Spatial Analysis of Informal Recyclable Station System for Integration to Formal Solid Waste Management System and Circular Economy–Proposing Integrated Methodology of GIS, Remote Sensing, and Statistical Learning

Abstract

Recently, the transition to the circular economy has become environmentally and economically urgent for every single nation in the world. Closing the loops of material is one of the key ideas behind the foundation of a circular economy (CE). The informal recyclable stations (IRSs) within the solid waste management (SWM) system play an important role as the reversed logistic system, being in charge of collecting and trading recyclable solid waste. This study aimed to comprehend the spatial nature of the system of IRSs in Danang city, Hue city, and Hoi An city as representative sites for the whole of central Vietnam and the nation. The integration of geographic information system (GIS), remote sensing, and statistical learning was performed to clarify spatial characteristics and dynamics of the system of IRSs as well as combat status of limitations of available data in developing countries. Results denoted that the system of IRSs was distributed in close proximity to transportation systems and residential areas with low vegetation coverage. Coverage ratios of the system of IRSs did not strongly fluctuate in case the number of IRSs decreased by 80% regarding the 3500 m distance covered. Negative binomial regression proved to be the most congruent model for understanding the prevalence of IRSs in central Vietnam. Population and normalized difference vegetation index were statistically related to prevalence of IRS. While linear regression depicted balance between variance and bias, support vector machine would be applied if prioritized aim is model performance. The results of this study are a scientific base for the management of the IRS system and the integration of this system into a formal SWM system as well as the transition to a CE.