Machine Learning and Big Data Analytics for Sustainability and Resilience

Dear Colleague,

Sustainability and resilience constitute major challenges for our society. The former is a core issue for a development that balances environmental, social, and economic needs at present and in the future. Resiliency concerns our capacity to face and adapt to the increasing natural and human-made hazards. These two issues are at the core of the actual major challenge for humanity: global warming and climate change. Addressing these challenges requires multidisciplinary research that combines fundamental science, social science, and technology. Recent developments in data collection, including smart technology and crowdsourcing, and data analysis, including Machine Learning and Big Data, offer an excellent opportunity to deal with complex scientific problems related to sustainability and resilience. The objective of this Special Topic is to share the latest developments in this area with a focus on the following issues:

• Scientific challenges related to sustainability and resilience;
• Data collection in sustainability and resilience (remote sensing, smart sensors, open data, social media, mobile applications);
• Specificities and patterns of data related to sustainability and resilience;
• Use of Machine Learning in addressing sustainability and resilience;
• Use of Big Data in addressing sustainability and resilience;
• Role of visualization and visual analytics in sustainability and resilience.

Prof. Dr. Isam Shahrour
Dr. Marwan Alheib
Dr. Wesam Al Madhoun
Dr. Hanbing Bian
Dr. Anna Brdulak
Dr. Weizhong Chen
Prof. Dr. Fadi Comair
Dr. Carlo Giglio
Dr. Zhongqiang Liu
Prof. Dr. Yacoub Najjar
Dr. Subhi Qahawish
Prof. Dr. Jingfeng Wang
Prof. Dr. Xiongyao Xie
Topic Editors