The distribution of taxable activity in buildings throughout a city, and the real estate value of these buildings, is a primary source of revenue per acre. This yield must contribute to a city’s total annual expense per acre, but a city does not calculate its revenue on this basis. This has led to a disconnect between the land use compatibility objectives of city planning and the revenue objectives of local government. It has led, in my opinion, to many revenue-deficient land use plans and decisions when compared to their long-term public expense. The relationship of land use acres to revenue is easily overlooked, however, when excess and deficient contributions per acre are merged into the total annual revenue received by a city. This leads a city to overlook the fact that the shelter capacity of land combines with its occupant activity to determine the revenue the city receives, and too much land can be devoted to too little revenue within a limited municipal area. This can lead to annexation when land is available and stagnation or redevelopment when it isn’t. This has led me to search for a better method of measurement, prediction, and evaluation because shelter capacity determines the scope of feasible economic activity, and more accurate predictions can lead to less land consumption.
THE CITY
Attention to building, parking, pavement, and open space context
has often been referred to as urban design, but the social, psychological,
environmental, and economic implications of these physical design decisions
have rarely been correlated with these measurable shelter capacity, intensity,
intrusion, and context implications.
THE NEED
The sustainable provision of shelter on the limited land of
our planet will depend on our ability to accurately predict the shelter
capacity of this land. We need to limit its consumption to protect its source
of life, the Natural Domain. A more accurate ability to calculate shelter
capacity in a limited Built Domain is needed to serve the activities of growing
populations and conserve their source of life, the Natural Domain.
A city is a collection of shelter capacity decisions served
by arteries of movement, open space, and life support on defined land areas
that can be occupied by any permitted activity. The mathematical measurement, prediction,
arrangement, and correlation of shelter capacity, intensity, and activity can
form the quantitative basis for further city design evaluation on limited land
areas.
THE ATTEMPT
The shelter capacity of land is its gross building area potential
per buildable acre. It is a function of calculations based on a building design
classification system and choice, values entered in the category’s design
specification template, and a column of optional floor quantity entries. I have
written about these forecast models on many occasions and will avoid repeating
myself by referring the reader to these essays on my blog at www.wmhosack.blogspot.com and to my
book, “The Equations of Urban Design”, available on Amazon.com.
THE OPINION
The distribution of shelter capacity and occupant activity among
a city’s taxable acres determines the revenue a city receives and the quality
of life it can provide, but the contribution from every taxable parcel has
never been calculated or mapped based on the land consumed; nor has its revenue
per acre been compared with the total annual cost of municipal government per
acre – to my knowledge. This has made it difficult, if not impossible, to
correlate the capacity and use of land with its revenue potential and quality
of life within sustainable, symbiotic geographic limits. This competence will
require improved information sharing, data management, shelter capacity
prediction, mapping evaluation, urban design assessment, and scientific
correlation before city design can become more than unlimited land consumption.
THE OPPORTUNITY
In other words, when revenue productivity from gross
building area can be measured or predicted per acre for every parcel or block within
a city; when it can be geographically mapped; and when it can be compared to a
city’s total annual cost per acre; the economic implications of a city’s land
use decisions will become apparent, and future planning decisions will be
better informed.
THE CHALLENGE
It sounds simple enough, but we have not been able to
accurately predict the shelter capacity of buildable land area, and we do not
know the annual revenue that can be expected from various occupant activities. An
investor can calculate the anticipated profit from an occupant activity, but an
investor can sell a mistake. A city has far less ability to predict its risk
and protect its investment. It is left with the result.
THE FOCUS
I have focused on deriving an accurate method of predicting
the shelter capacity of land and calculating the physical implications of the predicted
options. The definition of revenue potential per square foot of occupant
activity is information that remains to be assembled unless I am mistaken. If
it is available, it can be easily multiplied by predicted or measured shelter
capacity options to find the revenue options implied.
THE OPORTUNITY
Shelter capacity measurement and prediction, or Tegimenics,
can anchor the correlation of research and knowledge needed to lead us to the
goal of life within symbiotic limits.
THE EXAMPLE
I’ll borrow Table 5 from my previous essay, now labelled
Table 1, to create a simple example of shelter capacity evaluation. Table 1 is
based on the information given at the top of the table and the design
specification quantities entered in its gray cells. The gross building area
predictions that result are calculated in cells B44-B53.
I have arbitrarily entered a square foot revenue prediction
in cell K43 of Table 1. It is meant to represent total real estate, income, and
other revenue related to the gross building area predicted. Multiplying this by
the gross building area predictions calculated in cells B44-B53 produces the
revenue predictions in cells K44-K53. (A square foot revenue prediction based
on measurements from other similar activities would obviously be a better
choice.) If this were repeated for every parcel in a city’s inventory, a
picture of its current productivity and future potential would emerge, and the
ability to evaluate and map alternatives would require a few keystrokes.
CONCLUSION
My point has been to illustrate the usefulness of gross
building area predictions produced by shelter capacity algorithms and design
specification templates when they are combined with other information related
to these Tegimenic measurements, predictions, and implications.
Walter M. Hosack, January 2026
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