Integrating cyberGIS and big data for scalable spatial accessibility analysis

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Informatics

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Michels, Alexander

Contributors dc:contributor

• Wang, Shaowen
• Kolak, Marynia
• Li, Bo
• Padmanabhan, Anand
• Vogiatzis, Chrysafis

• cyberGIS
• spatial accessibility
• GIS

Statement dc:rights

• Copyright 2025 Alexander Michels

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129513

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129513