  Examining the relationship between vulnerability of the built environment and
community recovery is crucial for understanding disaster resilience. Yet, this
relationship is rather neglected in the existing literature due to previous
limitations in the availability of empirical datasets needed for such analysis.
In this study, we combine fine-resolution flood damage claims data (composed of
both insured and uninsured losses) and human mobility data (composed of
millions of movement trajectories) during the 2017 Hurricane Harvey in Harris
County, Texas, to specify the extent to which vulnerability of the built
environment (i.e., flood property damage) affects community recovery (based on
the speed of human mobility recovery) locally and regionally. We examine this
relationship using a spatial lag, spatial reach, and spatial decay models to
measure the extent of spillover effects of residential damage on community
recovery. The findings show that: first, the severity of residential damage
significantly affects the speed of community recovery. A greater extent of
residential damage suppresses community recovery not only locally but also in
the surrounding areas. Second, the spatial spillover effect of residential
damage on community recovery speed decays with distance from the highly damaged
areas. Third, spatial areas display heterogeneous spatial decay coefficients,
which are associated with urban structure features such as the density of
points-of-interest facilities and roads. These findings provide a novel
data-driven characterization of the spatial diffusion of residential flood
damage effects on community recovery and move us closer to a better
understanding of complex spatial processes that shape community resilience to
hazards. This study also provides valuable insights for emergency managers and
public officials seeking to mitigate the non-local effects of residential
damage.
