Network motifs reveal mobility disruption during Hurricane Ian

Understanding how natural disasters reshape daily mobility is essential for improving preparedness and strengthening community resilience. This study develops a motif-based analytical framework to quantify mobility disruption during Hurricane Ian in Lee County, Florida, using high-resolution smartphone location data. Daily mobility motifs are constructed at the individual trajectory level and classified by their relationship with inferred home locations, distinguishing home-anchored, home-passing, and non-home mobility structures. Motif changes are then aggregated to the census block-group scale to examine spatial disparities through canonical correlation analysis, clustering, and ordinal logistic regression. The results reveal substantial heterogeneity across both motif types and neighborhoods. Within Lee County, Hurricane Ian weakened home-anchored routines, increased home-only and non-home mobility, and produced sharper contractions in simple motifs relative to more complex ones. At the community scale, home-anchored disruption was primarily associated with household composition, education, age structure, and commuting patterns, while non-home motif increases were more strongly linked to geographic exposure, population density, local service proximity, and income conditions. By capturing both routine contraction and disruptions to home anchoring across scales, this study demonstrates a motif-based approach for examining mobility disruption in a severe hurricane context and provides a common analytical basis for comparative applications across geographies and disaster types.