{"id":{"repo_id":"queens","oai_identifier":"oai:queensu.scholaris.ca:1974/31920"},"canonical_url":"https://search.dev.ndltd.org/etd/queens/oai:queensu.scholaris.ca:1974/31920","repository":{"repo_id":"queens","name":"Queens University","base_url":"https://qspace.library.queensu.ca/server/oai/request"},"display":{"title":"High-Resolution Digital Noise Mapping of Urban Environments Using the Spectral Element Method","abstract":"The trend toward urbanization necessitates a detailed examination of noise pollution in densely populated areas. Interactions between architectural structures and transportation noise sources, including airways, railways, and highways, make this an intricate problem. Numerous studies have documented the adverse effects of continuous noise exposure on physiological and psychological health, highlighting the importance of understanding noise pollution in urban areas. This research employs the spectral element method (SEM), a numerical technique known for its ability to model complex geometries accurately. The SEM is employed to create high-resolution digital soundscape maps that allow for a comprehensive analysis of the spatial and temporal distribution of noise pollution in urban environments. The method employs high-order polynomial approximations on structured grids, facilitating detailed representation of both regular and irregular geometries, and complex boundary conditions. By doing so, it balances computational efficiency and accuracy, making it an effective tool for urban noise analysis. The models were constructed of two urban zones in Kingston, Ontario, specifically areas surrounding a central train station and a prominent cathedral, using real-world GIS data. These models offer a detailed depiction of the city's physical attributes. The resultant noise maps provide insights into the distribution of noise pollution, information that can be used to inform noise mitigation strategies and urban planning measures. The findings of this study have applications in urban planning, policy development, and decision-making processes. By delineating a computational modelling approach for the spatial and temporal evaluation of noise pollution, this research contributes to the growing field of understanding and managing urban noise. Additionally, the methodologies and models developed may be utilized as references for future investigations and practical applications, as well as tools in the ongoing efforts to improve urban living conditions, noise control, and environmental responsibility.","abstract_html":"The trend toward urbanization necessitates a detailed examination of noise pollution in densely populated areas. Interactions between architectural structures and transportation noise sources, including airways, railways, and highways, make this an intricate problem. Numerous studies have documented the adverse effects of continuous noise exposure on physiological and psychological health, highlighting the importance of understanding noise pollution in urban areas. This research employs the spectral element method (SEM), a numerical technique known for its ability to model complex geometries accurately. The SEM is employed to create high-resolution digital soundscape maps that allow for a comprehensive analysis of the spatial and temporal distribution of noise pollution in urban environments. The method employs high-order polynomial approximations on structured grids, facilitating detailed representation of both regular and irregular geometries, and complex boundary conditions. By doing so, it balances computational efficiency and accuracy, making it an effective tool for urban noise analysis. The models were constructed of two urban zones in Kingston, Ontario, specifically areas surrounding a central train station and a prominent cathedral, using real-world GIS data. These models offer a detailed depiction of the city's physical attributes. The resultant noise maps provide insights into the distribution of noise pollution, information that can be used to inform noise mitigation strategies and urban planning measures. The findings of this study have applications in urban planning, policy development, and decision-making processes. By delineating a computational modelling approach for the spatial and temporal evaluation of noise pollution, this research contributes to the growing field of understanding and managing urban noise. Additionally, the methodologies and models developed may be utilized as references for future investigations and practical applications, as well as tools in the ongoing efforts to improve urban living conditions, noise control, and environmental responsibility.","abstract_has_math":false,"creators":["Lapietra Garcia, Pedro"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Geological Sciences and Geological Engineering","school":null,"contributors":[],"advisors":["Gharti, Hom Nath"],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-27T20:35:19Z","subjects":["Urban acoustics","Spectral Element Method","Noise map","Applied acoustics","Numerical modelling","Geophysics","Noise","SPECFEM"],"languages":["eng"],"rights":["Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1974/31920","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Geological Sciences and Geological Engineering"]},{"key":"dc:contributor.supervisor","label":"Supervisor","values":["Gharti, Hom Nath"]},{"key":"dc:creator","label":"Author","values":["Lapietra Garcia, Pedro"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-10-05T15:57:40Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-10-05T15:57:40Z"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Urban