Thank you to Patrick Gerland for leading this week’s brown bag discussion.
Cities are home to half of the world’s population and more than 60% of city residents are also at risk from being affected by at least one natural disaster. Gerland and his colleagues at the UN Population Division analyzed city population data and spatial data on natural hazards in order to better understand the risks that cities face from natural disasters. As cities continue to grow, it will become increasingly important to understand the risks of natural disasters and how to best prepare for this risks.
The research presented some interesting findings:
Flooding and droughts are the two most frequent natural hazards
Coastal cities are prone to both floods and cyclones and therefore are more exposed to natural disasters than cities that are inland
In 2011, 374 out of 633 cities (or 977 million people) faced a relatively high risk of exposure to 1+ hazard;
98 cities were exposed to 2+ hazards;
17 of 23 megacities in 2011 were exposed to 1+ hazard
Cities in Europe and Africa are least exposed to relatively high risks of hazards
Cities in less developed countries are at higher risk of natural disasters and are growing faster than more developed countries
This research broadly illuminates the risks to the world’s major cities. Gerland acknowledged that there are limitations to this analysis due to availability of data, however the team will continue to build upon this research as additional data is collected. The next step for the project will be to expand the sample from 633 cities to include the world’s 1700 largest cities. You can find the full presentation here.
Tile image courtesy of Keith Moseley
Senior Analyst, Department of Economic and Social Affairs, United Nations
Patrick Gerland is a Senior Analyst and Population Affairs Officer at the United Nations Department of Economic and Social Affairs. Gerland focuses on demographic estimation and projections, especially in Africa and Asia. He is particularly interested in the development of new methodology and collaboration with academic research groups in improving the estimation of adult mortality and incorporating uncertainty in demographic modelling.