TAZ - Traffic Analysis Zone - demographics are reported at the level of these polygonsIn the fieldnames listed below:GQ is Group QuartersDEMOG refers to Demographic Area (a superset of the TAZ polygons.FIA is Fiscal Impact AreaT is totalEST is estimateHH is householdsPOP is populationThe number (for example 50) refers to the projection year.OBJECTID, fixed, fixed, TAZ polygon fileTAZID_CURRENT, NUMERIC - DOUBLE, official TAZ ID , TAZ polygon fileTAZNAME, TEXT, current TAZ, TAZ polygon fileCOUNTY, TEXT, Ada or Canyon, TAZ polygon fileIMPACTAREA, TEXT, attributed by "centroid" within impact area, reviewed city limits and assigned to one or the other. TAZs in Eagle / Star area where the impacts overlap are labeled overlap. Defaut off for open data. , TAZ polygon fileDEMOGAREA, TEXT, new ones established last year. Might be named demognew in previous TAZ file, TAZ polygon fileFIALABEL, TEXT, fiscal impact areas - based on center within intersect. Default off for open data, TAZ polygon fileFIADESCRIP, TEXT, fiscal impact areas - based on center within intersect. Default off for open data, TAZ polygon fileTAZACRES, NUMERIC, , TAZ polygon fileTPOPEST19, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST19, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST19, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST19, NUMERIC, Provided April following year, table attached to TAZ polygon fileTPOPEST20, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST20, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST20, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST20, NUMERIC, Provided April following year, table attached to TAZ polygon fileIn the fields below, “T” stands for total. For example TPOPEST21 refers to the total population and includes ‘group quarters’. Whereas POP50F does not contain group quarter populations.TPOPCENSUS, NUMERIC, Provided Fall of 2021, table attached to TAZ polygon fileGRPQTRCENSUS, NUMERIC, Provided Fall of 2021, table attached to TAZ polygon filePOPCENSUS, NUMERIC, Provided Fall of 2021, table attached to TAZ polygon fileHHCENSUS, NUMERIC, Provided Fall of 2021, table attached to TAZ polygon fileTPOPEST21, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST21, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST21, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST21, NUMERIC, Provided April following year, table attached to TAZ polygon fileTPOPEST22, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST22, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST22, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST22, NUMERIC, Provided April following year, table attached to TAZ polygon fileTPOPEST23, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST23, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST23, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST23, NUMERIC, Provided April following year, table attached to TAZ polygon fileTPOPEST24, NUMERIC, Provided April following year, table attached to TAZ polygon fileGQREST24, NUMERIC, Provided April following year, table attached to TAZ polygon filePOPEST24, NUMERIC, Calc TPOP-Group Quarters, table attached to TAZ polygon fileHHEST24, NUMERIC, Provided April following year, table attached to TAZ polygon fileTPOP25F, NUMERIC, CIM 2050 forecasts start here-these will be updated annually through reconciliation. Field names will not change, table attached to TAZ polygon filePOP25F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH25F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS25F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileTPOP30F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon filePOP30F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH30F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS30F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileTPOP35F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon filePOP35F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH35F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS35F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileTPOP40F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon filePOP40F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH40F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS40F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileTPOP45F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon filePOP45F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH45F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS45F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileTPOP50F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon filePOP50F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileHH50F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon fileJOBS50F, NUMERIC, CIM 2050 forecasts done in 2021 reconciled each spring afterward, table attached to TAZ polygon file

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

TAZ Population and Employment Forecasts for the DVRPC region, 2015 - 2050. To be used for planning purposes.

As a part of DVRPC’s long-range planning activities, the Commission is required to maintain forecasts with at least a 20-year horizon, or to the horizon year of the long-range plan. Allocation of growth is forecasted using a land use model, UrbanSim, and working closely with member county planning staffs. DVRPC has prepared regional, county, and municipal-level population and employment forecasts in five-year increments through 2050, using 2015 Census population estimates and 2015 National Establishments Time Series (NETS) employment data as the base. A forthcoming Analytical Data Report will document the forecasting process and methodologies.

While the forecast is not adopted at the transportation analysis zone (TAZ) level, it is allocated to these zones for use in DVRPC’s travel demand model and conforms to municipal/district level adopted totals. This data provides TAZ-level population and employment. Other travel model attributes are available upon request. Note: while 2019 land use model results are provided, the forecast was only adopted for 2015, 2020, 2025, 2030, 2035, 2040, 2045, and 2050.

