Urban Morphology Measuring Toolkit
See the code
Momepy is a library for quantitative analysis of urban form - urban morphometrics. It is part of PySAL (Python Spatial Analysis Library) and is built on top of GeoPandas, other PySAL modules, and networkX.
momepy stands for Morphological Measuring in Python
Some of the functionality that momepy offers:
Momepy aims to provide a wide range of tools for a systematic and exhaustive analysis of urban form. It can work with a wide range of elements, while focused on building footprints and street networks.
Comments, suggestions, feedback, and contributions, as well as bug reports, are very welcome.
The package is currently maintained by @martinfleis and @jGaboardi.
A quick and easy getting-started guide is part of the User Guide.
Documentation of momepy is available at docs.momepy.org.
tessellation['area_simpson'] = momepy.simpson(tessellation.area, contiguity_k3)

G = momepy.straightness_centrality(G)

To cite momepy please use the following software paper published in the JOSS.
Fleischmann, M. (2019) ‘momepy: Urban Morphology Measuring Toolkit’, Journal of Open Source Software, 4(43), p. 1807. doi: 10.21105/joss.01807.
BibTeX:
@article{fleischmann_2019,
author={Fleischmann, Martin},
title={momepy: Urban Morphology Measuring Toolkit},
journal={Journal of Open Source Software},
year={2019},
volume={4},
number={43},
pages={1807},
DOI={10.21105/joss.01807}
}
You can install momepy using Conda from conda-forge (recommended):
conda install -c conda-forge momepy
or from PyPI using pip:
pip install momepy
See the installation instructions for detailed instructions. Momepy depends on the Python geospatial stack, which might cause some dependency issues.
Contributions of any kind to momepy are more than welcome. That does not mean new code only, but also:
All contributions should go through our GitHub repository. Bug reports, ideas, or even questions should be raised by opening an issue on the GitHub tracker. Suggestions for changes in code or documentation should be submitted as a pull request. However, if you are not sure what to do, feel free to open an issue. All discussions will then take place on GitHub to keep the development of momepy transparent.
If you decide to contribute to the codebase, ensure that you are using an up-to-date main branch. The latest development version will always be there, including the documentation (powered by sphinx).
Details are available in the documentation.
If you have a question regarding momepy, feel free to open an issue or a new discussion on GitHub.
Axel and Margaret Ax:son Johnson Foundation as a part of “The Urban Form Resilience Project” in partnership with the University of Strathclyde in Glasgow, UK.
UK Research and Innovation (UKRI) through the Economic and Social Research Council's grant “Learning an urban grammar from satellite data through AI”, project reference ES/ T005238/1.
Charles University’s Primus programme through the project "Influence of Socioeconomic and Cultural Factors on Urban Structure in Central Europe", project reference PRIMUS/24/SCI/023.
Copyright (c) 2018-, Martin Fleischmann and PySAL Developers
64 followers · starred Mar 2024
1,589 followers · starred Aug 2019
19 followers · starred Feb 2025
19 followers · starred Sep 2021
Urban Morphology Measuring Toolkit
See the code
Momepy is a library for quantitative analysis of urban form - urban morphometrics. It is part of PySAL (Python Spatial Analysis Library) and is built on top of GeoPandas, other PySAL modules, and networkX.
momepy stands for Morphological Measuring in Python
Some of the functionality that momepy offers:
Momepy aims to provide a wide range of tools for a systematic and exhaustive analysis of urban form. It can work with a wide range of elements, while focused on building footprints and street networks.
Comments, suggestions, feedback, and contributions, as well as bug reports, are very welcome.
The package is currently maintained by @martinfleis and @jGaboardi.
A quick and easy getting-started guide is part of the User Guide.
Documentation of momepy is available at docs.momepy.org.
tessellation['area_simpson'] = momepy.simpson(tessellation.area, contiguity_k3)

G = momepy.straightness_centrality(G)

To cite momepy please use the following software paper published in the JOSS.
Fleischmann, M. (2019) ‘momepy: Urban Morphology Measuring Toolkit’, Journal of Open Source Software, 4(43), p. 1807. doi: 10.21105/joss.01807.
BibTeX:
@article{fleischmann_2019,
author={Fleischmann, Martin},
title={momepy: Urban Morphology Measuring Toolkit},
journal={Journal of Open Source Software},
year={2019},
volume={4},
number={43},
pages={1807},
DOI={10.21105/joss.01807}
}
You can install momepy using Conda from conda-forge (recommended):
conda install -c conda-forge momepy
or from PyPI using pip:
pip install momepy
See the installation instructions for detailed instructions. Momepy depends on the Python geospatial stack, which might cause some dependency issues.
Contributions of any kind to momepy are more than welcome. That does not mean new code only, but also:
All contributions should go through our GitHub repository. Bug reports, ideas, or even questions should be raised by opening an issue on the GitHub tracker. Suggestions for changes in code or documentation should be submitted as a pull request. However, if you are not sure what to do, feel free to open an issue. All discussions will then take place on GitHub to keep the development of momepy transparent.
If you decide to contribute to the codebase, ensure that you are using an up-to-date main branch. The latest development version will always be there, including the documentation (powered by sphinx).
Details are available in the documentation.
If you have a question regarding momepy, feel free to open an issue or a new discussion on GitHub.
Axel and Margaret Ax:son Johnson Foundation as a part of “The Urban Form Resilience Project” in partnership with the University of Strathclyde in Glasgow, UK.
UK Research and Innovation (UKRI) through the Economic and Social Research Council's grant “Learning an urban grammar from satellite data through AI”, project reference ES/ T005238/1.
Charles University’s Primus programme through the project "Influence of Socioeconomic and Cultural Factors on Urban Structure in Central Europe", project reference PRIMUS/24/SCI/023.
Copyright (c) 2018-, Martin Fleischmann and PySAL Developers
64 followers · starred Mar 2024
1,589 followers · starred Aug 2019
19 followers · starred Feb 2025
19 followers · starred Sep 2021