Optimizing the number and location of public litter bins using Geographic Information Systems

The distance that users need to walk to public litter bins is a strong predictor of littering behaviour. However, there is limited research that combines the spatial allocation of bins and users' preferences on access to litter bins. The goal of my thesis was to optimise the number and location of public litter bins by assessing the distance users are willing to walk to bins and incorporating these distances in a network analysis in Geographic Information Systems (GIS). Macquarie University, Sydney, New South Wales was the case study area. 200 face-to-face surveys were conducted to ascertain user opinion on the distances they were willing to walk to bins. I used the survey outputs to deveop 56 scenarios that provide managers of waste with a range of options to meet demand and user preferences, including allocating additional bins to the current distribution, redistributing bins and reducing the number of bins. I found that most users were willing to walk between 38 and 80 metres. Due to the heterogeneity of population distribution, I found that the most appropriate network analysis tools were maximise attendance and target market share. The approach I developed could be used to optimise the number and location of public litter bins at other locations of similar scale.