GIS is a critical tool in helping the world’s most vulnerable to climate change adapt and potentially even benefit. The world’s tropics and ocean lying populations are the most at risk to long term climate change – the gradual issues that are resulting from greenhouse gas pollution, such as increased extreme droughts and storms, or wildlife shifts and crop losses. According to Standard & Poor’s global analysis, the top 20 countries at risk to climate change are in the southern hemisphere, and most are among the world’s poorest.
The vulnerable need to adapt, and they need to do so with limited funding and resources. GIS is filling that gap – with simple knowledge transfer, complex layering analyses, or just saving time and money by pinpointing the best places to invest resources. Here are four examples of how GIS is helping the most vulnerable adapt and cope with climate change.
Rainwater Runoff Harvesting in Africa
A comprehensive study of best adaptation strategies for West African farmers vulnerable to increased drought and changing rain patterns creatively used GIS to map areas most prone to surface area runoff collection of rain water.[i] Those areas are now being developed in partnership with international NGOs to serve as natural rain water collectors for small farmer irrigation.
Specifically, in Kenya, a government secretariat is working with the NGO Kenya Rainwater Project (KRP) to water proof best identified sites from GIS mapping to ensure both farmer and domestic household water security in areas vulnerable to changing rainy seasons.
Pinpointing Best Dam Locations in Flood Zones with Projection Modeling
More than a billion people live in low lying coastal regions that will eventually flood either partially or entirely without intervention due to rising sea levels.[ii] GIS is helping, however, pin point the exact locations of where to build dams to mitigate flooding.
Bangladesh is considered the most at risk with a huge, poor population living directly within ocean flood zones. By 2050, 17% of the country will be inundated.[iii] While many people will have to move, risks can be mitigated and migration efforts saved with careful dam placing. Md. Abu Zafer Siddik and Mursheda Rahman used GIS data layering analysis to track exactly where to put a dam in one of the worst flood zones – Sirajganj. They tracked layers of river tributary levels, geological analysis, and ocean levels over time and with predictive modelling to scientifically forecast with mapping where a dam would be most helpful in 50 years.
Dengue Fever Tracked and Stomped
Slight increases in temperature can reduce entire cold seasons for tropical countries. While good news for beach goers, a decrease in cold means an increase in insects – and all of their pesky diseases. Dengue is one of the worst, and it is exacerbated not only by a decrease in cold temperature, but also by an increase in urban migration already seen and expected to intensify in coming years as rural farmers adapt to climate change and global economic pressures.
Scientists are able to successfully predict dengue outbreak areas now with GIS spatial analysis, as demonstrated in a Malaysian case study.[iv] Remote sensing satellite data can provide data on environmental factors such as land cover, land surface temperature, and topography, which then can be correlated with rainfall, air temperature, humidity, and population density to analyze and predict conditions prime for dengue. The data can help inform where and when to spray for mosquitoes and inform residents in those areas to take precautions.
Participatory Mapping Overlaid with Satellite GIS in Amazonian Indigenous Tribes
Indigenous groups that still rely on the land and its resources for their basic economies are some of the most vulnerable to climate change. Mapping has proven an instrumental tool to help change their economic systems in concert with dwindling natural resources, however.
Richard Chase Smith took participatory maps created by 14 indigenous communities in the Peruvian Amazon dependent on hunting and gathering and overlaid them with GIS satellite imagery of deforestation and resource changes. The result of this work in the 1990s is that the communities themselves are now applying GIS to their own resource management plans – tracking animal populations, vegetation cover, land use, and soil types among other factors.[v]
Since the world’s poorest are also the most vulnerable to climate change risks – including to their health, their basic needs, and their livelihoods – a simple, low cost tool like GIS is instrumental in helping mitigate risks and adapt to tremendous challenges in our altering world.
[i] Ngigi, Stephen N. 2009. Climate Change Adaptation Strategies: Water Resources Management Options for Smallholder Farming Systems in Sub-Saharan Africa. The Earth Institute at Columbia University. http://www.rockefellerfoundation.org/uploads/files/9eacd477-e2ef-4b72-9207-5a18135dceb3.pdf
[ii]World Ocean Review. 2014. http://worldoceanreview.com/en/wor-1/coasts/living-in-coastal-areas/
[iii] Harris, Gardiner. 28 Mar. 2014. Borrowed Time on Disappearing Land. The New York Times. http://www.nytimes.com/2014/03/29/world/asia/facing-rising-seas-bangladesh-confronts-the-consequences-of-climate-change.html?_r=0
[iv] Nazri, CD, I Rodziah, and A. Hashim. 2009. Distribution pattern of a dengue fever outbreak using GIS. Journal of Environmental Health Research 9:2. http://www.cieh.org/uploadedFiles/Furniture/JEHR/JEHR_Vol09_2.pdf.
[v] Smith, Richard Chase. 1994. GIS and Long Range Economic Planning for Indigenous Territories. Cultural Survival 18:4. http://www.culturalsurvival.org/ourpublications/csq/article/gis-and-long-range-economic-planning-indigenous-territories.