Presentation on theme: "Alan D. Jensen GIS and Planning Specialist ISU Extension Community and Economic Development."— Presentation transcript:
Alan D. Jensen GIS and Planning Specialist ISU Extension Community and Economic Development
On June 8, 2008, waterways in the Cedar and Iowa River watersheds began to flood.
Eight communities of different sizes four metropolitan areas, one micropolitan community and three rural towns to determine the effectiveness of state and federal assistance programs on the ability of communities to replace the housing that was lost in this natural disaster..
Intent of study : create a housing needs assessment model with which communities can evaluate their long- term demand for affordable, decent and safe housing for all ranges of income, family size, and special needs within their populations The cities:
The Iowa Department of Economic Development (IDED), in partnership with the Iowa Finance Authority (IFA) and the Rebuild Iowa Office (RIO), engaged the services of Iowa State University and Iowa State University Extension and Outreach Community and Economic Development to undertake a study of eight communities heavily impacted by the Iowa floods of IDED, IFA and RIO selected the cities…
Flood recovery would be a complicated endeavor: $4.37 billion in federal and state assistance was allocated for eastern Iowa flood recovery through December This funding came from 27 different programs sponsored by 14 government agencies, nine of which are federal and five of which are state agencies.
METHODOLOGY Economic Benchmarks and Impact Analysis Focus Groups Online Survey Key Informant Interviews Archival Documentary Review of Pre-Existing Planning Materials Geospatial Analysis of Housing Data
A few of the challenges to overcome for the GIS study portion: : 1.Identify consistent and accurate data sources that include benchmark data prior to the disaster. 2.The same source should provide data for a period or periods of time following disaster. 3.The data need to have spatial dimension so that actual impacts of the disaster can be targeted and not be reliant on place aggregate data. 4.Housing units impacted with that zone need to be identified. 5.Identify subsequent housing unit development within the impacted area, as well as the broader community, to determine how the area has compensated for lost housing units.
Potential Data Sources Examined but Not Utilized: investor-owned electric utilities public water utilities Why not? Investor owned utilities…proprietary information Public utilities…not generally found within a workable format for GIS Obtaining longitudinal data on hookups by address also proved problematic data Limited means of some city utilities data management systems to export data
Data Sources Examined and Utilized: County Assessors Office County GIS Coordinators Iowa Department of Natural Resources GIS Library (esp. Flood Extent from SPOT Satellite Data) Iowa Department of Transportation Iowa State University GIS Support and Research Facility the ortho server:
Geospatial Analysis of Housing Data X=(UL-P)+D Whereas: X = Net housing need in community UL = Units lost due to natural disaster P = New housing units constructed D = Housing demand from local economic performance
Flood impact or recession?
Employment and school enrollments: recession or flood?
Final Observations from the GIS Portion of the Study: 1.Privately- and publicly-owned utilities are not practical sources for GIS housing data. 2.While assessors offices are excellent sources of GIS data, limitations exist when conducting long-term planning and analysis. 3.The housing market gap should be evaluated by units lost and by the difference in the value of replacement housing. 4.The impact of natural disasters on housing tend to be more significant in low-growth or declining economies.
General findings of the study: The local economic growth of Iowa City, Coralville and Cedar Rapids, created a housing demand beyond the units lost from the flood. Economic conditions in Charles City and Columbus Junction added no real growth in housing demand; the overall housing impacts derived from either the flood or the local economies remain negligible.
Waterloo and Mason City actually realized more new housing units in the past two years than would have been predicted by flood losses and the economic growth – a slight excess of housing is indicated.
Replacement housing is often not the equivalent of the housing lost through flooding. More affordable housing lost in the flood is being replaced with significantly more expensive housing.