In 1995 the King County Growth Management Planning Council established the Land Capacity Task Force, as part of its mandate under the Countywide Planning Policies, to monitor the effectiveness of growth management policies.

The Task Force was composed of

• elected officials,
• representatives from:
  • the University of Washington's Department of Urban Design and Planning,
  • public interest groups, and
  • the private sector, including the construction and development industry.

The Task Force was established to develop a methodology that all jurisdictions would use to develop accurate assessments of their capacity for accommodating the 20-year housing and employment targets, and to establish a baseline land capacity estimate for monitoring of future growth trends.

The standard methodology recommended by the Task Force is outlined here:

1. Estimate of the number of gross acres of vacant and redevelopable land in each zoning classification.
   
2. Apply a series of percentage discounts to arrive at an estimate of net acres in each classification.
   
3. Apply zoned densities for estimating the number of housing units on residential land.
   
4. Apply floor area ratios (FAR) for estimating potential commercial and industrial building square footage on commercial land.
   
5. Apply an appropriate square footage per employee factor to estimate the number of employees represented by that building square footage.
   
6. Account for existing housing units and employees to arrive at an estimate of growth capacity
   

We thought that a parcel-based approach within a GIS and relational database context would yield the most accurate results from applying such a methodology.

We used a preliminary release of King County GIS's comprehensive parcel database (RECDNET) along with other geospatial data inputs to create a fully-attributed parcel coverage. This was used, along with high-quality "legacy" zoning maps, to generate accurate zoning data coverages, for both current and potential zoning. In addition to these typical cadastral data sources, we also included environmental data, such as stream and wetland buffers, and steep slopes.

Current geospatial and parcel attribute digital data for the city gave us a base for calculating the number of current housing units, employees, and parcels, and for identifying vacant parcels and those with redevelopment potential. The geospatial digital data also allowed us to quickly eliminate certain lands with no potential for residential or commercial development from the analysis during the initial stage.

The application of zoning prescriptions on vacant and redevelopable parcels, combined with estimates of current housing units and employees, yielded figures for the net number of new housing units and employees that the city could accommodate under its adopted Comprehensive Plan.

Abstract Data Sources