Project Setup and Calibration

STEP 1: Select a Planning Geography

The planning geography should be selected based on the scale of the proposed planning effort and available data.  Small-scale plans often require a high degree of design control, so parcels may be most appropriate.  For large-scale (city/county/region) planning a larger planning geography may be advisable, such as Census Blocks.

  • Parcel boundaries for detailed or small-scale planning (with land and structure value data)
  • Larger boundaries (Census Block etc) for city-wide or regional planning
  • Hybrid boundaries (some combination of above)

Parcel-based Scenario Planning 

Painting scenarios on existing parcels is a common desire as it allows for a high level of design control and detail.  Obtaining accurate and consistent parcel data can be challenging, however.  Property assessors, in theory, maintain the parcel-based attributes needed to populate your scenario layer with the existing development.

STEP 2: Basic Setup

Developed and Vacant Lands

Envision Tomorrow relies on two primary GIS fields to quantify the amount of buildable land for each polygon.  The VAC_ACRE field is a numeric acreage field where the amount of vacant, buildable (not constrained) land is quantified.  The DEVD_ACRE field is a numeric field where the amount of currently developed, but redevelopable land is quantified.  Constraints may or may not be taken out of the DEVD_ACRE field depending on local regulations.  For instance, in some places developed areas in floodplains may be redevelopable.

Constrained Lands

In any region, there is land that is not suitable for development, whether it is open water or based on a policy that restricts development.  Typically, the “hard” environmental constraints are removed from the developable lands within your Envision Tomorrow scenario layer.  “Soft” constraints, on the other hand, may not explicitly restrict growth but to test policy options in a scenario, it may be helpful to include these layers in the base map for reference. 

'Hard' Environmental Constraints (Vary by Project Location)

  • Parks and open space
  • Topography (DEM and/or  topo lines)
  • Water, lakes, rivers, streams (lines and polygons)
  • Wetlands (NWI or local)
  • FEMA Zones (floodways)
  • Steep Slopes
  • Riparian areas

‘Soft' Environmental Constraints (optional - can vary by scenario policy objectives) 

  • Natural hazards (land slide area, tsunami, seismic zones, wildfire areas)
  • Brownfields
  • Soil types
  • Aquifer recharge zones
  • Wildlife habitat
  • Others

STEP 3: Advanced Setup


  •  Parcel-based Assessor data
    • Existing land use: should be sufficiently detailed to translate each parcel in to the Envision Tomorrow existing land use categories.
    • Residential dwelling units (count)
    • Building square footage
    • Year built (effective year built is preferred)
    • Value: Market value is preferred; appraised value is second choice; and assessed value is third choice.  It must be clear which type of valuation is provided.
      • Land Value
      • Improvement Value

 Additional GIS Data

  • General Plan/Comprehensive Plan
    • GIS layer and symbology
    • Entitlement allowances (height, density, FAR etc)
  • Zoning
    • GIS layer and symbology
    • Entitlement allowances (height, density, FAR etc)
  • Other special or sub-area plans

STEP 4: Populating the Scenario Layer with Existing Development 


Tax assessors use a variety of words and phrases to describe different types of land uses.  Envision Tomorrow has a standard classification system for describing land use.  The user is responsible for translating the Assessor’s unique land use classification into the standard system described below.  The ET-friendly land use classification attribute field in the scenario layer is “EX_LU” – which is shorthand for Existing Land Use. 

Envision Tomorrow’s Land Use Classification Schema:

Existing Land Use Classification EX_LU GIS Name
Mixed-Use MU
Multifamily MF
Townhome TH
Single Family Small Lot* SF_SM
Single Family Conventional Lot SF_MD
Single Family Large Lot SF_LRG
Mobile Home MH
Retail RET
Office OFF
Industrial IND
Public / Civic PUB
Educational EDU
Hotel / Hospitality HOTEL
Utilities / Infrastructure UTIL
Commercial Parking PKG
Agricultural AG
Open Space OS
Vacant VAC
Unknown NONE

* There is no definitive standard to distinguish between “small lot” and “large lot” single family.  Local norms can be quite different from place to place.  The user can select single family parcels of different size thresholds in order to code them with the appropriate description.

