Author here, I wrote this to show how you can use the rayshader package to generate 3D maps in R using free and open data (in this case, Landsat 8 imagery and SRTM elevation data). You can check out rayshader's Github repo here:
Cudos to this code and the beautiful artwork (great README file for a github repository, btw). As somebody who worked a bit in visualization in scipy and blender, I can appreciate how much hard work have been put there. I did visualization as a small side project during my astrophysics PhD, and it was a pain in the ass to get anything good looking out of the data.
Thanks! I always enjoy when a library has a solid README with examples, especially when it's a visualization library. Wanted to make sure I had one myself.
This is the best option for free terrain tiles. There are four formats, though "Terrarium" is the most used. It maps RGB pixels in a PNG to raw elevation values using this formula [0].
If you're using Mapbox GL, you can just point your map to [1] to fetch the tiles, and then use it as a hillshade. I do that in my topographic map style [2].
Additionally, the `elevatr` package (https://github.com/jhollist/elevatr) serves tiles directly from AWS Open Data Terrain Tiles. I don't believe it requires a key.
Related: in my masterclass (free and open source, materials here: https://github.com/tylermorganwall/MusaMasterclass) I also walk through how you can convert LIDAR data into hi-res DEMs to generate 2D and 3D maps
Mapbox has an API you can query from--I believe they have a free tier. The `ceramic` package makes this easy to pull from, but you need to get a Mapbox key first:
Github: https://www.github.com/tylermorganwall/rayshader
And browse the documentation (with rendered examples) and README on its website: https://www.rayshader.com