Quantifying Functional Criticality of Lifelines Through Mobility-Derived Population-Facility Dependence for Human-Centered Resilience
Junwei Ma, Bo Li, Xiangpeng Li, Chenyue Liu, Ali Mostafavi

TL;DR
This paper introduces a human-centered metric for infrastructure criticality based on mobility data, revealing disproportionate dependence on a small subset of facilities and highlighting increased future risk due to climate change.
Contribution
It develops a novel behavioral-based criticality measure integrating mobility patterns with hazard models, bridging engineering risk analysis and human mobility analysis.
Findings
Dependence is concentrated: 2.8% of grocery stores and 14.8% of hospitals are super-critical.
Future flood hazards increase population-weighted vulnerability by 67.6%.
Behavioral criticality amplifies risk assessment beyond physical asset analysis.
Abstract
Lifeline infrastructure underpins the continuity of daily life, yet conventional criticality assessments remain largely asset-centric, inferring importance from physical capacity or network topology rather than actual behavioral reliance. This disconnect frequently obscures the true societal cost of disruption, particularly in underserved communities where residents lack service alternatives. This study bridges the gap between engineering risk analysis and human mobility analysis by introducing functional criticality, a human-centered metric that quantifies the behavioral indispensability of specific facilities based on large-scale visitation patterns. Leveraging 1.02 million anonymized mobility records for Harris County, Texas, we operationalize lifeline criticality as a function of visitation intensity, catchment breadth, and origin-specific substitutability. Results reveal that…
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Taxonomy
TopicsInfrastructure Resilience and Vulnerability Analysis · Flood Risk Assessment and Management · Disaster Management and Resilience
