The Built Domain

I have written a number of essays over the years and have created a set of forecast models to predict the development capacity of land using a number of generic design scenarios, but essays can be lost and models conceal equations that represent knowledge.  

I plan to publish these essays and equations under the title, The Built Domain. The equations will be applicable to both U.S. and metric systems of measurement, which solves one of my problems. They will also relate to a vastly simplified forecasting system that focuses on gross building area as the common currency of architecture and city planning. 

In the process I have written an Introduction that represents my best effort to explain why this is relevant, in as few words as possible, and am posting it here for your review. I would appreciate any comments you may have but reserve the right to ignore them all. Designers everywhere should understand my attempt at humor.

 

The Built Domain 

The planet was a gift that we have subdivided until it is now in pieces. We have placed a hair net of property lines over its face and still fight for control. We have continued with consumption and pollution that should make wise men pause, since we are protected by a thin film of atmosphere on unstable land surrounded by fragile, turbulent seas; and our decisions are placing it all at risk in a universe of silent judgment.  

Subdivision continues to promote the illusion that we own the planet, but we dominate with power that pales in comparison to the forces we challenge with ignorance. All land is now claimed and we continue to subdivide, but the net is irrelevant when we stop to consider our source of life. It is simply a device to mark territory that a wolf does with ease. The struggle to survive is identical since we both live under the same conditions, but we have discovered a way to separate ourselves and conceal the consequences with political, legal, and economic abstractions. These have altered our perception of survival, but Instinct and intuition are producing an awareness of danger. Our decisions have created momentum that will challenge our ability to adapt once again; but domination will not solve the riddle of symbiotic survival on a planet that continuously evaluates our behavior.

Since we have been able to roam freely, we have assumed that the land, sea, and air have been ours to claim, inhabit, consume, and pollute; but is the case? I happen to agree with John Muir that the Natural Domain must be protected until we improve our ability to preserve it as our source of life. If you agree, the challenge is to define the Built Domain that is left for us. 

Our ability to shelter growing populations within a limited Built Domain will be a function of our land use allocation and intensity decisions; our ability to live with these decisions; and the demands these decisions place on our planet and its limited resources.  

Land Use Allocation 

Think of land use allocation within the Built Domain as fields on a farm, activity as the crops planted in each field, and intensity as the bushels per acre produced by each crop. Income is a function of field areas, crops, bushels per acre, and value per bushel.  

In city planning terms, fields are represented by land use allocation. Crops are land use activities. The square feet of shelter present, planned, or permitted per acre of activity is intensity. Intensity is a decision to limit development capacity. Income is a function of the revenue potential per square foot of activity introduced.  

A city defines fields and plants crops with a land use plan. Yield is influenced by the development capacity permitted. A city rarely correlates land use areas, activities, and capacity with its revenue, expense, and intensity implications; and it has great difficulty adjusting allocation imbalance to changing conditions and declining revenue. When annexation is not an option the problem is compounded. The revenue produced by annexation for the wrong activities and intensities, however, may have no better chance of off-setting the city’s operating, maintenance, and improvement expense over time. In these cases, annexation can delay the inevitable with new money that will not meet its future expense while consuming our source of life with sprawl. When annexation cannot meet its future expense, sprawl symbolizes a Ponzi scheme that leaves decay in its wake. The result is hardly the highest and best use of a city’s land area. In other words, a city is a farm that rarely correlates its crops and yield with the income needed to support a desirable quality of life over an extended period of time. 

Land use allocation and intensity can be correlated to produce adequate income for a desired quality of life within limits; but it requires new tools, applications, information, and awareness. If you accept that we must learn to live within geographic limits to protect our source of life, then you may also agree that we must begin to understand development capacity and intensity within these limits.  

Development Capacity 

I have mentioned that intensity is a design decision to limit development capacity. The challenge is to forecast capacity and limit intensity. The goal is to live within limits without sacrificing our quality of life. This will depend on our ability to accurately predict development capacity options with equations and values that can also be measured at existing locations to understand the intensity implied by these values. 

Intensity is the relationship of building mass and pavement to project open space on a given buildable land area. It is an increment of land development capacity and is a function of the parking system chosen and design specification values entered in the system’s design specification template.  

Building mass is volume that remains when building appearance is ignored. Gross building area within the volume can be tailored to suit any activity and is the common currency of architecture. It is also a prerequisite for survival. When you can accurately and efficiently predict the capacity of land to accommodate gross building area, you will be able to shelter population activities within limited geographic areas; but will have to learn more about the implications of intensity, revenue, and expense to our quality of life.  

Intensity 

Architectural intensity has been a condition without an adequate definition, but it will determine our ability to survive within sustainable geographic limits while protecting our quality of life.

Intensity is created by the relationship of four fundamental architectural components. These relationships are defined by the following equation. The logic leading up to this equation is summarized in Table I.1 and discussed in detail in my essay, “Quantifying Intuition“.  