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

Important Dataset Update 6/24/2020:Summit and Wasatch Counties updated.Important Dataset Update 6/12/2020:MAG area updated.Important Dataset Update 7/15/2019:This dataset now includes projections for all populated statewide traffic analysis zones (TAZs).Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below.Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.As with any dataset that presents projections into the future, it is important to have a full understanding of the data before using it. Before using this data, you are strongly encouraged to read the metadata description below and direct any questions or feedback about this data to analytics@wfrc.org.Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2019-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2015 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.As these projections may be a valuable input to other analyses, this dataset is made available at http://data.wfrc.org/search?q=projections as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.Wasatch Front Real Estate Market Model (REMM) ProjectionsWFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:Demographic data from the decennial census;County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature;Current employment locational patterns derived from the Utah Department of Workforce Services;Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff;Current land use and valuation GIS-based parcel data stewarded by County Assessors;Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations; andCalibration of model variables to balance the fit of current conditions and dynamics at the county and regional level.‘Traffic Analysis Zone’ ProjectionsThe annual projections are forecasted for each of the Wasatch Front’s 2,800+ Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).‘City Area’ ProjectionsThe TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.Summary Variables in the DatasetsAnnual projection counts are available for the following variables (please read Key Exclusions note below):DemographicsHousehold Population Count (excludes persons living in group quarters)Household Count (excludes group quarters)EmploymentTypical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)Retail Job Count (retail, food service, hotels, etc)Office Job Count (office, health care, government, education, etc)Industrial Job Count (manufacturing, wholesale, transport, etc)Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count.All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).* These variable includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.Key Exclusions from TAZ and ‘City Area’ ProjectionsAs the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

The Connect 2045 population forecast is based on county level population forecasts for 2045 from Woods and Poole economics Inc. The county level population was assigned to towns in proportion to each town's share of the county's population. Each town's population growth was assigned to TAZs based on input from town staff on where growth is expected to happen over the next 20 years.

Environmental Justice areas are identified at the Transportation Analysis Zone (TAZ) level. A TAZ is an agglomeration of Census Blocks, but smaller than a Census Tract, allowing for a refined approach with significant accuracy, small enough to capture population within often overlooked geographies, yet large enough to leverage accurate sample data.A TAZ will be identified as a location of EJ concern if it has a minority population percentage at or above the lesser of the regional average or the national average and/or a population in poverty whose percentage of the full TAZ is at or above the lesser of the regional average or the national average. For the criteria mentioned above, a location identifies as an EJ area if either or both of the following thresholds are met:Percent of residents of minority status at or above 31.65%Percent of residents at or below poverty level: 13.63%Data Source: American Community Survey (ACS) 5-year EstimatesCurrent Vintage: 2018-2022Data Processing Notes:NOACA staff implement their EJ analysis through the following steps so they can identify and map EJ areas in Northeast Ohio:Calculate the percentage of both the United States current population and NOACA’s current population that is “minority.”Calculate the percentage of both the United States current population and NOACA’s current population that is below the poverty level.Compare the values in Step 1; the lesser value is the minority criterion. Compare the values in Step 2. The lesser value is the poverty criterion.For each TAZ, NOACA staff estimate the minority and poverty percentages of that TAZ’s current population.If either the TAZ’s minority percentage or poverty percentage exceeds the minority criterion or the poverty criterion, respectively, then NOACA staff identify that TAZ as an Environmental Justice Area of Concern.For more information visit Northeast Ohio Areawide Coordinating Agency (NOACA)

The Metropolitan Planning Organizations (MPO) uses a travel demand model called the Triangle Regional Model (TRM). All the socioeconomic input data (e.g., population and employment) is done by a zone called the Traffic Analysis Zone (TAZ). Durham County, for example, is divided into 510 TAZs and the socioeconomic data for each of those TAZs in input into the model.

2010 The 2010 population data is based on the 2010 US Census. The 2010 employment data is estimated based on a methodology in which local planning staff collect employment location and numbers for their planning areas.

