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City design and architecture adapt shelter, movement, open space and life support systems to The Natural Domain. From this perspective, design determines our ability to shelter growing populations within a limited Built Domain that does not threaten its source of life; and intensity is a label for the knowledge required. When this knowledge is accumulated, design recommendations will be defended with expanded explanations of benefit that include our physical, social, psychological and economic quality of life -- not to mention our sustainable future.
The following examples depend on a forecast model to predict architectural capacity and intensity from the data entered in its design specification template, but the impact implied by the intensity levels predicted is unknown. We simply know from experience that some of these predictions represent excessive intensity. We will have to rely on experience until research produces the conclusions we need to acquire knowledge. It’s an essential step into the sustainable future, because we cannot shelter growing populations within a limited Built Domain until we learn more about intensity; and we must learn in order to protect their source of life – The Natural Domain.
BACKGROUND
Open space, however, will define the quality and opportunity for a sustainable future. This essay will discuss the potential of intensity options to preserve open space within and beyond a limited Built Domain, since The Natural Domain is open space that does not compromise with ignorance.
A lack of intensity awareness has led to limited shelter options; over-development; excessive sprawl; consumption of agriculture; reduction of The Natural Domain; and pollution of the planet. These habits cannot continue indefinitely, because they discard a sustainable future for growing populations.
Open space is the essential ingredient in a recipe that produces context. Recipe quantities produce a farm at one end of the context spectrum and a tenement at the other. This context spectrum is “intensity”, and we have labeled excess “overdevelopment”; but have been unable to accurately forecast or calibrate the physical, social, psychological and economic impact of intensity decisions within this spectrum of possibilities. In fact, only social reform could force us to recognize abuse; but it could not be measure the extent and was forced to adopt partial solutions as a consequence. Our city plans and zoning ordinances remain at this level of awareness today.
TOOLS
In order to measure and forecast intensity I’ve had to create two specification outlines because residential and non-residential development involve substantially different characteristics. The forecast models within each family contain customized design specification templates that relate to specific design categories. Embedded equations process the area and height values entered to predict intensity options for the design category involved. These options are expressed as gross building area GBA potential. Each GBA forecast is divided by the number of buildable acres available to produce a measurement that defines an intensity option.
I have discussed forecast models in many essays, and forecast model selection in “Improving the Argument for Architecture and City Design”. I won’t repeat myself here, but plan to use a forecast model to explain the effect open space has on context and capacity. The forecast model pertains to one land use family (C), one parking system (G), one design category (G1) and one design specification template. The gross land area (L) must be given in the model chosen. The forecast model is called CG1L and is illustrated by Table 1. It pertains to non-residential land uses with a grade parking lot around, but not under, the building when the gross land area is given.
All quantities used in this essay were derived by entering values in the design specification template of CG1L. In its Planning Forecast Panel, four building floors has been emphasized to indicate that this building height has been adopted as a given to simplify this explanation. As you can see, I could have chosen any building height, or entered substitutes for the ones shown, but choosing more than one would have unduly complicated this effort. If you have read “Replacing Density”, you also know that anything over 5 building floors served by a grade parking lot produces a negligible increase in gross building area when open space is not reduced.
Table 1: Forecast Model CG1L with Design Specification Values Entered in Blue
OBJECTIVE
My objective is to explain the variable relationships between gross building area, parking area and open space that produce the context, capacity and intensity of shelter within cities. The design specification values that determine these relationships have not been previously distilled, and this lack of knowledge has compromised our ability to produce livable cities within sustainable limits. Design specification values produce shelter context and capacity. The relationship between context and capacity becomes a measurable level of intensity when these values are understood, since they can be used to either define or predict the intensity of a design option being evaluated.
Site Plan Hierarchy
Figure 1 shows that gross land area is reduced by planned rights-of-way and paved easements to produce net land area NLA. The net land area is reduced by unbuildable land and existing conditions to produce buildable land area BLA. Buildable land is reduced by an open space percentage to leave core area CORE for building floor plan (“footprint”) and parking area. Open space in the net land area sets the stage for context and core area sets the stage for development capacity, or intensity. Unbuildable areas may represent amenity and visual appeal, but they are not part of open space context within the buildable land area that determines intensity.
It is possible that no open space and / or parking area will be provided, leaving a larger core area for the “building footprint”. It is also possible that the parking area will be placed under the building or underground. This approach can be used to either preserve open space or expand the potential core area at grade for a larger “building footprint”. Figure 1 serves to explain the site plan hierarchy involved when one remembers that any band can be zero, except for the building “footprint” area.
