Brisbane Paid Parking Occupancy Forecasts

2026 data from Brisbane City Council provides machine learning forecasts for paid parking availability across all council meters. The dataset is intended for developers to build tools for residents and visitors, and is linked to meter location data via a MOBILE_ZONE field.

Use Cases

• Develop a web or mobile app that displays forecasted parking availability using the MOBILE_ZONE field for location mapping.
• Analyze forecast patterns linked to specific parking meter locations to identify high-demand zones.
• Integrate occupancy forecasts with external traffic or environmental data sources mentioned in the methodology.

Strengths

• Covers all of Brisbane City Council's paid parking meters.
• Forecasts are generated using advanced analytics and machine learning on multiple data sources.
• Data is linked to a separate meter locations dataset for spatial context.

Limitations

• Specific data volume (row count, column count) and temporal coverage are not provided in the input.
• Core data attributes and sample values are unavailable, requiring users to download metadata separately.

Provenance

Source

Brisbane City Council open data portal (data.brisbane.qld.gov.au).

Collection Method

Compiled using advanced analytics and machine learning on parking occupancy surveys, meter transactions, and other traffic/environmental data.

Time Range

null

Freshness

Last updated March 2026.

Geography

Brisbane, Queensland, Australia.