INT = (f/S) * (TDA/BLA)  

When:

INT= intensity

f= the number of building floors present, planned, or permitted

S= the percentage of buildable land area devoted to project open space

TDA= the sum of gross building area GBA and pavement PVT in sq. ft. or sq. meters

BLA= the buildable land area present or proposed in sq. ft. or sq. meters 

NOTE:

The INT result can be a rather large number when high-rise buildings are considered. Dividing the INT result by 10 or 100 is one option. The low end of the intensity spectrum under these circumstances can become a very small fraction, however. The choice is one of preference. The only condition is consistency. 

The challenge is to predict the total development capacity of land TDA, including its gross building area potential GBA; to limit capacity with project open space S and building height (f) regulations that produce levels of intensity; and to correlate intensity with activity and context to produce economic stability and a desirable quality of life within sustainable geographic limits.  

 

Conclusion 

The equations to be presented can forecast development capacity for land areas of any size. Capacity is a relatively unlimited spectrum of opportunity until parking systems are chosen and design specification decisions are made. These decisions limit capacity and produce intensity. The result is gross building area GBA per acre. 

When intensity is aggregated across project areas, the result is urban form and space. Architectural design tailors urban form one project at a time with context, occupancy, engineering, and appearance decisions. 

When you consider our symbiotic imperative, the implications of these decisions become dramatic. We must shelter growing populations within sustainable geographic limits to protect our source and quality of life. It begins with the city design of urban form; but this is only part of the symbiotic puzzle. Truly “organic” shelter must be served by symbiotic systems of movement, open space, and life support. When successful, urban form will grow from symbiotic function and organic architecture will symbolize sustainable decisions based on symbiotic knowledge.

 

I am confident that shelter is intuitively recognized as a survival issue. It is simply a more abstract topic than medicine. After all, we only began seeing the anatomy of our patient with the advent of satellite photography -- and that awesome image from the Moon. It’s time to start treating the sprawl we have observed before the patient is consumed by disease. It’s hard for me to imagine that we cannot recognize responsibility now that we have seen the gift we have been given.

The Influence of Design Decisions

Twentieth century architecture pointed to our symbiotic imperative with two famous phrases: “form follows function” and “organic architecture”. They both meant that a flower grows from its roots in the land and blooms when in harmony with a universe of forces beyond its comprehension, in my opinion. Architecture has roots in the land, but only symbiotic human decisions can make it bloom in harmony with the planet's sovereign power.

Five decisions determine the development capacity of land to shelter activity when surface parking is the preferred storage solution. Architects often take these decisions for granted because they learn to evaluate options and make decisions intuitively; but this impedes the accumulation of knowledge since it depends on talent that cannot be taught. It can only be improved.

These decisions involve five primary variables that affect gross building area GBA potential on a given buildable land area BLA when surface parking around, but not under, the building is contemplated (G1 design category).

I’ll explain these topics by beginning with an equation derived in “Replacing Density”. It stated that:

GBA = f*(CORE) / (1+ (fs/a))

 

Key:

f = Number of building floors

CORE = BLA – (S+M)

BLA = Buildable land area in sq. ft.

S= Project open space as a % of BLA

M = Misc. pavement as % of BLA that includes loading area & pavement beyond parking lot area

s = Average area per parking space in sq. ft., including landscaping, within the parking lot perimeter

a = GBA sq. ft. permitted per parking space provided

 

This can be reduced to a universal equation with five variables when the equation is unwrapped.

 

Given: GBA = f*(CORE) / (1+ (fs/a))

 

GBA*(1+ (fs/a)) = f*(CORE)

Since CORE = BLA-(S+M)

GBA*(1+ (fs/a)) = f*(BLA-(S+M))

GBA = (f*(BLA-(S+M))) / (1+ (fs/a))

When BLA=1,

Equation (1):  GBA = (f*(1-(S+M)) / (1+ (fs/a))   

NOTE: GBA is expressed as a fraction of BLA

The five variables in Equation (1) are (f), S, M, (s), and (a) and the values assigned represent shelter design decisions that set the stage for all decisions that follow. The values (f) and (a) are generally specified in a zoning ordinance, but the values S, M, and (s) are often overlooked. They are critical to successful leadership, however; and their omission is the easiest way to explain why zoning has been able to separate incompatible land uses but unable to avoid over-development and sprawl. Any regulation that omits one or more of these five elements for the G1 design category simply encourages arbitrary debate over isolated detail. Equation (1) shows that all five are needed in the equation and that results are produced by their interaction. The next five tables are examples of this interaction.

Table 1 illustrates the GBA options produced by Equation (1) when project open space S is a variable along the x-axis; building height is a variable along the y-axis; and the values (a), (s), and M are held constant. GBA options are expressed as percentages of BLA and the option range is stated as a percentage of BLA in the upper right hand corner of the table. In this case, the range is 30.1% and begins with GBA=1.4% BLA when (f) =1 and S=90%. Some of these options are undesirable, but research is still not available to support intuition with knowledge.

