State-of-the-Art simplification of street network geometry with Python

The curated & tested code base for the project & publication, including:

• The novel algorithm(s) developed and demonstrated; and
• Utility and plotting functionality to support the publication and algorithm(s)

Parameterized notebooks.

• /preprocessing/: workflows used to preprocess raw data (clipping and removing degree 2 nodes)
• /methods/: exploration of different simplification methods, including the new method proposed here, neatnet
• /evaluation/: comparative evaluation of each simplification method
• /usecases/: collection of use cases
• /typology/: exploration of different types of face artifacts, foundational to the neatnet algorithm
• /archive/: archived notebooks

Curated data in parquet format for 6 example urban areas

Each FUA directory contains (or will contain) the following items housing bespoke data:

• manual/
• no_degree_2/
• original/
• parenx/
• polygons/

Observations & hightlights from each package.

• osmnx.md
• cityseer.md

Demonstration plots generated through simplification_protocol.ipynb.

This directory only exists once that notebook has been run locally.

Additional resources and previous related research.

Demonstration visualizations on specific types of urban form.

• 809 (Douala)
  • cityseer (from notebooks/cityseer_overview_gaboardi.ipynb)
    • examples as douala_{1-5}.png
• 869 (Auckland)
  • averagedegree (from notebooks/evaluate_h3cells.ipynb)
  • totallength (from notebooks/evaluate_h3cells.ipynb)
• 1656 (Liège)
  • cityseer
    • parallel_edges_1_midline_False.mp4
    • parallel_edges_1_midline_True.mp4
    • parallel_edges_2_midline_False.mp4
    • parallel_edges_2_midline_True.mp4
    • parallel_edges_3_midline_False.mp4
    • parallel_edges_3_midline_True.mp4
  • osmnx
    • highway.mp4
    • intersection.mp4
    • parkinglot.mp4
    • roandabout.mp4
  • points.json - use case locations

This project uses reproducible multi-platform environments using Pixi. To create an environment able to run all the code in the repository, clone the repository and install the locked environment using:

pixi install

To install the development environment allowing testing:

pixi install -e tests

If you would like to run the tests, use the tests Pixi environment:

pixi run -e tests pytest

Installing pre-commit hook to the env:

pixi run pre-commit install

The work 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.