Architecture, Agriculture & Planning

If you think of architecture as urban and agriculture as rural, you will have classified the two phyla of a Built Domain containing shelter, movement open space, and life support divisions. The Built Domain is habitat for a species that is capable of consuming its source of life with sprawl. Planning for a geographically limited Built Domain capable of protecting a growing population’s welfare, or quality of life, is the obvious solution; but it will require a new language and science of city design before architects and planners will be able to correlate the diversity of effort needed to lead us to symbiotic survival.

Agriculture is a victim of annexation for urban development within an expanding Built Domain. Agriculture will continue to be at risk until credible knowledge can defend rural land use allocation with revised legislation. Adequate agricultural allocation is imperative if you agree that growing populations must learn to live within a limited Built Domain that contains both urban and rural areas. In other words, urban areas for shelter will be constrained by rural areas for agriculture if they are contained within a geographically limited Built Domain.

I have focused on urban areas in the past and have failed to include line 3 in Table 1 as a consequence. It is a classification level of The Built Domain that precedes its four divisions, since these divisions are found in both rural and urban areas.

In this context, The Built Domain is not a project, district, city, region, or conurbation. It is the sum of all man-made creations, and a project, farm, or ranch is its cellular unit of growth. The allocation of land for its phyla, divisions, categories, and groups will determine our ability to shelter growing populations within a geographically limited Built Domain that protects our quality and source of life. “Quality” in this context includes an adequate food supply that has not been provided by The Natural Domain for quite some time. It can only be provided by adequate agricultural land use allocation within the Life Support Division of the Rural Phyla in The Built Domain.

In the case of the Rural Phyla, gross building area on a farm divided by total farm acres produces a shelter capacity measurement that is extremely low.

In the case of the Urban Phyla, gross building area divided by buildable project acres can be extremely high. In fact, it can be pushed to produce excessive intensity, intrusion, and dominance measurements that threaten the public welfare and quality of life. These measurements are one indication of the difference between rural and urban activity.

Gross building area divided by buildable project acres is shelter capacity. It is a function of design category choices, a category forecast model, design specification decisions within the model, and related master equation calculations. The design category master equation produces gross building area options that vary with the number of building floors under consideration.

Shelter capacity is occupied by activity and the gross building area introduced per acre determines the scope of activity that can be accommodated. The decisions that produce shelter capacity determine building mass and its impact on the surrounding population. Traditional architecture converts a building mass specification to the form, function, and appearance of its shelter capacity. Obviously, this impact is marginal in the Rural Phyla. It can be excessive in the Urban Phyla when measured in terms of capacity, intensity, intrusion, and dominance.

At the present time, we know more about the bushels of corn that can be produced per acre than the shelter capacity of an acre. We know even less about the intensity, intrusion, and dominance produced by shelter capacity options; and have not considered that the Built Domain is a second world on a single planet with rural and urban phyla that require shelter, movement, open space, and life support. I doubt that we have even considered the acres of The Natural Domain that must be preserved to protect our source of life.

Instinct, intuition, and anticipation are telling us that balance must be found between The Built and Natural Domains. The relationship between urban and rural land use allocation within a limited Built Domain is another puzzle we must solve.

I doubt that the shelter capacity of land in rural areas is considered when food production is the goal, and I doubt that food production is seriously considered in urban areas when shelter for activity is the goal. They are part of the same question, however. What is the geographic balance between the Built and Natural Domains that is required to protect a growing population’s source of life; and what is the relationship of land use allocation and urban form within The Built Domain that will protect a growing population’s quality of life? (Urban form is produced by a collection of individual land use allocation and shelter capacity decisions. They combine to produce spatial context, shelter composition, and shelter capacity, intensity, intrusion, and dominance within The Built Domain.)

Architectural design categories, forecast models, specification formats, and master equations are needed to predict shelter capacity options for land at the cellular level of allocation, conversion, and project formation within a limited Built Domain. When architects learn to use these tools they will be prepared to advance from the tactical to strategic level of shelter capacity evaluation.

Land use allocation and the composition of urban form within a limited Built Domain will reflect the progress we make toward a policy of symbiotic survival. This policy represents a design problem currently faced with an inadequate pattern language. The classification in Table 1 is a departure from this language to The Science of City Design.[1] It is a strategic language that can be used to lead an army, but this is simply a claim based on a vision at the present time. In the end, we will either adapt and survive or consume our source of life. Inability to adopt a climate change policy may hasten the process, but climate solutions will not contain a sprawling Built Domain served by movement, open space, and life support systems that threaten to consume our source of life.

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[1] Hosack, Walter M., The Science of City Design: Architectural Algorithms for City Planning and Design Leadership, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com)

Graduating from The Floor Area Ratio

The floor area ratio FAR is a zoning regulation originally created to protect public health, safety, and welfare from excessive construction in urban areas. It is a project measurement equal to gross building area divided by gross land area in square feet. A floor area ratio of 5, for instance, means that 5 acres of gross building area may be constructed on one acre of gross land area. The simplicity of the regulation is attractive, but its simplicity inadequately leads the decisions that combine to determine shelter capacity, intensity, intrusion, and dominance within projects, neighborhoods, districts, cities, and regions.  

CORRELATION

I’ll make my point with Table 1. It is a forecast model constructed to predict shelter capacity in square feet of gross building area per buildable acre of land when no parking is required. There are eight boxes in the Land Module and five boxes in the NPL Module. The values entered in these boxes may be modified at will and represent design specification decisions. These decisions are correlated to find the maximum core area available for a building floor plan in cell G32 using the architectural algorithm in cells H3-H33. The core area found in cell G32 is used by the master equation in cell A35 to predict gross building area options in cells B40-B49. These options are based on the floor quantity alternatives entered in cells A40-A49.

The shelter capacity options related to the gross building area predictions in Col. B of the Planning Forecast Panel are calculated in cells D40-D49 using the equation in cell D39. Shelter capacity is expressed in building sq. ft. per acre.

