Authors: Samuel Rufat*, , Eric Tate, University of Iowa
Topics: Hazards and Vulnerability, Hazards, Risks, and Disasters, Geographic Information Science and Systems
Keywords: hazards, GIS, social vulnerability, measure, validation,
Session Type: Paper
Start / End Time: 10:00 AM / 11:40 AM
Room: Napoleon B3, Sheraton 3rd Floor
Presentation File: No File Uploaded
Currently, the most common method to map social dimensions of vulnerability is the aggregation of class, race, age, gender and other universal descriptors into thematic sub-indices or statistical factors and then the mapping of a one-dimensional synthetic indicator. This relative uniformity might reflect growing consensus in the field. However, several gaps in the construction of social vulnerability assessments and discrepancies with qualitative studies have been revealed. Typically, the rationale for decisions regarding variable selection, analysis scale or method is based on simplicity or choices made in previous studies. And in many cases, no justification is provided at all. Validity refers to the extent to which a measure adequately represents the underlying construct that it is supposed to measure. For the construct of social vulnerability, to what extent do indices and measurements reflect the multidimensionality, interactivity, and effects of its causal processes? Is a measure of social vulnerability really measuring vulnerability and not a different construct as poverty or a different proxy as density? Validating social vulnerability measurements is challenging due to difficulty linking these processes with index construction parameters, and because social vulnerability is not directly observable. The aim is to use the Sandy 2012 case study to confront different social vulnerability indices and estimates based on inductive and hierarchical configurations and vulnerability profiles on the same data set from ACS 2012 for New York and New Jersey. Their results are somewhat convergent, but their statistical power varies when confronted to the Sandy outcomes as portrayed by FEMA data.