cities, smart devices can be considered as a tool to enhance
safety. Edge sensing, Internet of Things (IoT), big data, social media analytics, edge …

Efficient handling and planning for the urban regions' sustainable development require a
vast range of up-to-date and thematic information. Besides, obtaining an uncontaminated …

Fast and effective responses are required when a natural disaster (eg, earthquake and
hurricane) strikes. Building damage assessment from satellite imagery is critical before relief …

Abstract Since the 1985 M 8.0 central Chile earthquake, national strong‐motion seismic
networks have recorded ten megathrust earthquakes with magnitudes greater than M 7.5 at …

Emergency situations encompassing natural and human-made disasters, as well as their
cascading effects, pose serious threats to society at large. Machine learning (ML) algorithms …

The application of metamodeling technique to overcome computational challenge of Monte
Carlo simulation (MCS) technique for response uncertainty quantification under stochastic …

Earthquake forecasting poses significant challenges, especially due to the elusive nature of
stress states in fault systems. To tackle this problem, we use features derived from seismic …