2040 County-level population forecast data from the N.C. Office of State Management and Budget is input into a land use model, called Community Visualization, that distributes that county-level forecast to the various TAZs in each county based on the relative attractiveness of land parcels for development. County-level employment forecasts for the year 2040 are based on county-level growth forecasts from Woods-and-Poole Economics, that are then distributed to the TAZs by Community Visualization. Last updated on 08/29/2014.

Using data from the 2009-13 ACS 5 Year Estimates at the Census Designated Place level (CDP), calculate total percentage of minority population and total percentage of households in poverty for each CDPAlso using census tract data from the 2009-13 ACS 5 Year Estimates, tabulate percentage of minority population and total percentage of households in poverty for each City of Los Angeles Community Planning Area (CPAs)Intersect CPAs with Census Tracts and tabulate new totals for partial CPA/Census Tracts based on spatial interpolationSum total Poverty, households, minority, and population values for each CPAMerge CDPs and City of Los Angeles Community Planning Areas to create a single “Place” file for the entire SCAG region. Remove the City of Los Angeles CDP from layer. Tabulate % of households in poverty and % of minority population for each “Place”Using ranked sorting, select the places that are in the upper third in the SCAG region for both % of households in poverty (x > 0.169156) and% minority (x > 0.768549)Identify those places and export to new shapefile – “Communities_of_Concern”Union “Communities_of_Concern” shapefile with Tier2 TAZ file and tabulate % of each tract that falls in “Communities_of_Concern”Calculate total square meters in Tier2 TAZ shapefileUnion shapefile with “Communities_of_Concern”Tabulate new square meters in Tier 2 TAZ shapefileExport attribute table to DBFLoad DBF in excel and use pivot tables to tabulate total acreage by TAZ only for tracts that intersect with “Communities_of_Concern”. Create new DBF with results and load into ArcMapJoin new DBF with Tier2 TAZ shapefile and calculate % of TAZ that falls in “Communities_of_Concern” only for the records that join. All other TAZs remain 0%, if they do not intersect.

The dataset includes the CDR of Riyadh city, the Traffic Analysis Zones (TAZs) locations, proposed metro stations, demographic data about the city, and the road network. Those will be explored in the following.CDRCDR data represents a digital record containing information about a telephone call or communication session. A CDR typically includes information such as the caller's and recipient's phone numbers, the date and time of the call, the duration of the call, and any additional services or features used during the call (e.g., call forwarding, call waiting). In addition, CDRs may contain information about the type of call (voice, video, data), the caller's or recipient's location, and details about any supplementary services utilized during the call.The CDR file used is provided by STC for Riyadh and collected from 1,712 towers over a month, separated by hours. Each hour contains call details during that hour. These details include information about where calls originated and ended and at what hour of the day. TAZTraffic Analysis Zones (TAZs) are geographical areas defined and used for transportation planning and traffic analysis purposes. TAZs are created by dividing a large region or area into smaller sub-areas based on population density, land use patterns, transportation infrastructure, and socio-economic characteristics.TAZs are defined to facilitate transportation planning and analysis by providing a more granular and manageable unit for studying travel patterns and forecasting transportation demand. TAZs are often used in transportation models and simulations to estimate and analyze traffic flows, travel behavior, and travel demand within specific areas. As part of this study, Riyadh city is defined as 1,492 TAZs.Metro StationsIn this study, we consider the 84 metro stations. Based on the spatial information of each TAZ, we associated each TAZ with the closest metro station. This made it easier to predict metro usage.Demographic DataThe demographic data is available in TAZ. Each TAZ includes data on the total population of males, females, and non-Saudis. Females and non-Saudis are expected to utilize the metro more based on the sociocultural implications of the region. Hence, areas with higher concentrations of those populations expect more metro usage.Road NetworkThe road network comprises several thousand lines, each represented by numerous points defined by latitude and longitude. These points constitute nodes. These road lines are the pathways that users travel on while making a call.

As a part of DVRPC’s long-range planning activities, the Commission is required to maintain forecasts with at least a 20-year horizon, or to the horizon year of the long-range plan. Allocation of growth is forecasted using a land use model, UrbanSim, and working closely with member county planning staffs. DVRPC has prepared regional, county, and municipal-level population and employment forecasts in five-year increments through 2050, using 2015 Census population estimates and 2015 National Establishments Time Series (NETS) employment data as the base. A forthcoming Analytical Data Report will document the forecasting process and methodologies.While the forecast is not adopted at the transportation analysis zone (TAZ) level, it is allocated to these zones for use in DVRPC’s travel demand model and conforms to municipal/district level adopted totals. This data provides TAZ-level population and employment. Other travel model attributes are available upon request. Note: while 2019 land use model results are provided, the forecast was only adopted for 2015, 2020, 2025, 2030, 2035, 2040, 2045, and 2050.

