This dataset represents the Flood Plain Management Services Study (FPMS) ares, 100-Year Flood for the Great Salt Lake. The area included Salt Lake City, Davis, Weber, tooele and box elder County The information was collected by digitzing the quad maps (Salt Lake, Tooele, boxelder county) and plat maps (weber and Davis county). The digital data contain the zone boundary and shoreline boundary. The FPMS study was limited to the general area along the Salt Lake County shoreline of the Great Salt Lake Only the 100-year flood elevation was evaluated and included wind and wave action for the Great Salt Lake. This dataset is the most current digital information available.

Retail shopping centers were identified using data from the following sources:

WFRC Real Estate Market Model (REMM) Retail Jobs by TAZ Utah Department of Workforce Services 2018 Employment Data County Assessor Tax Parcels

Selection Criteria: TAZs with 200 or more retail jobs were selected. Parcel Data was filtered to commercial parcels only (or retail only in Salt Lake County). Clustered commercial parcels within the selected TAZs were cross-checked using aerial imagery and google maps street-view to identify shopping centers. DWS retail employment data was heat-mapped and used to cross-check locations of identified shopping centers.

This dataset contains the urban growth simulation results of future land use in 2040 of the Wasatch Range Metropolitan Area (WRMA) .In this study, we defined the WRMA as a broad, ten-county region that surrounds the Wasatch Mountain Range east of the Great Salt Lake and Salt Lake City in Utah. This region encompasses four Wasatch Front counties west of the mountain range (Weber County, Davis County, Salt Lake County, and Utah County), three Wasatch Back counties east of the mountain range (Morgan County, Summit County, and Wasatch County), and three counties neighboring the Wasatch Front (Cache County, Box Elder County, and Tooele County).

SLEUTH-3r urban growth simulation model is used to generate this dataset. Detailed SLEUTH model protocol can be found at: http://www.ncgia.ucsb.edu/projects/gig/index.html. The data used to run the SLEUTH-3r model include National Land Cover Database 2001, 2006, and 2011, US Census TIGER/Line shapefile for 2000 and 2011, United States Geological Survey 7.5 min elevation model, and Utah Landownership map from Utah Automated Geographic Reference Center.

Three alternative scenarios were developed to explore how conserving Utah’s agriculturale land and maintaining healthy watersheds would affect the patterns and trajectories of urban development: 1) The first scenario is a “Business as Usual” scenario. In this scenario, federal, state, and local parks, conservation easement areas, and surface water bodies, were completely excluded (value = 100) from development, and all the remaining lands are were naively assumed as developable (value = 0). This is the same excluded layer that was also used during model calibration. Under this scenario, we hypothesized that future urban grow will occur following the historical growth behaviors and trajectories and no changes in land designation or policies to restrict future growth will be implemented. 2) The second scenario is an “Agricultural Conservation” scenario. Within the developable areas that we identified earlier, we then identified places that are classified by the United States Department of Agriculture (USDA) as prime farmland, unique farmland, farmland of statewide importance, farmland of local importance, prime farmland if irrigated, and prime farmland if irrigated and drained. Each of these classes were assigned with an exclusion value from urban development of 100, 80, 70, 60, 50, and 40 respectively. These exclusion values reflect the relative importance of each farmland classification and preservation priorities. By doing so, the model discourages but does not totally eliminate growth from occurring on agricultural lands, which reflects a general policy position to conserve agricultural landscapes while respecting landowners’ rights to sell private property. 3) A “Healthy Watershed” scenario aims to direct urban growth away from areas prone to flooding and areas critical for maintaining healthy watersheds. First, we made a 200-meter buffer around existing surface water bodies and wetlands and assigned these areas an exclusion value of 100 to keep growth from occurring there. In addition, we assigned areas that have frequent, occasional, rare and no-recorded flooding events with exclusion values of 100, 70, 40 and 0 accordingly. We also incorporated the critical watershed restoration areas identified by the Watershed Restoration Initiative of Utah Division of Wildlife Resources (https://wri.utah.gov/wri/) into this scenario. These watershed restoration areas are priority places for improving water quality and yield, reducing catastrophic wildfires, restoring the structure and function of watersheds following wildfire, and increasing habitat for wildlife populations and forage for sustainable agriculture. However, there are not yet legal provisions for protecting them from urbanization, so we assigned these areas a value of 70 to explore the potential urban expansion outcomes if growth were encouraged elsewhere.

Future land use projections of 2040 are in GIF format, which can be reprojected and georeferenced in ArcGIS or QGIS, or be read directly as a picture.

This file contains all population census tracts designated as Qualified Opportunity Zones (QOZs) as well as all population census tracts originally eligible for designation as a QOZ for purposes of §§ 1400Z–1 and 1400Z–2 of the Internal Revenue Code (the Code).

   Section 1400Z–1(b)(1)(A) of the Code allowed the Chief Executive Officer (CEO) of each State to nominate a limited number of population census tracts to be designated as Zones for purposes of §§ 1400Z–1 and 1400Z–2. Revenue Procedure 2018–16, 2018–9 I.R.B. 383, provided guidance to State CEOs on the eligibility criteria and procedure for making these nominations. Section 1400Z–1(b)(1)(B) of the Code provides that after the Secretary receives notice of the nominations, the Secretary may certify the nominations and designate the nominated tracts as Zones.

   Section 1400Z–2 of the Code allows the temporary deferral of inclusion in gross income for certain realized gains to the extent that corresponding amounts are timely invested in a qualified opportunity fund. Investments in a qualified opportunity fund may also be eligible for additional tax benefits.

   Field Descriptions:

   GEOID10 = 11 character census tract number

   STATENAME = Name of State

   COUNTYNAME = Name of County

   QOZ: "DESIGNATEDQOZ" = List of designated Qualified Opportunity Zones (QOZs). This variable was updated June 14, 2018, to reflect the final QOZ designations for all States. A total of 8762 population census tracts were designated. See IRS Notice 2018-48, 2018–28 Internal Revenue Bulletin 9, July 9, 2018, for the official list of all population census tracts designated as QOZs for purposes of §§ 1400Z-1 and 1400Z-2 of the Code.

   TYPE = Lists by State of all population census tracts eligible for designation as a QOZ. A "LIC" is a Low-Income Community census tract. A "contiguous" tract refers to Eligible Non-LIC Contiguous Tracts. A total of 31,848 LICs and 10,312 Non-LIC Contiguous Tracts were potentially eligible for QOZ designation.


   Data sourced from the U.S. Department of the Treasury Community Development Financial Institutions Fund. Further information found here: 

https://www.cdfifund.gov/Pages/Opportunity-Zones.aspx

   UPDATE 4/8/20: Demographic characteristics added from Stats America.