Massing ratios related to the gross building area options in Col. B of the Planning Forecast Panel are calculated in Col. E. These ratios are used by the equation in cell F39 to calculate the intensity represented by each gross building area option in Col. B of the Planning Forecast Panel.

Related intrusion measurements are calculated in Col. G. They are used to calculate dominance options in Col. J of the Planning Forecast Panel using the equation in cell H39.

Finally, the floor area ratio representing each gross building area option in Col. B of the Planning Forecast Panel is calculated in Col. J using the equation in cell J39.

The point is that the floor area ratios calculated in Col. J of the Planning Forecast Panel react to the specification decisions entered in the 23 boxes of the NPL forecast model. The floor area ratio does not lead them, and our emphasis on the ratio as a leadership tool has produced confusion, argument, conflict, and the application of legal opinion based on the precedent of mistaken assumptions. I’ll make my point with one issue.

In my opinion, the most significant topic omitted from floor area regulation is the provision of social open space for people at street level. The opposing argument has contended that social open space is a public benefit that should be purchased at public expense. The open space specification in cell F11 of Table 1 is zero percent in cell F11 to begin an evaluation of these two positions. The value represents a developer’s attempt to maximize leasable building area on a given, high-cost urban land area. If the floor area ratio limit for Table 1 is 19, the design specification predicts that a 20 story building will produce 823,776 sq. ft. of gross building area and a floor area ratio of 18.91. I could have adjusted the specification values to make the floor area ratio exactly 19 in cell J47, but left it so I could point out that predictions will change whenever one or more specification values are modified in Table 1.

Table 2 has revised the zero percent value in cell F11 of Table 1 to 32.18%. All other specification values from Table 1 are held constant in Table 2. The 32.18 percentage has been entered to make the floor area ratio in cell J49 of Table 2 identical to that in cell J47 of Table 1. A comparison shows that the same floor area ratio and gross building area can be achieved when 32.18% of open space is provided for pedestrian relief at street level, but the trade-off is an increase from 20 stories in Table 1 to 30 stories in Table 2. The additional stories represent additional cost to reach an equal gross building area. In the past an increase in height was considered a bonus in return for social open space at the pedestrian level, but the calculations in Table 2 show that ten additional floors produce gross building area parity.

It could be argued that a bonus would involve negotiations for building height in excess of ten stories to compensate for the cost of increased building height. It could just as easily be argued that the floor area ratio of 16 was a reasonable limit; that social open space has been ignored as an essential part of the effort to protect public health, safety, and welfare within urban pattern and form; and that the deficiency should not be allowed to continue. I do not intend to resolve the argument. I only wish to point that it can be debated on a more credible foundation of measurement, evaluation, prediction, and knowledge. Cooperation between public and private interest will not be secured until all parties can sit around a table discussing options with a common language that can accurately predict implications.

GROSS BLDG AREA

In most cases a developer will know the land area involved, but in some cases he or she will be exploring the buildable land area needed to serve a given gross building area objective when a floor area ratio is given. Table 3 has been constructed to answer this question. If a floor area ratio of 16, a gross building area objective of 850,000 sq. ft. and a 30% social open space objective are given in addition to the other specification values noted, the master equation in cell A36 and the secondary equations in row 40 of the Planning Forecast Panel predict that 1.212 buildable acres will produce a floor area ratio of 16.10 in cell K49 when a 25 story building is chosen in cell A49. A slight modification to the specification values entered in the NPB Module of Table 3 could reduce 16.10 to a precise floor area ratio value of 16 in cell K49. The entire specification would represent a public/private agreement.

Table 4 shows that when no open space is provided in cell F10, the same gross building objective and floor area ratio can be reached on the same land area with only 17.5 building floors. The floors needed to compensate for the 30% public open space dedication in Table 3 would be a subject for negotiation as mentioned previously.

CONCLUSION

When social open space was introduced in Tables 2 and 3, the intensity and dominance calculations in columns F and H of the Planning Forecast Panel dropped from those calculated in Tables 1 and 4. There is no research that defines acceptable levels of intensity and dominance, but the ability to measure these conditions brings us closer to the knowledge needed to protect public welfare and improve quality of life within urban areas.

At the present time, most cities are woven together with ribbons of sidewalk and torrents of traffic. In the most extreme cases, these rivers flow between canyons of artificial stone and glass governed by skyplane regulations that attempt to ensure light, air, and ventilation penetrate to street level. In other cases, the sidewalk is omitted and replaced by a parking lot that qualifies as a front yard. In both cases, it has been our method of protecting the public health, safety, and welfare with minimum standards that are now coming into question. Why is the public being protected with government standards meant to keep them alive with a minimum quality of life (welfare)? The measurements of shelter capacity, intensity, intrusion, and dominance in Tables 1-3 represent a method of calibrating “welfare” so that research can begin to produce the knowledge needed to define minimum standards for livable cities.

The physical intensity, intrusion, and dominance of shelter, movement and life support within cities is offset by social open space. The result is referred to as urban form composition. We have yet to write the first score in this composition with a language that can lead the orchestra. The result has been discordant practice as virtuosos independently tune their instruments.

The first step is to recognize that a language is needed. The second is to recognize that cities must be woven together with social open space before they can begin to protect a population’s physical, social, psychological, environmental, and economic welfare.

Tables 1-3 were included to illustrate how open space negotiations can begin when assumptions are replaced with accurate measurement and calculation. The debate concerns the need for this open space to protect the public welfare, and the public/private share of this expense. These are political questions that require additional knowledge, and I do believe that answers are needed. The Science of City Design[1] has been written to encourage you to explore these questions with a credible language. It can lead us to a geographically limited Built Domain capable of protecting our quality and source of life -- the Natural Domain.

