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=== Description ===

Geo2SigMap is an efficient framework for high-fidelity RF signal mapping leveraging geographic databases, ray tracing, and a novel cascaded U-Net model. The project offers an automated and scalable pipeline that efficiently generates 3D building and path gain (PG) maps. The repository is split into two distinct partitions:

* Scene Generation: A pure Python-based pipeline for generating 3D scenes for arbitrary areas of interest.
* ML-based Propagation Model: ML-based signal coverage prediction using our pre-trained model based on the cascaded U-Net architecture described in [https://ieeexplore.ieee.org/document/10632773 this paper].

As of November 2025, v2.0.0 enhances the scene generation pipeline to include:

* LiDAR Terrain Data
* Building height calibration using Digital Elevation Models (DEMs)

This drastically improves the accuracy of the environment being processed by the ML-based Propagation Model or a ray tracer of your choice. Throughout the following notebook examples, we utilize Sionna RT. This package is open-source and highly accurate for generating coverage maps. If you are unfamiliar with Sionna RT, feel free to read Nvidia's [https://arxiv.org/abs/2504.21719 Technical Report] to better understand how it works.

=== Prerequisites ===

=== Package Installation ===

=== Demos ===

==== Cite ====