STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

Amirhossein Ghaffari, Huong Nguyen, Lauri Lovén, Ekaterina Gilman
9/4/2025
cs.LGcs.AI

Official code: Ahghaffari/stm_graph (4 stars, MIT, last commit 2025-09-03). 1 more implementation below.

Abstract

Urban spatio-temporal data present unique challenges for predictive analytics due to their dynamic and complex nature. We introduce STM-Graph, an open-source Python framework that transforms raw spatio-temporal urban event data into graph representations suitable for Graph Neural Network (GNN) training and prediction. STM-Graph integrates diverse spatial mapping methods, urban features from OpenStreetMap, multiple GNN models, comprehensive visualization tools, and a graphical user interface (GUI) suitable for professional and non-professional users. This modular and extensible framework facilitates rapid experimentation and benchmarking. It allows integration of new mapping methods and custom models, making it a valuable resource for researchers and practitioners in urban computing. The source code of the framework and GUI are available at: https://github.com/Ahghaffari/stm_graph and https://github.com/tuminguyen/stm_graph_gui.

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Code Implementations(2)

Ahghaffari/stm_graphOfficial100%
MIT

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

40PythonMay 14, 20251 years agoMIT
gnnspatio-temporal-prediction
tuminguyen/stm_graph_guiOfficial100%
MIT

An user-friendly GUI for STM-Graph Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

30PythonJun 2, 202511 months agoMIT
guipyqt6spatio-temporal-prediction

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Cite this paper

@article{ghaffari2025stmgraph,
  title  = {STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions},
  author = {Amirhossein Ghaffari and Huong Nguyen and Lauri Lovén and Ekaterina Gilman},
  year   = {2025},
  eprint = {2509.10528},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.10528v1}
}

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