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[1] Hosack, Walter M., The Science of City Design: Architectural Algorithms for City Planning and Design Leadership, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com)

Power, Policy and Planning

It is no longer feasible to indefinitely protect the health, safety, and welfare of growing populations while consuming their source of life. This does not mean that protection is irrelevant. It means that we are now aware that this is no longer a world without end, that annexation cannot be pursued indefinitely, and that planning policy must be revised to reflect this awareness.

Adequate shelter has always been a component of the ambiguous term “welfare”. It also affects our health and safety. In fact, it affects our physical, social, psychological, environmental, and economic quality of life. We cannot survive without it, and we cannot survive when it is allowed to sprawl without limit across the face of the planet like an oil spill.

It has now become apparent that we must shelter growing populations within a geographically limited, symbiotic Built Domain that protects their health, safety, quality, and source of life – The Natural Domain. Unfortunately, we have an inadequate vocabulary and leadership language to pursue the goal. The underlying premise of the goal is that master plans and zoning regulations were successful in separating incompatible, unsafe, and unhealthy land use activities; but have been unsuccessful in guiding annexation and the formation of shelter toward geographically limited, economically stable, and self-sufficient cities that protect a population’s quality and source of life.

I’d like to begin with an analogy that explains what I mean when I use the words power, policy, goal, strategy, objective, tactic, information, intelligence, and execution.

INTRODUCTION

Franklin Roosevelt struggled with public opinion and a congressional policy of political isolation for years. Opinion and policy were reversed when the Japanese invaded Pearl Harbor and Germany declared war. Roosevelt now had the power to respond with a declaration of war, and Congress abandoned its policy of isolation. George Marshall was given the responsibility for victory. It was a goal that included the planning and correlation of national effort. Eisenhower was given the responsibility for strategic success through correlation of planning and command from England. Field commanders were given the responsibility for correlation of armies and divisions in pursuit of plan objectives. The officer corps was given the responsibility for correlation of tactical effort to achieve an objective in the plan. Non-commissioned officers were given the responsibility for correlation of execution by individual heroes attacking or defending an objective.

The word “correlation” appears throughout the previous paragraph, and it is teamwork by another name. What isn’t mentioned is “intelligence”. It begins with imagination that raises a question. Information is required to distill an answer. Distillation reduces information to knowledge and options. Options are reduced to decisions. Decisions are correlated to produce direction. Failure to ask the right question leads to inadequate information, arbitrary evaluation, unstable decisions and uncertain leadership direction.

INFORMATION

The right question depends on an adequate vocabulary. It has been building since we began to name the drawings and parts of predator and prey in the caves of Lascaux, Font-de-Gaumme, Altamira et al. Accumulation of vocabulary eventually enabled the construction of a parallel road as science began to define the objects, anatomy, and function of all plants and animals in the Natural Domain. We now live in a Built Domain with another inadequate vocabulary. It restricts our ability to form questions and explore shelter options that do not threaten our source of life.

MEASUREMENT, EVALUATION and PREDICTION

A forecast model predicts the capacity of land to provide shelter within a limited geographic area based on the values entered in its design specification template. The model presented as Table 1 pertains to the G1 building design category. It applies to buildings served by surface parking around, but not under, the building; and contains a Land specification module and a G1 specification module. There are fifteen boxes that request value decisions in the two modules. Thirteen of these values are correlated by an algorithm to calculate the core area available for building and parking cover in cell G32. The master equation in cell A37 requires additional value entries in cells F33 and F34. When all values are entered, the equation predicts gross building area options in cells B42-B51 based on the ten floor quantity options entered in cells A42 to A51. The options change when one or more values are modified in the specification.

The language of City Design begins with the recognition that (1) There are now two worlds on a single planet -- The Built Domain and The Natural Domain; (2) There are four divisions within The Built Domain – Shelter, Movement, Open Space, and Life Support; (3) There are six primary building design categories within the Shelter Division; (4) A design specification template and master equation can predict shelter capacity and intensity options for each building design category; (5) A change in the values entered in a design specification produces a shelter capacity option for comparison and evaluation; and (6) Many specification values are undesirable.

Further explanation of Table 1 can be found in “The Density Distraction”, and “Removing the Blindfold from Economic Development”. The Science of City Design can be found in paperback and e-book versions on Amazon.com.

The values entered in Table 1 were anecdotal. We need measurement and evaluation to improve value decisions for each specification item in Table 1, and in all tables that are part of the language of city design.

POLICY

The specification values entered in Table 1 were correlated by the algorithm in Col. H and the master equation in cell A37. Comparison and evaluation of the results produced in cells A42-A51 with measurements of existing specifications and conditions can begin to define a value spectrum for city design decisions that is capable of protecting our quality of life without consuming our source of life. This is the vocabulary we need to define shelter strategy in a leadership language capable of contributing to a policy that I’ll call symbiotic survival.

THE POWER to PLAN

A second form of correlation involves relational databases. When two fields of information are identical in two separate databases, all information in both databases can be shared to reveal previously unrecognized relationships. The problem is that separate database owners are reluctant to share under any privacy protocol agreement. There is also fear of the relationships that may be discovered, since they could have real estate value implications. The result can be avoidance, denial, and deceptive opinion that inevitably lead to decline. These are problems that plague city planning and design efforts. Public opinion and special interest advocacy become substitutes for knowledge. Sharing information reduces the power of the repository. The result is opinion filling a void in knowledge, and isolated information that cannot support a strategy to achieve economic stability and symbiotic survival.

City planning does not have the legislative power to insist on sharing agreements, and rarely has the budget to implement them; because it has not justified the request with an adequate information plan and explanation of public benefit. Credibility will improve with proof that it is possible to accurately predict gross building area options for the six primary shelter design categories on the planet. Table 1 was presented as an example of the proof provided in The Science of City Design. The gross building area options presented in cells B42-B51 are examples of the power to calculate shelter capacity potential and intensity implications for a given land area under specified conditions. This information is useful in its own right, but becomes powerful when gross building area measurements and forecasts are linked to their many implications. Unfortunately, these implications can only be discovered when information in separate databases is connected. For instance, real estate tax, income tax, and population data is contained in three separate databases. Condition and location ratings are rarely collected on a consistent schedule in any database.

