{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/140062"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/140062","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Heat Vulnerability and Risk Analytics for The Built Environment","abstract":"Climate change risks are considered one of the major global concerns that face humankind in the 21st century. Heatwaves have been identified as one of the deadliest climate hazards, especially in urban areas. Also, extreme heat events have been growing in intensity, duration, and frequency; more risks are expected to affect the urban population. Heat vulnerability assessment in the built environment is a complex process with multiple dynamics and components of human-natural systems and their interaction with the surrounding built environment. These dynamics include social, demographics, urban growth, environmental changes, access to public services, and policy impacts. Yet, there are considerable gaps in the literature on the effect of heat exposure and the built environment as a protective factor from potential vulnerability and risk perspectives. This dissertation addresses this need by developing a multifaceted and multi-scalar framework for heat vulnerability assessment. The framework is designed to inform decision-makers on the local dimension and the distribution of vulnerable populations by answering two key questions: where and what are the impacts of heat exposure in an urban setting? Who are the most susceptible populations to heat exposure? The dissertation explores vulnerability at multiple levels starting with a detailed assessment of the built environment by integrating the impacts of the physical characteristics of the existing building stock, available urban resources for long-term adaptation, and individuals’ adaptive capacity and potential health impacts under varying indoor exposure. Next, a methodology for rapid vulnerability analytics using novel technology such as aerial thermography coupled with Computer Vision (CV) and Machine Learning (ML) techniques to assess the thermal performance of building envelopes to provide actionable data for adaptation strategies at both the building and district levels. Finally, an evaluation framework to assess policy impact on the vulnerability of the urban system during heat events and how delays in the public policy response can increase risk levels","abstract_html":"Climate change risks are considered one of the major global concerns that face humankind in the 21st century. Heatwaves have been identified as one of the deadliest climate hazards, especially in urban areas. Also, extreme heat events have been growing in intensity, duration, and frequency; more risks are expected to affect the urban population. Heat vulnerability assessment in the built environment is a complex process with multiple dynamics and components of human-natural systems and their interaction with the surrounding built environment. These dynamics include social, demographics, urban growth, environmental changes, access to public services, and policy impacts. Yet, there are considerable gaps in the literature on the effect of heat exposure and the built environment as a protective factor from potential vulnerability and risk perspectives. This dissertation addresses this need by developing a multifaceted and multi-scalar framework for heat vulnerability assessment. The framework is designed to inform decision-makers on the local dimension and the distribution of vulnerable populations by answering two key questions: where and what are the impacts of heat exposure in an urban setting? Who are the most susceptible populations to heat exposure? The dissertation explores vulnerability at multiple levels starting with a detailed assessment of the built environment by integrating the impacts of the physical characteristics of the existing building stock, available urban resources for long-term adaptation, and individuals’ adaptive capacity and potential health impacts under varying indoor exposure. Next, a methodology for rapid vulnerability analytics using novel technology such as aerial thermography coupled with Computer Vision (CV) and Machine Learning (ML) techniques to assess the thermal performance of building envelopes to provide actionable data for adaptation strategies at both the building and district levels. Finally, an evaluation framework to assess policy impact on the vulnerability of the urban system during heat events and how delays in the public policy response can increase risk levels","abstract_has_math":false,"creators":["Bayomi, Norhan Magdy"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Architecture","school":null,"contributors":[],"advisors":["Fernandez, John E."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09","date_published":"2021-09","updated_at":"2026-07-22T22:21:19Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"rights_urls":["http://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/140062","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Fernandez, John E."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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Heatwaves have been identified as one of the deadliest climate hazards, especially in urban areas. Also, extreme heat events have been growing in intensity, duration, and frequency; more risks are expected to affect the urban population. Heat vulnerability assessment in the built environment is a complex process with multiple dynamics and components of human-natural systems and their interaction with the surrounding built environment. These dynamics include social, demographics, urban growth, environmental changes, access to public services, and policy impacts. Yet, there are considerable gaps in the literature on the effect of heat exposure and the built environment as a protective factor from potential vulnerability and risk perspectives. This dissertation addresses this need by developing a multifaceted and multi-scalar framework for heat vulnerability assessment. The framework is designed to inform decision-makers on the local dimension and the distribution of vulnerable populations by answering two key questions: where and what are the impacts of heat exposure in an urban setting? Who are the most susceptible populations to heat exposure? The dissertation explores vulnerability at multiple levels starting with a detailed assessment of the built environment by integrating the impacts of the physical characteristics of the existing building stock, available urban resources for long-term adaptation, and individuals’ adaptive capacity and potential health impacts under varying indoor exposure. Next, a methodology for rapid vulnerability analytics using novel technology such as aerial thermography coupled with Computer Vision (CV) and Machine Learning (ML) techniques to assess the thermal performance of building envelopes to provide actionable data for adaptation strategies at both the building and district levels. Finally, an evaluation framework to assess policy impact on the vulnerability of the urban system during heat events and how delays in the public policy response can increase risk levels"]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Heat Vulnerability and Risk Analytics for The Built Environment"]}]}],"canonical_facts":{"dc:contributor.advisor":["Fernandez, John E."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Architecture"],"dc:creator":["Bayomi, Norhan Magdy"],"dc:date.accessioned":["2022-02-07T15:21:54Z"],"dc:date.available":["2022-02-07T15:21:54Z"],"dc:date.issued":["2021-09"],"dc:description.abstract":["Climate change risks are considered one of the major global concerns that face humankind in the 21st century. Heatwaves have been identified as one of the deadliest climate hazards, especially in urban areas. Also, extreme heat events have been growing in intensity, duration, and frequency; more risks are expected to affect the urban population. Heat vulnerability assessment in the built environment is a complex process with multiple dynamics and components of human-natural systems and their interaction with the surrounding built environment. These dynamics include social, demographics, urban growth, environmental changes, access to public services, and policy impacts. Yet, there are considerable gaps in the literature on the effect of heat exposure and the built environment as a protective factor from potential vulnerability and risk perspectives. This dissertation addresses this need by developing a multifaceted and multi-scalar framework for heat vulnerability assessment. The framework is designed to inform decision-makers on the local dimension and the distribution of vulnerable populations by answering two key questions: where and what are the impacts of heat exposure in an urban setting? Who are the most susceptible populations to heat exposure? The dissertation explores vulnerability at multiple levels starting with a detailed assessment of the built environment by integrating the impacts of the physical characteristics of the existing building stock, available urban resources for long-term adaptation, and individuals’ adaptive capacity and potential health impacts under varying indoor exposure. Next, a methodology for rapid vulnerability analytics using novel technology such as aerial thermography coupled with Computer Vision (CV) and Machine Learning (ML) techniques to assess the thermal performance of building envelopes to provide actionable data for adaptation strategies at both the building and district levels. 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