It should be obvious that many different gross
building areas can be created on the same buildable acre, and that they may be
occupied by many different activities. (Assuming these activities comply with all
related zoning and building code regulations.) It should also be obvious that
different activity generates different taxable revenue per square foot of
shelter, and that larger buildings containing the same activity on the same
acre have greater shelter capacity and revenue potential. Unfortunately, we
have been unable to correlate these self-evident principles across all taxable
acres of a city. This has limited our ability to produce shelter capacity and
activity relationships that yield average annual revenue per acre equal to, or
exceeding, a city’s average annual expense per acre to deliver a desired
quality of life over time.
A city cannot successfully plan its economic future and continuing
quality of life until it can correlate the shelter capacity of land with the
revenue implications per sq. ft. of its occupant activity. Until then, it
cannot evaluate the activity and intensity options that will improve its
average revenue production per acre. We have called our partial efforts
economic development; but our project-oriented focus has been too limited, our
knowledge too undeveloped, and our tools too inexact to produce consistent
leadership correlation at the strategic level of effort implied by the term
city planning.
We are not ready to plan cities without annexation as a
crutch and sprawl as a result. Improvement will require the ability to
correlate the economic potential of activity per square foot of shelter with the
gross building area options available per buildable acre. Unfortunately, many
of these gross building area options produce excessive physical intensity,
intrusion, and dominance in the pursuit of profit. This result has prompted more
than a century of flight to the suburbs, but our limited knowledge has produced
rings of sprawling land consumption in a search for solutions on a planet that
is no longer a world without end.
The physical intensity of shelter within cities has been a
term without an adequate definition. It has been exacerbated by movement and
life support systems that have magnified the condition and been inadequately
offset by quantities of dedicated open space. The condition worsens when a city
becomes surrounded and economically suffocated by its inability to adjust
shelter capacity, activity, and revenue within its limited boundaries. Improvement
requires a delicate balance among these topics, but we have not been able to
address them with the knowledge and tools available. Our only choices have been annexation and
sprawl for new revenue that often proves inadequate over time; tax increases;
or budget reductions that can prompt decline when the status quo cannot be
maintained.
My efforts have focused on the algorithms and forecast
models needed to consciously and consistently correlate the shelter capacity of
land with the revenue potential of its occupant alternatives – and on the
consistent measurement of the physical intensity, intrusion, and dominance
produced by shelter alternatives that can compromise our quality of life when
ignored.
The economic potential of gross building area is a function
of the occupant activity present or planned. Therefore, if the shelter capacity
options for a given land area can be accurately predicted in sq. ft. per
buildable acre and the revenue potential of occupant activities is known in
dollars per sq. ft. of building area, the economic contribution of the potential
combinations can be predicted. In other words, taxable land area represents a primary
financial resource for every city. Its potential depends on the shelter capacity
and activity introduced on every buildable acre.
If a city knows its expense to operate, maintain, improve,
and finance its services per acre, it can subtract all known sources of revenue
that are unrelated to land use in order to find the remaining expense that must
be served by its average revenue per acre. If I borrow the word “productive”
from farming, urban revenue per acre that equals or exceeds a city’s remaining average
municipal cost per acre is productive. All acres will not be productive with
this definition, however. Every city’s challenge is to make the average yield
per acre from all of its crops (zones, census blocks, census districts, lots,
parcels and so on) equal to or greater than its remaining expense to provide a
desirable quality of life. This means it must learn much more about its shelter
capacity, activity, and intensity alternatives.
Revenue data per parcel, block, or tract is a simple matter
of relational database creation, information assembly and correlation -- if political
cooperation can be found. Geographic mapping systems based on this data can
reveal existing conditions and strategic alternatives for ensuring economic
independence based on land use and shelter capacity correlation. It is a
concept a farmer describes with terms like crop allocation, yield, and
productivity per acre. Urbanists will be threatened by a fear of geographic discrimination,
but it is already a problem to be resolved.
A farmer knows that his/her revenue per acre depends on both
yield and quality. We have referred to yield as “density” and quality as “health,
safety, and welfare” in the history of city planning; but density and welfare
have proven to be inadequate leadership terms and measurement yardsticks.
Density is a function of shelter capacity per acre. Capacity
is produced by the correlation of design specification topics and values
entered in one of six building design category templates. These templates
classify most, if not all, shelter we construct on the planet. Welfare is influenced
by the physical intensity, intrusion, and dominance of shelter capacity. It surrounds
and contains activity that we pursue on a daily basis. It is initiated with a combination
of design specification decisions that have been partially recognized and
independently addressed. Unfortunately, they function together like the
sections in an orchestra and produce similar dissonance when uncorrelated. A
focus on isolated shelter design topics and items has frustrated our efforts to
produce a symphony.
Building design categories can be classified at existing
locations. Their design specification topics can be identified and their values
can be measured. The shelter capacity, intensity, intrusion, and dominance of
the project can be calculated from the measurements taken using the new
equations in its related forecast model. These measurements represent the
correlated starting point for every shelter capacity project. Few are aware,
however, that excessive intensity and profligate land consumption can be
produced by many uninformed design specification decisions. The discovery of
these measurements will produce the knowledge needed to begin considering the
implications of symbiotic urban pattern and form. It can provide the shelter we
need to survive as a parasite on a planet that does not compromise with
ignorance.
