Choropleth Mapping

Fundamentals of choropleth mapping and map design

Colorpleth mapping is one of the most commonly used method of thematic mapping. It is used for “phenomena” that have spatial variation in the boundaries of enumeration units.


Choice of classification method and number of classes:
The classification of this map is “Equal Interval” and the map has five classes to classify the range of data. Decision making to find appropriate classification is important because final result of map may look significantly different based on characteristics of data. Thus, exploring enough to find the characteristic of data and suitable classification is an essential task. In this case, the data is showing the percentage of adult literacy. Viewers of this map will expect to see at a glance which country has lower, moderate, higher literacy level in Africa. Thus, I decided to use equal interval for this case to deliver the sense of lower grade to higher grade. Also I used five classes to give more accuracy but not too much diversity that may disturb intuitiveness for viewers.
Attribute table, a graphic visualization, and a map:
Attribution table shows what kind of data we can visualize. It is a storage of rare sources but thanks to a development of the software we can easily sort information with the way we want to use. Geovisualizers can analyze the raw data before we decide which classification would be the best for the purpose. However, it would be very challenging and time consuming to analyze vast amount of data. Also, it is not efficient to deliver the core message since it is not visualized in effective way.
Graphic visualization, in this case, the vertical bar graphs shows the adult literacy in Africa. It is relatively easier to interpret the percentage of literacy than reading numeric figures on table. The graph also color coded by the range of class so that it helps viewers comprehend information. However, the graph is also not appropriate to show lots of information at the same time. In this case, this graph cannot show all the name of countries in its x-axis due to the lack of the space. Also, if we decide to put all names of countries and other information, the graph will completely lose its advantage as a good visualization method.
The choropleth map also shows the percentage of adult literacy with five different classes. In this case, I chose the sequential color scheme to compare the ratio of same phenomena. By showing the brightness changes, the map delivers the information more intuitively and logically. However, when the map maker chose the color scheme poorly, the choropleth map loses its advantage and brings more confusions. Also, the accuracy of data is reduced by generalizing and standardizing the information by its Enumeration Units.
What is your recommendation to improve the adult literacy rate in Africa?:
Regarding an invest on improving the adult literacy rate in Africa, the investment needs to be used efficiently which can be estimated based on the calculation of with factors of population, literacy rate, areas etc. I think the basic infrastructure investment is needed and the overall result should bring the maximum incensement of the literacy rate of the African as whole.
Since an infrastructural investment can affect limited area, choosing the location should mainly consider the population density and literacy rate of the affected area where the investment can happen. For example, the investment will be most effective for a small place with high population density and low literacy rate.

I would approach this with a simple formulate such as the following:
((100-litracy rate)×population)/area

Then the value calculated by the formula can be visualized on the map with different colors. Based on the color, one can easily pick which place will be most effective when the investment is done.
However, the reality can involve so many different factors such as income, life expectancy and so on. Even if the simple formula says that the investment will be effective, if people do not have other basic needs, they will not be able to get much benefit from the infrastructures.
Ultimately, the best data can be obtained by having sample investment and the results. With that data, we can have more accurate formula that involves other factors.

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