Once we had a table with a record for each possibly redevelopable parcel within the City, we then began applying filtering and calculating algorithms to generate data summaries. These filters and calculations took place entirely within the MS-Access project.

The first step was to separate the records into residential and non-residential types (Figure 5).

Residential (Housing Units)

The net number of new residential housing units was calculated for both vacant and non-vacant parcels in both low density and medium-high density residential areas.

For single-family areas, we looked at the number of residential lots allowed by the zoning classification. For example, under UL-7200 zoning, the minimum lot size is 7,200 square feet. For vacant parcels, we simply divided the existing lot size by 7,200 to determine the number of potential lots, and by extension, the number of potential housing units. Partial lots were dropped: if the calculation resulted in 3.2 lots, we treated it as 3 potential lots. For non vacant parcels, we followed the same procedure, but assumed one existing housing unit.

For medium- and high density areas, we applied the density allowed by the zoning to each vacant or redevelopable parcel, to yield a potential number of housing units To determine redevelopment potential, we calculated the structure-to-land value ratio. Where the value of the land was greater than twice the value of the structure, these parcels were marked as redevelopable.

Parcels not meeting the redevelopment criteria were not figured into the calculations for potential new housing units. Figure 6 shows the flow chart for filtering groups of parcels for calculations and data summaries.

For both redevelopable non-vacant as well as vacant parcels, we calculated the net number of new units using Equation 1:

*

Commercial & Industrial (Employees)

For Commercial/Industrial parcels, we were interested in the net number of new employees, rather than housing units. However, we used a similar methodology for partitioning parcels and flagging parcels as redevelopable (Figure 7).

Note that we applied a floor area ratio (FAR) to estimate the square footage of the potential buildings on vacant and redevelopable commercial and industrial parcels. By summarizing existing FAR data and eliminating outliers, we were able to determine an existing average FAR for each comp plan designation. We were then able to base the future FAR assumption for each comp plan designation on existing local conditions. Future employment was then estimated by applying square feet per job multipliers to the estimates of building square footage. Table 4 shows the square feet per job and FAR by parcel type used in the analysis.

The calculation of new employees was also similar to the calculation of new housing units (Equation 2):

†

In addition to calculating the number of new employees, we also had to account for the number of housing units within Commercial/Industrial zones which would be lost with redevelopment. We tallied this number of lost housing units and subtracted them from the number of new housing units.

GIS Analysis Data Summaries