Statistical and Spatial Analysis of Hurricane-induced Roadway Closures and Power Outages

Abstract

Hurricanes lead to substantial infrastructure system damages, such as roadway closures and power outages, in the US annually, especially in states like Florida. As such, this paper aimed to assess the impacts of Hurricane Hermine (2016) and Hurricane Michael (2018) on the City of Tallahassee, the capital of Florida, via exploratory spatial and statistical analyses on power outages and roadway closures. First, a geographical information systems (GIS)-based spatial analysis was conducted to explore the power outages and roadway closure patterns in the city including kernel density estimation (KDE) and density ratio difference (DRD) methods. In order to provide a more detailed assessment on which population segments were more affected, a second step included a statistical analysis to identify the relationships between demographic- and socioeconomic-related variables and the magnitude of power outages and roadway closures caused by these hurricanes. The results indicate that the high-risk locations for roadway closures showed different patterns, whereas power outages seemed to have similar spatial patterns for the hurricanes. The findings of this study can provide useful insights and information for city officials to identify the most vulnerable regions which are under the risk of disruption. This can lead to better infrastructure plans and policies.

A Study on the Association of Socioeconomic and Physical Cofactors Contributing to Power Restoration After Hurricane Maria

“…According to the model parameters, the density of the power distribution line was one of the major factors for the recovery. Following other studies [26], [27], [29], here we used distribution line density to investigate how the power infrastructures of the island influenced the restoration process. With bivariate correlation coefficient analysis, we found the power distribution line density is strongly correlated with the population density (r =0.90), substation density (r = 0.55), and 38KV transmission line density (r = 0.47).…”

“…Similar to the road network, the electrical power system is a complex network built on interconnection and interdependence among different components, including generators, power lines, transformers, substations, and others [88]. To find the association of power systems in hurricaneinduced outages, many studies used power lines density as a cofactor in their power outage model [26], [27], [29], [35].…”

“…Han et al (2008) [26] improved the GLM model by adding variables including local climatology, geography, and power systems. A recent study also includes socioeconomic and demographic variables to predict outages with a linear regression model [27]. Some studies also levered machine learning algorithms, including Random forest (RF), Classification and regression tree (CART), Bayesian additive regression trees (BART), Multivariate adaptive regression splines (MARS) [28]- [33].…”

The Road toward Smart Cities: A Study of Citizens’ Acceptance of Mobile Applications for City Services

“…With respect to other practical and research applications, survey data similar to those collected for the current study can also be combined with technical data on disaster-related disruptions to city functioning and infrastructure in order to better understand citizen needs and the use of smart city functions [75]. Specifically, such survey data can be combined or cross-validated with data on infrastructure disruptions, such as power outages and roadway closures [76][77][78][79] as well as with city data on demographics and socioeconomics [80,81].…”

Developing City-Wide Hurricane Impact Maps using Real-Life Data on Infrastructure, Vegetation and Weather

“…The significant contribution was to forecast the evacuation travel demand and conduct an evacuation traffic analysis through the application of intelligent transportation systems (ITS) technologies based on the concept of convolutional neural network, a well-known machine learning technique. Recently, Ghorbanzadeh et al ( 12 ) studied the power outages and roadway closures in the City of Tallahassee based on real-life data on the impacts of Hurricane Hermine (2016) and Michael (2018) throughout the city. The study showed those locations that were under high risk of electricity outages and roadway disruptions, both statistically and spatially.…”