Friday, 27 June 2014

GIS and Poverty Reduction: Part 1

While I often cringe at the idea of technological solutions to poverty, there is one I am profoundly interested in exploring further, and that technology is Geographic Information Sciences, Systems and Studies. A disclaimer would first be appropriate: I am still a student in GIS and development, and as such do not claim to know everything on these two subjects. A GIS is "an integrated collection of computer software and data used to view and manage information about geographic places, analyze spatial relationships, and model spatial processes" (Esri, 2014), and as such it has immense implications for fighting poverty. I will explain this definitions further, and once we have a better under

"manage information about geographic places": Every aspect of our lives is in one way or another dictated by our geographic location and the circumstances that are affiliated with these locations. The sheer size of information involved with geographic locations requires explicit decisions to be made regarding what will be managed, and what will be ignored, and this aspect brings on other implications in itself.
"analyze spatial relationships": A GIS allows one to actively manage and analyze what processes take place regarding these locations, and how the relationships of structures and objects interact and influence each other within and between locations. Unlike aspatial data and information which works according to underlying principles of independence between variables, spatial relationships are NOT independent, and as such influence each other.
"model spatial relationships": A model is a representation of something that cannot be fully replicated because of complexity, cost or a wide variety of reasons. Models can used as a means of predicting future or current events based upon historical trends and existing data. As mentioned in point 1, models are instantly biased in that every influencing factor cannot be replicated or included, and the user must therefore make decisions as to what will be left out of the analysis.

These definitions are my interpretations of Esri's definition of a GIS, which itself carries some controversy. With this understanding of GIS as a complex tool capable of managing vast quantities of data, and providing visual and graphical representations of processes on the surface of the planet, we can look a little further at what it can do. 

Environmental Studies and Analysis: A powerful aspect of a GIS is the capabilities regarding environmental variables. A simple example of this could be using combined data, satellite and remote sensing imagery to measure deforestation in an area, and how it will progress with a "business as usual" scenario through a constructed model.

Network Analysis: An effective tool that allows for, you guessed it, network analysis. Networks are interconnected sets of points and lines that represent routes from one location to another, such as a pipeline, road, or even a social network between people. Common tools for this could be determining the best location for an emergency facility, a new store, or finding the best route to deliver goods.

Urban Analysis: While not being a separate toolset within most GIS platforms, urban analysis is (to me) one of the most awesome ways that a GIS can be used. Determining a new bus route, what roads can support new bike lanes, where new buildings or stores can be placed, determining market segments, population centres or any other wide array of things are just some of the urban analyses that can be completed.

Now that we have a better idea of what a GIS is, we can start to see how an analytical geographic approach  can fight something as real, cold, and ugly as poverty, which will be followed up with in Part 2.

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