We have been preoccupied with land use relationships and the
word “compatibility” since we began to recognize that some relationships were
unhealthy, unsafe, and detrimental to a quality of life that we originally
called “welfare” -- until it became associated with poverty. We have fled the intensity
of cities in a search for answers but have produced sprawl that threatens our
source of life. This will continue until we recognize that the quantities of
activity protected by the square feet of shelter provided per acre must be
correlated to produce average revenue per acre that equals a city’s annual
expense per acre for a desired quality of life over time -- without excessive
physical intensity that dominates the quality desired and within geographic
limits that protect our source of life.
Quality of life is influenced by the capacity, intensity, intrusion, and dominance of shelter we
construct to protect activity. These are terms that have consistent
mathematical definitions as noted on line 43 of Table 1. They can be measured,
evaluated, and correlated to lead and limit the results implied by their
titles. Their intuitive definitions, partial recognition, and lack of
correlation have led to the contradictions and sprawl we face today.
I have written extensively about this topic in my blog at www.wmhosack.blogspot.com; on my page at Linked-In; and in my books entitled: Land
Development Calculations, editions 1 and 2, The Equations of Urban
Design, and Symbiotic Architecture. They are available from
Amazon.com and I will not attempt to repeat their content in this brief essay.
I would also like to mention one essay in Symbiotic
Architecture in particular. It is entitled, “The Least a Smart City Should
Know”. It is not the easiest to read, but contains a blueprint for the
relational database content that can be used to build knowledge regarding the
values needed by the equations and forecast models of urban design.
I’ll close by including Table 1 as an example of an urban
design forecast model that applies to all buildings served by an adjacent
parking lot on the same premise. It is called the G1 Building Design Category
and is the most common category used to shelter non-residential activity in
many parts of the world -- when parking is required.
The gray cells in Table 1 indicate design specification
variable locations. The values entered are mathematically correlated to produce
the results shown in the Planning Forecast Panel. A change to one or more of
the design specification values entered will modify the results produced in the
panel. The point is that these specification values are not independent and isolated.
They represent combinations that must be correlated -- and illustrate the
interactive relationship of building design decisions.
The ten floor quantities entered in gray cells A44-A53
complete a set of gray cell specification options. The Planning Forecast Panel
predicts their design implications using the equations on line 43. The impact
of these options is classified by shelter capacity, intensity, intrusion, and
dominance with the equations on line 43 of the Implications Module. I am not
providing an evaluation of these impact measurements since this is a
hypothetical example; but measurement, evaluation, and accumulated knowledge is
the leadership promise offered by this system of building classification, design
specification, planning prediction, and implication measurement.
The public revenue implications of the development capacity
forecast in Table 1 is easiest to explain by looking at the gross building area
options predicted in cells B44-B53. If $10 of revenue were expected per sq. ft.
of gross building area, the total annual revenue would range from $48,843 to
$73,511 depending on the floor quantity chosen. Since the buildable land area
noted in cell F10 is 100% of the gross land area given in cell F3, the total
revenue projections would be divided by 5.230 acres to find the revenue potential
per acre consumed from the city’s inventory. This would range from $9,339 to
$14,055 per acre. A simple comparison with the city’s annual expense per acre
would indicate the contribution or subsidy implications of the project.
The results that evolve from fundamental design
specification decisions have been overlooked for centuries; and claims of
overdevelopment and oppression are not easily overcome in the face of economic
hardship claims -- until the examples become too extreme to ignore during the
debate that ensues. The Implications Module in Table 1 illustrates one method
of measuring the impact of shelter composition on our quality of life within
the urban fabric we create. When these measurements are combined with the
financial evaluation mentioned in the paragraph above, it will become easier
for a city to evaluate the combined impact of urban design decisions. A city
that understands these implications for every parcel within its jurisdiction is
a city that is prepared to evaluate the land use and urban design decisions
that will affect its future.
Two Simple Questions
Question 1: What does the taxable land in a city’s inventory
yield in average revenue per acre? A city knows its taxable acres per lot or
parcel and the answer is as simple as dividing its total annual revenue by the
total number of these acres.
Question 2: What does it cost a city to operate, maintain,
improve, and finance a desirable quality of life per taxable acre? It knows its
total annual expense and the answer is as simple as dividing this expense by
the taxable acres served. However, a city is required to balance its budget
each year. This means that its revenue per acre must equal its expense per
acre, but this does not mean that the city is providing a desirable physical,
social, psychological, environmental, and economic quality of life. If it
isn’t, the only solution is to improve the total revenue produced by the sum of
the acres available, and this is a function of the taxable activity present on
each parcel within its corporate limits.
A city’s historic, and current, solution is annexation to
increase the taxable acres within expanded corporate limits. This provides new
money to meet current obligations when land is available, but the new revenue
per acre can prove inadequate to meet increasing expense as the annexed area
ages. The problem is exacerbated when a city has no land to annex and decline
increases as redevelopment meets extensive opposition. It is rooted in a lack
of knowledge concerning the revenue per buildable acre that can be expected
from the spectrum of land use activity options available. This makes it
impossible to equate urban land with its estimated revenue productivity per
acre, and to allocate these acres to achieve a desired balance that is
economically sustainable over time.
The acres in a city’s inventory are a primary
source of its revenue, but all do not produce the income needed to equal a
city’s average expense per acre. If a city does not understand the economic
implications of land use and development capacity allocation, it will continue
pursuing random economic development projects without the comprehensive
strategy needed to lead its physical decisions to foreseeable financial
improvement in a revenue and expense equation that determines its quality of
life.
