The Language Needed to Measure Urban Design Decisions
The shelter capacity of land has been estimated and more land has been acquired when needed by converting/consuming agriculture, undeveloped areas, and/or natural settings. The entire concept of master planning has assumed that annexation can adjust for mistaken land use allocation and population growth.
Growing
populations cannot survive without shelter for their many activities, but it
seems obvious that land is not infinite and must be shared with the Natural
Domain to protect our source of life from eventual consumption.
Surveying defines
land areas. It does not define the shelter capacity of land or its
environmental significance. This has made land a commodity. The result has been
the lack of general recognition that the land areas we define must be
consciously managed, conserved, protected, preserved, and shared as a source of
life. The lack of a common, consistent language of mathematically correlated shelter
capacity evaluation has produced inconsistent decisions leading to sprawl,
excessive intensity, and random land consumption.
A honeybee knows
better. It builds limited shelter; grows in limited quantities; feeds in
limited areas; and pollinates in return for consumption. It responds to the Law
of Limits on a planet that responds to a universe beyond our comprehension. We
have yet to create a language of shelter capacity evaluation that can build any
segment of comparable knowledge or contribution, and the planet does not
compromise with ignorance.
INTRODUCTION
Shelter capacity
is first a function of the building design category chosen among six in the Shelter
Division of the Built Domain. Until now, shelter has never been classified by
mathematically useful building design categories. The design specification
decisions related to each category and occupant activity have never been
comprehensively identified or correlated with the algorithms needed to measure
and/or predict shelter capacity, intensity, intrusion, and context options for
any given area.
The shelter
capacity of a given land area is a function of the building design category forecast
model chosen; the values entered in its design specification template for each
topic listed; and the floor quantity options considered. The result is a
correlated mathematical prediction of shelter capacity options in sq. ft. per
acre and the intensity, intrusion, and context implications related to each.
Shelter capacity decisions
determine the scope of activity that can be contained within the gross building
area per buildable acre measured, planned, or predicted. The nature of this
activity combines with shelter capacity and intensity to determine the revenue
and investment potential of the buildable land area occupied.
The correlation
of mathematical decisions and floor quantity options in a design specification
template produces gross building area options and related shelter capacity,
intensity, intrusion, and context implications. These implications are
measurements of the physical relationships involving building mass, parking,
pavement, and unpaved open space that combine with movement, open space, and
life support systems to form the places within our Built Domain.
ECONOMIC
DEVELOPMENT IMPLICATIONS
An informed
allocation of capacity, intensity, and activity within a city can make the
evaluation of financial stability more than an annual guessing game. It will,
however, require the participation of data science and the correlation of many
related data silos with the leadership calculation and evaluation of shelter
capacity alternatives. It is the only way to provide shelter for growing
populations within limited geographic areas defined to protect and preserve their
quality and source of life. It is a fundamental physical issue.
The consistent measurement
of shelter capacity, intensity, activity, and revenue from every acre within a
city makes the evaluation and accumulation of knowledge feasible. The
implications are significant. The knowledge will offer the opportunity to
mathematically correlate and monitor a city’s land use allocation plan. This will
make it possible to produce and maintain an average economic yield per acre equal
to or greater than a city’s expense per acre. The implied objective is to
establish, afford, and maintain financial stability that can produce a
desirable quality of life within limited geographic areas.
SHELTER CAPACITY DESIGN
DECISIONS
I’m including a
brief example of shelter capacity forecasting in Table 1. It will be quite
repetitious for previous readers but will provide an example of a tool that can
be used at joint meetings of planners, investors, developers, and advisers to
mutually evaluate options, reach decisions, and define objections before the
expense of graphic evaluation begins. In fact, hundreds of spreadsheet options
can be evaluated in the time it would take to sketch one.
The entire
collection of forecast models is meant to introduce a mathematical language of
correlated design specifications to replace comparable but partial and mathematically
uncorrelated zoning regulations. Consistent measurement and evaluation of
existing conditions based on a comparable, correlated set of design
specification topics can build knowledge regarding their implications and
future leadership parameters.
