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When Domains Collide (epan 2011)

When Domains Collide (epan 2011)






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    When Domains Collide (epan 2011) When Domains Collide (epan 2011) Presentation Transcript

    • When Domains Collide: Linking Databases to Determine Pupil Generation Rates Jessica Gormont , Jefferson County GIS/Addressing Office Tori Myers , Jefferson County Assessor’s Office Mark Schiavone , Jefferson County Department of Capital Planning and Management
    • School Impact Fee
      • Fee levied against new residential construction
      • Calculated to ensure capacity expansion
    • School Impact Fee Impact Fee = ( Cost - Credit ) x Demand Generator Asset value per student Non-impact fee revenue per student Students per residential unit
    • Pupil Generation Rate: The number of school-aged children, usually expressed as level of schooling, per household.
      • Traditionally Determined:
      • Using Census/PUMS data
      • Local census/sampling
    • Current Status: Jefferson County
      • Pupil Generation data linked to Housing Unit Type:
        • Single Family Detached (includes manufactured homes)
        • Townhome/Duplex
        • Multifamily Apartment
    • Example: Miami-Dade County Pupil Generation Rates vs. Housing Unit Size (idealized)
    • Board of Education Transportation Database
      • Highly granular: pupil generation per address
      • Lacks information about housing unit type or size
    • Assessor’s Database
      • Highly granular: Housing unit type and size
      • Addresses not accurate – Parcel_ID highly accurate
    • How to Link? BOE data (good addresses) Assessor data (good map/parcel) County GIS Link addresses to addresses Link parcel_id to parcel_id
    • The Plan
      • Analyze BOE data and clean
      • Pass BOE data to GIS for join
      • GIS pass data to Assessor to add building data
      • Deliver combined dataset to consultant for analysis
    • Preliminary Data
      • Original parcel layer created in 2009
      • IAS queries for tax code data
    • Finding Residential Addresses
      • Spatial Join - address points & parcel polygons
        • added Parcel ID to points
      • Tabular Join - address points & IAS data
        • added tax codes to address points
    • Adding BOE Data
      • Tabular Join - BOE data & address points
        • Loss of 12.5%
        • Loss caused by variety of errors
      • Secondary Visual Clean Up of BOE data
      • Second Tabular Join of BOE data
        • loss of 10% - deemed acceptable
    • Adding Additional Information
      • Decided to add secondary information in case needed by contractor
      • Spatial Join to Jurisdiction layer
        • Allowed for removal of address points within towns if necessary
      • Spatial Join to Subdivision/MHP layer
        • Allowed for separation of Mobile Homes in MHPs
    • Final Data
      • Data received from GIS
      • Several queries to retrieve data for Living unit size and number of bedrooms.
    • Final Data
      • Final data sent to contractor contained:
        • Physical Location Address
        • Parcel ID
        • Tax Code
        • Number of School Kids by Grade Level
        • Building Assessment Data
        • Jurisdiction
        • Subdivision/MHP name
    • Results
      • Original census data from 2000
      • Only 3 housing unit types recognized
      • No further granularity
    • Results
    • Results
    • Results
    • Results
    • Conclusion
      • Multiple databases linked with no loss of fidelity
      • GIS datasets are rich and merge well with other domains
      • Agencies able to create sophisticated studies at low cost