The objective is to predict gross building area options per acre of buildable land available. This is called shelter capacity and is occupied by activity. The acre allocations for activity have been called zones. Zones, census blocks and tracts contain shelter capacity that produces average revenue per acre. This revenue offsets the average public expense per acre to deliver a desired quality of life; but revenue can be inadequate to meet an objective since all acres do not produce the same yield. When added together and combined with all other available revenue, however; they must produce an average yield per acre equal to a city’s average expense per acre.

The goal is to measure current yield and predict future acres of activity allocation that can improve a city’s average revenue per acre. The objective is to improve a city’s quality of life without excessive intensity. The balancing act is called “city design”, and it will depend on the creation of a relational database network. It is needed to link a city’s shelter capacity, intensity, and activity plan to its social, psychological, environmental, ecologic, and economic implications. There is no option. We either learn to perform the balancing act required or continue to consume our source of life. 

A few isolated databases related to city design immediately to mind. They involve (1) Real estate, (2) Income tax and other revenue, (3) Zoning districts including land use activity and physical condition, (4) Census, and (5) Traffic. (Each zoning district would have to be numbered since the same district can be present in different geographic locations.) Each database includes extensive lists of information, and they all contain a few common fields. These common fields can be assembled to form an address database. It can be used to link all separate information under an accepted privacy protocol. For example, a database that lists a street address and its related parcel number(s), census block, census tract, and zoning district designations can be used to correlate all information compiled by any of these primary keys. This makes it possible to plan for urban form that represents far more than physical appearance.

A relational database represents connected information waiting for an idea. For instance, it can be used to link activity and capacity options for a given land area to its real estate tax implications. When shelter capacity options can be forecast in gross building area per acre, the results can be multiplied by the real estate tax potential per square foot of occupant activity to calculate potential revenue yield per acre of shelter capacity and activity.

Real estate tax potential per acre of land and square foot of building activity is intelligence that can be distilled from a real estate database and correlated with land use information in a planning database. The result is revenue per square foot of activity. It can be multiplied by predicted shelter capacity options in square feet per acre to reveal future strategic alternatives for economic improvement. Future percentages of land use activity and shelter capacity allocation can then be evaluated on a more rational foundation. The underlying message is that a city is a farm, the land is its resource; and the way it uses this land determines the yield available to serve shelter populations and deliver quality of life that protects its source of life.

The same relational database concept can be used to link land use allocation and shelter capacity per acre options to their income tax implications. When shelter capacity options can be forecast in gross building area per acre, the square foot options can be multiplied by the income tax potential per square foot of occupant activity to derive the potential revenue yield per acre. The potential yield per acre can be multiplied by the acres of activity contemplated to predict the role this percentage of land use allocation would play in meeting a city’s average expense per acre. However, a privacy protocol would have to be established to protect individual information.

Aggregations of income tax data by census block, tract, activity or zone will make it possible to evaluate the economic potential of future shelter capacity and activity allocation when database cooperation is accepted. Informed city design decisions cannot be pursued until: (1) A city understands the shelter capacity, intensity, intrusion, and dominance options available, (2) Is capable of evaluating the implications of shelter capacity and occupant activity options, and (3) Can balance the revenue potential of shelter capacity and activity options to protect its physical, social, psychological, environmental, ecologic, and economic quality of life within a limited Built Domain.

CONCLUSION

IF you believe (1) That strategic plans are needed to protect a city’s health, safety, and welfare within a symbiotic Built Domain that is limited to protect its source of life, and (2) That information must precede the formation of strategic options and the adoption of strategic plans; THEN you recognize that public opinion based on emotion, special interest logic, and wishful thinking is a weak substitute. Improved knowledge is required, but it requires better tools and better homework. The tool involves accurate shelter capacity, intensity, intrusion, and dominance prediction that I’ve referred to as the vocabulary and language of City Design. The homework involves the creation of an address database; the organization of a relational database; the measurement and evaluation of existing physical conditions; and the imagination to seek the right answers from the data correlation enabled.

A policy represents approval to pursue a goal. I suggested that a policy of symbiotic survival be adopted. One objective is to lead shelter for growing populations toward a geographically limited, symbiotic Built Domain that protects their health, safety, quality, and source of life – The Natural Domain.

A declaration of policy intent regarding our presence on the planet has not been considered. A goal has not been defined, and objectives have not been listed. The closest we’ve come is climate change, which could be solved while we continue to consume our source of life. The lack of intent and definition of a goal means that a strategic plan is missing and the intelligence required has not been pursued or correlated. If we wait to reverse our own indifference, we can easily lose before we agree on the threat; and it will not be as obvious as a raid on Pearl Harbor or a declaration of war from Germany. Recognizing a threat has required instinct, intuition, and awareness that have always stimulated imagination; but we have had proof of a threat to stimulate a response. In this case, imagination must substitute for proof to give us time to respond. This substitution represents the next level of adaptation.

Removing the Blindfold from Economic Development

When a city doesn’t understand its revenue stream in relation to its land use allocation and shelter capacity, it can’t correct deficiencies in these relationships to permanently improve its economic stability. This lack of knowledge eventually produces decline and flight from an expanding core of blight. Decline has now progressed to include portions of surrounded suburbs with inadequate land use activity and shelter capacity correlation. The solution has been sprawl that annexes land to blindly repeat old mistakes. It is slowly consuming our source of life and the blindfold must be lifted. Surrounded suburbs have no option.

LAND USE ALLOCATION

A city’s land use allocation is defined by its zoning map. Its revenue comes from the acres in each zone, the value of the acres, the gross building area available, the activity that is sheltered in the gross building area present, the revenue potential per square foot of activity sheltered, the condition of the shelter, and the specific location of the shelter. The productivity, or financial yield per acre from the zone, is a function of these fundamental factors.

