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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.
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
No Parking (N)
Gross Land Area (L)
Refer to template associated with the forecast model identified
Gross Bldg. Area Objective (B)
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
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.
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.