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Friday, October 28, 2016

Removing the Blindfold from Economic Development

When a city doesn’t understand its revenue stream in relation to its land use allocation and shelter capacity, it can’t correct deficiencies in these relationships to permanently improve its economic stability. This lack of knowledge eventually produces decline and flight from an expanding core of blight. Decline has now progressed to include portions of surrounded suburbs with inadequate land use activity and shelter capacity correlation. The solution has been sprawl that annexes land to blindly repeat old mistakes. It is slowly consuming our source of life and the blindfold must be lifted. Surrounded suburbs have no option.

A city’s land use allocation is defined by its zoning map. Its revenue comes from the acres in each zone, the value of the acres, the gross building area available, the activity that is sheltered in the gross building area present, the revenue potential per square foot of activity sheltered, the condition of the shelter, and the specific location of the shelter. The productivity, or financial yield per acre from the zone, is a function of these fundamental factors.
There are six design categories that produce gross building area. Shelter capacity is gross building area divided by the project acres consumed. Gross building area multiplied by the percentage of project pavement introduced and divided by one acre, or 43,560 sq. ft., produces an “intensity” measurement. The number of building stories divided by five produces an “intrusion” coefficient. An intensity measurement multiplied by an intrusion coefficient produces a “building dominance” measurement.
Building dominance has a shelter capacity component that is occupied by activity. Every taxable activity produces revenue per gross building square foot related to the activity. These values are presently undefined, but activity revenue per square foot multiplied by the gross building area per acre devoted to the activity produces predicted revenue per acre from the activity. The total acres devoted to the activity multiplied by the anticipated revenue per acre produces a total revenue forecast for the acres allocated to the activity. Potential revenue increases as predicted shelter capacity per acre increases, but the trade-off is increased intensity and building dominance that can compromise a city’s quality of life.
Most cities do not know the revenue produced by each zone, census tract, and census block within its boundaries. They cannot calculate the data because they do not know the acres consumed by an activity group, the gross building area occupied by the group,, and the revenue potential per square foot of activity. This means that it cannot calculate the revenue implications that would be produced by increasing or decreasing the square feet of shelter available per acre for a given activity. In agricultural terms, this would be considered lack of knowledge regarding “yield per acre”. It would produce arbitrary crop choices, arbitrary field area allocation, and eventual insolvency.
Most cities have arbitrary zoning plans. They have not understood the options and economic implications of land use allocation and shelter capacity in enough detail to guide their financial future and convince a skeptical public. Their emphasis has been on the separation of incompatible activities. In addition, these cities rarely know their operating, maintenance, improvement, and debt service expense per acre. This means they cannot compare their expense per acre with the average revenue produced per acre, and they cannot produce revenue data in enough detail (by census block, tract, or municipal zone) to evaluate and adjust their economic stability.
When a municipality has completed its city design homework, it will know what its blocks, tracts, and zones are yielding per acre and will be able to compare this performance to its expense per acre. The result will define the current economic balance of its land use allocation plan and form a baseline for future strategic option evaluation.
If a city does not have relevant land use allocation data, gross building area data, and activity revenue per square foot knowledge; it will not have the ability to predict gross building area revenue options per acre. It will continue to waste land and blindly produce urban form that has no relationship to the economic stability required.
Intelligence is needed to prepare strategic plan options with the potential to achieve an economic goal over time. Cities have not pursued the required intelligence and do not have the tools required to predict strategic plans and tactical options that have the potential to achieve an economic goal.
I’m going to repeat a section I wrote in “The Density Distraction in City Planning” to provide a little insight into the spectrum of gross building area options that can be produced on a given land area when specification values are modified; and the impact this has on revenue potential. My point is that if a given activity has an estimated revenue yield per square foot, gross building area options can produce a broad range of revenue choices. Keep in mind that the gross building area options presented relate to the G1 Design Category and two sets of fifteen specification values. There are many other specification value choices and five other design categories and specification lists that can be used to expand the options available. Many specification values are not desirable, however, and research is required to convert design intuition to knowledge.

Six parking design categories encompass most of the shelter provided on the planet. They are:
1)      G1: Buildings with surface parking around, but not under the building
2)      G2: Buildings with surface parking around and/or under the building
3)      S1: Buildings with structure parking adjacent to the building on the same parcel
4)      S2: Buildings with underground parking
5)      S3: Buildings with structure parking at grade under the building
6)      NP: Buildings with no parking required

The parking structure options may have supplemental surface parking, but when a parking garage is present, the building is classified by the garage configuration present. These building categories may be occupied by any activity group that complies with local building and zoning requirements.
The point is that shelter classification begins with the parking design category involved, and each category has gross building area limitations defined by design specification decisions. These decisions limit the scope of land use activity and revenue potential that can be introduced.
Table 1 presents a set of optional decisions for the G1 Design Category. They are represented by the specification values entered in the boxes of its Land and G1 Modules. There are fifteen specification boxes and each value represents a design decision that can be adjusted to explore gross building area alternatives. The equations in Col. H of Table 1 convert specification decisions to implications in Col. G. The objective of the algorithm is to distill the core buildable land area available for a building and surface parking plan in cell F32. 

