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 Base Social Vulnerability Indicators (percentages) 2 nd Order 3 rd 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 9. Non-white population/total population 10. Population in group quarters/total population 11. Housing units built 20 years ago/total housing Units 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 16. Population 16+ in labor force and unemployed/pop in Labor force 16+ 17. Population above 5 that speak English not well or not at all/pop > 5 Temporary Shelter and housing recovery needs Civic Capacity needs 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. Socially Vulnerable Hotspot
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 poorlyconstructed 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.
FINDING: Transportation-dependent 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.
FINDING: PREDICTED Using the Social Vulnerability Indicators from the Coastal Community Planning Atlas Households with high recovery needs 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.
House Value FINDING: Lower-value homes recovered more slowly $250,000 $200,000 $150,000 $100,000 $50,000 $0 19% 39% Single-Family Housing 2008_09 2009_04 2009_09 2010_09 Appraisal date 5% Distribution of Damage No Damage Minor 37% Moderate Severe The average property value pre-storm was $152,155, and dropped 20.1% due to Ike damage. Average property values regained 95.5% of the prestorm value within two years. Lower value homes experienced greater damage, lost a greater proportion of their value, and have only recovered 82% of their prestorm value. 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.
FINDING: Long-term displacement of African-Americans 25% 25% Hispanic White African-American 46% Galveston 39% 1% 51% Bolivar Mainland Distribution of Students enrolled in GISD, January 2010 42% 19% 35% 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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