neatnet: Street Geometry Processing Toolkit
Introduction
neatnet offers a set of tools pre-processing of street network geometry aimed at its simplification. This typically means removal of dual carrieageways, roundabouts and similar transportation-focused geometries and their replacement with a new geometry representing the street space via its centerline. The resulting geometry shall be closer to a morphological representation of space than the original source, that is typically drawn with transportation in mind (e.g. OpenStreetMap).
Examples
A fully-reproducible example can be found in the User Guide.
import neatnet
simplified = neatnet.neatify(gdf)
Installing
You can install neatnet from PyPI or from conda-forge using the tool of your choice:
pip install neatnet
Or (recommended):
conda install neatnet -c conda-forge
Contribution
While we consider the API stable, the project is young and may be evolving fast. All contributions are very welcome, see our guidelines in CONTRIBUTING.md.
Recommended Citations
The package is a result of a scientific collaboration between The Research Team on Urban Structure of Charles University (USCUNI), NEtwoRks, Data, and Society research group of IT University Copenhagen (NERDS) and Oak Ridge National Laboratory.
If you use neatnet for a research purpose, please consider citing the original paper introducing it.
Canonical Citation (primary)
Fleischmann, M., Vybornova, A., Gaboardi, J.D., Brázdová, A., Dančejová, D., 2026. Adaptive continuity-preserving simplification of street networks. Computers, Environment and Urban Systems 123, 102354. https://doi.org/10.1016/j.compenvurbsys.2025.102354
BibTeX:
@article{fleischmann2026Adaptive,
title = {Adaptive Continuity-Preserving Simplification of Street Networks},
author = {Fleischmann, Martin and Vybornova, Anastassia and Gaboardi, James D. and Br{\'a}zdov{\'a}, Anna and Dan{\v c}ejov{\'a}, Daniela},
year = 2026,
month = jan,
journal = {Computers, Environment and Urban Systems},
volume = {123},
pages = {102354},
issn = {01989715},
doi = {10.1016/j.compenvurbsys.2025.102354},
urldate = {2025-10-31},
langid = {english}
}
Repository Citation (secondary)
- Fleischmann, M., Vybornova, A., & Gaboardi, J.D. (2025).
uscuni/neatnet. Zenodo. https://doi.org/10.5281/zenodo.14765801
Funding
The development has been supported by the Charles University’s Primus program through the project "Influence of Socioeconomic and Cultural Factors on Urban Structure in Central Europe", project reference PRIMUS/24/SCI/023.
This package developed & and maintained by:
Copyright (c) 2024-, neatnet Developers
Metadata
Release files for neatnet 0.1.6
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| File | Size | Uploaded | Provenance | Actions |
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|---|---|---|---|---|
| neatnet-0.1.6-py3-none-any.whl | Python 3 | none | any | Details for neatnet-0.1.6-py3-none-any.whl |
Total release size: 25.4 MB
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