Poor and Minority Impacts from Hurricane Ike
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Poor and Minority Impacts from Hurricane Ike Shannon Van Zandt, Ph.D., AICP Research supported by a grant from the National Science Foundation (#0928926) entitled Developing A Living Laboratory for Examining Community Recovery and Resilience After Disaster and from a series of grants funded by NOAA, the TGLO and the CCC. The authors and not the NSF, NOAA, TGLO, or the CCC are responsible for the any findings and opinions expressed in this presentation or the paper upon which it is based. The full paper can be found in Housing Policy Debate, 22:1, 29-55
Objectives and outline
• Introduce group to “living laboratory”
research from 2008’s Hurricane Ike on
Galveston Island (TX)
– My focus on social vulnerability factors,
particularly as they relate to the spatial
distribution of housing
• Highlight related findings
Geography of Opportunity
• Sprawl, concentrated poverty,
and segregation have shaped
metropolitan areas in ways that
exacerbate existing economic
and social inequalities
• The geography of opportunity is
based on two main premises:
– where one lives is critical for
taking advantage of available
opportunities;
– households have unequal
abilities to live in places with
good opportunities
Inequalities may be due to:
• Discrimination in lending and real estate industries
• A lack of, and a poor distribution of housing
opportunities
Housing market segmentation
Uneven regional growth
Clustering of low-income housing
Consequences include:
Poorer access to opportunity
Greater exposure to hazards
Housing inequalities determine the spatial pattern of Social Vulnerability (SV)
Levels of Social Vulnerability Analysis
nd rd
Base Social Vulnerability Indicators (percentages) 2 Order 3 Order
1. Single parent households with children/Total Households Child care
2. Population 5 or below/Total Population Needs
3. Population 65 or above/Total Population Elder Care
4. Population 65 or above & below poverty/Pop. 65 or above Needs
5. Workers using public transportation/Civilian pop. 16+ and employed Transportation
6. Occupied housing units without a vehicle/Occupied housing units (HUs) needs
7. Occupied Housing units/Total housing units
8. Persons in renter occupied housing units/Total occupied housing units Socially
Temporary
9. Non-white population/Total population Shelter and Vulnerable
10. Population in group quarters/Total population housing Hotspot
11. Housing units built 20 years ago/Total housing Units recovery
needs
12. Mobile Homes/Total housing units
13. Persons in poverty/Total population
14. Occupied housing units without a telephone/Total occupied HU
15. Population above 25 with less than high school/Total pop above 25 Civic Capacity
16. Population 16+ in labor force and unemployed/Pop in Labor force 16+ needs
17. Population above 5 that speak English not well or not at all/Pop > 5
Source: Van Zandt, S., W.G. Peacock, *D. Henry, H. Grover, W. Highfield, and S. Brody. 2012. Mapping
Social Vulnerability to Enhance Housing and Neighborhood Resilience. Housing Policy Debate 22(1): 29-55.
Example: SV indices overlaid with Cat 1&2 surge zones coastalatlas.tamug.edu
Hurricane Ike
• Hurricane Ike (Galveston, TX 2008)
provided an opportunity to validate
SV mapping technique and examine
impacts for socially vulnerable groups
• Select study objectives
– Did the spatial distribution of vulnerable populations
mitigate or exacerbate damage and loss to property?
– Do social vulnerability factors facilitate or impede
decision-making with regard to dislocation and early
repair/rebuilding decisions?
– How do pre-existing physical and social development
patterns alter the long-term recovery trajectories for
socially vulnerable households and housing in
physically and socially vulnerable neighborhoods?
Data and methods
• Multiple data sources used:
– Primary data:
• Longitudinal panel survey of 1500 single family structures
• Longitudinal panel survey of approximately 550 households
– Secondary data sources
• Galveston permit data
• County appraisal district (CAD) parcel data
• Analyses include:
– Correlation analysis of impacts and actions taken by
socially vulnerable groups
– Spatial analysis relating development patterns to damage
– Longitudinal analysis of housing recovery
– Long-term displacement
FINDING: Inequitable development patterns affected damage received In the urban core of Galveston, many lower quality homes are only elevated a foot or less off the ground, if at all. Here, a poorly- constructed home has slid off its foundation, and the other structural systems have also collapsed.
