Temporal analysis of settlement areas and city footprints on construction and demolition waste quantification using Landsat satellite imagery

Abstract

Municipal solid waste management has seen a surge in the use of satellite imagery in decision-making processes, yet its application to analyze quantitative variations in construction and demolition (C&D) waste remains under-investigated. This study employs satellite imagery and multivariate analysis to comprehensively assess and predict C&D waste generation in four diverse urban jurisdictions of Canada (Regina) and the USA (Seattle, Buffalo, and Philadelphia). Factors such as settlement area expansion, economic activities, and population growth significantly influence C&D waste rates. Stepwise multivariate regression models tailored to different city types, such as moderately populated (Group 1) and highly populated (Group 2), showcase acceptable predictive capabilities. For moderately populated cities, settlement area, average humidity, and GDP are identified as key predictors, while for highly populated cities, settlement area, unemployment rate, and building permit value prove effective indicators. These models, characterized by R² values from 0.70 to 0.94, provide tailored insights for distinct demographic conditions, aiding waste management planning. This research underscores the importance of satellite imagery and multivariate analysis in understanding C&D waste dynamics and empowers policymakers and waste management agencies with evidence-based strategies for effective waste management in urban centers.