TABLE 1
I have explained
Table 1 many times, so I’ll keep it brief. The table is a forecast model that
applies to the CG1L building design category. This category includes all
buildings served by a surface parking lot around, but not under, the building
on the same designated premise.
The shelter
capacity options in cells F44-F53 of Table 1 are predicted from the
specification values entered in its shaded cells. The results may be occupied
by any permitted activity. The scope of activity is affected by the shelter
capacity measured, predicted, planned, and/or available.
The correlation
of capacity, intensity, and activity produces a context measurement that combines
with location to determine the revenue potential of the land area involved. The
allocation of these relationships on every taxable parcel/acre of land within a
city’s boundaries determines its total average revenue per acre. This must
equal a city’s total annual operating, maintenance, improvement, and debt
service expense per acre, or budget cuts ensue. The public reaction to the
municipal services provided is a measure of its context allocation success and
ability to explain its decisions.
Lines (a-e)
identify the forecast model in Table 1. Line (g) identities the Design
Specification Template. Line 2 identifies the Land Module in the specification template.
The shaded cells in the module identify the locations requiring design
specification decisions. The values entered are simply for illustration. The
text to the left of the values explains the topic. Column G converts all values
to their sq. ft. equivalents.
The Core Module in
Table 1 begins after the Land Module. The shaded cells in the Core Module
continue to designate design specification locations. The CORE value found in
cell F33 is correlated from all specification values entered in both modules.
It is converted to a sq. ft. value in cell G33, and is needed by the master
equation in cell B39. Parking specification values are entered in shaded cells B35,
B36. Optional floor quantity values are entered in cells A44-A53. All
specification values entered are correlated for use by the master equation to
find the gross building area options in cells B44-B53 of the Planning Forecast
Panel. All other predictions in the Planning and Implication Modules are
functions of these gross building area predictions.
CONTEXT
The values in
cells J44-J53 of Table 1 are context measurements. They are a function of the
capacity, intensity, and intrusion options calculated in the preceding columns.
I originally designated the column as containing dominance values (DOM) but
have since come to believe that context measurement (CXT) is a better title
indicating the entire range of options that can result from a design
specification.
DESIGN
SPECIFICATION DECISIONS
There are 27
shaded design specification topics in Table 1. The first is a given land area
that can be of any size. Eleven of the ensuing topics in the Land and Core
Modules involve percentage decisions that can range from 0-100%. The values in
cells F27-28 and A35-36 of the Core Module involve integer decisions and a more
limited range of options. The column of floor quantity options in Column A44-53
is often limited by a zoning ordinance, but the potential list of choices can range
beyond 100. I’ll make my point in the ensuing paragraphs.
Each specification
topic requires a mathematical entry/design decision even if it is zero. Changing
one or more values assigned to any shaded specification topic produces revised
results in the Planning Forecast Panel and Implications Module. I’ll ignore the
whole number topics and the given land area. I’ll limit the floor quantity range
of choices to 100 to simplify this explanation.
The 12 topics involving
decisions ranging from 1-100 in Table 1 represent a relatively infinite
spectrum of low to high intensity combinations associated with the CGL1
building design category, which is the simplest of the six building design
classifications. Twelve specification topics times 100 potential options each
produces a great number of potential combinations. The factorial of 1200 is 6.3507890863e+3175.
This can also be written as 6.3507890863 x 103175, or 63507890863+3165
more digits.
This is the first
time I have come to recognize the true complexity of the physical design decision
process, the experience required to navigate these options, and the scope of
research/knowledge required to improve a leadership language that currently uses
intuition, talent, contradictory regulations, and missing information to
produce random results. We need to more thoroughly understand the implications
of the options involved and improve our ability to comprehensively,
consistently lead these decisions toward desired outcomes within geographic
limits designed to protect both our quality and source of life.
