Pymdu (Python Urban Data Model)
Pymdu (Urban Data Model) is a Python package designed to collect, post-process, model, and analyze urban data. It draws inspiration from and reuses tools like GeoClimate, UWG, UMEP-DEV, t4gpd, and pythermalcomfort to offer a complete solution for urban environmental analysis. A key application of pymdu is outdoor thermal comfort analysis, enabling the simulation and optimization of urban spaces to improve the well-being of residents.
Documentation
https://rupeelab17.github.io/pymdu/
Installation
https://rupeelab17.github.io/pymdu/installation/
Citations
If you reuse or adapt any of the work from this GitHub repository, please ensure to properly cite this reference. Proper attribution helps maintain the integrity of the original work and supports the contributors. Thank you!
Martinez, S., Vellei, M., Rendu, M., Brangeon, B., Griffon, C., & Bozonnet, E. (2025). A methodology to bridge urban shade guidelines with climate metrics. Sustainable Cities and Society, 124 link
Martinez, S., Bozonnet, E., Rendu, M., & Brangeon, B. (2024). Modèle de données urbain pour l’étude de la surchauffe des quartiers. link
Funding
This project has received funding from the France Relance program under the agreement number ANR-21-PRRD-0010-01. This project is supported by funding granted to the Tipee Platform as part of the LRTZC project / Task 3.1.1 (Programme d'Investissements d'Avenir) by the Banque des Territoires, coordinated by the urban community of la Rochelle, France. We strongly acknowledge the support provided for the development and implementation of this work!
Team
Created by Tipee and LaSIE, as part of the joint laboratory RupeeLAB.
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