Machine Learning and Big Data Analytics for Natural Disaster Reduction and Resilience

Dear Colleague,

Countries worldwide are subjected to new and complex challenges related to the intensification of the frequency and severity of natural disasters because of the impact of climate change, rapid demographic growth, and intense urbanization. These challenges have a significant socio-economic impact because of the large-scale damage due to natural disasters. Indeed, natural disasters generally cover large areas, causing substantial human losses, severe environmental damage, and destruction of infrastructures that support social and economic activity.

The latest advances in monitoring using IoT, crowdsourcing, satellites, and drones provide new opportunities to collect large amounts of data related to natural disasters.

The use of machine learning and big data enables the development of effective solutions that improve urban systems' resilience to natural disasters, including a better understanding of the response of complex socio-technical systems to natural disasters, the development of early warning systems, rapid scanning of damage, optimization of emergency actions, use of automation to reduce and protect critical infrastructures, and the adaptation of infrastructures to the new level of natural hazards.

The objective of this Topic is to share the latest developments in this area with a focus on the following questions:

• What are the new scientific challenges related to the intensification of natural disasters (floods, earthquakes, storms, heat waves, disasters, wildfire and landslides)?
• How could digital technology (IoT, crowdsourcing, and satellite) enhance natural disaster monitoring?
• How could ML and BigData empower real-time analysis of data related to natural disasters?
• How could ML and BigData improve the efficiency of early warning systems?
• How could ML and BigData help adaptation strategies to natural disasters?
• How could ML and BigData help reduce damage related to natural disasters?

Prof. Dr. Isam Shahrour
Dr. Marwan Alheib
Dr. Anna Brdulak
Prof. Dr. Fadi Comair
Dr. Carlo Giglio
Prof. Dr. Xiongyao Xie
Prof. Dr. Yasin Fahjan
Dr. Salah Zidi
Topic Editors