Assessing construction and demolition waste generation rates using satellite imagery
| dc.contributor.advisor | Ng, Kelvin Tsun Wai | |
| dc.contributor.author | Ray, Sagar | |
| dc.contributor.committeemember | Veawab, Amornvadee (Amy) | |
| dc.date.accessioned | 2024-10-11T17:46:23Z | |
| dc.date.available | 2024-10-11T17:46:23Z | |
| dc.date.issued | 2024-04 | |
| dc.description | A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Environmental Systems Engineering, University of Regina. ix, 110 p. | |
| dc.description.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 underexplored. Especially the COVID- 19 pandemic disrupted conventional municipal solid waste (MSW) management practices and affected waste generation rates. While MSW streams have been extensively studied and reported, the impact on construction and demolition (C&D) waste remains overlooked. As such, the first part of the study develops an innovative analytical framework utilizing satellite imagery to quantify C&D waste disposal rates during COVID-19 restrictions in a mid-sized Canadian city. Supervised classification of Landsat-8 images is conducted to derive the settlement area over a period of 8.8 years (2014-2022). The relationship between C&D disposal rates and settlement area is evaluated using regression analysis. Results reveal a 73.4% reduction in mean weekly C&D disposal in 2020 compared to pre-pandemic years, reflecting diminished construction activity. The settlement area exhibits a strong positive correlation (R2=0.812) with per capita C&D disposal rate, providing spatial evidence of urbanization patterns affecting C&D waste generation. Among socioeconomic factors examined, the value of building permits issued most influences C&D quantities (R2=0.934). The satellite imagery-based approach allows indirect estimation of disrupted C&D waste streams when on-site auditing is restricted during pandemics. The framework offers municipal authorities spatial decision support to formulate data-driven C&D waste management policies that are resilient to future public health emergencies. The second part of the 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). In Seattle, the annual mean C&D waste amount per capita is 0.624 tonnes, while in Regina, Buffalo, and Philadelphia, it is 0.224, 0.330, and 0.014 respectively. 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. | |
| dc.description.authorstatus | Student | en |
| dc.description.peerreview | yes | en |
| dc.identifier.uri | https://hdl.handle.net/10294/16438 | |
| dc.language.iso | en | en |
| dc.publisher | Faculty of Graduate Studies and Research, University of Regina | en |
| dc.title | Assessing construction and demolition waste generation rates using satellite imagery | |
| dc.type | Thesis | en |
| thesis.degree.department | Faculty of Engineering and Applied Science | |
| thesis.degree.discipline | Engineering - Environmental Systems | |
| thesis.degree.grantor | University of Regina | en |
| thesis.degree.level | Master's | en |
| thesis.degree.name | Master of Applied Science (MASc) |