How CoGC used Forecaz to build an evidence-based Planning and Urban Growth model
- Bradley Rasmussen
- Apr 1, 2025
- 3 min read
Updated: 2 days ago
CASE STUDY BACKGROUND
The City of Gold Coast (CoGC) needed a robust, evidence-based modelling framework to support long-term capital works planning and financial modelling across a rapidly growing city. In partnership with Griffith University’s Cities Research Institute, CoGC set out to develop a repeatable growth projections methodology that could be shared with other local governments and the State, supported by an Innovation and Improvement Grant from the Queensland Government.
In 2018, Forecaz was selected as the preferred modelling platform after an independent options analysis, and became the core engine behind CoGC’s new Planning and Urban Growth (PUG) model.
Evidence-based growth modelling for smarter infrastructure planning
The challenge of demand modelling
CoGC required a planning tool that could:
Align with statutory requirements, including LGIP Statutory Guideline 03/14.
Integrate both top-down and bottom-up development projections.
Provide reliable, parcel-level insights for residential and non-residential growth.
Support long-term capital works, infrastructure prioritisation, and scenario testing.
Existing approaches were not designed to combine these needs into a single, repeatable framework, and did not fully leverage the latest research or data science techniques.
THE AIM OF THE PROJECT: Create a robust, evidence-based urban growth modelling framework to support long-term capital works and infrastructure planning for the City of Gold Coast. It also sought to develop a repeatable growth projections methodology—validated through research—that could be shared with other local governments and the State. |
Enabling predictive modelling for evidence-based infrastructure planning
After an independent options analysis, CoGC chose the Forecaz modelling tool as the platform for the PUG model. Forecaz offered the flexibility to incorporate planning assumptions, statutory requirements, and advanced analytics in one environment, while remaining usable for planners and analysts across Council.
Building the Planning and Urban Growth (PUG) model
Working alongside CoGC, Forecaz supported the development of a comprehensive urban growth model that:
Aligned with LGIP Statutory Guideline 03/14, ensuring compliance with statutory planning and infrastructure requirements.
Integrated both top-down and bottom-up growth projections to capture strategic growth patterns as well as local parcel-level development propensity.
Analysed densities and land-use outcomes across neighbourhood centres and development zones.
Included staged development for large sites to provide realistic, time-phased growth projections.
In collaboration with Griffith University’s Cities Research Institute, CoGC used Forecaz to implement and validate a repeatable growth projections methodology, designed so it could be used by other local governments and the State.
Data, alignment and advanced modelling - Aligning with official projections
To ensure consistency with State forecasts, the PUG model was sequenced and calibrated to:
Match the Queensland Government Statistician’s Office (QGSO) 2018 medium series population projections for residential growth.
Align non-residential growth with employment projections from the Department of Transport and Main Roads and the National Institute of Economic and Industry Research.
Bayesian Network models for improved accuracy
Building on research led by Griffith University, the PUG model was enhanced to use separate Bayesian Network (BN) models for:
Residential development.
Non-residential development.
This separation improved predictive accuracy by recognising that residential and non-residential growth follow different drivers and patterns, while still being modelled within a consistent Forecaz framework.
Adding continuous learning with Machine Learning
To further improve predictive performance over time, Forecaz implemented an automated Machine Learning (ML) system that:
Continuously learns from the BN models and approved development applications.
Updates estimates of development propensity at the parcel level as new approvals and outcomes are observed.
Allows CoGC to refine projections without rebuilding the entire model from scratch.
This creates a feedback loop where the model becomes more accurate and responsive as more data is collected.
Outcomes
The PUG model, powered by Forecaz, has become a core tool for the City of Gold Coast, supporting:
Land use analysis across neighbourhood centres and development zones.
Scenario testing for different growth, zoning, and infrastructure assumptions.
Assessment of major infrastructure initiatives, including projects such as the Light Rail extension.
By grounding projections in statutory guidelines, official population and employment forecasts, and ongoing model learning, CoGC can plan capital works and infrastructure with far greater confidence.
Forecaz continues to work closely with the City of Gold Coast to:
Provide ongoing technical support and model maintenance.
Enhance the PUG model as new data, policies, and growth scenarios emerge.
Support internal teams in using the model for planning, infrastructure, and investment decisions.
The PUG model now serves as a benchmark for evidence-based urban growth modelling and has demonstrated a scalable, repeatable approach that can be adopted by other councils and agencies.