In contrast, a West End vacation home sits well above the surge level, a block off the gulf coast, these high-quality homes received only wind damage, which as seen here, was quite minimal.
Transportation-dependent
FINDING: populations
PREDICTED
Using the Social
Vulnerability
Indicators from the
Coastal Community
Planning Atlas
r=-0.249*
OBSERVED
From Primary Data
Collected After
Hurricane Ike
Evacuated later
Source: Van Zandt, S., W.G. Peacock, *D. Henry, H. Grover, W. Highfield, and S. Brody. 2012. Mapping
Social Vulnerability to Enhance Housing and Neighborhood Resilience. Housing Policy Debate 22(1): 29-55.Households with high
FINDING: recovery needs
PREDICTED
Using the Social
Vulnerability
Indicators from the
Coastal Community
Planning Atlas
r=-0.235*
OBSERVED
From Primary Data
Collected After
Hurricane Ike
Had higher levels of overall damage
Source: Van Zandt, S., W.G. Peacock, *D. Henry, H. Grover, W. Highfield, and S. Brody. 2012. Mapping
Social Vulnerability to Enhance Housing and Neighborhood Resilience. Housing Policy Debate 22(1): 29-55.FINDING: Households with high social vulnerability
PREDICTED
Using the Social
Vulnerability
Indicators from the
Coastal Community
Planning Atlas
r=-0.289*
OBSERVED
From Primary Data
Collected After
Hurricane Ike
Applied less to FEMA and SBA for aid
Source: Van Zandt, S., W.G. Peacock, *D. Henry, H. Grover, W. Highfield, and S. Brody. 2012. Mapping
Social Vulnerability to Enhance Housing and Neighborhood Resilience. Housing Policy Debate 22(1): 29-55.FINDING: Minority neighborhoods received
greater degrees of damage
Higher levels of damage seen to
minority neighborhoods—even
after accounting for the age of the
housing and the proximity of the
housing unit to water and the
seawall.
Source: Highfield, W., W.G. Peacock, and S. Van Zandt. 2013. Determinants of Damage to Single-Family Housing from
Hurricane-induced Surge and Flooding: Why Hazard Exposure, Structural Vulnerability, AND Social Vulnerability Matter in
Mitigation Planning. Conditional accept at the Journal of Planning Education & Research.FINDING: Lower-value homes
recovered more slowly
Single-Family Housing
$250,000 • The average property value
pre-storm was $152,155, and
$200,000
dropped 20.1% due to Ike
damage.
House Value
$150,000
• Average property values
$100,000
regained 95.5% of the pre-
storm value within two years.
$50,000
• Lower value homes
experienced greater damage,
$0
2008_09 2009_04 2009_09 2010_09 lost a greater proportion of
Appraisal date their value, and have only
5% Distribution of Damage recovered 82% of their pre-
No Damage storm value.
19%
Minor
37%
Moderate
39%
Severe
Source: Van Zandt, S. T. Chang, and W.G. Peacock. 2011. Residential Rebuilding After Disaster: Findings from
Galveston, TX. Association of College Schools of Planning, Salt Lake City, UT, October 14, 2011.Hispanic
FINDING: Long-term displacement White
African-American
of African-Americans Galveston
25%
46%
25%
Bolivar
1%
39%
51%
Mainland
42% 35%
Distribution of Students enrolled in GISD, January 2010
19%
Van Zandt, S. , W.G. Peacock, D. Henry, and S. Willems. Demographic Impacts of
Natural Disasters. Urban Affairs Association Annual Meeting, Pittsburgh, PA, April
21, 2012.Summary • Disparate impacts to SV populations and their housing generate the potential for redevelopment and population change, including: – Loss of affordable housing stock – Exacerbation of pre-existing inequities • Highlights need for: – Targeting of resources – Capacity-building within SV populations – Pre-event planning for equitable recovery
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