of its revenue, but not all 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 activity and development capacity allocation, it will continue pursuing random 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.
Annexation increases the taxable acres within a city’s
expanded corporate limits and gives the impression of relief from immediate
budget deficiencies. This provides new money to meet current obligations when
land is available, but the new revenue from the acres consumed can prove
inadequate to meet increasing expense per acre as the city’s infrastructure ages.
Repeated annexation ensues with hope as a strategy and sprawl as a result that
has no better understanding of the revenue implied per acre of activity and its
relationship to the city’s total annual expense per acre. The problem is
exacerbated when a city has no land to annex and decline increases as
redevelopment for greater revenue meets extensive opposition.
I’m sure there are exceptions to the absolutes I’ve written in the
previous paragraph, but I hope they serve to raise the following questions that
can lead to an improved awareness of the knowledge we must
create and the tools we need to begin addressing a problem that is not limited
to a city’s annual accounting summaries and independent silos of professional
knowledge.
THE QUESTIONS
Question 1: What does the taxable land in a city’s inventory yield
in average revenue per acre?
Answer: 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?
Answer: A city knows its total annual expense including debt
service. The answer is as simple as dividing this expense by the taxable acres
served.
Question 3: Is a city’s annual expense producing a desirable
quality of life?
Answer: This question is complicated by the presence of
conflicting opinion. A municipal budget must balance each year, but this is no
indication of the physical, social, psychological, environmental, and economic
quality of life being provided. In fact, it may include painful budget cuts. Improvement
is often a function of the revenue available from the taxable acres and activity
present or planned for each parcel within its corporate limits. I doubt that
many cities have the relational databases required to understand the
relationship of land use activity to land development capacity, intensity and revenue
potential to support the quality of life present or desired.
Question 4: What is the revenue yield per taxable acre of
activity within a city?
Answer: A city knows the acres occupied and the activity
present in most cases, but it rarely knows the total real estate tax, income
tax, and other revenue provided by each activity on the acres occupied. The
information is contained in separate silos to protect a concept of privacy that
prevents the correlation of essential urban economic data. If it could be
correlated, it would be a simple matter to divide total activity revenue by the
acres occupied to determine its yield per acre; the relationship of activity
yield to the city’s annual expense per acre; and the balance of activity,
capacity, intensity, and yield needed within municipal boundaries to provide
the average revenue per acre needed.
Since a city does not know the yield per acre that can be
expected from shelter capacity, intensity, and activity alternatives, the
entire process of land use allocation for economic stability depends on a guessing
game of annexation and sprawl that seeks elusive balance in the face of
inexorable population growth. In other words, a city is like a farmer who cannot
estimate the yield he/she can expect from field and crop allocation on land
within his/her boundaries.
Question 5: In urban terms, what is a “crop” and what is a
“field”?
Answer: A crop is a land use activity that can be
specifically identified by standard industrial classification code or grouped
by similarity in a zoning code. These zoning groups are referred to as districts
rather than fields, and a district may include areas that are placed in more
than one city location. Since the economic productivity of district areas may
differ by location, each isolated area within a zoning district category is a
field that requires a secondary designation to distinguish it from another.
This can be as simple as a relational address database that correlates each
“field” to its constituent census blocks, tracts, parcel numbers, street
addresses, zoning designation and so on. From an urban perspective, information
collected by one index that is not related to others is knowledge drowning in a
common sea.
Question 6: What is shelter capacity, intensity, and yield?
Answer: Shelter capacity is also referred to as
development capacity. It is the gross building area in sq. ft. that is, or can
be, placed on an acre of buildable land area. It is a function of the building
design category chosen and design specifications adopted.
Intensity is a measure of the capacity introduced per
acre, and excessive amounts can produce an undesirable quality of life.
Capacity and intensity are important considerations because they define the
shelter available to accommodate activity within a given land area.
Yield is the public revenue received per square foot
of activity and per acre of land occupied. The mix of capacity, intensity, and
activity on acres within a city’s incorporated boundaries determines the
financial stability of its land use allocation portfolio. It is a missing store
of information per activity that severely limits our ability to balance land
use activity, shelter capacity, and intensity with the revenue potential needed
to achieve a desired quality of life within sustainable geographic limits.
Question 7: How is the Gross Building Area Capacity of a
Given Land Area Predicted?
Answer: I’d like to refer you to Table 1. It shows that the
gross building area predictions in Column B of the Planning Forecast Panel are
a function of the building design category chosen, the land area given, the 26 mathematically
correlated values entered in its shaded boxes, and the equation in cell B39. A
change to one or more of these shaded values will change the equation’s gross
building area predictions in Column B of the Planning Forecast Panel.
