Resources

The City of Gold Coast partnered with Forecaz and Griffith University to develop an evidence-based Planning and Urban Growth (PUG) model, aligning with statutory guidelines and official QGSO projections. The model combines Bayesian Networks and Machine Learning to predict parcel-level development, supporting land use analysis, scenario testing, and major infrastructure planning such as the Light Rail extension.

The City of Gold Coast's PUG Model, built on Forecaz's Forecaz platform in collaboration with Griffith University, received a Commendation at the 2024 PIA Queensland Awards for Planning Excellence. The judges recognised the project's technical innovation in AI-driven urban growth forecasting, which gives Gold Coast planners a property-level, spatially sequenced view of both residential and non-residential development.

Urban Utilities partners with Forecaz to deliver data-driven growth planning. With SE Qld’s rapid expansion placing increasing pressure on critical water and sewerage infrastructure, UU needed a smarter, spatially detailed way to plan for growth. Using the Forecaz platform, UU now models urban development at property level, bringing data accuracy and operational efficiency to long-term infrastructure forecasting.

Bradley Rasmussen, CEO of Forecaz, demonstrated to the SEQ's Housing Diversity Community Practice group how the Forecaz AI-driven Bayesian Network modelling platform assesses each parcel against weighted development factors to produce a property-level Development Desirability Index, giving councils a spatially grounded, evidence-based view of which lots will actually redevelop under higher zoning densities rather than relying on theoretical zoning capacity assumptions.

Toowoomba Regional Council partnered with Forecaz to transform its strategic growth planning from static projections to dynamic, parcel-level scenario modelling. By integrating spatial datasets, development layers, and AI-driven Bayesian Network models, TRC gained the tools to test policy impacts, align infrastructure investment with forecasted demand, and make defensible, evidence-based decisions — positioning the region at the forefront of intelligent urban planning.

Partnering with Unitywater, Forecaz developed the Demand Modeller and Tracking Tool (DMaTT)—a geospatial forecasting platform that puts dynamic scenario modelling directly into the hands of planners. Within days, Unitywater can generate property-level forecasts that once took months, optimising over $3 billion in infrastructure assets. The result: faster decisions, smarter investments, and measurable environmental and customer savings.