gdal VS geos

TiTiler is a dynamic tile server built on FastAPI and Rasterio/GDAL. Its main features include support for Cloud Optimized GeoTIFF(COG), multiple projection methods, various output formats (JPEG, JP2, PNG, WEBP, GTIFF, NumpyTile), WMTS, and virtual mosaic. It also provides Lambda and ECS deployment environments using AWS CDK.

GDAL is the real heart, the python aspect is mostly wrappers around that I'm fairly sure. I love python for the record, the only reason I bring it up, is cause python haters accuse it of being slow, but QGIS drops down to C++ when speed is necessary, like most modern packages do.

gdal 0.15 (repo, docs), a set of Rust bindings for the GDAL library, used for access to geo-spatial data formats, is now out!

GDAL (Geospatial Data Abstraction Library) is a the geospatial data processing library. It handles a lot of Raster/Vector analysis and alteration. gdal_contour and gdal_rasterize which would be used to create isolines (contour lines) . There's more complex processing and analyses than that. More common is reprojecting multiple layers, and some that being as Vector files, into different coordiatne systems.

Access: GDAL

As an example we use GDAL heavily through its C# binds. We do all the additional data processing, that isn't done by the C++ GDAL, in C#. The final results are both Data (held in memory or temp exported to a file), and a normalized Raster Texture that we can display on a TextureRect. Most of the C# data processing scripts aren't even Inheriting from any Godot Class.

I think this would be the best way to handle this. GDAL is what you should look into for this project.

https://libgeos.org/

    GEOS is a C/C++ library for computational geometry with a focus on algorithms used in geographic information systems (GIS) software. It implements the OGC Simple Features geometry model and provides all the spatial functions in that standard as well as many others. GEOS is a core dependency of PostGIS, QGIS, GDAL, Shapely and many others.

It has the same purpose as [libgeos](https://libgeos.org/) but is implemented in Go rather than in C/C++. The primary use case is to reduce CGO dependencies while working with Go!