Replication Pack - Assessing the Health Potential of Parks in 35 Cities Worldwide

Data

• lexicon.csv The lexicon of OSM tags and the corresponding health-promoting activity category.
• scores_cities.csv Park health scores of all cities.
• fingerprints_cities.csv All raw counts of elements and spaces in the parks of all cities.
• ignored_keys.txt Ignored OSM Keys
• ignored_values.txt Ignored OSM Values

All files can be found in the data folder.

Setup

• Install Python 3.9.
• Install a current version of R
• Install and start a couchDB
• Install Python dependencies: pip install -r requirements.txt
• Install R dependencies: Rscript dependencies.R

Scripts:

• curl -X PUT http://<USERNAME>:<PASSWORD>@127.0.0.1:5984/osm_tags_cache_osmium_<CITY_NAME> create a database for each city
• 1-osm.py: Extracts the parks and their elements and spaces from OpenStreetMap and stores them in a couchDB. Example invocation: python 1-osm.py --couchdb http://<USERNAME>:<PASSWORD>@127.0.0.1:5984 --city vienna --osm_id 109166 --region europe/austria
• 2-park_fingerprints.py: Counts the elements and spaces within each park. Example invocation: python 2-park_fingerprints.py --couchdb http://<USERNAME>:>PASSWORD>@127.0.0.1:5984 --city vienna
• 3-park_scores.R: Compute the park health scores. Example invocation: Rscript 3-park-scores.R --city_name vienna

Visualization

The visualization folder contains a web-based interface to explore the park scores. It can be viewed by opening the index.html file.