Tables 2-4 repeat the exercise with different variables along the x-axis. Table 2 illustrates GBA options when the average parking lot area provided per parking space (s) varies. The GBA range noted is 14.2% and begins with GBA=1.15% when (f) =1 and (s) =900 sq. ft. of total parking lot area per parking space.

Table 3 illustrates GBA options when the parking space requirement per thousand sq. ft. of GBA (alt-a) varies along the x-axis. The GBA range noted is 192.4% of BLA and begins with GBA=7.6% when (f) =1 and (alt-a) =20 parking spaces required per thousand sq. ft. of GBA.

Table 4 illustrates GBA options when the miscellaneous pavement percentage M varies along the x-axis. The GBA range noted is 12.3% of BLA and begins with GBA=12.9% when (f) =1 and M=25% BLA.

Table 5 is the primary battlefield of zoning. It presents GBA options when project open space S varies along the x-axis and parking requirements (a) vary along the y-axis. The number of building floors is constant at f=5 for this example. The greatest development capacity potential GBA can be found in the S.1, or 10% open space, column. This GBA capacity can be increased further by requesting a variance to the parking requirement (a) that applies. For instance, a variance from 5 to 4 parking spaces per thousand sq. ft. of GBA would produce a 9% increase in GBA potential in the S.1 column.

The ten percent open space in Table 5 is not desirable, nor is 375 sq. ft. of parking lot area per space, and a parking requirement of 4 spaces per thousand is not enough to support some land use activities. I make this point because I’m not trying to advocate individual design specification values. I’m trying to explain how they interact. When one or more is omitted it is impossible to accurately predict development capacity with Equation (1); and I have already pointed out that three are often overlooked in zoning ordinances and the other two are considered independently. In other words, it is impossible to plan and lead shelter for growing populations within sustainable geographic limits when these equations are not understood. This in turn makes it impossible to protect the Natural Domain from sprawl and the Built Domain from excessive intensity because special interest arguments often trump public uncertainty.

At the present time my guess is that most zoning ordinances do not regulate project open space S, miscellaneous pavement M, and/or minimum parking lot area per space (s). Even if they did, their requirements in isolation can be contradictory when not correlated.


In addition, zoning requirements are rarely based on a land use plan with self-imposed geographic limits; or a massing plan for the urban form of shelter that is correlated with its physical, social, psychological, environmental, and economic implications. In other words, city planning has separated incompatible land use activities, but it has done it with sprawl that threatens our source of life.

Architects take the five variables in Equation (1) for granted. They use intuition to correlate these elements with design sketches. He or she cannot complete a project without considering these five variables; but the graphic methods of solution have limited the options that could be evaluated, and their mathematical foundation has been overlooked by an emphasis on “talent”. This has limited the accumulation of knowledge.

Table 6 summarizes the results in Tables 1 -5, but these results only illustrate how Equation (1) works. They do not represent recommendations. All results are expressed as a multiple of the buildable land area BLA available.

It should be fairly obvious from the results that building height (f) influences development capacity GBA, but that the surface parking requirement (a) is the most influential. A closer look at Table 3 will explain this more fully. If you look at the (f-1) row, the development capacity GBA varies from 7.6% to 40% of BLA depending on the parking requirement (a). This is a range of 32.4%. The two-story range is 64.7%. The five-story range is 161.8%. All of these ranges are a function of a variable parking requirement (a) within a constant building height (f) row, and they all exceed the development capacity ranges available in the other tables. In other words, modifying the value (a) has the greatest potential to increase development capacity GBA for the G1 design category. It’s not hard to understand the number of variance requests from parking requirements (a) when looking at the potential GBA range in Table 6, but keep all of the tables in mind. It is not only (a) that influences development capacity, and design leadership must have all five reins under control to prevent a run-away.

Design begins with the correlation of relationships in Equation (1). This defines the context format for architecture and city design when the G1 design category is considered. Buildings emerge from a context format and symbolize our progress toward shelter for growing populations within symbiotic limits that do not threaten our source and quality of life.

Intensity and over-development become a problem because project open space S, miscellaneous pavement M, and minimum parking lot area per parking space (s) are rarely specified or correlated in zoning ordinances. The omission inadvertently emphasizes building mass and pavement. The public is compressed in a right-of-way of increasing traffic and pollution. Storm sewer capacity is threatened by excessive impervious cover, and the list goes on. The battle is often fought within Tables 1-5 when surface parking is involved, and many real estate investors / building owners / speculators would prefer choices in the left-hand column of each, but this is a recipe for excessive intensity that will not protect our quality of life.

Architects will have a lot to offer when they decide to quantify intuition, demand context, and accumulate knowledge to defend design decisions that benefit the public interest.