The master equation in cell A37 correlates the core area found in cell F32 with the parking decisions entered in cells F33 and F34 and the floor quantity options entered in cells A42-A51. It predicts gross building area alternatives in cells B42-B51 based on these floor quantity options. The remainder of the Planning Forecast Panel predicts additional implications related to the gross building area options calculated in Col. B using the secondary equations on line 41. Shelter capacity options corresponding to the gross building area options forecast in Col. B are located in Col. F. The entire panel illustrates a few of the many implications that can be forecast as a function of gross building area predictions. Revenue, expense, construction cost, return on investment, population, traffic generation and so on are a few that are not shown.
Table 1 illustrates the many specification decisions required to calculate shelter options for the G1 Design Category. A change to one or more values entered in the boxes of Table 1 would produce a new forecast in Col. B of the Planning Forecast Panel, and hundreds of options could be predicted in less time than it would take to produce one sketch.
The unpaved open space percentage specification in cell F11 of Table 1, and the impervious cover limit calculated in cell F12, represents one of the decision / implication relationships that play a significant role in the calculation of gross building area options. An unpaved open space decision, however, is only one box among many design specifications decisions that combine to determine shelter capacity options.
Table 1 is based on 40% unpaved open space in the buildable land area. When the gross building area values in Col. B of the Table 1 Planning Forecast Panel are mapped in Figure 1, the results can be expressed in the following terms:
The rate of increase in gross building area declines at an accelerating rate as the number of building floors increase in the G1 Design Category.

Building cover declines more rapidly than gross building area increases because the gross building area permitted per parking space (a) in Table 1 is less than the parking lot surface area planned per parking space (s).
Figure 1 illustrates the dramatically decreasing rate of increase in gross building area as building height increases. Gross building area increases from 38,577 sq. ft. to 59,000 sq. ft., but it barely increases above the five story mark of 55,722 sq. ft. This occurs because gross building area does not increase as rapidly as surface parking area when (a) is less than (s). Expanding parking area for additional spaces is required to justify increased building area, but this eventually reduces the land remaining for building cover to unrealistic levels.

Figure 2 is based on (a) being greater than (s) and 15% unpaved open space being entered in Table 1. Figure 2 shows that gross building area still increases at a decreasing rate, but the results produced are dramatically different because of the specification value changes. Gross building area increases from 85,630 sq. ft. to 186,152 square feet, but gross building area slowly increases above the 5 story mark of 164,673 sq. ft. Parking cover consumes the same amount of land per space, but gross building area per parking space grows more than parking lot area per space. This scenario explains why the gross building area arc increases more rapidly than the building cover arc declines in Figure 2.

When the five story gross building area potential in Tables 1 and 2 is subtracted from the one story gross building area potential predicted, the results expose another G1 design principle. In the case of Figure 1, the total gain for 1-5 stories is 17,145 sq. ft. The total gain for 5-10 stories is 3,278 sq. ft. In the case of Figure 2, the total gain for 1-5 stories is 79,043 sq. ft. The total gain for 5-10 stories is 21,749 sq. ft. This observation produces the following principle.
The most rapid increase in G1 gross building area occurs within a 1-5 story range.
The actual gain from 1-5 stories is a function of all design specification decisions entered in Table 1. Above 5 stories, the gross building area gain per additional floor becomes increasingly less cost-effective.
Figure 2 produces much greater gross building area potential, but is the open space and parking reduction desirable? I won’t attempt to answer the question. I’m simply pointing out an issue that can be accurately measured and evaluated with comparative studies using the language of City Design. In fact, the complete language of City Design can be used to measure existing conditions, evaluate future potential, and accurately define leadership decisions with confidence based on objective measurement and comparative evaluation.

Figures 1 and 2 explain why the gross building area permitted per parking space (a) and the unpaved open space percentage proposed per project (OSAU) are two of the most common points of public and private disagreement. Greater open space and parking requirements reduce potential gross building area, private return on investment, and public revenue per acre, but at what point do the reductions produce excessive intensity in the neighborhood? This cannot be answered without a comprehensive method of measuring and evaluating existing conditions. It cannot be improved without an accurate method of converting measurement and evaluation to accurate, comprehensive, and correlated shelter capacity and revenue potential options.

The G1 design principle behind this section of the essay can be stated in a single sentence.
Every additional surface parking space justifies increased gross building area; but reduces the core land area available for building cover, until the core area remaining becomes too small to accommodate a realistic floor plan.
Figures 1 and 2 demonstrate that gross building area options can be forecast in mathematical terms. When a gross building area option is multiplied by activity revenue potential per square foot and divided by the acres consumed, the result is a yield per acre that can be compared to city’s average expense per acre. When total yield is divided by total acres and compared to a city’s average expense per acre, the results must balance or budget cuts will be required. These cut options often represent unpleasant reductions in quality of life. The objective is to plan shelter capacity, intensity, and activity allocation in a city to establish a stable economy that is capable of avoiding budget cuts. This has the potential to improve quality of life within a limited Built Domain that protects its source of life.
There will always be those who disagree with the program of services offered by a city and the budget emphasis placed on each. This will lead them to advocate program elimination or budget cuts at the very least. The debate will continue until a community votes on the program of services desired. If a program is adopted, the minimum cost to deliver the service can be debated, but elimination will be removed from the discussion.
We all know that it is possible to pay too little and receive inadequate products and services. The second public debate will surround the minimum cost to deliver acceptable products and services. The bottom line is that a city must pay for a desired program. Let’s dispense with the concept of getting something for nothing. Define what “something” is and get over the concept of getting it for nothing. Focus on the minimum cost to receive an acceptable level of service for an adopted program item. Then a city must develop land use allocation and shelter capacity options that are equal to the current and future expense implied.
A public vote can give a struggling government the program direction it needs to define the average revenue per acre required to afford the program. The government can then focus on creating city design options for public review that have the potential to deliver this revenue.
I have written The Science of City Design to explain shelter design categories, activity groups, design specifications, architectural algorithms, master equations, and planning forecast potential. The goal is to introduce a vocabulary and language of city design that can consistently improve the planning results needed to protect a population’s quality of life within a limited Built Domain that protects its source of life – The Natural Domain.

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