Strategic Freight Forecasts – commodity origin map
Origin and destination models are estimates of the volume of freight based on its entire journey to understand the true origins and destinations. The origin is by statistical areas – here by SA4 which contain a population between 100,000 and 500,000 people.
About the Data
Dataset name: Strategic Freight Movement Model
Data owner: Transport Performance and Analytics, Transport for NSW
Data range: 2016 to 2056
Frequency: 5-year intervals
Description: This visualisation presents the destinations of freight generated within a specific origin at SA4 level. The data can be filtered by year and commodity.
How to use
What does the published freight commodity data measure?
The data measures the total volume of commodities moved on the NSW road and rail network. Volume is measured in tonnes.
The geographical area used to group the data is Statistical Area Level 3 (SA3) and Statistical Area Level 4 (SA4).
- There are approximately 90 SA3s and 30 SA4s in NSW.
- The SA3 and SA4 level is considered to be the appropriate level at which to measure, understand and forecast commodity freight movements for strategic purposes.
For base year of 2016 and forecast years, the total volume of commodities moved on the NSW road and rail network comprises the following freight markets:
- NSW intrastate market:
- Commodity volumes originating in a NSW SA3 and moved to a destination in another NSW SA3;
- Within SA3 market:
- Commodity volumes originating in a NSW SA3 and moved to a destination in the same SA3;
- NSW to interstate market:
- Commodity volumes originating in a NSW SA3 and moved to an interstate destination (and vice versa);
- Interstate market:
- Commodity volumes originating interstate and destined for interstate. An example of VIC originated and QLD destined commodities. This requires travel through NSW.
Is the published 2016 freight commodity data an actual or estimate?
The published 2016 data for total NSW freight volumes is an estimate. While actual data is available for some commodities at certain points along the freight supply chain data for most commodities is estimated.
Data for most commodities is estimated using a range of publicly available sources including Australian Bureau of Agricultural and Resources Economics (ABARES), Australian Bureau of Statistics (ABS), rail and road infrastructure network managers (Sydney Trains, Australian Rail Track Corporation, Country Regional Network, Transport for NSW), industry associations, region and commodity specific studies and companies’ annual reports.
Does the published Transport for NSW data capture freight commodity volumes moved in my Local Government Area (LGA)?
To some extent yes, but it is important to recognise the applicability of the SA3 freight commodity volume data to a particular LGA may vary considerably across the state. This is because SA3 areas are larger than LGA areas.
In some cases, an SA3 will cover two to three LGAs while in other cases an SA3 will cover six to seven LGAs. Generally, the less LGAs per SA3 the more applicable the SA3 data is to each LGA. This is because production and freight activity is not evenly spread across LGAs, particularly in regional LGAs where agricultural commodities (grain, cotton, livestock, logs etc) tend to be consolidated at large terminals, silos or gins located in one LGA.
How is the published Transport for NSW freight commodity growth rate forecasts useful for LGA freight infrastructure planning?
The commodity growth rate forecasts at the SA3 and SA4 level will reflect what is expected to happen in the LGAs. This is because the forecast pattern for underlying commodity production growth is likely to be similar across LGAs. The forecasts are instructive in that they provide strategic guidance on forecast growth in freight volumes at the LGA level. This can assist local councils with future freight infrastructure planning.
For more information on the assumptions and methods behind the forecasts, see the published NSW Freight Commodity Demand Forecasts Report (PDF, 2.76 MB).
The Open Data Hub Freight Forecast excel document provides a disaggregation of the SFM visualisation data by SA3 origin and destination, mode (road or rail), commodity and annual kilotonne value.
- Statistical Area Level 4 (SA4) - the largest sub-State regions in the Main Structure of the Australian Statistical Geography Standard (ASGS). They have been designed for the output of a variety of regional data.
- Further definitions of commodities are available in the Data Dictionary here (PDF, 235.94 KB).
The forecasts that underpin this visualisation are generated from base year estimates for commodity demand in 2016. All 2016 numbers are estimates of actual demand.
The Strategic Freight Movement Model forecasts have been compiled by Transport Performance and Analytics using a mixture of methods including:
- General economic research and literature review as well as specific industry freight investigations (including those on construction materials, waste and forestry).
- Data analysis and statistical modelling.
- Consultation with other agencies including BITRE and Department of Industry NSW.
If you require further assistance, please contact us at firstname.lastname@example.org.