At this point, I’ll simply say that gross building area
capacity calculation is not as simple as increasing floor quantity or reducing
parking space and setback requirements; even though these are common variance
requests that seek to increase the profitability of a given land area. They
occur because the correlation required for adequate urban design leadership is
not understood.
Question 8: What is a building design category?
Answer: I have written about this extensively, so I’ll try
to keep it brief. Shelter is provided for activity by using one or more of six
primary building categories around the world. These categories are
distinguished by their method of parking provision: (G.1) Buildings with grade
parking around but not under the building on the same premise; (G.2) Buildings
with grade parking around and under the building on the same premise; (S.1)
Buildings with structure parking adjacent to the building on the same premise;
(S.2) Buildings with underground parking on the same premise; (S.3) Buildings
with structure parking beneath the building on the same premise; (NP) Buildings
with no parking provided or required. Buildings with structure parking may
include supplemental grade parking lots, but this is not their primary source
of parking capacity and classification.
Question 9: What makes development capacity significant?
Answer: I’ve also referred to “development capacity” as
“shelter capacity” to distinguish this essential element of survival from the
systems of movement, open space, and life support that we build to serve it. We
use shelter to protect activity, and the capacity of shelter combines with the
value of occupant activity to produce public and private revenue and expense
per acre. It also produces physical intensity, intrusion, and dominance that
can compromise our quality of life when excessively introduced within the urban
pattern.
Our ability to predict gross building area options per acre
gives us control over the revenue potential of land and the intensity implied.
I can make this claim because gross building area can be occupied by any
permitted activity, and various occupant activities produce various levels of
revenue per sq. ft. of gross building area capacity. In other words, the
allocation of acres, activity and shelter capacity within a city determines its
present or planned average revenue per acre, and this average yield must equal
a city’s total annual cost to operate per acre. Budget cuts result when this
simple equation does not balance and the debate over decline begins.
The challenge is to correlate the revenue produced by shelter
capacity and activity with the physical intensity, intrusion, and dominance
implied; since these physical, social, and economic implications aggregate
across a city’s project acres to produce the revenue and quality of life available.
Our current inability to correlate shelter capacity, activity and intensity with
its revenue potential and quality of life implications has led to the guesswork
and Ponzi solutions we call sprawl, but it is possible to see the future more
clearly. I’ll use Table 1 and the G1 Building Design Category to explain in
more detail.
TABLE 1
The first objective in Table 1 is to define the
buildable land area available. This is calculated using the variables entered
in shaded cells F3-F6 and F8. The answer calculated from these entries can be
found in cells F10 and G10.
The second objective is to define the shelter land
area that remains after an unpaved open space quantity is subtracted from the
buildable land area available. The variable percentage chosen has been entered
in cell F11 and its quantity equivalent has been calculated in cell G11. The
impervious cover area remaining after this subtraction is calculated in cell
F12 and G12. This is the land area remaining for building cover, parking cover,
and pavement. The optional shared open space percentages in cells F13 and F14
would only be greater than zero when a portion of the total open space entered
in cell F11 is shared as common open space serving more than one independent project
area. In this example there is no common open space and the buildable land area
calculated in cell G10 is equal to the remaining shelter area calculated in
cell G17. The impervious cover area available in cell G12 also remains the same
in cell G19.
The third objective is to calculate the core project
area that will remain for building cover and parking lot area after all other
pavement and miscellaneous building cover is subtracted. The design variables
entered in cells F23-F29 are subtracted from the shelter area impervious cover
found in cell G19 to define the core area remaining in cells F33 and G33 for
building and parking cover.
The fourth objective is to define the gross building
area permitted, planned or present per parking space in cell A36; and the
estimated average parking lot area per space in cell A35 that is allocated or
present to serve the space, its circulation drive, and its associated landscape
area.
The fifth objective is to define the range of floor
quantity options under consideration in cells A44-A53.
The sixth objective is to calculate the range of
gross building area options that can be built in the core area remaining. These
areas are calculated in cells B44-B53 using the equation in cell B39. It is
related to the G1 Building Design Category chosen and predicts the gross
building area potential of any given land area based on the variables entered
in its shaded cells. A change to one or more of these variables will
immediately change the results calculated.
In essence, the equation explains that G1 gross building
area increases with floor quantity, and its parking lot area must increase to
serve the larger building. Since core land area is the area remaining for
building footprint and parking lot after all other present or proposed open
space and pavement areas have been subtracted, parking lot area can only
increase within this core area when building footprint area declines. However,
a smaller building footprint can produce greater gross building area when floor
quantity increases. These relationships are shown in the Planning Forecast
Panel of Table 1. The gross building area predictions in cells B44-B53 increase
at a decreasing rate as floor quantity increases in cells A44-A53; and building
footprint area declines in cells C44-C53 to make room in the core area for the
increasing parking lot area shown in cells D44-D53. This lot increase is needed
to accommodate the increasing parking spaces calculated in cells E44-E53. In
other words, the equation in cell B39 and the data in the Planning Forecast
Panel of Table 1 describe the fundamental characteristics of the G1 building design
category. The characteristics don’t change, but the results forecast will
change whenever one or more of the variables entered in the shaded cells of
Table 1 are revised.
