Crowdsourcing Geospatial Data for Earth and Human Observations: A Review

A Systematic Literature Review of Empirical Validation of Disaster Resilience Indicators

Hazard Exposure Heterophily in Socio-spatial Networks Contributes to Post-disaster Recovery in Low-income Populations

Untangling the relationship between power outage and population activity recovery in disasters

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.

Non-locality and Spillover Effects of Residential Flood Damage on Community Recovery: Insights from High-resolution Flood Claim and Mobility Data

The ability to measure and track the speed and trajectory of a community's post-disaster recovery is essential to inform resource allocation and prioritization. The current survey-based approaches to examining community recovery, however, have significant lags and put the burden of data collection on affected people. Also, the existing literature lacks quantitative measures for important milestones to inform the assessment of recovery trajectory. Recognizing these gaps, this study uses location-based data related to visitation patterns and credit card transactions to specify critical recovery milestones related to population activity recovery. Using data from 2017 Hurricane Harvey in Harris County (Texas), the study specifies four critical post-disaster recovery milestones and calculates quantitative measurements of the length of time between the end of a hazard event and when the spatial areas (census tracts) reached these milestones based on fluctuations in visits to essential and non-essential facilities, and essential and non-essential credit card transactions. Accordingly, an integrated recovery metric is created for an overall measurement of each spatial area's recovery progression. Exploratory statistical analyses were conducted to examine whether variations in community recovery progression in achieving the critical milestones is correlated to its flood status, socioeconomic characteristics, and demographic composition. Finally, the extent of spatial inequality is examined. The results show the presence of moderate spatial inequality in population activity recovery in Hurricane Harvey, based upon which the inequality of recovery is measured. Results of this study can benefit post-disaster recovery resource allocation as well as improve community resilience towards future natural hazards. 

/pdf/data-driven-tracking-of-the-bounce-back-path-after-disasters-1dh3vnea.pdf

Data-driven tracking of the bounce-back path after disasters: Critical milestones of population activity recovery and their spatial inequality

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Data-driven tracking of the bounce-back path after disasters: Critical milestones of population activity recovery and their spatial inequality