1. CREATING LAND USE PROFILES.
If we are going to produce a map showing all of the potential land usages in a given area, we must first create, for each type of land use, a set of parameters, such as slope, orientation to sun or prevailing winds, soil constituents, underlying minerals, water supply and many others that are necessary or desirable for the usage to be implemented on any tract of land under examination. Some parameters will be numerical, such as a slope flatter than 1 in 20. Some will be boolean (Yes/no values) indicating the presence or otherwise of desired minerals. Others will consist of one or more selections from an alphabetical list of numerical or alphabetic values. A profile can be drawn up for any given usage and it will list the relevant parameters and specify for each one the range of values appropriate for that usage. One could take this methodology further and create a number of profiles ranging from the optimal down to the point where the usage should not be considered at all for any land matching the profile, simply by varying the numerical values or ranges of the parameters. The sub-optimal profiles could be used in aggregating information about any parcel of land being analysed
2. IDENTIFYING LAND THAT MATCHES PARTICULAR PROFILES.
Because any particular tract of land may be suitable in varying degrees for several different usages and it is necessary to try and identify all possible locations for human involvement, a comprehensive set of statistics must be tabulated for the entire country. By scanning these statistics for the occurrence of combinations of parameter values which match usage profiles, a map of potential land usage may be obtained. The methodology may be refined by varying the required property values on a patterned or trial-and-error basis.
In years gone by, recording the physical characteristics of a tract of countryside required the presence on the ground of many human beings such as surveyors, geologists and the like. Any research on the lines outlined above would be an impossibly expensive undertaking. With the development of satellite imaging, however, a wealth of data is now available for investigation as any visit to Google Earth will testify. There is also much software around to examine this data and extract the values for particular parameters. Where the required software does not exist, there is great scope for research and development of new products.
It is suggested that a grid of (say) 1 km square be laid over the entire land mass of Australia and each grid element be identified uniquely by GPS co-ordinates. The values of all parameters observed in each grid element should be noted and tabulated. For any given land usage, the tables should be scanned for combinations of parameter ranges which fit within the profile(s) of that usage. This should result in a list of land usages appropriate for the grid element. If multiple profiles are available, the various usages in the list can be ranked (Note 1).
3. IDENTIFYING SETTLEMENT LOCATIONS.
If clusters of grid elements can be identified where multiple types of land usage are close to optimal levels, they may be considered “hot spots” suitable for consideration as locations for human settlements. If they are near an existing settlement, it may be investigated to see whether returns from the optimal usage of the land (assuming usage is currently sub-optimal) would either support the settlement in its current configuration or generate a return justifying the upgrading of the land usage and the expansion of that settlement.
In the 1970s, while working for a highly-regarded town planning consultancy, I was involved in a master plan for the Molonglo Valley in the ACT. An analysis of the Valley was conducted, using a limited version of the methodology suggested here. Remarkably, it was carried out on a desktop microcomputer with 16 Kbytes (!) of memory and two audio cassettes for program and data storage. The programming language was a version of BASIC. Fortunately, the machine was quite sophisticated in that code not required immediately could be overlaid with other code, so that quite a large program could be processed.
A grid was laid over various maps of the Valley and a team of university students computed the values of the various parameters within each element and entered them on marked-sense cards (similar to punched cards, but where boxes were marked in pencil to assign binary values). These were then processed and a plotter was used to cross-hatch each element in the grid with a pattern identifying the optimal usage for the land. The grids were then laid over the maps and the underlying land assigned the appropriate zoning codes.
The scale of the analytical work required is, of course, much greater than the modest project which I undertook (which was undoubtedly more interesting in its analytic sophistication than its scale), but there are avenues for marshalling the number of people required to participate. To name only one example, “Re-engineering Australia” at rea.org.au finds projects to interest senior school pupils in engineering and scientific careers and may be able to set up some teams of analysts. I have no connection to this organisation, though I have now become a follower. The choice of name for our activities was entirely accidental, though perhaps serendipitious if this all comes to fruition