Figure 1: Site Plan Hierarchy
When an open space percentage is held constant for a given land area and a CG1 design category is considered, gross building area is increased by increasing building height; but its “footprint” must be reduced to provide more land for the increased parking spaces required. Figure 2 is repeated from “Replacing Density” and is a series of pie charts simulating site plans that illustrate this relationship. You should notice in the pie charts that green remains constant while black becomes smaller and gray increases.
Figure 2: Site Plans Reflecting Building Capacity Produced by Parking Lot, Building “Footprint” and Building Height Options -- when Open Space Remains Constant
A designer’s second reaction is to reduce parking space and circulation aisle dimensions to reduce the gross parking lot area required. This increases the potential “footprint” area. His or her third reaction is to request a variance to the parking regulations. All three of these reactions, however, represent an attempt to increase the gross building area capacity of the site by modifying design specifications. A few examples should serve to illustrate how these design specifications affect the context, capacity and intensity of the cities we inhabit.
Figure 3: Building Height Effect on Building Capacity When Parking Lot Area Varies and Open Space Remains Constant
BUILDING CONTEXT and CAPACITY
Table 2 itemizes the constants and variable ranges used in the design specification templates of Table 1. They have been used to produce Charts 1, 2 and 3.
Table 2: Variables and Constants Entered in Design Specification Template of Table 1
In other words, if you choose an open space increment S on the x-axis and project vertically from this location, the intersection with a diagonal line above indicates the gross building area potential of the combination. When the result is divided by the number of buildable acres involved, a level of intensity is calculated for the entire set of design specifications involved.
Chart 1: Parking Requirement Restrictions on Building Capacity When the Avg. Parking Lot Area per Space is Constant (s = 350 sq. ft.)
Chart 2 is identical to Chart 1 with one exception. The average parking lot area per space constant has been increased to 400 sq. ft. Chart 2 illustrates the impact of this increase on gross building area capacity. Such increases are considered for greater maneuverability and internal landscape improvement, but they reduce gross building area potential.
Chart 2: Parking Requirement Restrictions on Building Capacity When the Avg. Parking Lot Area per Space is Constant (s = 400 sq. ft.)
The gross building area GBA lines in Charts 1 and 2 become zero at 80% open space (S) because 5 gross acres was a given and 4 were calculated as remaining, or buildable, in the design specification template of Table 1. This is 80% of the gross land area; and when all is devoted to open space, there is no land remaining for building and parking.
The three lines in Charts 1 and 2 represent 3 different parking requirements. They converge as the open space percentage (S) increases along the x-axis. These requirements are designated a100, a250, and a400. The number indicates the sq. ft. of building area permitted per parking space. The s350 and s400 values indicate the average sq. ft. of parking lot area provided per parking space. A higher (s) value indicates greater maneuverability and more landscape amenity within the parking lot.
The GBA lines converge as open space increases and the core area remaining for development declines. Since open space is the raw material for context, Charts 1 and 2 document the relationship between an improvement in context and a reduction in capacity . This can lead to the elimination of context, over-development, and excessive intensity.
Chart 3 has been created by placing open space options (S) on the x-axis and charting gross building area decline when the average parking area per space (s) increases from s350 to s400 and s450 sq ft. This illustrates the impact of greater parking lot area per space on gross building area capacity under various project open space alternatives. Increased average parking lot area per space is a design decision that can produce greater maneuverability and / or for parking lot landscaping. The parking requirement a200 is held constant to examine the design impact of greater parking lot area per space.
Chart 3 shows the same converging lines as Charts 1 and 2 but the spread is much narrower. This tells us that the average area provided per parking space has much less impact than the parking requirement itself. In other words, building capacity is less affected by the parking lot area provided per parking space (design) than it is by the building area permitted per parking space (regulation). Both reduce building capacity, however; and the combination is a funcamental design concern.
PARKING LOT CONTEXT and CAPACITY
Chart 4 shows that gross building area potential GBA increases 624% when the parking requirement declines from a50 to a450. This occurs when the open space variable (S) is held constant at 30%, the buildable land area is 4 acres, and the parking lot design provides an average of 350 average sq. ft. per parking space (s). Parking regulations from a50 to a450 are placed along the x-axis and the chart shows that gross building area (development capacity) increases by 624% as the parking requirement (a) declines.