POSTSCRIPT

In the end it’s all about gross building area GBA potential on a given buildable land area BLA because GBA can be used to shelter any activity. For instance, if you divide the gross area of an existing apartment building by the number of dwelling units present the result will be an average gross dwelling unit area ADU statistic. If you divide the GBA forecast for another buildable land area by the same ADU, its dwelling unit capacity can be predicted, assuming the same dwelling unit mix and areas. The critical piece of information is the development capacity GBA of land, and it can be forecast.

Single family homes are no different. Gross building area shelters a specific activity on a given land area. The GBA capacity of a residential lot is a function of the five variables in Equation (1). Gross building area is the universal currency. It is simply tailored to meet the needs of a specific activity. I’ll have more to say about this in the future.

 

 

 

 

 

 

 

Quantifying Intuition

Intuition is telling many that we can’t continue to consume, pollute, and disrupt the land and resources of the Natural Domain without consequences. When the built environment includes agriculture, I’ve referred to the combination as a Built Domain that must not consume our source of life - the Natural Domain. When population grows within a limited Built Domain however, shelter intensity must increase based on the development capacity of land because sprawl is not an option. This means we must be able to efficiently and comprehensively predict shelter capacity options and evaluate the impact of shelter intensity on our quality of life.  In other words, intuition is telling me that we must protect our source of life from sprawl and our quality of life from excessive intensity within sustainable geographic limits.

I have focused on the prediction of shelter intensity options with templates related to generic building design categories to quantify the evaluation of options within sustainable geographic limits. These building categories are part of a classification system for the Shelter Division of the Built Domain. Choices within the classification system lead to a specific forecast model. The values entered for each template topic in a forecast model are used by the model’s embedded equations to predict gross building area GBA options in its planning forecast panel. These GBA alternatives represent potential levels of intensity for a given buildable land area. Table 2 illustrates the specification template and forecast panel format of a typical model.

Forecast models can be used to evaluate the development capacity of land areas in a city, but first let me explain the term. Development capacity is the gross building area GBA that can be constructed under the conditions specified in a design specification template. Changing one or more values in a template changes the GBA forecast. The GBA produced by a set of template values has also been referred to as a level of intensity. This means that design specification templates can be used to correlate land use allocation with intensity. This knowledge can be used to predict anything that is a function of gross building area intensity such as, but not limited to, population, traffic, construction cost, and return on investment; not to mention municipal revenue and expense.

Urban economic stability is a function of land use allocation, shelter intensity, building condition, and prosperous activity. This combination also affects a city’s physical, social, psychological, and environmental quality of life. Even if you don’t agree that our source of life can be consumed by the sprawl we build, this may persuade you to more seriously consider the impact of intensity on a quality of life that begins with the economic stability present.

In other words, shelter intensity is the relationship of building mass and pavement to open space. It is a condition that can be measured, predicted, and has lifestyle implications. In my opinion, it is one key to protecting our quality of life within sustainable geographic limits; but many are required. For instance, acceptable levels of shelter intensity must be supported by organic functions before we can consider them part of a symbiotic survival solution.

The term “organic” began with the paraphrase “form follows function” from the poetry of Louis Sullivan. “Organic” was a Frank Lloyd Wright translation that referred to building style, space, appearance, and landscape integration; but this was not Sullivan’s intent in my opinion. Sullivan meant that a flower blooms from organic function that is programmed by design from a power beyond comprehension, and that building design must attempt to emulate this example. Building appearance has yet to bloom from organic function, and this is the design challenge architecture, city planning, engineering, and science have been given. The fact that this must occur within sustainable geographic limits introduces the issue of development capacity and shelter intensity.

I was able to forecast the development capacity of land (gross building area potential per acre) long before I was able to calibrate the intensity options represented with a standard measurement system. In fact, I’ve made a number of attempts that were too complicated to explain or too simple to consistently lead many efforts toward common objectives. This is my best effort to date, but it only addresses shelter intensity. Organic architecture is still a dream that began with fine art when domination began to threaten global survival and coexistence became a common concern for many. It continues to remind us of the goal that must be won.

Intensity design represents the context format for organic architectural functions. In other words, the urban form of shelter is produced by intensity design that must eventually be served by organic systems.  Shelter intensity represents my effort to begin quantifying context intuition, and it begins with the following assumptions. The result is an intensity equation and a method of intensity measurement that can help us index research and build knowledge for succeeding generations. In the end organic functions will improve our chances of survival and intensity context will make life worth living.

ASSUMPTIONS:

1)   Increasing building height (f) increases intensity INT on the same land area.

2)   Increasing gross building area GBA increases intensity on the same land area.

3)   Increasing parking, loading, and miscellaneous pavement PVT increases intensity on the same land area.

4)   Increasing a project open space percentage S decreases intensity on a given land area.

Based on these assumptions, intensity increases when the number of building floors (f) increase and project open space S remains constant on the same land area. Intensity declines when project open space increases and building height remains constant. In other words, f/S represents a partial index of intensity. This explains the relation of building height and project open space to intensity but does not explain the relationship of gross building area and pavement.

