This project folder is the backbone for the Data Ambassadors Parking Project, curated by DSSG. The goal of this repository is to collect and analyse parking data by the district Friedrichshain-Kreuzberg, in order to generate ideas and evaluate data for the upcoming hackathon by DSSG in November 2021.
- How do the officially counted parking spots by the district, registered cars and counted cars by the Cartagger project compare?
- Do provided parking spots per LOR correlate with age?
- Do provided parking spots per LOR correlate with background of inhabitants?
- Do provided parking spots per LOR correlate with gender?
- How do parking zones influence parking in Friedrichshain Kreuzberg?
- (Visualisation of parking spaces for disabled persons - how does that correlate with other demographics?)
--> maybe we have to reframe that a bit - I don't think we should only look at correlations but patterns within the different datasets.
- LOR Districts Friedrichshain-Kreuzberg https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/lor_friedrichshain_kreuzberg.GeoJSON
- Official Counted Cars in Friedrichshain-Kreuzberg By Street - Incomplete (Kindly Provided By Friedrichshain-Kreuzberg) https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/counted_parking-fk.geojson
- Estimated Parking Lanes and Parking Count for the District Friedrichshain-Kreuzberg based in OSM data - Complete https://github.com/tifa365/data-ambassadors-parking-project/blob/97671bb7f6b66cd291724b8bb85551402dc1cb9a/data/raw/friedrichshain-kreuzberg/qgis-python-parking-spot-estimation/data/parking_lanes.geojson
- Projected Parked Cars onto Parking Lanes in Friedrichshain-Kreuzberg based on OSM data https://github.com/tifa365/data-ambassadors-parking-project/blob/97671bb7f6b66cd291724b8bb85551402dc1cb9a/data/raw/friedrichshain-kreuzberg/qgis-python-parking-spot-estimation/data/parking_kfz.geojson
- Demographic Data For Friedrichshain-Kreuzberg, "Age" and "National Background" in two separate files https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/demographics_age_of_inhabitants_friedrichshain_kreuzberg.csv, https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/demographics_nationalities_lor_fk.csv
- Registered Cars per LOR in Friedrichshain-Kreuzberg https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/registered_cars_per_lor_fk.geojson.GeoJSON
- Official Parking Spots for Disabled Persons In Friedrichshain-Kreuzberg https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/parking_spaces_for_disabled_persons_in_fk.geojson
- Paid Parking Zones in Friedrichshain-Kreuzberg https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/paid_parking_zones_friedrichshain_kreuzberg.geojson
- Counted Cars in Friedrichshain-Kreuzberg From Satellite Images Counted By Volunteers (The Cartagger Project). Aerial Images Were Captured between 1th and 6th of April 2019. More Info On https://github.com/hanshack/car-tagging-data-berlin https://github.com/tifa365/data-ambassadors-parking-project/blob/main/data/raw/friedrichshain-kreuzberg/counted_cars_cartagger_project.geojson
- Reference data: Neukölln data? (all the raw data just in case one wants to compare→ data quality) https://github.com/tifa365/data-ambassadors-parking-project/tree/main/data/raw/neukoelln
- (Possibly Overpass API Tags and view for public transport