Summary

This PhD research examines how open geospatial data and optimization methods can support more equitable healthcare access planning, particularly in low- and middle-income countries. By integrating datasets such as OpenStreetMap road networks, satellite-derived population data, and health facility registries, the research develops models that help policymakers identify underserved areas and determine optimal locations for healthcare infrastructure and services.  A key contribution is the development of the Public Infrastructure Service Access (PISA) ecosystem, a set of open-source tools that translate complex geospatial and optimization methods into practical decision-support systems. Through real-world case studies in countries such as Timor-Leste, Vietnam, and Nepal, the research demonstrates how these tools can guide infrastructure planning, improve healthcare accessibility, and reveal critical gaps in underlying data systems.