Measuring Community Resilience to Coastal Hazards along the Northern Gulf of Mexico

Abstract

The abundant research examining aspects of social-ecological resilience, vulnerability, and hazards and risk assessment has yielded insights into these concepts and suggested the importance of quantifying them. Quantifying resilience is complicated by several factors including the varying definitions of the term applied in the research, difficulties involved in selecting and aggregating indicators of resilience, and the lack of empirical validation for the indices derived. This paper applies a new model, called the resilience inference measurement (RIM) model, to quantify resilience to climate-related hazards for 52 U.S. counties along the northern Gulf of Mexico. The RIM model uses three elements (exposure, damage, and recovery indicators) to denote two relationships (vulnerability and adaptability), and employs both K-means clustering and discriminant analysis to derive the resilience rankings, thus enabling validation and inference. The results yielded a classification accuracy of 94.2% with 28 predictor variables. The approach is theoretically sound and can be applied to derive resilience indices for other study areas at different spatial and temporal scales.

Validating Resilience and Vulnerability Indices in the Context of Natural Disasters

“…The five indices selected are: Cutter, Burton, and Emrich's Baseline Resilience Index for Communities (BRIC); Peacock et al .’s Community Disaster Resilience Index (CDRI); Foster's Resilience Capacity Index (RCI); Cutter, Boruff, and Shirley's Social Vulnerability Index (SoVI); and Flanagan et al .’s Social Vulnerability Index (SVI) . These indices have been assessed by others, used as a basis to build upon, applied in case studies, and added to toolkits for federal and international agencies (BRIC, CDRI, RCI, SOVI, SVI). In this section, we describe each index in detail and provide a comparison of the stated performance.…”

Measuring County Resilience After the 2008 Wenchuan Earthquake

“…They further defined resilience for both physical and social systems to consist of four properties: robustness, redundancy, resourcefulness, and rapidity (Bruneau and Reinhorn 2006). Recently, the concept of resilience is often mixed with other closely related concepts such as vulnerability, adaptability, and sustainability, making the measurement of resilience more complicated (Cutter et al 2008;Lam et al 2015a).…”

“…The regression coefficients were then used to determine the weight of each variable in the composite index. Lam et al (2015a) also developed the resilience inference measurement (RIM) method for measuring community resilience to coastal hazards. The RIM method follows the rationale of using real observable outcomes to derive the index and employs two statistical procedures: K-means cluster analysis and discriminant analysis (Li et al 2005;Li 2011;Lam et al 2015a, b).…”

“…As influence on life quality caused by seismic disasters draws increasing attention from the public, a need arises to consider the recovery and adaptive aspect of a community after disaster. For this reason, and by building on the RIM model, we assess community resilience to seismic disasters by choosing population growth rate as the key indicator of the recovery capability (Chang 2010;Finch et al 2010;Li et al 2010;Lam et al 2015a) of counties in the area that were hit hard in Sichuan, Gansu, and Shaanxi Provinces by the 2008 Wenchuan Earthquake.…”

“…To address some of these issues, Lam and her fellow researchers developed the resilience inference measurement (RIM) model to assess community resilience and to identify the key variables affecting resilience (Lam et al 2015a). The RIM model has been applied in the Gulf of Mexico region to measure community resilience to coastal hazards (Lam et al 2015a, b), and at different geographical scales in Louisiana (Li 2013).…”