Spatial characteristics and multifactorial driving analysis of fly-tipping bulky waste in Beijing based on the random forest model

The phenomenon of fly-tipping of bulky waste is becoming increasingly serious with the development of economy and the improvement of living standards. The fly-tipping of bulky waste causes a waste stream with a high proportion of good quality recyclable materials and a wide range of social and environmental problems including damaging the environment and aggravating traffic in a megacity like Beijing. In this study, we analyzed the quantitative spatial distribution of fly-tipping bulky waste in Beijing for the first time and identified its driving forces to explore the fly-tipping rule of bulky waste. We used Anselin's Local Moran I method to reveal the spatial characteristics, and Random Forest machine learning method to examine the driving factors based on multiple data sources such as geographical, population and survey data. The results showed that the spatial agglomeration of fly-tipping presented a typical core edge diffusion spatial distribution pattern. High-High clusters of cases were found in most regions of Dongcheng District and the east part of Xicheng District. In the multifactorial drivers, the three most important driving factors were found to be accommodation, floating population and income level. Surprisingly, any kind of road and educational level had small effect on the fly-tipping case. These results provide a theoretical basis for the government to advance comprehensive prevention and control strategies of bulky waste fly-tipping. And it is helpful to formulate management policies of fly-tipping bulky waste and provide targeted guidance and suggestions for senior decision makers and managers. •Random forest machine learning method was used to analyze bulky waste fly-tipping.•Fly-tipping presented a typical core edge diffusion spatial distribution pattern.•15 driving factors were extracted from multiple data sources.•Accommodation and floating population had the highest impact on fly-tipping.