Using Australia’s Land Use Mapping Dataset

Recently we were sub-contracted by Tessele Consultants to assess the potential for the use of bio-based soil conditioners and fertilisers around 127 red meat processing establishments across Australia (Figure 1). The project focus was to investigate resource recovery opportunities aligned with Net Zero and Circular Economy principles. We looked at the potential to use bio-based soil conditioner and fertiliser, specifically dried digestate pellets and/or biochar, recovered from red meat processors’ wastewater sludge in mining, forestry, municipal, natural resource management (NRM) and Landcare activities near each establishment. We identified the Catchment scale land use of Australia mapping (ABARES, 2021) dataset as a suitable tool. This article focuses on how that dataset was used.

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Figure 1 - Intersection of land use data with nominal 50 kilometre demand catchments for potential resource recovery facilities

Our first step was to determine if the mapping data was suitable for the purpose. The Catchment scale land use of Australia mapping dataset is undertaken by each of the 8 States and Territories theoretically down to 50 by 50 metre grids using the Australian Land Use and Management (ALUM) classification standard (ABARES, 2016). The ALUM classification system uses 6 primary land use classifications, under which are nested 32 secondary classifications and 159 tertiary classifications. There is considerable variation across and within States in the date, scale and accuracy of mapping.

Because the project was at a conceptual stage the objective was to get a ball park estimation of whether there could be sufficient demand near the potential resource recovery establishments for the bio-based soil conditioner and fertiliser. We were confident the mapping would be sufficient though we were aware there were other industry or issue specific datasets which could be used if necessary.

After mapping the location of the establishments and cleaning the dataset we applied a 10 kilometre radius for the catchment, but after preliminary analysis we determined a 50 kilometre radius catchment would be more realistic while also aligning to Circular Economy principles. Land use in the catchment of each establishment was analysed and a catchment land use map (figure 2) and associated data analysis generated.

Figure 2 - Land use in each demand catchment is generally mapped using the Australian Land Use Management Classification (ALUM)

Land use sectors identified in the brief were quite broad, so we further categorised these into 10 demand segments. Indicative application rates for dried digestate pellets and biochar were determined for each segment based on a literature review and a market survey. The indicative supply from each establishment was compared with the indicative demand for each of the 10 segments to identify whether supply would exceed demand for each segment or vice versa. Results indicated that in the 50 kilometre catchment of each establishment there was likely demand exceeding potential supply.

In selected cases we assessed other datasets to further our understanding of potential. For example, bio-based soil conditioner and fertiliser could be used to repair land affected by degradation issues such as soil acidity, erosion, and salinity. So we assessed the level of relevance of these issues in the vicinity of each establishment.  

Our analysis indicated there were a wide variety of potential users of bio-based soil conditioner and fertiliser in the 50 kilometre catchment of each establishment and that in most cases the demand would significantly exceed supply. We found that the Australian land use dataset was a useful resource to use at a regional scale and potentially even finer scales. While the focus of this project was evaluating resource recovery and re-use opportunities for a specific industry sector, the land use dataset could be used for a range of other land use planning and natural resource management (NRM) projects.