First Advisor

Jiunn-Der Duh

Date of Award

2023

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Geography

Department

Geography

Language

English

DOI

10.15760/geomaster.26

Abstract

The influence of natural hazards on social vulnerability is an important topic in the risk analysis of natural disasters in the human-environment system. Due to the difficulty of directly measuring social vulnerability, composite indexes are used as a surrogate. Social vulnerability indexes attempt to characterize access to societal and local social services during or after disastrous events, using various indicators such as age, gender, ethnicity, socioeconomic status, housing organization, access to shelters, and medical facilities. Geographic information systems (GIS) are used for vulnerability analysis due to their visualization methods and demographic data analysis. However, limitations in GIS applications for social vulnerability analysis are associated with a selection of a GIS method and based on different spatial resolutions. For example, performing vulnerability analysis at a coarse spatial resolution can lead to an overestimation or underestimation of vulnerable populations. Though most studies use census data for vulnerability analysis, the spatial size of census data does not always correlate well with the spatial variations of hazards or demography. Therefore, research should be performed at a finer spatial resolution to receive a more comprehensive analysis of social vulnerability. In this research, I disaggregated the census block group data at the parcel level to estimate the social vulnerability indexes. I also compared and contrasted two GIS methods, the areal apportionment and dasymetric methods, to estimate social vulnerability in the West part of the City of Tualatin. The areal apportionment method, which is based on the estimation of vulnerable populations as the proportion of those affected by the natural hazard to those in the whole census enumeration unit, is widely applied in social vulnerability research. The dasymetric method is based on the disaggregation of vulnerable populations from the whole census enumeration unit to each residential parcel within the parts of the whole census enumeration unit affected by hazards. This method considers additional social information, which can improve the social vulnerability assessment results. This study investigates if the dasymetric method provides an accurate estimate of vulnerable populations. The research reveals that the dasymetric method is more suitable for the estimation of vulnerable populations and social vulnerability analysis than the areal apportionment method when characterizing the flooding risk vulnerability in the city of Tualatin, Oregon. The results of this research can be applied to vulnerability assessment of other areas.

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Comments

A research paper submitted in partial fulfilment of the requirements for the degree of Master of Science in Geography.

Persistent Identifier

https://archives.pdx.edu/ds/psu/40743

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