{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129513"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129513","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Integrating cyberGIS and big data for scalable spatial accessibility analysis","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_has_math":false,"creators":["Michels, Alexander"],"institution":"University of Illinois Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Informatics","degree_department":null,"school":null,"contributors":["Wang, Shaowen","Kolak, Marynia","Li, Bo","Padmanabhan, Anand","Vogiatzis, Chrysafis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-04-07","date_published":"2025-04-07","updated_at":"2026-07-22T22:25:05Z","subjects":["cyberGIS","spatial accessibility","GIS"],"languages":["en","eng"],"rights":["Copyright 2025 Alexander Michels"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/129513","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wang, Shaowen","Kolak, Marynia","Li, Bo","Padmanabhan, Anand","Vogiatzis, Chrysafis"]},{"key":"dc:creator","label":"Author","values":["Michels, Alexander"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-04-07","2025-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Informatics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cyberGIS","spatial accessibility","GIS"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Alexander Michels"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/129513"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Alexander Michels, accepted the attached license on 2025-04-07 at 10:10.","The student, Alexander Michels, submitted this Dissertation for approval on 2025-04-07 at 10:15.","This Dissertation was approved for publication on 2025-04-07 at 12:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21717 on 2025-10-19 at 19:14:30","Spatial accessibility describes the uneven spatial distribution of access to vital resources and services like healthcare and critical infrastructure. Access is typically measured using travel time and ratios of supply-to-demand at the population-level to determine a level of access for each spatial unit such as a census tract. While the growth in geospatial big data and advances in cyberinfrastructure-based geographic information science and systems (cyberGIS) have widened the possibilities for spatial accessibility analysis, providing new data sources and research capabilities, the spatial accessibility literature has lagged behind this trend. This dissertation details methodological advancements in the field of cyberGIS-enabled spatial accessibility with three main research objectives: (1) the development of algorithms and methods for scalable travel time and spatial accessibility analyses, (2) the design of innovative approaches to harnessing emerging mobility data sources, and (3) the application of machine learning techniques to emerging big data sources to enhance the comprehension and approximation of travel time within spatial accessibility analyses. Our results underscore the efficacy of cyberGIS-enabled spatial accessibility through novel applications to real-world datasets and case studies. This approach enables researchers and decision-makers to analyze accessibility at larger scales, finer granularities, and with higher accuracy than what is currently achievable with existing methods."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Integrating cyberGIS and big data for scalable spatial accessibility analysis"]}]}],"canonical_facts":{"dc:contributor":["Wang, Shaowen","Kolak, Marynia","Li, Bo","Padmanabhan, Anand","Vogiatzis, Chrysafis"],"dc:creator":["Michels, Alexander"],"dc:date":["2025-04-07","2025-05"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Alexander Michels, accepted the attached license on 2025-04-07 at 10:10.","The student, Alexander Michels, submitted this Dissertation for approval on 2025-04-07 at 10:15.","This Dissertation was approved for publication on 2025-04-07 at 12:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21717 on 2025-10-19 at 19:14:30","Spatial accessibility describes the uneven spatial distribution of access to vital resources and services like healthcare and critical infrastructure. Access is typically measured using travel time and ratios of supply-to-demand at the population-level to determine a level of access for each spatial unit such as a census tract. While the growth in geospatial big data and advances in cyberinfrastructure-based geographic information science and systems (cyberGIS) have widened the possibilities for spatial accessibility analysis, providing new data sources and research capabilities, the spatial accessibility literature has lagged behind this trend. This dissertation details methodological advancements in the field of cyberGIS-enabled spatial accessibility with three main research objectives: (1) the development of algorithms and methods for scalable travel time and spatial accessibility analyses, (2) the design of innovative approaches to harnessing emerging mobility data sources, and (3) the application of machine learning techniques to emerging big data sources to enhance the comprehension and approximation of travel time within spatial accessibility analyses. Our results underscore the efficacy of cyberGIS-enabled spatial accessibility through novel applications to real-world datasets and case studies. This approach enables researchers and decision-makers to analyze accessibility at larger scales, finer granularities, and with higher accuracy than what is currently achievable with existing methods."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129513"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Alexander Michels"],"dc:subject":["cyberGIS","spatial accessibility","GIS"],"dc:title":["Integrating cyberGIS and big data for scalable spatial accessibility analysis"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Informatics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:05Z"}