Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

The advances in remote sensing sensors during the last two decades have led to the
production of very high spatial resolution multispectral images. In order to adapt to this rapid …

This paper presents a vision for a Disaster City Digital Twin paradigm that can:(i) enable
interdisciplinary convergence in the field of crisis informatics and information and …

Undoubtedly, the age of big data has opened new options for natural disaster management,
primarily because of the varied possibilities it provides in visualizing, analyzing, and …

The application of artificial intelligence (AI) and machine learning in geohazard modelling
has been rapidly growing in recent years, a trend that is observed in several research and …

Structural disaster damage detection and characterization is one of the oldest remote
sensing challenges, and the utility of virtually every type of active and passive sensor …

In all types of disasters, from earthquakes to armed conflicts, aid workers need accurate and
timely data such as damage to buildings and population displacement to mount an effective …

Every year, earthquakes result in severe economic losses and a significant number of
casualties worldwide. In limiting the losses that occur after these extreme events, timely and …

An important and effective method for the preliminary mitigation and relief of an earthquake
is the rapid estimation of building damage via high spatial resolution remote sensing …

This article provides a literature review of state-of-the-art machine learning (ML) algorithms
for disaster and pandemic management. Most nations are concerned about disasters and …