The (a) and (s) values can be confusing, so let me explain with Table 3. The table shows that a parking requirement permitting 50 building sq. ft. per parking space (a50) means that 20 spaces are required per 1,000 sq. ft. of gross building area. A parking requirement permitting 400 building sq. ft. per parking space means that only 2.5 spaces are required per 1,000 building sq. ft. In other words, a higher (a) value indicates a less restrictive parking requirement. A higher (s) value, however, means that fewer parking spaces can be provided per 1000 sq. ft. of surface area. For example, if the average area per space (s) is 400, 2.5 spaces can be provided per 1000 sq. ft. of area, but if (s) is 500, only 2 spaces can be provided per 1000 sq. ft. of area.
Table 3: Explaining the (s) and (a) Values of Development Capacity Evaluation
Chart 4: The Impact of Parking Regulations on Gross Building
Chart 5 shows that gross building area potential GBA increases 100% when the average area per parking space declines from s750 to s350. This occurs when the project open space variable (S) is held constant at 30% of the buildable land area; and the parking requirement is held constant at a200, or 200 building sq. ft. permitted per parking space. Average parking area per space is placed along the x-axis in a range from s750 to s350. Gross building area increments are located along the y-axis. The chart shows that development capacity increases by 100% as the average area per parking space (s) declines.
CONTEXT, CAPACITY and INTENSITY
In most cases, the number of parking spaces provided determines the gross building area that can be constructed. In some cases, parking is not required. In this example, a parking lot design category CG1 has been given. When it is, improved parking lot context means less capacity and a smaller gross building area when all other factors remain constant.
When building context is improved with more project open space, the core area is reduced. This reduces the land available for building “footprint” and parking lot area. A smaller gross building area is the result when all other factors remain constant.
When the average parking lot area per space increases to improve parking lot context and the core area is reduced by a project open space provision, gross building area potential is affected by both. This is evident when Chart 1 and Chart 2 are compared. They both contain three lines for the parking requirement range involved (a100 to a400), but Chart 1 plans for 350 sq. ft. per parking space (s350) and Chart 2 plans for s400. The impact of project context (S) and parking lot context (s) on building capacity (GBA) can be clearly seen by comparing the gross building area produced by the same (S) and (a) value intersection in both charts.
The design implications should be clear. Project context (S) and parking context (s) combine to influence achievable shelter capacity, but maximum design eliminates context to increase capacity and intensity. We have always known this intuitively, but have not documented the design specification components and values in play. These interact to produce intensity in the cities we inhabit.
At the risk of over-simplifying the challenge before us, let me ask you to choose between Chart 1 and Chart 2. This choice determines parking lot design context and capacity. After choosing a chart, choose a project open space increment along the x-axis. This choice determines building context and capacity. The three lines above this increment represent the parking requirements a100, a250 and a400. This parking requirement choice is generally dictated by a zoning ordinance, but when you combine these decisions with the building height given, the result is a specification for shelter context and capacity, or intensity, that determines the gross building area potential per buildable acre involved.
Table 1 illustrates one of 40 forecast models and contains the simplest example of a design specification template. The values entered represent context and capacity design decisions. Many potential decisions will produce excessive intensity. Our challenge is to rule them out with research while incorporating the remainder in city design for a limited Built Domain. This limited domain must provide shelter for growing populations, but not threaten their quality of life with excessive intensity. The challenge is enormous, because the limits of a Built Domain must also be designed by science to protect its source of life – The Natural Domain.
CONCLUSION
We have not been able to efficiently forecast capacity, or understand the context and intensity represented, because we have not had an adequate and accurate research, measurement, forecasting, evaluation and decision-making system. I wrote Land Development Calculations and created Development Capacity Evaluation software1 to fill this gap.
This essay has illustrated a few capacity and context options relating to the CG1 parking lot design category. The options discussed were forecast in Table 1 using the variables noted in Table 2. This produced many data tables since any change to a bold and blue value in Table 1 produces a new forecast, but the full set of data is not included for the sake of brevity. Table 1 has been included to illustrate the parent forecast model involved.
This essay is meant to convey an underlying message. It is possible to pursue city design with architecture that protects a growing population’s physical, social, psychological and economic welfare within a limited Built Domain. It will not be possible, however, until we perceive the need and organize to achieve the goal with context research, intensity forecasting, development capacity evaluation and city design supported by political commitment, legal opinion and economic priority.
1 Hosack, Walter M., Land Development Calculations, ed. 2, and attached forecasting software, Development Capacity Evaluation, v2.0 published by The McGraw-Hill Companies, 2010.
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