The seventh objective is to define the implications
of the results calculated in the Planning Forecast Panel of Table 1. The implications
of the gross building area forecast in Column B are calculated in Column F of
the Implications Module by dividing the buildable acres calculated in cell G10
into the gross building area predictions of Column B in the Planning Forecast
Panel. Column F simply explains that the shelter capacity of land in sq. ft. per
buildable acre increases with floor quantity at a decreasing rate when all
other design specification values in Table 1 remain constant.
Capacity options are converted to intensity options in
Column G with the equation in cell G43 of the Implications Module. The column
shows that intensity increases with capacity in Column G, but there has been no
research to determine the implications of these measurements. It is similar to
the lack of knowledge that existed with the first blood pressure measurements.
The increasing floor quantity in cells A44-A53 is converted
to a column of intrusion implications with the equation in cell H43. Capacity,
intensity and intrusion are converted to a column of project dominance implications
with the equation in cell J43. The result is a four-part method of capacity and
intensity measurement that can be used to index and evaluate our relationship
to the places we create and the shelter that surrounds them.
In other words, the allocation of shelter capacity, activity,
and intensity per buildable, taxable acre within a city’s municipal boundaries
determines the revenue potential of its land use allocation long before
appearance becomes an issue. They are the topics and quantities in a recipe
that must be correlated to have a chance of producing a desirable result.
Land use allocation, therefore, is not simply a quest to
separate a city’s incompatible activities. It is a financial balancing act that
is expected to define, monitor, and adjust the yield from each acre while
ensuring that the physical intensity, intrusion, and dominance introduced for
the sake of economic stability and financial profitability does not overwhelm
the quality of life desired. In the end however, the result cannot respond to
population growth with sprawl that threatens to consume its source of life
while seeking to preserve its quality of life.
ADDITIONAL OBSERVATIONS
Any building design category may be used to shelter any
activity, but the nature of the activity may increase or decrease the gross
building area capacity predicted. For instance, Table 2 applies to the G1
Building Design Category when it is used to shelter R3 Apartment activity. The
R3 Apartment Module has been added in Table 2 to specify the characteristics of
the apartment building under consideration. All values entered in the shaded
cells of the Land and Core Modules remain the same as Table 1. The floor quantity
options entered in cells A56-A65 of Table 2 also remain the same. The values
entered in the shaded cells of the R3 Apartment Module, however, have been
added and affect the gross building area results predicted in cells B56-B65.
There are a number of reasons for the increase in the gross
building areas predicted in Table 2 when it is occupied by apartment activity,
but the simplest explanation is that the gross building area permitted per
parking space in cell A35 of Table 1 has increased from 400 sq. ft. to 752.81
sq. ft. in cell J47 of Table 2. This produces a reduced parking lot in the core
land area and a corresponding increase in the floor plan area available. When
the increased floor plan area in Table 2 is multiplied by the same floor
quantity options in Table 1, the larger gross building area options in Table 2
are produced.
It would have been possible to enter 752.81 in cell A35 of
Table 1 and arrive at the same gross building area predictions as those in
Column B of the Planning Forecast Panel in Table 2 without completing the R3
Apartment Module. This only shows, however, that Table 1 can be used to predict
the development capacity of any buildable land area based on the shaded values
entered, but additional activity specifications may be required to define the
controlling design specification values for a specific land use activity.
FINAL POINT
It is not enough to separate incompatible land use activity
in a master plan; depend on annexation to solve planning deficiencies; and
include a few hopeful site plan and building design regulations that are often
in conflict in a zoning ordinance. These regulations were included to protect
our access to light, air, and ventilation within cities, but they have done
little to protect us from excessive intensity that is a threat to the “public
welfare” we now refer to as our quality of life. Table 1 has revealed a portion
of the mathematical correlation involved. Its absence often makes design
regulation appear inconsequential and vulnerable to variance requests. However,
its invisible presence remains at the heart of the
leadership needed to shelter
growing populations within limited geographic areas that do not sprawl to
consume their source of life.
If you are interested in pursuing this topic, you can find all building design categories, equations, and explanations in my book, The Equations of Urban Design, 2020, that is available from Amazon.com. If you are interested in related essays, you can find them in my book, Symbiotic Architecture, 2020, that is also available from Amazon.com. They represent my rough drafts and are not polished publications; but I chose to take no chances with my advancing age, since I felt the content could be a contribution to our continuing presence on a planet that does not compromise with ignorance.
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