Description
The San Francisco Bay Area is one of the most progressive transportation regions in the deployment of high-capacity transit and use of policies to encourage active transportation. Yet like many other metro regions, there remains a dearth of knowledge on the abundance and location of parking infrastructure supply. Parking infrastructure remains one of the least catalogued infrastructure but is perhaps the most spatially dominating set of assets. This research estimates the extent and location of parking supply, including on-street and off-street spaces for the nine-county Bay Area. This parking space inventory is the most detailed assessment of parking infrastructure produced for the Bay Area, and represents an important starting point for addressing the impacts of and crafting policy for future transportation goals.
Key findings from the parking census include:
- The nine-county Bay Area has 15 million parking spaces, enough parking to wrap around the planet 2.3 times.
- Twenty percent of the region's unincorporated land is devoted to driving and storing cars.
- There are approximately 2.4 spaces for every car and approximately 1.9 parking spaces for every person in the Bay Area.
This technical report, and accompanying San Francisco Parking Census dataset, was the result of a partnership between MTI and SPUR, a nonprofit public policy organization in the San Francisco Bay Area.
Publication Date
2-2022
Publication Type
Report
Topic
Planning and Policy, Sustainable Transportation and Land Use
Digital Object Identifier
10.31979/mti.2022.2123
MTI Project
2123
Mineta Transportation Institute URL
https://transweb.sjsu.edu/research/2123-Bay-Area-Parking-Inventory
Keywords
San Francisco, parking, inventory, census, urban
Disciplines
Infrastructure | Urban Studies and Planning
Recommended Citation
Mikhail Chester, Alysha Helmrich, and Rui Li. "Inventorying San Francisco Bay Area Parking Spaces: Technical Report Describing Objectives, Methods, and Results" Mineta Transportation Institute (2022). https://doi.org/10.31979/mti.2022.2123
Dataset