LEADERSHIP
CHALLENGE
The design
specification values entered in the shaded cells of Table 1 are examples of the
decisions that must be correlated and led to consistently achieve desired
results from the CG1L building design category. Without leadership, the options
available to every owner, developer, real estate investor, architect, landscape
architect, urban designer, civil engineer, city planner, and so on are too vast
to expect results capable of consistently avoiding sprawl, excessive intensity,
and continuing consumption of land that is also our source of life.
Table 1 represents
one forecast model that can be used to measure and evaluate our past physical
design performance, build knowledge, and improve results with a leadership
language based on the mathematical knowledge acquired. It is one model in a
city design portfolio of models. The portfolio choices are not a substitute for
architectural form, function, and appearance decisions. They precede them. The
topic values involved are meant to lay an urban design foundation of building
mass, parking, pavement, and unpaved open space quantity decisions. These
define massing composition/relationships that will be refined during the ensuing
phases of design and construction.
City design is a
strategic concept meant to achieve the goal of sustainable, symbiotic survival.
Urban design defines an objective that must be achieved to move toward the
goal. The specification topics in shelter capacity evaluation represent a leadership
language. The value decisions assigned require mathematical correlation. These
invisible decisions can lead many others to produce the visible, physical,
three-dimensional form, function, and appearance of shelter that symbolizes the
entire scope of knowledge acquired.
FOUR TOPICS
Four topics in
Table 1 deserve special mention.
Unpaved Open
Space
Cell F11 is a
critical but often ignored specification. The 30% unpaved open space specified
determines the amount of impervious cover that will produce stormwater runoff.
In this example, the related storm sewer capacity must be able to accommodate
the runoff from 70% impervious cover. This relationship has often been ignored
for many reasons. One of which is the pipe size cost to accommodate the demand.
Cell F11 is included to attract attention to this important
planning/engineering coordination issue.
Area per Parking
Space and Associated Circulation Drive Area
Cell A35 is
another topic often ignored and included here to gain design attention. The sq.
ft. planned per parking space and its related circulation aisle can be
minimized to eliminate landscape relief and increase the parking spaces
provided. The debate over function and appearance versus parking capacity affects
achievable gross building area and needs careful consideration and commitment
based on convincing research.
Number of Parking
Spaces
Cell A36 is one
of the most hotly contested topics in zoning regulation. It defines the number
of parking spaces required for a given land use category and building area. The
argument generally surrounds an applicant’s proposed activity and the number of
parking spaces the activity requires. It often involves a conflict between
experience and regulation that ignores the fact that parking deficiencies will
apply to future owners. These deficiencies may affect the value/revenue
potential of the land and building(s) to both the city and future owners. It is
another fundamental topic that needs careful leadership attention, but the
demands of a specific activity will always make a general regulation
controversial.
Building Height
Cells A44-A53
display a limited range of building height options that can be changed with a
few keystrokes to examine the implications of other options. It is another typical
zoning regulation that is often hotly contested, but with a limited
understanding of the implications. These are shown in the Implication Module of
Table 1, but it is like reading blood pressure readings with no prior
diagnostic history. It is no wonder that fear attends increasing building
height proposals at the present time.
All building
height options are not undesirable. If they were there would be no shelter for
man. The potential range may suffer from generalizations that come with a lack
of measurement, evaluation, and debate. There is much to learn regarding the
social and economic quality of life produced by building design categories, design
specification choices, and related floor quantity decisions that define the
form and fabric of the Shelter Division in our Built Domain.
OBSERVATIONS
We have depended
on market forces to determine the scope of shelter capacity required by growing
populations. Growth has been met with supply given the assumption that land is
a commodity without end. Municipal economic deficiencies have been met with the
annexation of land for new revenue that may again prove inadequate as the
annexation ages, prompting more annexation and sprawl. Encircled cities worry
that they have no land for annexation to compensate for budget deficiencies.
We have not
learned how to correlate shelter capacity, intensity, activity, and location to
produce economic stability within limited geographic areas that protect our
quality and source of life; but we cannot continue indefinitely on our random
path without finding a solution. It will inevitably involve data science, and
the formation of shelter capacity strategy based on the correlation of
technical knowledge from many related professional disciplines.
Walter M. Hosack:
August 2024
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