Recyclable Materials Transportation - Spatial Decision Support System

The large distances between major population centres in Queensland pose a challenge to the efficient movement of recyclable materials. These large distances impact on existing recovery facilities or recycling plants and affect the overall viability of this recycling industry, with low incentives for shires to operate such schemes and private recyclers to collect material from these areas.

Transport costs vary as a proportion of all costs associated with the recycling of waste materials. But they are typically 30-60 percent of the overall costs of recycling.

Traditional approaches to developing a detailed logistics model rely heavily on spreadsheet and database analysis, with results being presented in report format supported by tabular information and static maps. In this case, GHD recognised that for the model to fully meet the requirements of our client the Queensland Environmental Protection Authority (EPA), we needed to allow the user to interactively test scenarios using multiple criteria, calculating and displaying the viable collection catchments in real-time.

To meet this requirement, GHD chose to employ Geographic Information Systems (GIS) technology to develop a decision support solution that would allow the EPA to fully leverage the significant volume of research and analysis that went into the development of the logistics model.

GHD implemented the logistics model as a desktop-based decision support system. This was to enable the EPA to interactively evaluate logistics scenarios for each material type based on transportation costs, material recovery costs and end user costs. The system considers a number of modelled and user-entered parameters, supporting the testing of specific scenarios.  

In comparison to standard spreadsheet-based models, the GHD approach delivers the following benefits:

• Responsivness, allowing near real-time evaluation of scenarios based on user selected parameters
• Ease of use, with little or no reliance on GIS experience for operation and the ability to produce intuitive, high-quality visual outputs
• Scaleablity in terms of functions and the models being used
• Ability to support maintenance/upgrade of both spatial and model parameter data
• A solution based on standard technologies that can be easily disseminated and further extended as required