the community must equal or exceed the community’s total annual expense per taxable acre, including debt service. The term “balance” is used to indicate budgetary success, but balance can be the product of reductions required by inadequate municipal revenue per acre. “Adequate” balance requires conscious mathematical evaluation of the shelter capacity, intensity, and activity introduced throughout a community -- and these tools remain to be assembled.
I’ve previously mentioned in many essays that shelter capacity
calculation begins with a choice among six building design categories and a
given gross land area. Design decisions begin with choices involving design
specification quantities. Correlated results are expressed as gross building
area options expressed in square feet. When these options are divided by the
buildable acres involved, the result is “shelter capacity” expressed as gross
building area in square feet per buildable acre occupied. When anticipated
revenue per square foot of activity is multiplied by the shelter capacity
present or planned, the result is revenue potential per acre. The sum of all
municipal revenue per acre divided by the number of properties involved
produces the average financial productivity of a city’s land area, and it must
at least balance with its expense. The challenge is to increase the average
over time by monitoring and evaluating the financial performance of all vacant
and occupied taxable land in a city’s investment portfolio.
TABLE 1
Table 1 illustrates the decisions that produce development
capacity options for occupant activity and revenue production. (Keep in mind
that gross building area is opportunity that may be occupied by any permitted
activity.) This example pertains to the G1 Building Design Category, which
includes all buildings served by a grade parking lot around, but not under, one
or more buildings on the same premise.
Design specification topic decisions and quantity options in
Table 1 are indicated by the shaded cells in the table. The gross building
options produced by the floor quantity options entered in cells A44-A53 are
calculated in cells B44-B53. Thise options are converted to shelter capacity
measurements in cells F44-F53 with the master equation in cell F43. When shelter capacity options are
multiplied by activity revenue per square foot, the result is anticipated
revenue per acre. The result can then be compared to a city’s total annual expense
per acre. Individual calculations may be greater or less than the city’s
expense, but the average revenue per acre across the city must at least
“balance” with its expense. This, therefore, is the mathematical foundation of
design decisions that determine not only a city’s budget, but its ability to
sustain its health, safety, and physical, social, psychological, environmental,
and economic quality of life. When a city is able to measure, predict,
evaluate, monitor, and plan these results, it will be in a better position to
evaluate future development decisions that directly affect the “balance” it
must strike within its boundaries and with a surrounding Natural Domain that is
its source of life.
INTERACTIVE EVALUATION
If revenue information per acre is calculated and mapped with
a geographic information system and a set of relational databases, a
jurisdiction can evaluate the economic performance of its entire land use area.
The map will no longer be a static plan. It will become an interactive map
based on relational database information that presents the revenue per acre implications
of past shelter capacity, intensity, and activity decisions for every property,
block, zone, tract, or district within a jurisdiction. The results will present
the first correlated picture of the decisions that have produced a city’s
physical, social, psychological, environmental, and economic condition. Since
the picture would be based on geographic information system software and
relational databases, the jurisdiction would also have a digital format capable
of evaluating future options and decisions that have the potential to improve
the revenue it receives and the quality of life it can offer. It would also be
able to monitor these decisions and opportunities with the interactive
potential of shelter capacity evaluation mathematics.
I have written a great deal about the mathematical
foundation of shelter capacity forecast models and context prediction but have
only discussed the relational databases needed to step from an interactive
project planning and economic development focus in one essay entitled, “The Least
a Smart City Should Know”.
The problem with the relational database concept is the
public cooperation required. Property tax and personal income tax represent a
substantial portion of a city’s total annual revenue. In my limited experience,
property tax revenue is collected and distributed by a county and considered
public information. Income tax revenue can be collected by a county or city but is considered confidential
information. As a result, the information needed to begin understanding a
jurisdiction’s financial foundation is in two separate, independent data
management systems that are not trained to speak to each other or to a third
urban design planning function.
A city will continue to search for financial stability until
it can more accurately correlate its land use decisions with their real estate
and income tax revenue implications. The challenge is to begin understanding
the economic performance of blocks, neighborhoods, zones, and districts in cities
that must sustain themselves over time without annexation that continues to
consume agriculture and the Natural Domain. A planning link to selective and protected
versions of the information needed may not be an insurmountable problem, even
though a county’s parcel identification system may have to be correlated with the
city’s property address, zoning district, and census tract information systems.
Relational databases represent the key in my opinion. They
make it possible to compile information in one location and share it in a
different form with different restrictions. For instance, income tax
information can be assembled by parcel/property in a secure location and
aggregated by city block, census block, neighborhood area, census tract, or
municipal zone before sharing. The same is true for real estate revenue
information. It simply requires an urban design database synchronized with the information
restrictions applied by its cooperating sources. The result would be a
geographic information system of correlated physical and economic data capable
of mapping, monitoring, and planning the economic performance and future urban
design potential of a city’s land. The challenge is to reduce or eliminate the
unlimited annexation and sprawl that continues to reflect our unsuccessful
search for “balance” .
There are at least two advantages to this approach. (1) An
economic development plan can focus on the entire city. (2) The revenue
contribution per buildable acre of an individual proposal can be placed in the
context of a city’s current comprehensive physical, social, and financial plan.
These objectives will be difficult to achieve without investing
in the data assembly, information management, and shelter capacity mathematics
required to make and monitor the leadership decisions needed. The challenge is
to progress from static land use plans to digitally interactive planning models
for urban design evaluation and leadership.
FURTHER INFORMATION
Further information about the building design categories,
design specification topics, prediction panels, and implication modules of
shelter capacity forecast models, can be found in my book, “The Equations of
Urban Design”, using the following url:
https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330
You may also be interested in some of the 285 essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity evaluation forecast models and their implication measurement modules.
Walter M. Hosack, August 2026
Photo credit: NASA/JPL – Caltech/SOFIA
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