SHELTER CAPACITY, INTENSITY, INTRUSION and DOMINANCE

There are six design categories that produce gross building area. Shelter capacity is gross building area divided by the project acres consumed. Gross building area multiplied by the percentage of project pavement introduced and divided by one acre, or 43,560 sq. ft., produces an “intensity” measurement. The number of building stories divided by five produces an “intrusion” coefficient. An intensity measurement multiplied by an intrusion coefficient produces a “building dominance” measurement.

Building dominance has a shelter capacity component that is occupied by activity. Every taxable activity produces revenue per gross building square foot related to the activity. These values are presently undefined, but activity revenue per square foot multiplied by the gross building area per acre devoted to the activity produces predicted revenue per acre from the activity. The total acres devoted to the activity multiplied by the anticipated revenue per acre produces a total revenue forecast for the acres allocated to the activity. Potential revenue increases as predicted shelter capacity per acre increases, but the trade-off is increased intensity and building dominance that can compromise a city’s quality of life.

PLANNING INTELLIGENCE

Most cities do not know the revenue produced by each zone, census tract, and census block within its boundaries. They cannot calculate the data because they do not know the acres consumed by an activity group, the gross building area occupied by the group,, and the revenue potential per square foot of activity. This means that it cannot calculate the revenue implications that would be produced by increasing or decreasing the square feet of shelter available per acre for a given activity. In agricultural terms, this would be considered lack of knowledge regarding “yield per acre”. It would produce arbitrary crop choices, arbitrary field area allocation, and eventual insolvency.

Most cities have arbitrary zoning plans. They have not understood the options and economic implications of land use allocation and shelter capacity in enough detail to guide their financial future and convince a skeptical public. Their emphasis has been on the separation of incompatible activities. In addition, these cities rarely know their operating, maintenance, improvement, and debt service expense per acre. This means they cannot compare their expense per acre with the average revenue produced per acre, and they cannot produce revenue data in enough detail (by census block, tract, or municipal zone) to evaluate and adjust their economic stability.

When a municipality has completed its city design homework, it will know what its blocks, tracts, and zones are yielding per acre and will be able to compare this performance to its expense per acre. The result will define the current economic balance of its land use allocation plan and form a baseline for future strategic option evaluation.

If a city does not have relevant land use allocation data, gross building area data, and activity revenue per square foot knowledge; it will not have the ability to predict gross building area revenue options per acre. It will continue to waste land and blindly produce urban form that has no relationship to the economic stability required.

Intelligence is needed to prepare strategic plan options with the potential to achieve an economic goal over time. Cities have not pursued the required intelligence and do not have the tools required to predict strategic plans and tactical options that have the potential to achieve an economic goal.

EXPLANATION

I’m going to repeat a section I wrote in “The Density Distraction in City Planning” to provide a little insight into the spectrum of gross building area options that can be produced on a given land area when specification values are modified; and the impact this has on revenue potential. My point is that if a given activity has an estimated revenue yield per square foot, gross building area options can produce a broad range of revenue choices. Keep in mind that the gross building area options presented relate to the G1 Design Category and two sets of fifteen specification values. There are many other specification value choices and five other design categories and specification lists that can be used to expand the options available. Many specification values are not desirable, however, and research is required to convert design intuition to knowledge.

Six parking design categories encompass most of the shelter provided on the planet. They are:

1)      G1: Buildings with surface parking around, but not under the building

2)      G2: Buildings with surface parking around and/or under the building

3)      S1: Buildings with structure parking adjacent to the building on the same parcel

4)      S2: Buildings with underground parking

5)      S3: Buildings with structure parking at grade under the building

6)      NP: Buildings with no parking required

The parking structure options may have supplemental surface parking, but when a parking garage is present, the building is classified by the garage configuration present. These building categories may be occupied by any activity group that complies with local building and zoning requirements.

The point is that shelter classification begins with the parking design category involved, and each category has gross building area limitations defined by design specification decisions. These decisions limit the scope of land use activity and revenue potential that can be introduced.

Table 1 presents a set of optional decisions for the G1 Design Category. They are represented by the specification values entered in the boxes of its Land and G1 Modules. There are fifteen specification boxes and each value represents a design decision that can be adjusted to explore gross building area alternatives. The equations in Col. H of Table 1 convert specification decisions to implications in Col. G. The objective of the algorithm is to distill the core buildable land area available for a building and surface parking plan in cell F32. 

The master equation in cell A37 correlates the core area found in cell F32 with the parking decisions entered in cells F33 and F34 and the floor quantity options entered in cells A42-A51. It predicts gross building area alternatives in cells B42-B51 based on these floor quantity options. The remainder of the Planning Forecast Panel predicts additional implications related to the gross building area options calculated in Col. B using the secondary equations on line 41. Shelter capacity options corresponding to the gross building area options forecast in Col. B are located in Col. F. The entire panel illustrates a few of the many implications that can be forecast as a function of gross building area predictions. Revenue, expense, construction cost, return on investment, population, traffic generation and so on are a few that are not shown.

Table 1 illustrates the many specification decisions required to calculate shelter options for the G1 Design Category. A change to one or more values entered in the boxes of Table 1 would produce a new forecast in Col. B of the Planning Forecast Panel, and hundreds of options could be predicted in less time than it would take to produce one sketch.

The unpaved open space percentage specification in cell F11 of Table 1, and the impervious cover limit calculated in cell F12, represents one of the decision / implication relationships that play a significant role in the calculation of gross building area options. An unpaved open space decision, however, is only one box among many design specifications decisions that combine to determine shelter capacity options.

SEVERAL SHELTER DESIGN PRINCIPLES

Table 1 is based on 40% unpaved open space in the buildable land area. When the gross building area values in Col. B of the Table 1 Planning Forecast Panel are mapped in Figure 1, the results can be expressed in the following terms:

The rate of increase in gross building area declines at an accelerating rate as the number of building floors increase in the G1 Design Category.

