In Asia and in many other places around the world, growing populations increasingly intersect with natural hazards. The Risk group investigates this intersection. Our research seeks to improve understanding of how and why societies are impacted by natural hazards and to identify strategies that reduce vulnerability and increase resilience.
The Volcanic Hazards and Risk group focuses on quantifying the volcanic hazard, physical vulnerability and risk around active volcanoes. They do this by using numerical models, carrying out pre-, syn- and post-eruption field studies and through the statistical interrogation of large datasets.
The Natural Hazards and Society group at EOS, directed by Patrick Daly, explores the intersections between society and hazards in Asia. Our research aims to generate new knowledge and potentially paradigm-shifting insights into the impact of hazards upon societies (past and present), post-disaster reconstruction and recovery, and risk, adaptation and resilience.
The work of the Art+Media Group directed by Isaac Kerlow fosters the collaboration between artists and Earth scientists and through highly interdisciplinary projects, focusing on the deep connection of human life and civilization with Earth and Nature.
The Coupled Human and Natural Systems Lab (CHNS-Lab) is interested in developing research questions that address pertinent environmental challenges in Asia. We use a combination of socioeconomic datasets and geospatial information, and analyse this data using statistical models. The aim of our research is to derive a better and more nuanced understanding of complex socio-ecological systems, and to use our research outputs to develop policy recommendations towards sustainability.
The Disaster Risk and Resilience Analytics Lab is focused on using novel technologies and analytical methods to understand, model, and predict the impact of natural disasters on society, and develop tools to promote resilient cities. We combine methods from spatial statistics, risk / reliability analysis, machine learning, remote sensing and probabilistic modeling to develop information systems on pre-disaster risk, post-disaster impact and long-term disaster recovery.