Active transport accessibility to potential mobility hubs in Salzburg province

This repository presents a workflow to assess and rank the active transport accessibility to potential mobility hubs. It computes accessibility as the share of the population inside the catchment area of the hub that can reach the hub using only streets which are suitable for the corresponding active transport mode, without taking a unacceptable detour. It then shows how different definitions of what a suitable street is, and different threshold for detour acceptance, influence the computed accessibility levels. The workflow is presented by means of an interactive notebook.

DISCLAIMER: The potential mobility hub locations used in the examples are not part of any concrete implementation plans, but chosen as examples to showcase the workflow

Requirements

Software

The interactive notebook can be started through a Docker container in which all required software dependencies are installed. This means you only have to have Docker installed. See here for the installation instructions. In addition, you will need Git to clone this repository on your local disk.

Data

The notebook requires pre-processed input data in RData format, meaning that they can be directly loaded as R objects into an R workspace. These data are stored in the data folder of this repository and contain for each hub and each active transport mode (i.e. bike and walk) the following information:

Layer	Description
hub	The name and location of the hub
network	The complete street network around the hub
households	All household locations in proximity of the hub
suitable_networks	The bikeable/walkable networks around the hub for different bikeability/walkability thresholds
connected_households	The household locations with bikeable/walkable access to the hub for different bikeability/walkability thresholds and different detour factors

The source data from which the pre-processed data are inferred are listed below. Some of them are proprietary. Data pre-processing can be reproduced with the script process.R in directory scripts, given you have the source data available. Please contact mobilitylab@plus.ac.at for more information.

Data	Description	Source
hubs.csv	The examplary hub locations in Salzburg province	Provided by Research Studio iSpace
salzburgerland-netascore-20240123.gpkg	Street network of the Salzburg province with computed bikeability and walkability indices for each street	Created using the NetAScore Toolbox, version v1.0.1. The mode profiles for respectively the bike and walk modes can be found in directory profiles
salzburgerland-population.gpkg	Population data of the Salzburg province for the year 2016 on a 100x100m grid	Purchased from Statistics Austria
ADRESSE.csv	Address locations in Austria for the year 2021	Openly available through this link

Usage

Running the notebook through a Docker container

The interactive notebook presenting the analysis can be started using Docker. This repository includes a Dockerfile from which a container can be build that has all required software dependencies installed. Running that container will run the interactive notebook on port 3838.

First, clone this repository and navigate to the cloned directory:

git clone https://github.com/plus-mobilitylab/accmobhub-salzburgerland.git
cd accmobhub-salzburgerland

Then, build the Docker image:

docker build -t accmobhub .

Then, run a Docker container using that image:

docker run --rm -p 3838:3838 accmobhub

Finally, navigate in your browser to http://localhost:3838/. Here you should see the interactive notebook.

Running the notebook directly in RStudio

Alternatively, if you have R and RStudio installed, you can open the R project in RStudio and run the notebook document. You will need to first install the requirements:

install.packages("rmarkdown")
install.packages("knitr")
install.packages("shiny")
install.packages("tidyverse")
install.packages("DT")
install.packages("here")
install.packages("leaflet")
install.packages("plotly")
install.packages("units")
install.packages("sf")
install.packages("sfnetworks")

And unzip the pre-processed data archive:

unzip("data/data.zip")

Exploring the web app

Instead of running the interactive notebook yourself, you can also just explore a hosted version online: https://plusmobilitylab.shinyapps.io/accmobhub-salzburgerland/ To keep the size of the app managable, the content displayed there is a subset of the full content. It only shows bicycle accessibility, for a limited set of potential hub locations.

Acknowledgements

Parts of this research were funded by a commission from Research Studios Austria - iSpace.

License

This project is licensed under the MIT license. For details please see LICENSE.

References

For more background on the underlying methodologies, see our conference paper.