Building cover declines more rapidly than gross building area increases because the gross building area permitted per parking space (a) in Table 1 is less than the parking lot surface area planned per parking space (s).

Figure 1 illustrates the dramatically decreasing rate of increase in gross building area as building height increases. Gross building area increases from 38,577 sq. ft. to 59,000 sq. ft., but it barely increases above the five story mark of 55,722 sq. ft. This occurs because gross building area does not increase as rapidly as surface parking area when (a) is less than (s). Expanding parking area for additional spaces is required to justify increased building area, but this eventually reduces the land remaining for building cover to unrealistic levels.

Figure 2 is based on (a) being greater than (s) and 15% unpaved open space being entered in Table 1. Figure 2 shows that gross building area still increases at a decreasing rate, but the results produced are dramatically different because of the specification value changes. Gross building area increases from 85,630 sq. ft. to 186,152 square feet, but gross building area slowly increases above the 5 story mark of 164,673 sq. ft. Parking cover consumes the same amount of land per space, but gross building area per parking space grows more than parking lot area per space. This scenario explains why the gross building area arc increases more rapidly than the building cover arc declines in Figure 2.

When the five story gross building area potential in Tables 1 and 2 is subtracted from the one story gross building area potential predicted, the results expose another G1 design principle. In the case of Figure 1, the total gain for 1-5 stories is 17,145 sq. ft. The total gain for 5-10 stories is 3,278 sq. ft. In the case of Figure 2, the total gain for 1-5 stories is 79,043 sq. ft. The total gain for 5-10 stories is 21,749 sq. ft. This observation produces the following principle.

The most rapid increase in G1 gross building area occurs within a 1-5 story range.

The actual gain from 1-5 stories is a function of all design specification decisions entered in Table 1. Above 5 stories, the gross building area gain per additional floor becomes increasingly less cost-effective.

Figure 2 produces much greater gross building area potential, but is the open space and parking reduction desirable? I won’t attempt to answer the question. I’m simply pointing out an issue that can be accurately measured and evaluated with comparative studies using the language of City Design. In fact, the complete language of City Design can be used to measure existing conditions, evaluate future potential, and accurately define leadership decisions with confidence based on objective measurement and comparative evaluation.

Figures 1 and 2 explain why the gross building area permitted per parking space (a) and the unpaved open space percentage proposed per project (OSAU) are two of the most common points of public and private disagreement. Greater open space and parking requirements reduce potential gross building area, private return on investment, and public revenue per acre, but at what point do the reductions produce excessive intensity in the neighborhood? This cannot be answered without a comprehensive method of measuring and evaluating existing conditions. It cannot be improved without an accurate method of converting measurement and evaluation to accurate, comprehensive, and correlated shelter capacity and revenue potential options.

The G1 design principle behind this section of the essay can be stated in a single sentence.

Every additional surface parking space justifies increased gross building area; but reduces the core land area available for building cover, until the core area remaining becomes too small to accommodate a realistic floor plan.

Figures 1 and 2 demonstrate that gross building area options can be forecast in mathematical terms. When a gross building area option is multiplied by activity revenue potential per square foot and divided by the acres consumed, the result is a yield per acre that can be compared to city’s average expense per acre. When total yield is divided by total acres and compared to a city’s average expense per acre, the results must balance or budget cuts will be required. These cut options often represent unpleasant reductions in quality of life. The objective is to plan shelter capacity, intensity, and activity allocation in a city to establish a stable economy that is capable of avoiding budget cuts. This has the potential to improve quality of life within a limited Built Domain that protects its source of life.

BUDGET CUTS

There will always be those who disagree with the program of services offered by a city and the budget emphasis placed on each. This will lead them to advocate program elimination or budget cuts at the very least. The debate will continue until a community votes on the program of services desired. If a program is adopted, the minimum cost to deliver the service can be debated, but elimination will be removed from the discussion.

We all know that it is possible to pay too little and receive inadequate products and services. The second public debate will surround the minimum cost to deliver acceptable products and services. The bottom line is that a city must pay for a desired program. Let’s dispense with the concept of getting something for nothing. Define what “something” is and get over the concept of getting it for nothing. Focus on the minimum cost to receive an acceptable level of service for an adopted program item. Then a city must develop land use allocation and shelter capacity options that are equal to the current and future expense implied.

A public vote can give a struggling government the program direction it needs to define the average revenue per acre required to afford the program. The government can then focus on creating city design options for public review that have the potential to deliver this revenue.

CONCLUSION

I have written The Science of City Design to explain shelter design categories, activity groups, design specifications, architectural algorithms, master equations, and planning forecast potential. The goal is to introduce a vocabulary and language of city design that can consistently improve the planning results needed to protect a population’s quality of life within a limited Built Domain that protects its source of life – The Natural Domain.

The Density Distraction in City Planning

Density is a social statistic. It cannot lead the formation of shelter for human activity within urban areas. It has caused confusion, contradiction, disagreement, and conflict within and between those in the public and private sectors; but it is now possible to replace the statistic with a language that can accurately measure the past, evaluate the present, predict the future, and define decisions in terms that have the accuracy needed for leadership direction. In order to make my point, I need to introduce the language, illustrate its leadership potential, and compare it to the performance of density statistics.

INTRODUCTION TO THE LANGUAGE

Gross building area is a fully enclosed square foot area that can be occupied by any activity. Shelter capacity is the gross building area that can be constructed per buildable acre available, and there are many options. The amount of gross building area provided per acre, in addition to the supporting pavement introduced, is referred to as a level of “intensity”. Intensity is moderated by the amount of unpaved project open space that remains. At one end of the spectrum is a small building on thousands of ranch acres. At the other is a high-rise building on a fraction of an acre. In both cases, the square feet of shelter and pavement constructed consume land that is a natural source of life.

