Disaster Vulnerability Looks Different for Women

In the case of "natural" disasters, women are more often than not the ones who take the brunt of the impacts following the event. According to the article “The Gendered Nature of Natural Disasters: The Impact of Catastrophic Events on the Gender Gap in Life Expectancy, 1981–2002” written by Eric Neumayer of the London School of Economics and Political Science and Thomas Plümper of the University of Essex and Max-Planck Institute of Economics, women are more vulnerable given social, biological, and economic differences between men and women. 

They define vulnerability as being ‘‘the characteristics of a person or group and their situation influencing their capacity to anticipate, cope with, resist and recover from the impact of a natural hazard”. As opposed to looking to the magnitude of the disaster for their analysis, the authors decided to utilize the number of causalities in a given disaster to better understand the factors at play in widening the gender gap. “The gender gap in life expectancy shows large variations across time and space. Worldwide, on average, women’s life expectancy is 4.69 years higher than that of men. However, in 64 out of 2,266 country-years men actually lived longer than women.” Why is this the case? The authors cite socio-economic standing and the limitations that society places on women as probable causes. 

A few of the compelling reasons that the authors cited for reasons why mortality would be higher for women in disaster include strict dress codes that keep women in clothing that would restrict movement during a disaster, the inability to climb tree or to swim (which many men do as parts of their jobs), and even the fact that many men are allowed to sleep outside during warm evenings on the roofs of their abodes while women remain housebound, regardless. 

Although this article does not include any GIS maps within its text, it provides a number of interesting factors that could be easily represented by utilizing a visualization. By mapping out the elements that are presented within the text, GIS may be used to help predict which areas may need more funding towards educational or adaptation programs based on their vulnerability in terms of likelihood of experiencing a large scale disaster, the female population, and the relative socio-economic classes of the female population. 

The following map “charts how nations stack up on the World Economic Forum’s Gender Gap Index, which gauges the magnitude of the gender gap in four areas: economic participation and opportunity, political empowerment, educational attainment and health and survival. Note that the higher the score, the lower the gap”.

How can society change to make sure that the gender gap is closed and that all people are given the skills they need to survive and thrive with or without facing disasters?

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Map taken from http://www.theatlanticcities.com/jobs-and-economy/2012/01/how-economic-development-helps-worlds-women/907/

Neumayer, Eric and Plümper, Thomas. 2007. “The Gendered Nature of Natural Disasters: The Impact of Catastrophic Events on the Gender Gap in Life Expectancy, 1981–2002” Annals of the Association of American Geographers, 97(3), 2007, pp. 551–566.

De-railed by Climate Change: Public Transportation & Sea Level Rise

There are many more consequences resulting from Climate Change beyond ecological devastation and increasingly strong super-storms. One such consequence occurs each passing day. Little by little the Earth’s ocean levels are rising, resulting in many possible floods zone in and around coastal areas. This means that coastal communities are at high risk for future inundation. In their article “Identifying Sea Level Rise Vulnerability using GIS: Development of a Transit Inundation Modeling Method” Oswald and Treat utilize Geographic Information Systems (GIS) to make models of communities whose transit would be the most impacted by future potential flooding. Their study uses Philadelphia’s transit system (which includes both busses and trains) as a case study for their Transit Inundation Modeling Method (TIMM) considering that this large city lies on the side of the Delaware river. 

“TIMM is based on a five-step process that can be applied to transit agencies to identify vulnerabilities. The process is repeatable, straightforward, GIS- based, and uses publicly available geographic data. The five steps include: (1) Define Study Area, (2) Gather Data, (3) Create Inundation Layers, (4) Analyze Data, and (5) Synthesize Results and Recommendations”(Oswald 2013, 3). According to the Intergovernmental Panel on Climate Change (IPCC)’s 2007 report, “these levels will increase between 0.18 to 0.59 meters over the next 100 years... Furthermore, current IPCC data compared to predicted values show that these predictions may be underestimated (Rahmstorf et al, 2007). Worst case scenario values include a 5.0 meter increase of world sea levels due to catastrophic collapse of the Antarctic ice sheets (Vaughan, 2006)”(Oswald 2013, 2).

The given predictions by the IPCC indicate a key vulnerability to be added into the data section of the TIMM. Taking this information into account and layering geo-referenced historic maps of Philadelphia’s transportation systems, the authors were able to create maps modeling the impact of climate change on Philadelphia’s public transportation system.  

One such concern highlighted in this study was exemplified by the aftermath of Hurricane Sandy which flooded most of the Northeastern United States. In New York City, there was a massive amount of flooding specifically in the Subway system. Oswald and Treat cite that “In particular, since railways are often located in low-lying areas, they are specifically at-risk to flooding of underground tunnel and rail tracks, erosion of the rail base, and reduced clearance under bridges”(Oswald 2013, 2). As seen on the map below, this concern is relevant to Philadelphia’s extensive rail routes.

After utilizing GIS, Oswald and Treat strongly recommend that Philadelphia adapt a TIMM to best predict which areas of transit are at the highest risk for inundation and for those areas to be granted adaptation plans that would allow for necessary changes to be made to transit systems before climate induced disasters and gradual flooding. 

Perhaps it’s time to start investing in city gondola lifts! 

http://upload.wikimedia.org/wikipedia/commons/thumb/c/cd/Gondola_lift_lucerne_2006.03.18.jpg/800px-Gondola_lift_lucerne_2006.03.18.jpg

Oswald, M. R., & Treat, C. C. (2013). Identifying Sea Level Rise Vulnerability using GIS: Development of a Transit Inundation Modeling Method. International Journal Of Geoinformatics, 9(1), 1-10.