{"id":{"repo_id":"tamu","oai_identifier":"oai:oaktrust.library.tamu.edu:1969.1/1593892"},"canonical_url":"https://search.dev.ndltd.org/etd/tamu/oai:oaktrust.library.tamu.edu:1969.1/1593892","repository":{"repo_id":"tamu","name":"Texas A&M University","base_url":"https://oaktrust.library.tamu.edu/server/oai/request"},"display":{"title":"Understanding Urban Resilience through Post-Disaster Human Mobility Patterns and Recovery Dynamics","abstract":"This dissertation investigates urban resilience through post-disaster human mobility patterns and recovery dynamics, offering insights into the complex interdependencies of urban systems in crises. Utilizing extensive mobility data, this study examines how urban populations adapt and recover from disasters, providing a multi-scale analysis of mobility networks and infrastructure robustness. The research encompasses four distinct phases, each addressing different aspects of resilience and recovery. Phase A analyzes human mobility across macroscopic, substructure, and microscopic scales, revealing varying resilience characteristics. Phase B focuses on the relationship between power outages and population activity recovery, identifying key thresholds that impact recovery speed. Phase C introduces a novel classification of resilience curve archetypes, enhancing the predictability of recovery patterns. Phase D explores the spillover effects of built-environment vulnerabilities on business resilience, highlighting the economic impacts of infrastructure damage. Collectively, these phases contribute to a granular understanding of resilience, emphasizing the need for targeted, data-driven strategies in urban planning and disaster management. The findings suggest that effective recovery from urban disasters requires a coordinated approach that considers the diverse impacts on human mobility, infrastructure resilience, and economic stability. This research underscores the critical role of integrated, multi-scalar analyses in developing resilient urban systems capable of withstanding and recovering from future disasters.","abstract_html":"This dissertation investigates urban resilience through post-disaster human mobility patterns and recovery dynamics, offering insights into the complex interdependencies of urban systems in crises. Utilizing extensive mobility data, this study examines how urban populations adapt and recover from disasters, providing a multi-scale analysis of mobility networks and infrastructure robustness. The research encompasses four distinct phases, each addressing different aspects of resilience and recovery. Phase A analyzes human mobility across macroscopic, substructure, and microscopic scales, revealing varying resilience characteristics. Phase B focuses on the relationship between power outages and population activity recovery, identifying key thresholds that impact recovery speed. Phase C introduces a novel classification of resilience curve archetypes, enhancing the predictability of recovery patterns. Phase D explores the spillover effects of built-environment vulnerabilities on business resilience, highlighting the economic impacts of infrastructure damage. Collectively, these phases contribute to a granular understanding of resilience, emphasizing the need for targeted, data-driven strategies in urban planning and disaster management. The findings suggest that effective recovery from urban disasters requires a coordinated approach that considers the diverse impacts on human mobility, infrastructure resilience, and economic stability. This research underscores the critical role of integrated, multi-scalar analyses in developing resilient urban systems capable of withstanding and recovering from future disasters.","abstract_has_math":false,"creators":["Hsu, Chia Wei"],"institution":"Texas A&M University","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Mostafavidarani, Ali"],"committee_chairs":[],"committee_members":["Ye, Xinyue","Najafi, Amirali","Damnjanovic, Ivan"],"year":2024,"date_issued":"2024-12","date_published":"2024-12","updated_at":"2026-08-21T16:48:40Z","subjects":["Engineering, Civil"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1969.1/1593892","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"source_record":{"url":"https://oaktrust.library.tamu.edu/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aoaktrust.library.tamu.edu%3A1969.1%2F1593892","prefix":"dim"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Mostafavidarani, Ali"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Ye, Xinyue","Najafi, Amirali","Damnjanovic, Ivan"]},{"key":"dc:creator","label":"Author","values":["Hsu, Chia Wei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-09-03T20:15:05Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-12"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Texas A&M University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Civil"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1969.1/1593892"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation investigates urban resilience through post-disaster human mobility patterns and recovery dynamics, offering insights into the complex interdependencies of urban systems in crises. Utilizing extensive mobility data, this study examines how urban populations adapt and recover from disasters, providing a multi-scale analysis of mobility networks and infrastructure robustness. The research encompasses four distinct phases, each addressing different aspects of resilience and recovery. Phase A analyzes human mobility across macroscopic, substructure, and microscopic scales, revealing varying resilience characteristics. Phase B focuses on the relationship between power outages and population activity recovery, identifying key thresholds that impact recovery speed. Phase C introduces a novel classification of resilience curve archetypes, enhancing the predictability of recovery patterns. Phase D explores the spillover effects of built-environment vulnerabilities on business resilience, highlighting the economic impacts of infrastructure damage. Collectively, these phases contribute to a granular understanding of resilience, emphasizing the need for targeted, data-driven strategies in urban planning and disaster management. The findings suggest that effective recovery from urban disasters requires a coordinated approach that considers the diverse impacts on human mobility, infrastructure resilience, and economic stability. This research underscores the critical role of integrated, multi-scalar analyses in developing resilient urban systems capable of withstanding and recovering from future disasters."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Understanding Urban Resilience through Post-Disaster Human Mobility Patterns and Recovery Dynamics"]}]}],"canonical_facts":{"dc:contributor.advisor":["Mostafavidarani, Ali"],"dc:contributor.committeemember":["Ye, Xinyue","Najafi, Amirali","Damnjanovic, Ivan"],"dc:creator":["Hsu, Chia Wei"],"dc:date.accessioned":["2025-09-03T20:15:05Z"],"dc:date.issued":["2024-12"],"dc:description.abstract":["This dissertation investigates urban resilience through post-disaster human mobility patterns and recovery dynamics, offering insights into the complex interdependencies of urban systems in crises. 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