A class to create custom maps of the Earth's surface. There are thousands of combinations of color-schemes, projections, and aspects. Includes Mercator, Gall-Peters, Orthographic, Peirce Quincuncial, and More!

If you are a fancy Windows user, I recommend the convenient fancy Windows binaries. Double-click to install them and then keep pressing buttons until something good happens. If you see a map, you're in the right place.

If you are not on Windows or are otherwise not fancy enough to deserve such executables, simply double-click on the .jar files in the main directory and, if you have Java installed (10/10 would recommend), it should just run without any set-up.

You could also compile and run the source code, but if you do, there are a few dependencies. The Java dependencies can be obtained as .jar files:

• Apache Commons Mathematics Library
• Java Tools for Experimental Mathematics "ellipticFunctions" package, which requires their "mfc" package

If you want to use the Python, you'll need a couple of packages from PyPI. Just install Python 3 and pip, and then call the following from a command line (or use Anaconda or something, I don't know. Up to you).

pip3 install numpy pyshp

generate_coastlines.py also takes input data from naturalearthdata.com, which should be placed in src\\zupplemental\\data\\.

There are three executable Java files, three runnable Java scripts, and four runnable Python scripts. These are, in order:

• MapDesignerRaster.jar – The original program. Create custom oblique raster images of the Earth's surface using a variety of algorithms called projections.
• MapDesignerVector.jar – The same idea, but working in vector images instead in case you want to cut a vinyl sticker or something.
• MapAnalyzer.jar – See graphs and figures quantifying the amount of scale and angular distortion present in each map projection.
• MapPlotter.java – Plot a large group of map projections by the amount of distortion they produce.
• MapOptimizer.java – Run gradient descent on parametric projections to minimize their distortion.
• MapExplainer.java – Generate an HTML blurb outlining and displaying every map projection.
• generate_coastlines.py – Generate an SVG string outlining the continents, islands, and major lakes of the world, to be used as vector input.
• generate_graticule.py – Generate an SVG string displaying a map graticule, to be used as vector input.
• generate_indicatrices.py – Generate an SVG string outlining an array of Tissot's indiatrices of distortion, to be used as vector input.
• generate_orthodromes.py – Generate a mesh of orthodromes in an Equirectangular projection, to be used as vector input.

The executable applications all have similar layouts that let you select an input equirectangular map, a projection, an aspect (where the North Pole is situated with respect to the projection), and parameters if applicable. Go crazy! There are a practically unlimited number of combinations.

The runnable scripts just kind of work on their own. Those ones aren't really meant for mass consumption.

I'll write a little blurb here later.

For some examples, check out the output folder. For more information, go to jkunimune15.github.io/Map-Projections.

While I wrote all of the code in this repository myself, and I created several of the simpler images from scratch, other people did help. Here's a comprehensive list.

• The NASA for Basic.png, Satellite.jpg, and Altitude.png,
• Tom Patterson for Clouds.jpg, Rivers.png,
• Natural Earth for Pastel.png and their detailed vector data,
• The Apache Commons for their complex mathematics code,
• Technische Universität Berlin for their complex mathematics code,
• Gene Keyes for his impressively in-depth documentation of his map projection,
• Robert Gray for his research on Buckminster Fuller's map projection,
• AuthaGraph Co., Ltd. for their vague information about their map projection, and
• Wikipedia for their substantial collection of map projection information and equations.