Activity is referred to as “land use”. The relationship of shelter capacity and activity to geographic location affects economic stability and public acceptance. In other words, shelter capacity, condition, and location produce levels of physical intensity, social activity, and economic contribution that affect our quality of life within any urban area.

The Movement, Open Space, and Life Support Divisions of our Built Domain consume natural land to serve a Shelter Division that adds to the consumption and is sprawling without restraint. The square feet of building area and pavement introduced per acre determines the population and activity that can be served, as well as the physical intensity introduced. The social open space that remains contributes to the external quality of life provided. In other words, the physical, social, and economic characteristics of intensity not only affect the health, safety, and welfare of a population within The Built Domain; but the survival of its source of life beyond. We must begin to understand these relationships.

Six building design categories encompass most of the shelter provided on the planet. They are:

1)      G1: Buildings with surface parking around, but not under the building

2)      G2: Buildings with surface parking around and/or under the building

3)      S1: Buildings with structure parking adjacent to the building on the same parcel

4)      S2: Buildings with underground parking

5)      S3: Buildings with structure parking at grade under the building

6)      NP: Buildings with no parking required

The parking structure options may have supplemental surface parking, but when a parking garage is present, the building is classified by the garage configuration present. These building categories may be occupied by any activity group that complies with local building and zoning requirements.

The point is that shelter classification begins with the building design category involved, and each category has gross building area limitations defined by design specification decisions. These decisions limit the scope of land use activity and revenue potential that can be introduced.

LEADERSHIP POTENTIAL

Table 1 presents a set of optional decisions for the G1 Design Category. They are represented by the specification values entered in the boxes of its Land and G1 Modules. There are fifteen specification boxes and each value represents a design decision that can be adjusted to explore shelter capacity alternatives. The equations in Col. H of Table 1 convert specification decisions to implications in Col. G. The objective of the algorithm is to distill the core buildable land area available in cell F32.

The master equation in cell A37 correlates the core area found in cell F32 with the parking decisions entered in cells F33 and F34 and the floor quantity options entered in cells A42-A51. It predicts gross building area alternatives in cells B42-B51 based on these floor quantity options. The remainder of the Planning Forecast Panel predicts additional implications related to the gross building area options in Col. B using the secondary equations on line 41. Shelter capacity options corresponding to the gross building area options forecast in Col. B are listed in Col. F. The entire panel illustrates a few of the many implications that can be forecast as a function of gross building area predictions. Revenue, expense, construction cost, return on investment, population, and traffic generation are a few that are not shown.

Table 1 illustrates the many specification decisions required to calculate shelter options for the G1 Design Category. A change to one or more values entered in the boxes of Table 1 would produce a new forecast in Col. B of the Planning Forecast Panel, and hundreds of options could be predicted in less time than it would take to produce one sketch.

The unpaved open space percentage specification in cell F11 of Table 1, and the impervious cover limit calculated in cell F12, represents one of the decision / implication relationships that play a significant role in the calculation of shelter capacity options. An unpaved open space decision, however, is only one of many design decisions that combine to determine shelter capacity options.

Open Space

It’s easy to overlook open space because its value to our quality of life is currently a function of subjective opinion, and this opinion can reduce private return on investment. It is an inevitable conflict, but one open space decision has already been made that is unrecognized by most.

Unpaved open space protects storm sewer capacity from excessive runoff. Storm water runoff is produced by impervious cover and re-directed by storm sewer capacity. Capacity is expressed as the percentage of impervious cover that can be accommodated by a given pipe size. Subtracting this percentage from 100 yields the amount of unpaved open space expected, unless more intricate civil engineering solutions are introduced. A greater pipe size can accommodate a greater percentage of impervious cover, but the pipe cost increases as well. A developer often attempts to minimize cost by minimizing pipe size. This reduces the impervious cover percentage that can be accommodated, but the limit is often over-looked by decision-makers for any number of reasons. If an impervious cover limit is exceeded by many along a branch storm sewer line, unpaved open space declines and flooding is an inevitable consequence, unless detention solutions are introduced. Flooding can easily occur when a community does not know the impervious cover capacity of each branch line in its storm sewer system and approves building and pavement additions over years based on the assumption that growth is good. Unfortunately, the unpaved open space percentage required to protect storm sewer capacity may not be adequate to protect the neighborhood’s quality of life.

Shelter Capacity and Intensity

The gross building area options forecast in Col. B of the Planning Forecast Panel of Table 1 were used to produce the shelter capacity options in Col. F and the intensity options in Col. G. These intensity levels are like the first blood pressure readings. I can only hope that continued measurement and evaluation will produce intensity knowledge and parameters that can lead to an improved quality of life.

Intensity options are produced by values entered in a design category specification template. A leadership decision is taken by defining the design category and specification values adopted for a given location.

Design category choices and specification decisions have gross building area implications. Gross building area divided by buildable land area is shelter capacity. The ability to accurately define gross building area options with a design category master equation makes it possible to predict many implications that are functions of the square foot options predicted.

Urban Form

Building arrangements are often referred to as massing compositions. A collection of compositions is referred to as urban form. Ideally, a plan for urban form allocates the Shelter, Movement, Open Space, and Life Support Divisions of The Built Domain to serve growing populations within geographic limits that protect their quality and source of life – The Natural Domain.

Master equations make it possible to measure, evaluate, diagnose, and prescribe urban form one project at a time. When a Built Domain is geographically limited, the quality of life within these limits will be a function of the design categories and specification values chosen to create urban form. Our quality of life is affected because we must live within and among the buildings, pavement, spaces, and movement systems we create.

Several Shelter Design Principles

Table 1 is based on 40% unpaved open space in the buildable land area. When the gross building area values in Col. B of the Table 1 Planning Forecast Panel are mapped in Figure 1, the results can be expressed in the following terms:

The rate of increase in gross building area declines at an accelerating rate as the number of building floors increase in the G1 Design Category.