acoustics","Spectral Element Method","Noise map","Applied acoustics","Numerical modelling","Geophysics","Noise","SPECFEM"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1974/31920"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The trend toward urbanization necessitates a detailed examination of noise pollution in densely populated areas. Interactions between architectural structures and transportation noise sources, including airways, railways, and highways, make this an intricate problem. Numerous studies have documented the adverse effects of continuous noise exposure on physiological and psychological health, highlighting the importance of understanding noise pollution in urban areas. This research employs the spectral element method (SEM), a numerical technique known for its ability to model complex geometries accurately. The SEM is employed to create high-resolution digital soundscape maps that allow for a comprehensive analysis of the spatial and temporal distribution of noise pollution in urban environments. The method employs high-order polynomial approximations on structured grids, facilitating detailed representation of both regular and irregular geometries, and complex boundary conditions. By doing so, it balances computational efficiency and accuracy, making it an effective tool for urban noise analysis. The models were constructed of two urban zones in Kingston, Ontario, specifically areas surrounding a central train station and a prominent cathedral, using real-world GIS data. These models offer a detailed depiction of the city's physical attributes. The resultant noise maps provide insights into the distribution of noise pollution, information that can be used to inform noise mitigation strategies and urban planning measures. The findings of this study have applications in urban planning, policy development, and decision-making processes. By delineating a computational modelling approach for the spatial and temporal evaluation of noise pollution, this research contributes to the growing field of understanding and managing urban noise. Additionally, the methodologies and models developed may be utilized as references for future investigations and practical applications, as well as tools in the ongoing efforts to improve urban living conditions, noise control, and environmental responsibility."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Sc."]},{"key":"dc:title","label":"Title","values":["High-Resolution Digital Noise Mapping of Urban Environments Using the Spectral Element Method"]}]}],"canonical_facts":{"dc:contributor.department":["Geological Sciences and Geological Engineering"],"dc:contributor.supervisor":["Gharti, Hom Nath"],"dc:creator":["Lapietra Garcia, Pedro"],"dc:date.accessioned":["2023-10-05T15:57:40Z"],"dc:date.available":["2023-10-05T15:57:40Z"],"dc:description.abstract":["The trend toward urbanization necessitates a detailed examination of noise pollution in densely populated areas. Interactions between architectural structures and transportation noise sources, including airways, railways, and highways, make this an intricate problem. Numerous studies have documented the adverse effects of continuous noise exposure on physiological and psychological health, highlighting the importance of understanding noise pollution in urban areas. This research employs the spectral element method (SEM), a numerical technique known for its ability to model complex geometries accurately. The SEM is employed to create high-resolution digital soundscape maps that allow for a comprehensive analysis of the spatial and temporal distribution of noise pollution in urban environments. The method employs high-order polynomial approximations on structured grids, facilitating detailed representation of both regular and irregular geometries, and complex boundary conditions. By doing so, it balances computational efficiency and accuracy, making it an effective tool for urban noise analysis. The models were constructed of two urban zones in Kingston, Ontario, specifically areas surrounding a central train station and a prominent cathedral, using real-world GIS data. These models offer a detailed depiction of the city's physical attributes. The resultant noise maps provide insights into the distribution of noise pollution, information that can be used to inform noise mitigation strategies and urban planning measures. The findings of this study have applications in urban planning, policy development, and decision-making processes. By delineating a computational modelling approach for the spatial and temporal evaluation of noise pollution, this research contributes to the growing field of understanding and managing urban noise. Additionally, the methodologies and models developed may be utilized as references for future investigations and practical applications, as well as tools in the ongoing efforts to improve urban living conditions, noise control, and environmental responsibility."],"dc:description.degree":["M.Sc."],"dc:identifier.uri":["https://hdl.handle.net/1974/31920"],"dc:language.iso":["eng"],"dc:rights":["Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["Urban acoustics","Spectral Element Method","Noise map","Applied acoustics","Numerical modelling","Geophysics","Noise","SPECFEM"],"dc:title":["High-Resolution Digital Noise Mapping of Urban Environments Using the Spectral Element Method"],"dc:type":["thesis"]},"updated_at":"2026-07-27T20:35:19Z"}