Caution

This project is under heavy development. Do not use.

Bicycle node network loop analysis

This is the source code for the scientific project Bicycle node network loop analysis. The code assesses the quality of a proposed bicycle node network in Denmark via loop census analysis.

Installation

First clone the repository:

git clone https://github.com/mszell/bikenwloops

Go to the cloned folder and create a new virtual environment via mamba using the environment.yml file:

mamba env create -f environment.yml

Then, install the virtual environment's kernel in Jupyter:

mamba activate bikenwloops
ipython kernel install --user --name=bikenwloops
mamba deactivate

You can now run jupyter lab with kernel bikenwloops (Kernel > Change Kernel > bikenwloops).

Data setup

Data of the knudepunkter network comes from BikeNodePlanner: Data for Denmark and BikeNodePlanner.

Step 1: Extract data with BikeNodePlanner: Data for Denmark

• Use BikeNodePlanner: Data for Denmark
• Uncomment the municipalities of your study area in config-municipalities.yml. Several config files are already prepared for copy-pasting in the retrieval/ folder for large study areas like Jutland or Zealand.
• Set all values in config-layers-polygon.yml to ignore. This file is already prepared for copy-pasting.
• Run the run.sh script
• Copy all subfolders of /input-for-bike-node-planner/ into the /data/input/ folder of bike-node-planner

Step 2: Add elevation data with BikeNodePlanner

This step is needed to add elevation data (from dem/dem.tif) to the edges, creating an edges_slope.gpkg file.

• Use BikeNodePlanner
• Run scripts 01 to 04
• Let's call loopspath the data/input path to your project, for example bikenwloops/data/input/funen/
• Copy the file edges_slope.gpkg from bike-node-planner/data/output/elevation into loopspath/network/processed/

Repository structure

├── code                    <- Jupyter notebooks and py scripts
├── data
│   ├── processed           <- Modified data
│   └── raw                 <- Original, immutable data
├── dissemination           <- Material for dissemination
├── plots                   <- Generated figures
├── retrieval               <- Config files for retrieving data
├── .gitignore              <- Files and folders ignored by git
├── .pre-commit-config.yaml <- Pre-commit hooks used
├── LICENSE.txt
├── README.md
└── environment.yml         <- Environment file to set up the environment using conda/mamba