My Experience Loading Vector Data into QGIS and Creating Thematic Maps

The maps below illustrate the percentage of a country's population that live in urban areas as related to the rest of the world. Each of the four maps is based on the same urban population data set, and all divide the data into five class, as seen in each Legend. The difference between the four maps is how those five classes are divided. Below I display each map and describe and explain the patterns observed based on  the four methods of classification. In order to highlight the patterns, I select four diverse countries based on the data, the US, Australia, Vietnam, and Bolivia.

Sorting data by Quantile is to take the list of countries, ranked from greatest urban population percentage to least, and divide them into five equal groups. Here we see that Vietnam is in the lowest group, Bolivia in the middle group, and the US and Australia in the highest group.

The Natural Breaks method ranks the countries in order of urban population intensity, then divides that list into five groups that share the same general attributes. Here we see that among our four countries, Vietnam has now moved up into the second group, and there are no countries in the bottom group, which denotes no urbanization. Bolivia has now moved from the middle group into the second group. This shows that even though there are roughly half of the countries above and below Bolivia in urban population percentage, in reality, Bolivia belongs in the second most urbanized group in the world. The US and Australia are in the top quintile of natural break rank, not surprisingly.

Now we have the Standard Deviation map. Standard Deviation seeks to group the countries by the margin with which they differ from the norm, so the closer the number is to zero, the closer that country's percentage of urban population is to the global average; the greater the number, the greater the deviation from the average in the direction of greater urban population; the less the number, the greater the deviation in the direction of less urban population than the norm. Vietnam has now moved up again, from the fourth group to the third (or middle) group, indicating that it is only slightly below the global norm, even though it was in the lowest quintile. Bolivia remains in the second group, indicating that it is slightly above the global norm even though it did rank in the middle quintile. Australia is still in the top rank, postively deviating from the norm by the maximum among the groups. But the US has now dropped a rank to second, indicating that its percentage of positive deviation is less than the maximum group. It is not one of the very top urbanized countries. Australia ranks 11th, and the US ranks 23rd.

Here we have the Equal Intervals map. Equal Intervals classification is done by taking the range of data values, from highest to lowest and dividing that equally by, in this case, 5 classes. The US is back up into the top rank with Australia. This map really shows that despite their differences, most countries rank in the top half of urban population, even Vietnam and Bolivia. 

All of these maps demonstrate the advanced state of urbanization around the world. Vietnam, the least urbanized country highlighted, exemplifies this trend. Even though it is in the bottom fifth of the countries in urbanization, and is still naturally grouped with those in the bottom half, it still has a relatively comparable urbanization, varying only slightly less than the norm.