The Earth is kind of a sphere, actually a 3D object (despite some challenges even this), while our printed maps and digital screens are 2D. The intermediate step that transforms the sphere into our 2D maps, whether it’s a cartographic atlas or a flowery GIS app, known as map projection.
There are many ways to map the ellipsoidal surface of the Earth right into a flat surface; nonetheless, as these are approximative models, there are likely to be some shortcomings we’d like to take note. In some projections, relative angles and polygon (e.g., country) shapes are preserved; in others, the true area or specific Euclidean distances are kept constant. These properties also assist you to pick the very best projection to your use case.
As for the forms of projections, there are multiple ways, similar to cylindrical, conic, azimuthal, and pseudocylindrical projections. A practical method of remodeling from each other is to vary the coordinate reference systems (CRS), where Python and the libraries PyProj and GeoPandas got here in very handy!
In response to Mathematics.com, there are six predominant categories of projection types:
- Cylindric
- Pseudocylindric
- Azimuthal
- Lenticular
- Miscellaneous
Here, I is not going to follow such a strict categorization but slightly show you nine map projections that I assumed looked interesting. Depending on the particular projection, these steps often lead to distortion of shape, area, distance, or direction, so you must select rigorously when going for a real-life project. For that, this collection of projection systems and my code provided below should help. So, without further ado, the maps:
1. Eckert II Projection
Characteristics: The Eckert II projection is an equal-area pseudocylindrical projection. It preserves area accuracy but distorts shapes and distances.
Common Use: Moslty used for novelty maps of the world showing a straight-line equal area…