Gross building area and pavement combine to produce total development area TDA. Intensity increases when total development area increases and the buildable land area BLA remains constant. Intensity declines when the buildable land area increases and the total development area remains constant. In other words, TDA/BLA also represents a partial index of intensity.

To think of intensity as simply a function of building height overlooks the effect of building mass, pavement, and project open space. Intensity is a function of all four. Any equation that predicts intensity INT therefore must show that intensity on a given land area increases with building height (f) and total development area TDA. It must also show that intensity INT declines when project open space S and/or buildable land area BLA increase.

THEREFORE:

Multiplying (f/S) by (TDA/BLA) is a simple way of expressing these intensity INT relationships.

INT = (f/S) * (TDA/BLA)

The equation states that intensity INT increases with increasing f and TDA values. It declines with increasing S and BLA values. In other words, increasing building height (f) and/or total development area TDA increases the intensity INT on a given buildable land area BLA and project open space provision.

This equation illustrates the complexity of intensity when you realize that total development area potential TDA is equal to gross building area plus pavement; that both are a function of many values entered in the design specification template of a forecast model; that one or more values in a template can be changed to produce a new TDA forecast; and that many templates are needed to define the range of generic building design categories available. (See Figures 1.1, 1.2, and 1.3 in “Planning with Architectural Intensity” for decision trees that lead to a specific forecast model. Each model includes a customized design specification template.)

To avoid confusion, I have referred to gross building area GBA options as “development capacity options” and to gross building area plus pavement options as “total development area options” TDA. In other words, TDA=GBA+PVT. Pavement area PVT is equal to the sum of parking, loading, and miscellaneous pavement areas.

Table 1 presents several generic intensity calculations to illustrate a range of intensity results. Table 2 illustrates how intensity is predicted in the forecast model CG1L when a full set of design specification values is entered.

CONCLUSION

Shelter intensity is similar to blood pressure, which is an analogy I’ve used in the past. Blood pressure is a benchmark that indicates the health of a complex set of anatomical relationships. Samuel von Basch is credited with the discovery of systolic blood pressure in 1881. Scipione Riva-Ricci introduced a more easily used version in 1896. Harvey Cushing modernized and popularized systolic measurement after visiting Ricci around 1900. Nikolai Korotkov added diastolic measurement in 1905.

Medical history is not the point, however, even though I’ve always found it amazing that medical progress of significant general benefit only began in the 20^th century. My point has been that von Basch developed a method of measurement  for intensity based on his intuitive belief that there was a relationship to illness. Diagnosis was correlated with measurement and knowledge accumulated over time to improve the credibility of prediction.

I am suggesting that shelter intensity is a similar topic related to the anatomy of our Built Domain. It can be measured and correlated with the evaluation of health, safety, and welfare that ensues. The knowledge gained will add to the credibility of planning and prediction based on measurement with leadership potential, and I hope it will help us learn to live within sustainable limits that do not threaten our source of life with sprawl and our quality of life with excessive intensity.
 

Planning with Architectural Intensity

***Please see my latest book, The Science of City Design: Architectural Algorithms for City Planning and Design Leadership, on Amazon.com in both e-book and paperback versions.***

Limiting areas of human occupation to achieve a sustainable future represents emerging symbiotic awareness, in my opinion; but success will depend on our grasp of intensity and space. They are keys to survival, but both are relatively ambiguous terms in our daily lives. The need to learn more is based on the argument that: (1) Limited population areas must be defined to protect our source of life. (2) Limited intensity within population areas must be adopted to protect our quality of life. It is no longer enough to protect our health, safety, and welfare unless “welfare” includes our source and quality of life.

I’ve referred to limited population areas as the Built Domain and to our source of life as the Natural Domain because I’ve come to agree with John Muir. We do not have the knowledge and wisdom required to integrate the two in a universe we barely understand. I only need to mention our success in polluting and disrupting environmental systems to prove my point. This means we must protect the Natural Domain as our source of life and construct the Built Domain with a symbiotic goal. Domination is out of the question unless extinction is our destiny. Coexistence is a mandate we must accept and the instinct to compete is a hurdle we must overcome.

Agriculture is a buffer between the Natural and Built Domains. It’s part of the Open Space Division of the Built Domain because of its man-made presence, pollution, and depletion of natural resources. I’ve generically referred to the remainder of the Built Domain as the Built Environment to distinguish it from agriculture that is being consumed by its growth. Obviously, consuming your source of food and life is not a recipe for survival.

The Built Domain can be divided into Shelter, Movement, Open Space, and Life Support Divisions. These divisions oppose the Natural Domain. It should not be a battle for dominance, however; and this is where our concept of competition contradicts the law of adaptation. It is a battle for coexistence and the intensity of our presence will be inversely related to its outcome.

