Using Persistent Homology to Analyze Access to Heterogeneous-Quality Resources and Heterogeneous-Severity Nuisances
This study addresses the analytical challenges in coverage assessment arising from the spatial heterogeneity of geographic resource quality and hazard severity by proposing a topological data analysis framework based on multiparameter persistent homology. Overcoming the limitations of conventional single-parameter approaches, this work designs a computationally efficient multiparameter approximation algorithm that enables quantitative evaluation of resource accessibility and hazard exposure under arbitrary quality criteria. Applied to a Chicago case study, the proposed method successfully identifies disparities in park accessibility as well as clusters of overexposure to facilities such as landfills and bars. By effectively capturing complex spatial dependencies, this framework establishes a new paradigm for assessing urban environmental equity.