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:
- Measuring dimensions of morphological elements, their parts, and aggregated structures.
- Quantifying shapes of geometries representing a wide range of morphological features.
- Capturing spatial distribution of elements of one kind as well as relationships between different kinds.
- Computing density and other types of intensity characters.
- Calculating diversity of various aspects of urban form.
- Capturing connectivity of urban street networks.
- Generating relational elements of urban form (e.g. morphological tessellation).
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.
coverage = momepy.AreaRatio(tessellation, buildings, left_areas=tessellation.area,
right_areas='area', unique_id='uID')
tessellation['CAR'] = coverage.series
area_simpson = momepy.Simpson(tessellation, values='area',
spatial_weights=sw3,
unique_id='uID')
tessellation['area_simpson'] = area_simpson.series
G = momepy.straightness_centrality(G)
To cite momepy please use 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:
- improvements to the documentation and user guide,
- additional tests (ideally filling the gaps in the existing suite),
- bug reports, or
- ideas for what could be added or done better.
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 discussion 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.
The initial release of momepy was a result of a research of Urban Design Studies Unit (UDSU) supported by the Axel and Margaret Ax:son Johnson Foundation as a part of “The Urban Form Resilience Project” in partnership with University of Strathclyde in Glasgow, UK. Further development was supported by Geographic Data Science Lab of the University of Liverpool wihtin Urban Grammar AI research project.
Copyright (c) 2018-, Martin Fleischmann and PySAL Developers