The word “intensity” covers a lot of ground. I’ve limited its scope by focusing on shelter intensity in the Shelter Division of the Built Domain. Architecture is most closely associated with project intensity within this division because of its client relationships. This has led to building and zoning codes that attempt to protect the public interest from private decisions with minimum requirements. The initial objectives were to protect the public health, safety, and welfare by separating incompatible land uses; and protecting building occupants from unsafe and unsanitary conditions. The result has been a sprawling threat to survival. The result is not from misguided intent, however. It is because we have not been able to measure, evaluate, forecast, and regulate the values that interact to produce intensity options. These define the urban forest and the quality of life we enhance with context design and habitation standards. Unfortunately, forest paths are more pleasant. Urban paths take us through urban form that often forces us to become “street people”.

At its most fundamental level therefore, intensity requires design with space. This includes space for the Natural Domain and space within the Built Domain to feed us and moderate intensity. All remaining context design will apply to the open space format adopted. When the adoption produces a symbiotic presence, we will have achieved organic design ability.

Background

Architecture can do better, not to mention city planning and design. Intensity is intuitively understood but has not been evaluated with a consistent measurement system. This means that intuitive design is often forced to exceed its better judgment. This occurs most often when intuition is confronted by memorized knowledge and precedent. Precedent has been pre-occupied by an emphasis on the separation of incompatible land use activities, but separation alone produces sprawl when growth is not contained.

The steps from intuition to knowledge remind me of language before the discovery of writing. Intuition and experience were explained around the campfire by wise men with talent, and memory was the only library of knowledge. Writing recorded and stored opinion, precedent, and knowledge that was eventually challenged by science. Talent lost credibility but retained insight to become fine art.

Intuitive intelligence cannot compete with memorized knowledge until it develops persuasive ability with logic. The vocabulary of shelter intensity can be used to measure, evaluate, and express planning arguments with logic that can consistently lead architecture with a language that does not depend on talent to preserve knowledge over generations.

The transition to intensity is simply another step in our attempt to comprehend the environment we have been given and to adapt accordingly. I like to imagine that this began with the Cro-Magnon paintings at Lascaux and Altamira, Font-de-Gaume, and Grotte de Chauvet. In my imagination these were teaching illustrations with mystical properties that moved with the light from fire. The mystery continues along with our attempts to adapt to our environment with intuition and logic that is eventually recorded as knowledge.

The Nature of Intensity

We are familiar with the residential term “density”, but it is a wildly inaccurate measurement of “intensity”, which is the relationship of building mass and pavement to open space on a given land area. (See “Replacing Density” and “Replacing the Floor Area Ratio”) Density ignores all three components of intensity (mass, pavement, and open space). It simply expresses the number of dwelling units present, planned, or permitted per acre. The definition of “acre” can even be ambiguous. When undefined, it is often considered gross land area even when a portion is unbuildable. Multiplying permitted density by gross land area in these cases produces a much higher density within the actual buildable land area occupied.

One could argue that yard requirements are open space requirements, but most are not dedicated to this purpose. Side yards are separators that are often paved. Rear yards are often converted to building mass and pavement, and front yards are often minimal or paved for parking in non-residential areas. This tendency to consider pavement open space can produce excessive development that often leads to physical decline. Deterioration in turn has an unsettling tendency to increase social, psychological, environmental, and economic stress when style and location do not spark renewed interest at some point in the decline.

I could see from experience that density led to unrealistic assumptions, arguments, and inconsistent results but also believed its premise was sound. Architecture, city planning and city design do have a mathematical foundation. Density was simply not a calculation with the potential to produce consistent success. The equation didn’t control the values that produce the format for context design. This meant we couldn’t hope: (1) to shelter growing populations within sustainable limits; (2) to protect their source of life from sprawl; and (3) to build shelter within these limits to protect their quality of life from excessive intensity. We simply couldn’t define the elements of intensity and the values that interacted to produce context format. This led me to define the topics involved and describe their relationships with equations.

My concept was to list context topics in a template that would receive values and use embedded equations to predict intensity for the design category represented. These options would be expressed as the gross building area GBA per acre that could be produced by these values; and modifying one or more values would produce a new prediction. I called the process “development capacity evaluation” and the results were called levels of intensity that were predicted in relation to a column of building height options. In other words, a design specification template was an architectural planning template.

Along the way I realized that part of the problem was an imprecise definition of “acre”, since it could mean gross land area, net land area, buildable land area, or core land area. (See “Context, Capacity & Intensity”) This had compromised density calculations from the very beginning, and often led to results referred to as “over-development”. Over-development is still a term without definition that is recognized when seen, but is actually an excessive level of intensity that can be mathematically defined.

I started referring to density as intensity to reflect the three-dimensional nature of the results and the role of open space as an off-setting influence, but realized it required an explanation because “intensity” has a negative connotation. In fact, it is a yardstick that measures the relationship of building mass and pavement to open space. These relationships range from ranch-houses on thousands of acres to high-rises in Manhattan. I realized that specification values entered in a template combine to create these relationships, and that choices regarding these values are the foundation for all intensity and context format decisions.