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

The data in this file include for each county the number of Federal income tax returns filed and the number of exemptions claimed. Within each category, data are provided on the number of tax filers that migrated into the county, the number that migrated out of the county, and the number for which migration status was unknown. The total number of returns filed is also provided.

This dataset contains tabular data at county, municipal/planning district, and zonal levels for the Adopted 2050 v1.0 Population & Employment Forecasts. DVRPC uses 2050 v1.0 to as the forecast vintage nomenclature, as it is the first forecast to use 2050 as a horizon year. Analytical Data Report (ADR 21014) documents the forecasting process and methodologies.

As a part of DVRPC’s long-range planning activities, the Commission is required to maintain forecasts with at least a 20-year horizon, or to the horizon year of the long-range plan. Allocation of growth is forecasted using a land use model, UrbanSim, and working closely with member county planning staffs. DVRPC has prepared regional, county, and municipal-level population and employment forecasts in five-year increments through 2050, using 2015 Census population estimates and 2015 National Establishments Time Series (NETS) employment data as the base.

Note: while 2019 land use model results are provided, the forecast was only adopted for 2015, 2020, 2025, 2030, 2035, 2040, 2045, and 2050.

While the forecast is not adopted at the transportation analysis zone (TAZ) level, nor for intervening years between those ending in "0" or "5", it is allocated to these zones for use in DVRPC’s travel demand model in our UrbanSim land use model. TAZ data conforms to municipal/district level adopted totals for population and employment. It also generates a number of other attributes required for the travel demand model.

MAG Projections of Population, Housing, and Employment for Buckeye by Traffic Analysis Zone 2019

This dataset is about countries per year in the United States. It has 1 row and is filtered where the date is 2021. It features 4 columns: country, tax revenue, and population.

This data collection supplies standard monthly labor force data as well as supplemental data on work experience, income, noncash benefits, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 14 years old and older. Additional data are available for persons 15 years old and older concerning weeks worked and hours per week worked, reason not working full-time, total income and income components, and residence. This file also contains data covering noncash income sources such as food stamps, school lunch programs, employer-provided group health insurance plans, employer-provided pension plans, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. This collection was formed by expanding CURRENT POPULATION SURVEY: ANNUAL DEMOGRAPHIC FILE, 1983 (ICPSR 8192) to include an estimate of after-tax income, "before-tax" money income from the previous year, and the amount of taxes paid. Taxes paid include federal and state individual income taxes, property taxes on owner-occupied housing units, Social Security taxes, and retirement taxes. Information on demographic characteristics, such as age, sex, race, marital status, veteran status, educational attainment, household relationship, and Hispanic origin, is available for each person in the household enumerated.

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

Table of population and demographic forecast numbers from Plan Bay Area 2040 for the San Francisco Bay Region. Population and demographic numbers are included for 2005, 2010, 2015, 2020, 2030, 2035, and 2040. There are no forecast numbers for 2025.The Plan Bay Area forecast numbers were generated by Transportation Analysis Zone (TAZ). The Population and Demographics forecast table will need to be joined to TAZ features in order to spatially visualize the data. The TAZ features are available for download here.2005-2040 data in this table:Total PopulationHousehold PopulationGroup Quarters Population0 - 4 Age Group5 - 19 Age Group20 - 44 Age Group44 - 64 Age Group65+ Age GroupShare of Total Population that is 62 and OverHigh School EnrollmentCollege Enrollment (full-time)College Enrollment (part-time)Other Plan Bay Area 2040 forecast tables:Employment (total employment, TAZ resident employment, retail employment, financial and professional services employment, health, educational, and recreational employment, manufacturing, wholesale, and transportation employment, agricultural and natural resources employment, and other employment)Households (number of households and household income quartile)Land Use and Transportation (area type, commercial or industrial acres, residential acres, number of single-family and multi-family dwelling units, time to get from automobile storage location to origin/destination, and hourly parking rates)

This scatter chart displays urban population (people) against tax revenue (% of GDP) in Costa Rica. The data is about countries per year.