Building cover declines more rapidly than gross building area increases because the gross building area permitted per parking space (a) in Table 1 is less than the parking lot surface area planned per parking space (s).

Figure 1 illustrates the dramatically decreasing rate of increase in gross building area as building height increases. Gross building area increases from 38,577 sq. ft. to 59,000 sq. ft., but it barely increases above the five story mark of 55,722 sq. ft. This occurs because gross building area does not increase as rapidly as surface parking area when (a) is less than (s). Expanding parking area for additional spaces is required to justify increased building area, but this eventually reduces the land remaining for building cover to unrealistic levels.

Figure 2 is based on (a) being greater than (s) and 15% unpaved open space being entered in Table 1. Figure 2 shows that gross building area still increases at a decreasing rate, but the results produced are dramatically different because of the specification value changes. Gross building area increases from 85,630 sq. ft. to 186,152 square feet, but gross building area slowly increases above the 5 story mark of 164,673 sq. ft. Parking cover consumes the same amount of land per space, but gross building area per parking space grows more than parking lot area per space. This scenario explains why the gross building area arc increases more rapidly than the building cover arc declines in Figure 2.

When the five story gross building area potential in Tables 1 and 2 is subtracted from the one story gross building area potential predicted, the results expose another design principle. In the case of Figure 1, the total gain for 1-5 stories is 17,145 sq. ft. The total gain for 5-10 stories is 3,278 sq. ft. In the case of Figure 2, the total gain for 1-5 stories is 79,043 sq. ft. The total gain for 5-10 stories is 21,749 sq. ft. This observation produces the following principle.

The most rapid increase in G1 gross building area occurs within a 1-5 story range.

The actual gain from 1-5 stories is a function of all design specification decisions entered in Table 1. Above 5 stories, the gross building area gain per additional floor becomes increasingly less cost-effective.

Figure 2 produces much greater gross building area potential, but is the open space and parking reduction desirable? I won’t attempt to answer the question. I’m simply pointing out an issue that can be accurately measured and evaluated with comparative studies using the language of City Design. In fact, the complete language of City Design can be used to measure existing conditions, evaluate future potential, and accurately define leadership decisions with confidence based on objective measurement and comparative evaluation.

Figures 1 and 2 explain why the gross building area permitted per parking space (a) and the unpaved open space percentage proposed per project (OSAU) are two of the most common points of public and private disagreement. Greater open space and parking requirements reduce potential gross building area and private return on investment, but at what point do the reductions produce excessive intensity in the neighborhood? This cannot be answered without a comprehensive method of measuring and evaluating existing conditions. It cannot be improved without an accurate method of converting measurement and evaluation to accurate, comprehensive, and correlated leadership expression. A new language of city design is needed. I’ll get to this in the final section of this essay.

The G1 design principle behind this section of the essay can be stated in a single sentence.

Every additional surface parking space justifies increased gross building area; but reduces the core land area available for building cover, until the core area remaining becomes too small to accommodate a realistic floor plan.

Figures 1 and 2 demonstrate that planning and design issues can be expressed in mathematical terms. This has the power to persuade in a political environment of conflicting opinion. It also improves our ability to collaborate with the science of others; since the land our planet can donate to shelter, and the shelter capacity of this land, is becoming an issue of survival. The answers we find will be reflected by the context, composition, and function of urban form. The appearance of these solutions will symbolize our progress toward the symbiotic correlation of Shelter, Movement, Open Space, and Life Support within a geographically limited Built Domain that protects our quality and source of life – The Natural Domain.

COMPARISON TO DENSITY

Density is a statistic that indicates the number of residential dwelling units provided or permitted per acre of land occupied. The gross building area potential of the land given the combined effect of all zoning regulations is ignored because accurate calculation has been elusive, but feasibility is a function of the relationship between dwelling unit quantity, unit area, and gross building area potential. A density statistic cannot provide the correlation required for adequate leadership.

Table 1 has illustrated the correlated design specification items, topics, and master equation that produce gross building area options per buildable acre for the G1 Design Category. A feasible density is one that multiplies dwelling unit area by quantity to fit within the gross building area potential of a given land area. Density does not lead to the gross building area potential of land. It is limited by the specification decisions that determine gross building area, and unachievable density regulations or goals simply introduce confusion and frustration.

Density is oblivious to the inter-active design specification decisions in Table 1, but they determine gross building area potential and intensity implications for any given land area. It is also oblivious to the various dwelling unit area decisions that can increase or decrease density within gross building area potential. The conflict between ambiguous density regulation, uncorrelated zoning regulation, and the gross building area potential of land is often inevitable.

CITY DESIGN

The creation of urban form begins with an ability to predict gross building area capacity, intensity, and activity options for every land area and location within the geographic area defined.

Our current inability to correlate the realistic gross building area potential of land with the activity permitted and quality of life desired produces confusion, conflict, and suspicion that can only be resolved with opinion and compromise. This often produces arbitrary decisions and unsatisfactory results that assemble over time.

The gross building area options produced by correlating the design specification decisions in Table 1 could not have been produced by an independent density statistic. The observations produced by charting the Table 1 options in Figures 1 and 2 would remain unknown or intuitive at best. There are just too may design decisions involved that affect and precede density calculation and can’t be led by a density statistic. It is not a credible minimum design standard capable of consistently leading shelter capacity toward urban form capable of increasing capacity and improving our quality of life. It is a rear view mirror, not a heads-up display of options and opportunities.

I have written The Science of City Design to explain design categories, activity groups, design specifications, architectural algorithms, master equations, and planning forecast panels. These topics introduce a vocabulary and language of city design that can consistently improve planning results by correlating the decisions required to shelter growing populations within a limited Built Domain. The goal is to protect this population’s quality and source of life.

For those interested in pursuing the study of city design, urban form, and its physical, social, psychological, environmental, ecologic, and economic implications; The Science of City Design can be found at Amazon.com in e-book and paperback versions.