Cities are complex urban environments. Detailed fine grain data is increasingly needed to provide the evidence base for integrated and locally focused planning and investment decisions.
We are a market leader in producing small area land use forecasts to aid decision making across government and the private sector.
Small Area Model (SAM) creates a suite of forecast variables which are:
- Estimated using a combination of ‘top-down’ and ‘bottom-up’ methodologies, ensuring that macroeconomic drivers are integrated with micro spatial data and trends
- Disaggregated to a fine-grain spatial scale, allowing for custom geographies to be defined based on the scope of analysis, such as an activity centre or renewal precinct
- Developed using a dynamic and systematic algorithm which enables robust scenario testing and impact analysis
- Presented via a web-accessible and interactive platform which allows for analysis and visualisation.
A vital aspect of SAM is that it can produce these forecasts using a transparent set of inputs, assumptions, and techniques. These parameters can, therefore, be altered to create sets of clearly defined scenarios, which are a key focus of policy evaluation.
SAM includes detailed information across three key variable types. These are:
- Dwellings and population, which includes a range of household and demographic attributes
- Employment, which includes labour force status, industry and occupation attributes by place of usual residence and place of work
- Students, which includes primary/secondary/tertiary student attributes by education provider type, place of usual residence and place of institution.