I began to call template variables design specification topics. In fact, I began to realize that different topic sets related to different building types and a separate template was required for each. This observation appeared to doom the effort until I realized that all building types and appearances fall into one of three land use families; that these families are served by one of three parking systems; that each parking system has at most four generic sub-types; that design specification templates could be attached to each potential land use, parking system and parking type decision; that template topics could be tailored to a small list of generic building types related to these parking options; that values could be entered in a template and used by embedded equations to predict the gross building area options implied; that this represented a forecast model; that existing projects could be classified, measured, and evaluated with the decisions that led to a forecast model; that measurement and evaluation could be used to build knowledge about existing values; that adopted values defined intensity with a forecast of gross building area GBA potential per buildable acre; that forecasts could consistently lead shelter toward planning objectives when connected to the city design of urban form; that urban form could be mathematically modeled and adjusted to achieve specific objectives based on template forecasts of gross building area potential; that gross building area options for the same land area represented levels of intensity; and that the ability to measure, evaluate, and predict intensity could lead to the protection of our physical, social, psychological, environmental, and economic welfare within sustainable geographic limits.

I was aware, along with most, that adding building floors increases gross building area potential on a given land area. Therefore, when a range of floors is included with a design specification template, the model can forecast a number of gross building area options on the same page for comparison; the results from separate forecast models can be compared;  and each prediction will represent a level of potential intensity and format for context design.

Table 1 outlines the classification concept behind development capacity evaluation. Figures 1.1, 1.2, and 1.3 are attached at the end of this essay to define it in detail. These figures are decision trees that read from left to right. The path chosen leads to a specific forecast model, and each model contains a design specification template. The objective is to forecast gross building area options (or buildable land area options) based on the forecast model chosen and the values entered in its design specification template.

Table 1: Architectural Classification Topics 

Choose one topic from each of first four columns to find a forecast model. Design specification variables are listed in the template associated with the model. Assign values to the variables in the model’s template to produce development capacity predictions, or measure these values to define existing conditions. The development capacity options forecast (gross building area options) represent intensity alternatives.

Land Use Family	Parking System and Type	Building Type	Information Given	Specification Variables
Non-residential (C)	No Parking (N)	Non-residential (C)	Gross Land Area (L)	Refer to template associated with the forecast model identified
Residential (R)	1)        None	Apartment (R)	Gross Bldg. Area Objective (B)
Mixed (M)	Surface (G)	Suburb House (F)	Density Objective (D)
	1)        Around Bldg.	Urban House (T)
	2)        Around / Under Bldg.
	3)        No Shared / Common Pkg.
	4)        Lot and/or Garage
	Structure (S)
	1)        Adjacent
	2)        Underground
	3)        Under Bldg.

Table 2 is attached to illustrate a design specification template with values entered and a planning forecast panel with related predictions. The technical label for Table 2 would be CG1CL, but the second “C” has been dropped to label the forecast model CG1L for the sake of brevity.

The Table 2 planning panel illustrates the range of gross building area GBA options produced by a set of template values, and a number of related predictions. Since a change in any template value produces a new forecast, it’s easy to calculate intensity after data entry or revision; but I have struggled to find a simple method of prescription. I’ve experimented with many options and will have more to say about this later under “Design Specification Deployment”.

In summary: (1) Open space offsets building mass and pavement to create a level of intensity on a given land area.  (2) Open space is a raw material molded by design to create context. (3) The values entered in a design specification template define the level of intensity present or planned. (4) Intensity options can be electronically predicted with efficiency and accuracy by modifying one or more template values. (5) Intensity options from different templates can be compared. (6) Design specification values can be measured and recorded at existing locations to define intensity for research into its physical, social, psychological, environmental, and economic implications. (7) Related disciplines can evaluate intensity based on a common measurement system. (8) A common measurement system introduces a vocabulary and language of intensity to record knowledge for future use, and to multiply it over generations; (9) This measurement system represents a common language for intensity evaluation; and (10) Intensity knowledge from evaluation makes it possible to study shelter options for growing populations within sustainable geographic areas.

The four arrows in Table 2 identify the primary variables that influence development capacity and intensity for the G1 and G2 surface parking design categories. Generically, these variables relate to building mass, pavement, and open space, but open space requirements are generally missing from current zoning ordinances and can be compromised by variance requests.

On an engineering note, excessive building mass and pavement exacerbate stormwater runoff. This runoff can exceed sewer design capacity because capacity is based on impervious cover assumptions. When these assumptions are exceeded, water becomes a common enemy. The argument for reserved open space to protect sewer capacity has persuasive power because it is based on engineering research and measurement. The approach began with awareness and was challenged, however; and I’ve used this example to illustrate the hill that intuition must climb to achieve persuasive power. Protecting our physical, social, psychological, environmental, and economic health is no less important than protecting sewer capacity; and intensity measurement gives us a vocabulary to begin the journey.

