This study propose a model for predicting household waste generation. In related studies, waste generation patterns are analyzed in macroscopic spatial units. In this study, household waste generation is estimated by building units and applied to the ...
This study propose a model for predicting household waste generation. In related studies, waste generation patterns are analyzed in macroscopic spatial units. In this study, household waste generation is estimated by building units and applied to the analysis. As independent variables, resident registration population, floating Population, credit card sales, and number of delivery orders are used. In order to determine the spatial analysis unit, correlation analysis is performed at 250m, 500m, and 750m grid spaces considering MAUP (Modifiable Areal Unit Problem). Finally, an occurrence prediction model is derived through multiple linear regression and geographically weighted regression analysis in the microscopic spatial unit with the highest statistically high correlation. Modeling was perfomed at a more detailed level than the spatial unit where the data were originally aggregated, and this methodology can be used as evidence for selecting priority management areas and intensive control areas for unauthorized dumping.