Brisbane Parking Occupancy Forecasts for 2025

2025 forecasts for Brisbane City Council's paid parking areas, compiled using advanced analytics and machine learning. The dataset is intended for developers to build tools providing residents and visitors with likely parking availability. It is linked to meter location data via the MOBILE_ZONE field.

Use Cases

• Develop web or mobile applications that display likely parking availability using the occupancy forecast data.
• Link occupancy forecasts to specific parking meter locations via the MOBILE_ZONE identifier for spatial analysis.
• Analyze the relationship between forecasted occupancy and environmental or traffic data sources mentioned in the methodology.
• Build models to validate or improve the machine learning-generated forecasts using the underlying survey and transaction data.

Strengths

• Data covers all of Brisbane City Council's parking meters.
• Forecasts are generated using machine learning on multiple data sources including occupancy surveys and meter transactions.
• Includes a metadata resource detailing all data attributes and their descriptions.

Limitations

• Specific data volume (rows, columns) and temporal coverage details are not provided in the input.
• Core forecast data attributes are not listed; users must consult the separate metadata file to understand the schema.
• Primary data format is HTML, which may require parsing for programmatic use compared to structured formats like CSV.

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 survey data, parking meter transaction data, and other traffic and environmental data.

Time Range

2025

Freshness

Last updated March 2026.

Geography

Brisbane, Queensland, Australia.