Design Specification Relationships

Table 3 is appended to this essay to explain design specification relationships in a simplified format. To make the percentage predictions universally applicable, it is based on one buildable acre. Parking requirements (a) and (s) are included in the design specification template. The planning forecast panel arranges open space requirements S in the top row and building floor options FLR in the left-hand column. The gross building area per acre GBA/AC and building “footprint” per acre BCA/AC predictions are based on the design specification topics and values entered.

Table 3 shows that GBA options within a 5 floor limit range from 50% to 3.8% of core area. (See “Context, Capacity & Intensity” for an explanation of “core area”) This range is a function of the project open space S columns presented. If 40% open space and 5 floors were chosen as design limits, the maximum gross building area would be 33.3% of core area, but 33.3% is still a function of two variables in the design specification template: (s) and (a). If a parking lot, including internal landscaping, were required to provide no less than 400 sq. ft. per space (a), intensity per acre would be a function of the number of parking spaces required (s). This would make intensity a function of one variable. In other words, gross building area per buildable acre is a function of the parking requirement for a specific activity when all other values are specified. In fact, the only variable missing from most zoning ordinance specifications is project open space S. What has really been missing is a common forecasting system to explain what these values imply when combined, and when open space is introduced as a specification. 

Table 3 provides a glimpse of the results produced by inter-active zoning requirements. The forecast equations that produce this table have not existed in the past, however; so developers have requested variances from individual requirements that conflict or seem excessive, and planners have not been able to forecast combined implications to focus the discussion. The medium for discussion has been a site plan, but this cumbersome graphic cannot predict the range of options shown in Table 3 within a reasonable time frame and design budget. The result has been suspicion and argument over detail rather than negotiation based on a common language.

Imagine that planners and developers are discussing Table 3 around a table and that it is projected on a screen from a notebook computer. Imagine also that topics (s) and (a) are zoning requirements along with FLR = 5 and S = 40%. Table 3 predicts that the maximum development capacity GBA/AC will be 33.33% of the buildable land area when all design specification requirements are considered together. Let’s imagine that the developer is not happy with this capacity and claims that he only needs 3 spaces per thousand sq. ft. of GBA from his experience, instead of the 4 specified. The planner could change this statistic to predict the GBA implications on screen. If the developer were satisfied, he or she would need a variance, but would have a better chance of success if the planner supported the request. The planner would have to consider future owners who may need more parking, since the building may be the owner’s dream, but it represents a city commitment of land to an activity and source of revenue that must contribute to common benefit without decline. The point, however, is that both would be speaking the same language and understanding the same implications when discussing the proposal.

In other words, Table 3 becomes a common language for discussion based on design specifications and capacity prediction, which is intensity evaluation by another name. This negotiation involves a number of inter-related zoning requirements that can be discussed separately but forecast together to reveal their combined implications. Costly site plans can be prepared after negotiation to illustrate decisions or remaining points of contention.

Design Specification Deployment

A single zoning requirement cannot hope to regulate shelter intensity; nor can a set of independent requirements scattered throughout a zoning ordinance because they often conflict without correlation. A design specification template lists requirement topics and correlates values entered with embedded equations. These equations forecast implications in terms of gross building area GBA potential per buildable acre. Design specification templates, therefore, are needed to convey the implications of isolated values and can be connected to land use categories and city design plans to regulate intensity.

It appears, therefore, that a single requirement like density or the floor area ratio is an inadequate policy statement that cannot substitute for a design specification template. A template understands the implications of all values and can be connected to a land use allocation plan to predict the implications of a combined city design strategy. In other words, design specification templates are architectural planning templates that can be used to correlate land use allocation with urban form to achieve economic objectives; and these objectives can be coordinated to include social, psychological, and environmental implications when research provides the answers.

Conclusion

Prediction is at the heart of negotiation and options have implications. Decisions are based on evaluation. When options and implications cannot be predicted, regulation becomes an argument over isolated detail. This is surrounded by suspicion over motive and subject to the law of unintended consequences. In my opinion, we must learn to correlate shelter design specifications before we can begin to contribute to the question: Can we protect our source and quality of life?

Intensity is a common problem and opportunity that will not be addressed by adversaries arguing over isolated details that produce random results. An intensity vocabulary without knowledge takes us back to intuition. This is where we are with shelter intensity. I have proposed a rudimentary classification and design specification vocabulary to forecast the gross building area GBA implications of design specification values. Each square foot of intensity predicted has a number or related implications such as, but not limited to: cost, revenue, return on investment, population, traffic generation, and energy consumption; but prediction of GBA without research into its implications is speech that will remain opinion and a threat to our source and quality of life. It’s like the first blood pressure readings. The inventor only had an intuitive understanding of what they meant until research converted intuitive intelligence to memorized knowledge.

Table 3 was projected on a wall like the paintings at Lascaux in my imaginary scenario. The table represents an abstract concept or a measured object in the Built Domain, which is a separate environment; and we have yet to fully understand the Natural Domain. It is a self-evident fact, however, that we create the Built Domain and it is a power of creation we must learn to restrain; because it has not been given as a gift, but as a responsibility.