INTRODUCTION
This chapter gives the background to the review of the ASGC, and the proposed new Australian Statistical Geography (ASG) to replace it.
The current ASGC concepts are based on the work of Professor G.J.R Linge undertaken in the mid 1960s. His urban/rural concepts were applied for the first time to the results of the 1966 Census. The concept of a capital city statistical division (SD) was used for the 1971 Census. A complete restructure of the ABS’s statistical geography, based on Professor Linge’s work, was implemented for the 1976 Census. These concepts and classification rules were formalised to create the ASGC in 1984.
The ASGC has been criticised in the past on a number of grounds:
- it is not stable due to the need to align boundaries with LGAs;
- the definition of urban and rural does not reflect recent developments in settlement patterns, transport and communications;
- the population range of the ASGC units at each level are too great;
- CDs are compromised by the requirement to be the basis for both collecting and publishing statistics;
- it is difficult to relate to other geographic boundaries such as postcodes and electoral divisions;
- and, it is not based on sufficiently objective criteria.
These criticisms were addressed in a review of the ASGC in 1996-1997 led by Professor Graham Hugo, but many of the recommendations were not implemented because the data and IT infrastructure did not exist. Since 1997 there have been several developments that have changed the situation. These include: the Geocoded National Address File (G-NAF) developed by PSMA Australia; the use of Intelligent Character Recognition and Automatic Coding to capture and cost-effectively code large volumes of data: and improvements in Geographic Information Systems generally.
In response to these developments the ABS developed Mesh Blocks, which will greatly improve the ability to create, disseminate and analyse spatial data and over time. The review is the next step: to develop more appropriate ways for the ABS to present spatial data to better meet the needs of the contemporary data user.
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