When Maps Made Me Dumb, Valuable Geospatial Insights Rescued Me
Whenever I am asked how big my country is, I usually give a relative answer: huge or small. I never truly understood its exact geographical size in comparison to other countries. My knowledge was limited to the world map I used in school during geography classes. Whenever this topic popped up in conversations with friends from other countries, I would recall a vague outline of the map that I once had to memorize for exams.
It wasn’t until I started working with satellite imagery and using software like Google Earth Engine and QGIS (a free Geographic Information System) that I began to explore the world in more detail, from a holistic view of the entire world down to street-level imagery.
By this point, I had familiarized myself with not only different countries but also their rough shapes and sizes; again, only in a relative sense. For example, I always assumed that India was about three times larger than Italy based on the world map I frequently saw. That assumption seemed reasonable until I looked at the actual numbers. India is, in fact, ten times larger than Italy.
As I became familiar with these open-source software tools, I started using them to solve the perplexing question that often made me feel dumbhead — the puzzling representation of the countries on virtual maps. It became more jumbled when I started to zoom into the street level where the photographs appeared more realistic.
Measurements of Geographic Areas
I figured geometric measurements might help me understand these differences. The table below describes the geometric calculations, such as area and perimeter, for Italy, India, and some regional states of India. The perimeter was included since Italy is narrower and longer in one direction than the states listed in the table.
To obtain these geometric calculations, one can use QGIS and estimate the measurements from a shape file by adding new fields in the attribute table. Below are the geometry functions for obtaining the measurements in QGIS for country polygons:
Area (in square kilometres):
$area/1000000Perimeter (in kilometres):
$perimeter/1000In python, geopandas can be used to obtain these geospatial measurements.
The saying "A picture is worth a thousand words" emphasizes that a single image can convey information more effectively than words or numbers. However, when that image contradicts reality, it often leads to a distorted understanding.
The map projection tells a different story, quite contrast to the actual numbers.
For example, Madhya Pradesh may appear smaller than Italy on certain maps, yet in reality, they are nearly the same size. This discrepancy arises from the Mercator projection, a widely used mapping system in virtual mapping tools today. The Mercator projection distorts country sizes, exaggerating them the further they are from the equator.
Below is a map of the world where countries are colour-coded, ranging from blue (smaller area by size) to red (larger area by size).
The most striking variations between actual land sizes and their distorted projections can be seen when comparing Greenland and Brazil or Greenland and the Democratic Republic of the Congo. Similarly, the actual size(represented with colours) differences between Nordic countries and South American countries like Bolivia, Peru, Venezuela, and Colombia are quite evident.
Next time you look at a world map on a virtual map, remember that it does not always represent actual proportions. If you want a more accurate representation, create your own colour-coded map based on geospatial measurements rather than relying on distorted projections.
