grass VS earth-reverse-engineering

https://grass.osgeo.org/

    GRASS GIS offers powerful raster, vector, and geospatial processing engines in a single integrated software suite. It includes tools for terrain and ecosystem modeling, hydrology, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It comes with a temporal framework for advanced time series processing and a Python API for rapid geospatial programming. GRASS GIS has been optimized for performance and large geospatial data analysis.

We haven't looked at integrating GRASS yet, as we're more interested in data display, not deep analysis. Just another example of a C/C++ library with front end bindings for Python. Numbers are crunched in C/C++, results returned to Python.

Anyone have good advice for where to learn how to use GRASS

Access: GRASS GIS

I see, that's useful information. Perhaps import lower resolution versions of the google earth model and textures instead? The model is already in multiple LODs. I used this one a few years ago: https://github.com/retroplasma/earth-reverse-engineering though I now see there's https://github.com/eliemichel/MapsModelsImporter

i've used retroplasma's exporter to get city sections into blender (fairly low resolution but probably good enough for a 3d print) and from there you could probably use a plugin to convert that to an STL.

I've seen a few people talk about this before, but the past hour of research has led me to believe it's actually possible: A driving simulator that uses satellite data let you take on real roads. Google Maps has been largely reverse engineered (Demo, Code) - the data just needs to be processed (barring some bugs, things under trees or bridges). I wouldn't try to keep the photorealism, there's simply not enough data, so some sort of cartoony simplifcation like Infinitown would be awesome. The idea sounds absolutely naive but I'm sure a strong team could do it.