LCI Opportunity Areas

Metadata also available as - [Outline]

Frequently anticipated questions:

What does this data set describe?

Title: LCI Opportunity Areas
Abstract:
This is the subset of parcels that meet all three of the following "specified criteria" in the King County code 26.12.003J definition of "Opportunity Areas". Areas within King County that:(a) "are located in a census tract in which the median household income is in the lowest one-third for median household income for census tracts in King County;(b) "are located in a ZIP code in which hospitalization rates for asthma, diabetes, and heart disease are in the highest one-third for ZIP codes in King County; and(c) "are within the Urban Growth Boundary and do not have a publicly owned and accessible park or open space within one-quarter mile of a residence, or are outside the Urban Growth Boundary and do not have a publicly owned and accessible park or open space within two miles of a residence." (King County Code 26.12.003J)
  1. How might this data set be cited?
    County, King, 20201221, LCI Opportunity Areas: King County, King County, WA.

    Online Links:

    Other_Citation_Details: None
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -122.371886
    East_Bounding_Coordinate: -121.954910
    North_Bounding_Coordinate: 47.782154
    South_Bounding_Coordinate: 47.184287
  3. What does it look like?
    http://www5.kingcounty.gov/sdc/DataImages/lci_opportunity_parcel.jpg (JPG)
    JPG File of layer overlain on base of WA counties or local cities
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 01-Jan-2016
    Ending_Date: 24-Sep-2024
    Currentness_Reference:
    Includes data from 2020 Census, 2022 5-year American Community Survey (2018-2022), 2018-2021 hospitalization data, and a composite layer of park and open space data compiled in September 2024
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: vector digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • GT-polygon composed of chains (28725)
    2. What coordinate system is used to represent geographic features?
      The map projection used is NAD 1983 HARN StatePlane Washington North FIPS 4601 Feet.
      Projection parameters:
      Standard_Parallel: 47.5
      Standard_Parallel: 48.73333333333333
      Longitude_of_Central_Meridian: -120.8333333333333
      Latitude_of_Projection_Origin: 47.0
      False_Easting: 1640416.666666667
      False_Northing: 0.0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.0005
      Ordinates (y-coordinates) are specified to the nearest 0.0005
      Planar coordinates are specified in foot_us
      The horizontal datum used is D North American 1983 HARN.
      The ellipsoid used is GRS 1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
  7. How does the data set describe geographic features?
    maint.WLR.lci_opportunity_parcel_area
    area data table (Source: King County)
    OBJECTID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    PIN
    Parcel number (Source: King County)
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    Shape.STArea()
    Shape.STLength()
    Entity_and_Attribute_Detail_Citation: King County

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
  2. Who also contributed to the data set?
    King County
  3. To whom should users address questions about the data?
    King County IT, GIS Center
    Attn: Fred Lott
    GIS Specialist
    201 S Jackson St, MS KSC-IT-225
    Seattle, WA
    US

    206-477-4758 (voice)

Why was the data set created?

Locations where households lack open space access and simultaneously fall in the bottom third of census tracts for household income and top third of ZIP codes for hospitalization rates due to asthma, diabetes, and heart disease. Dataset produced September 2024.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints:
Access Constraint: Data is available on GIS Data Portal: http://www5.kingcounty.gov/gisdataportal/Default.aspx
Use_Constraints:
Use Constraint: King County data are made available with the understanding that they shall be used exclusively by the obtainer or his/her authorized agents. Digital products may not be reproduced or redistributed in any form or by any means without the express written authorization of King County.
  1. Who distributes the data set? (Distributor 1 of 1)
    KCGIS Center
    Attn: giscenter@kingcounty.gov
    Data Distribution
    201 S Jackson St
    Seattle, WA
    US

    206-477-4403 (voice)
  2. What's the catalog number I need to order this data set? /plibrary2/natres/shapes/polygon/lci_opportunity_parcel.shp
  3. What legal disclaimers am I supposed to read?
    Distribution Liability: King County disclaims any warranty of use of any digital product or data beyond that for which it was designed.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 14-Sep-2022
Metadata author:
King County IT, GIS Center
Attn: Fred Lott
GIS Specialist
201 S Jackson St, MS KSC-IT-225
Seattle, WA
US

206-477-4758 (voice)
firstname.lastname@kingcounty.gov
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
Generated by mp version 2.9.50 on Sat Nov 2 12:02:54 2024