STEP 5: Translating Assessor Land Use Attributes into ET

Tax Assessors (theoretically) maintain many quantifiable attributes about the structures themselves that are useful to Envision Tomorrow scenarios.  For instance, Assessor data may include housing unit counts or square footages.  Coding and tracking this information within the scenario layer is important for two main reasons: 1) many of the scenario indicators require total counts (of housing, jobs etc) in order to calculate accurate outputs, and 2) quantifying the existing development allows ET to account for and track displacement through redevelopment.

Existing Development Fields (if data is present to populate):

Unit Type GIS Field Name (Double Format)
Population EX_POP
Housing Units EX_HU
Multifamily EX_MF
Townhome EX_TH
Single Family EX_SF
Small Lot Single Family * EX_SF_SM
Conventional Lot Single Family * EX_SF_MD
Large Lot Single Family * EX_SF_LRG
Mobile Home EX_MH
Retail EX_RET
Office EX_OFF
Industrial EX_IND
Public / Civic EX_PUB
Educational EX_EDU
Hotel / Hospitality EX_HOTEL
Hotel Room EX_HOTEL_RM
Utilities / Infrastructure EX_UTIL
Commercial Parking EX_PKG
Agricultural EX_AG


* There is no definitive standard to distinguish between “small lot” and “large lot” single family.  Local norms can be quite different from place to place.  The user can select single family parcels of different size thresholds in order to code them with the appropriate description.

Employment Data

Employment data is notoriously difficult to obtain at a fine-grained spatial level.  The Census LEHD dataset has detailed employment data, by sector, at the Block level.  In many regions, that is the best source of detailed employment data.  Other sources are Traffic Analysis Zone (TAZ) data produced by entities running travel demand models, which is most often area MPOs, or in some cases cities or counties.  

The table below offers advice on how to convert the detailed, NAICS employment counts in the LEHD dataset to ET-friendly naming convention.  

NAICS code Description ET GIS Employment Count Field
11 Agriculture, Forestry, Fishing and Hunting EX_AG
21 Mining, Quarrying, and Oil and Gas Extraction EX_IND
22 Utilities EX_PUB
23 Construction --
31-33 Manufacturing EX_IND
42 Wholesale Trade EX_IND
44-45 Retail Trade EX_RET
48-49 Transportation and Warehousing EX_IND
51 Information EX_OFF
52 Finance and Insurance EX_OFF
53 Real Estate and Rental and Leasing EX_OFF
54 Professional, Scientific, and Technical Services EX_OFF
55 Management of Companies and Enterprises EX_OFF
56 Administrative and Support and Waste Management and Remediation Services EX_OFF
61 Educational Services EX_EDU
62 Health Care and Social Assistance EX_OFF
71 Arts, Entertainment, and Recreation EX_RET
721 Accommodation EX_HOTEL
722 Food Services and Drinking Places EX_RET
81 Other Services (except Public Administration) EX_OFF
92 Public Administration EX_PUB


STEP 6: Base Map Reference Layers

Most of the layers included in the GIS map used for scenario planning are not used in processing but rather are available to be turned on and off for reference while the scenario builder designs a range of scenarios.

Infrastructure (Current and Planned)

  • Road network
  • Transit network
  • Railroad or freight network

Detailed Transportation (Optional)

  • Roads by type with additional info (e.g. speed, lanes, traffic volumes)
  • Transit by type with additional info (e.g. headways, stations/stops/points)
  • Road widths
  • Pedestrian network (including sidewalks and pathways)
  • Bicycle network (including bike lanes)
  • Trails and walking paths

Additional Infrastructure (Current and Planned)

  • Sewer
  • Water
  • Power
  • Drainage
  • Canals


STEP 7: Other Data Requirements for Core Envision Tomorrow Features


  • Official/adopted forecast – important to design a plan-based reference case scenario
  • Market demand forecast – important when designing alternative scenarios


In order to calibrate the rents and costs of the building library used in the scenario planning process, it necessary to gather up to date construction and market data.  Online sources and developer interviews are sufficient to gather the needed building-level inputs.

  • Construction and market data for urban, suburban and rural markets (as needed) 
  • Approximate land costs by land use type for existing developed land and by zone type for raw land 
  • Construction cost per square foot by land use type 
  • Rents for rental housing, retail, office and industrial uses 
  • Sales prices for owner residential units (single family, townhome and multifamily condo) 

Sample Dataset

First time users often find it helpful to see a complete sample dataset.  For an explanation of this dataset, download link, and information about how it was developed, follow the link below: