Arguing for a Science of City Design

These are slides from a presentation that argues for new tools to empower our approach to the growth of cities and the shelter they serve.

THE PROBLEM

Growing populations are currently building shelter for a wide range of activities in a pathogenic pattern of sprawl that is slowly consuming agriculture and our source of life – the land of The Natural Domain.  This continues because we have not been able to accurately predict the development capacity of land given the current disorganized nature of shelter design decisions and regulation.

THE OBJECTIVE

The challenge is to predict our capacity to shelter human activity within limited geographic areas defined to protect our quality and source of life – The Natural Domain.

THE APPROACH

(1)    Comprehensively list the shelter design categories available and their related specification topics;

(2)    Mathematically correlate specification topic relationships; and

(3)    Predict the gross building area potential of land based on the design category chosen and the values assigned to its specification topics.

THE DESIGN CATEGORIES

Six primary design categories may be occupied by any activity group. A category forecast model includes two specification modules and a forecast panel. An activity module is added to the category specification when it is tailored to a specific activity group.

THE FORECAST MODELS

A forecast model is written to predict answers to a question based on the specification values entered. A change to one or more values produces optional answers for comparison, evaluation, and direction.

THE QUESTIONS

1)      How much gross building area can be constructed on a given land area?

2)      How much buildable land area is needed to accommodate a given gross building area?

THE RESOURCES
Table 1 is a current list of forecast models. The Design Category Group can be occupied by any activity. The Activity Group addresses residential activity that occupies the G1 Category of buildings.

Table 2 is a sample of a completed G1 Forecast Model. It contains a Land Specification Module, a G1 Specification Module, and a Planning Forecast Panel. The values entered in the boxes of the specification modules represent design decisions that can be modified for comparison and evaluation. The implications of a mathematically correlated set of design specification decisions are presented in the Planning Forecast Panel.

Column A in the panel is a specification column of optional building heights. Columns B-E forecast the design implications of a full set of optional specification decisions. Column F forecasts shelter capacity per acre of land consumed. It is a key measurement of the land use efficiency being proposed by the design specification. When a city has a limited geographic area, the efficient allocation of shelter capacity and occupant activity determines the total revenue available to support operations, maintenance, improvement, debt service, and quality of life.

Columns G-J calculate the intensity, intrusion, and dominance implied by the shelter specification. They are quality of life measurements that will build knowledge with continued use.

THE IMPLICATIONS

1)      Gross building area predictions are relevant to real estate evaluation and private enterprise economics.

2)      The allocation of shelter capacity and activity per acre determines public revenue potential and municipal economic stability.

3)      Evaluation of the intensity, intrusion, and dominance produced by a design category specification will produce quality of life knowledge and improvement.

CONCLUSION

The solution to a problem begins with a language that can express concepts, define options, measure implications, evaluate results, and build knowledge. The argument for a science of city design[1] is an argument for a language that can begin the search for shelter solutions to the problem of symbiotic survival. Shelter solutions, however, are only one of the many essential answers required.

---

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

Surface Parking Limits on the Shelter Capacity of Land

A surface parking lot must expand to increase parking space quantity. An increased quantity increases permitted gross building area (GBA), but decreases the land remaining for building footprint (BCA). The conflict is resolved by either increasing the number of building floors associated with the reduced building footprint, or adjusting other areas of the site plan. This rather simple relationship has caused endless debate because surface parking requirements affect the shelter capacity of land, and their credibility is often challenged by the history of a specific activity at a specific location. This essay will ignore activity and drill down to understand the specification topics, values, and relationships that determine parking lot area and reduce shelter capacity for any activity on any land area.

Basics

A parking requirement specifies the square feet of gross building area (GBA) permitted per parking space provided. For instance, a parking requirement of 250 means that 250 sq. ft. of gross building area may be constructed for every parking space introduced.

Figure 1 plots the increase in gross building area (GBA) potential for a 5 story building as the parking requirement declines. (Keep in mind that a parking requirement of 600 is less restrictive than a requirement of 250 because more GBA is permitted per parking space provided.) The x-axis increments represent this decline in GBA restriction. The increase from 5,912 sq. ft. to 41,382 sq. ft. of GBA shows the dramatic impact of parking requirements.

Figure 2 plots the increase in GBA potential per floor of building height as increased amounts of GBA per parking space are permitted along the x-axis. The increase from 4,966 sq. ft. to 41,382 sq. ft. shows the combined impact of parking requirements and building height options.

The increases plotted in Figures 1 and 2 can be found in Table 1. They serve to explain why parking requirements and building height options are hotly debated across the table in every planning office of the nation. Frustration prevails because the accurate prediction options and implications is not a common practice.

Line (cd) in Figure 2 shows that GBA increases decline with each floor of increased building height; and that height increases above 2 stories produce declining increases in GBA. This make these height options increasingly less cost effective when all other design specification values remain constant.

Line (ab) shows that 15,000 sq. ft. of GBA can be achieved with a 1 story building when 1 parking space is required per 600 sq. ft. of GBA, and with a 5 story building when 1 parking space is required for every 275 sq. ft. of GBA. If you look at 20,000 sq. ft. of GBA on the y-axis in Figure 2, you’ll see that it cannot be achieved with a 1 story building; given the design specification values involved. Design specifications will be explained in the section to follow.

The point is that parking requirements and building height options play a significant role in determining the shelter capacity of core land area; that shelter capacity can be occupied by any activity; and that one design category equation makes it possible to calculate its GBA potential on any core land area. (The G1 Design Category is being used for this example and applies when surface parking around, but not under the building, is chosen as a parking design solution.)

Design Specifications and Core Area

The design specification decisions in Table 2 are represented by the values entered in the boxes of Column F. Calculating core area in cell F32 is the objective, since this is the land remaining for building footprint and surface parking after percentage estimates for all other site plan areas have been subtracted.

Cell F34 in Table 2 specifies the parking requirement (a) under study, and cell F33 specifies the total surface parking lot area per parking space (s) estimated. The master equation in Table 2 uses the (a) and (s) values entered; the core area calculated (CORE); and the building height options entered in cells A42-A51 to calculate the GBA options in cells B42-B51. The GBA options from cell B7 to L11 in Table 1 were found by modifying the (a) value entered in cell F34 of Table 2. These (a) value alternatives were noted in cells B6-L6 of Table 1.

The value (a) is only one of 25 specification boxes in Table 2, and a change to one or more of the values entered will produce a different set of GBA options in Col. B. All values were held constant as the (a) value was modified to produce the GBA options from cell B7 to L11 in Table 1.

The Specification Value (s)

The value (a) entered in cell F34 of Table 2 is a straight-forward parking requirement that restricts shelter capacity. The accuracy of all parking requirements is a matter of continuing debate. It results from their effect on GBA potential and the lack of research available to justify the values involved. The only certainty at this point in time is that parking is needed for the transition to sheltered activity, and can be provided in either remote or adjacent locations.

The value (s) is equal to total parking area, excluding loading area, divided by the number of parking spaces provided. The value is easy to find when a site plan can be measured, but difficult to predict. The 18 specification decisions that combine to create the value (s) are shown in the boxes of Table 3. Each of these decisions is a variable that can be modified to alter the results calculated in cells C15-K20. The objective is to find the values in column K. The calculated result in cell K15 shows that the (s) value entered in cell F33 of Table 2 is based on a 90 degree parking layout decision.

The design specification values (l), (a), and (e) in Cells J3-J5 of Table 3 are shown in Figure 3 as dimensions of a parking lot bay. (A “bay” includes a circulation aisle and parking spaces on both sides of the parking aisle.) A parking lot may also contain parking stalls, service stalls, and circulation aisles in addition to those found in parking bays. It may also contain landscape islands to relieve the sea of asphalt. The design specification values (C%) and (L%) in cells J7-J8 of Table 3 are introduced to estimate their presence in this example. The values chosen show that a utilitarian parking lot is planned with little amenity. Parking space angle and circulation aisle options are entered in cells A15-B20 of Table 3, and each value affects the gross and net parking lot areas predicted in cells H15-J20. The number of parking spaces in one row of a bay must be estimated in Cell J6 of Table 3 to forecast parking lot area. The 10 spaces entered in Table 3 produce an average of 406 sq. ft. per space in cell K15. Thirty spaces produce an average of 389 sq. ft. and 5 spaces produce an average of 432 sq. ft. when all other specification values remain constant. Understanding this range of areas can be helpful when choosing the value to enter in cell F33 of Table 2.

The objective is to forecast average parking lot area per space in cells K15-K20 of the Planning Forecast Panel in Table 3. The value in cell K15 has been chosen for entry in cell F33 of Table 2 because it is related to a 90 degree parking angle. The area options in column K are calculated from the values entered in Columns A and B of the Planning Forecast Panel and the values entered in Cells J3-J8. A change to one or more of these values will produce a new forecast.

The point of this exercise has been to explain the scope of design specification decisions that must be correlated to produce the value entered in cell F33 of Table 2. The decisions entered in Table 3 could use refinement, but the underlying purpose is to explain the many related decisions that stand behind the production of a single parking estimate (s), and the major role this value plays in the forecast of GBA options in Table 2.

Surface Parking Coefficients

I’ve created Table 4 to illustrate the impact of (s)-value options on gross building area potential (GBA). The results are based on the surface parking equation GBA=(af/(a+fs))*CORE. When CORE is equal to 1, gross building area potential is represented by the coefficient in this equation. It becomes a function of optional (a), (f), and (s) value decisions, and expresses GBA potential as a multiple of the core area available.

Table 4 places optional (s)-values in boxes above six matrices labeled 350-800. Each matrix locates (f) values on the y-axis and (a) values on the x-axis. A larger (s)-value indicates that more parking lot area is provided per parking space. This increased average area may result from increased landscaping; more generous parking space and circulations areas, or both.

Cell L18 is part of matrix 400 in Table 4. It shows that a 5 story building with a parking requirement (a) equal to 1,000 sq. ft. of GBA per parking space can yield a total GBA equal to 1.667 times the core area available. This is possible when the parking lot contains an average of 400 sq. ft. per space (s). (The maximum building footprint area would be equal to 1.667 / 5 times the core area.) In contrast, cell B14 shows that a one story building and a parking requirement of 100 sq. ft. of GBA per parking space will yield total GBA equal to 0.200 times the core area available when (s) is equal to 400.

In matrix 800, if 100 sq. ft. of GBA (a) is permitted per average parking space (s) equal to 800 sq. ft.; the parking lot will grow much more rapidly that gross building area. This ratio limits GBA potential to 0.111 times the core area as shown in cell B50 of Table 4. If 1,000 sq. ft. of GBA is permitted per average parking space of 800 sq. ft., cell L54 shows that the ratio produces GBA equal to 1.000 times the core area for a 5 story building. If you compare the results in matrix 800 to those in matrix 400, the differences in GBA potential illustrate the impact of the (s) and (a) decisions represented. The significance of the values entered in cell F33 and F34 of Table 2 may now be more apparent.

Line 50 in Table 4 illustrates a typical trade-off decision related to the G1 surface parking design category that is not immediately apparent. In the G1 category, gross building area potential declines when average parking lot area per space (s) increases and all other design specification decisions remain constant. In many cases, more parking lot area per space indicates greater landscape provisions. These provisions soften the impact of asphalt pavement, but fewer parking spaces reduce GBA potential in the G1 Design Category. This places landscape provisions at a distinct disadvantage. It has been exacerbated because comparative options and implications have been limited by the time required to manually prepare alternate site plans. Table 2 was introduced to explain how GBA options can be forecast, compared, and evaluated by changing one or more values in its design specification template. The (s) and (a) parking values represented two of these design decisions. Tables 3 and 4 have explained the implications of choice among these values. The mathematical format involved will not eliminate argument and debate over GBA implications when landscape provisions are considered, but it can eliminate confusion and distrust around a table that has had to depend on intuition, assumption, and opinion for evaluation and conclusion. In fact, confusion surrounds every specification value entered in Table 2 at this time. This has severely compromised the leadership potential of all public and private sectors responsible for the provision of shelter for the activities of growing populations within a geographically limited Built Domain that protects their quality and source of life – The Natural Domain.

Strategic Architecture

Architecture collects and correlates isolated information to reconcile complexity and confusion with logic and talent. The form, function, and appearance of a building symbolize this complicated process. The increasing focus on fine art emphasizes appearance, but does not transfer knowledge for improvement by future generations.

This is not an attempt to abandon fine art. It is an attempt to place it in the context of a creative process that can be taught. Talent will always die with the owner. Knowledge can be inherited, and improvement will enhance the contribution of exceptional talent and its many peers.

An architect is not an engineer, although it could be argued that he/she engages in systems engineering. This is a fancy term for creation of a logical strategy that correlates the contributions from many related technical disciplines. The result is project completion, but this is no longer the goal. Project completion represents the cellular formation of an artificial environment across the face of a planet that is no longer a world without end.

Architecture has been occupied with schematic design for shelter at the cellular level of The Built Domain, and this has contributed to an unlimited, pathogenic anatomy we call sprawl. If you believe that we must learn to shelter the activities of growing populations within a limited Built Domain that protects their quality and source of life – The Natural Domain, then you may agree that architecture has an expanded role to play. It involves strategic planning for schematic design within a limited Built Domain, and this has the potential to protect the public interest. Strategic architecture involves the science of city design,[1] and it can be taught, improved, and inherited. The form, function, and appearance of schematic design that rests on its foundation will begin to symbolize a new Symbiotic Period of human awareness.

---

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

Abdicating Surface Parking Requirements

Parking requirements have been considered a function of occupant activity since the introduction of zoning regulations. The concept has maintained that more intense activity requires more parking spaces. For instance, 1 parking space might justify 50 gross sq. ft. of restaurant activity or 200 gross sq. ft. of office activity. The concept, however, has produced two intractable problems: (1) The requirements are averages that are not tailored to the needs of a specific enterprise, and (2) The requirements do not solve pre-existing conditions that flood neighboring areas with incompatible overflow parking demand.

In both cases, land is the underlying issue. In new construction, a parking requirement can reduce the land available for a building footprint and the gross building area that can be constructed. In existing areas, there may be no land available to provide adequate parking. There will never be a perfect parking solution given the two problems noted, but the lack of perfection is not an excuse to ignore a fundamental problem as proposed in the following quotation:

Off-street parking should be a business decision, not a government decision.

Business is not motivated by the public interest, and I will argue that adequate parking for successive owners has significant public implications. It may help to begin by explaining the place of parking in a site plan and the design specification values that combine to produce its need for land.

New Construction

All land areas contain various percentages of four ingredients: (1) Unbuildable land area, (2) Buildable land area, (3) Common, or shared, buildable land area, and (4) Shelter land area. When common areas are not provided, buildable land area is equal to shelter land area.

Shelter land area contains various percentages of five ingredients, and one or more of these percentages may be zero: (1) Unpaved open space, (2) Service pavement, (3) Social pavement, (4) Parking pavement, and (5) Building footprint. When shelter is the issue, the first three layers are subtracted from the shelter area remaining to find the core area available for parking pavement and building footprint. The ratio between parking and footprint area combines with floor quantity to determine gross building area potential.

In other words, parking quantity determines the gross building area that can be constructed. Each additional parking space permits additional gross building area, but reduces the surface land area remaining for the building footprint. The building increases in height with a smaller footprint to accommodate the increased area permitted; but the relationship between parking and footprint stops producing meaningful increases in gross building area above five stories, when all other design specification values remain constant.

The shelter capacity of land is the gross building area that can be constructed per shelter acre. It is a function of design specification decisions that are correlated by an architectural algorithm for use in a master equation. The equation pertains to the design category under consideration and predicts gross building area options based on four variables:

1) The gross building area permitted per parking space (a), also known as a parking requirement.

2) The number of building floors under consideration (f).

3) The estimated gross parking lot area per parking space, (s).

4) The core land area available for parking lot and building footprint area after estimates for all other site plan areas have been subtracted (CORE).

The Design Specification Template in Table 1 pertains to the G1 Surface Parking Design Category and illustrates the calculation of core area in cell F32. The parking requirement (a) is entered in cell F34. An estimate of gross parking lot area per space (s) is entered in cell F33. Building floor quantity options (f) are noted in cells A42-A51. The master equation in cell A37 predicts gross building area options related to building height options in cells B52-B51. This is the point when the impact of a parking requirement becomes clear - and the point when it becomes vulnerable to variance requests when it does not produce a desired gross building area. This is not the only option, however. Since there are 25 specification boxes in the table, values can be modified to pursue change in many ways, but the design specification template in Table 1 is not in common use. In its absence, the expedient owner choice has been to reduce the parking provided to increase gross building area, but this can sacrifice its usefulness to successive owners and its public revenue potential over time. Since the city is essentially a farm, the yield from each of its acres determines the quality of life it can afford to provide.

Table 2 is based on a core area of 24,829 sq. ft. and an estimate of 400 sq. ft. per parking space. It presents a range of parking requirement options (a) on line 4. When these values are entered in cell F34 of Table 1, the table produces the gross building area options displayed in columns B-Q. If an owner had a choice among the parking requirements listed on line 4, most would choose the regulation that produces the desired gross building area with the least building height. The number of parking spaces might prove inadequate, but they would choose to live with the result and hope for the best. This is not necessarily in the public interest, however. A failing activity leaves a vacant building with inadequate parking that consumes potentially productive acres. Parking is an essential ingredient in this equation and its impact is felt long after the original owner’s departure.

In other words, a building owner is a temporary investor in shelter for activity on a given land area; and may also be a total or partial occupant of the premises. The building represents a permanent source of public revenue that fluctuates with location, condition and succeeding occupant activity. Under these circumstances, a privately owned building is a public resource that can be compromised by a parking quantity that proves insufficient for future activity. The City of Buffalo, NY has chosen to make parking quantity a business decision. We will never understand the impact until knowledge emerges from the adoption of scientific measurement, evaluation, and forecasting techniques.[1]

Pre-Existing Conditions

A city is an anatomy that grows at the cellular level of property ownership, and it surrounds its defects when there is land to annex. Unfortunately, a sprawling city does not learn to correct its mistakes and control its tendency to consume and pollute the land that is its source of life. In a way, sprawling cities represent an attempt to return to the farm where open space is abundant and equipment can be stored conveniently. Property in a surrounded city cannot expand, and density is magnified by increasing movement and decreasing open space donated to parked cars.

It is inevitable that business would attempt to serve residents in these areas under the deficient conditions created by the automobile, but decline is inevitable when intensity exceeds the limits of tolerance for those who can afford to escape. Columns G-J in Table 1 show that physical intensity, intrusion, and dominance are functions of 25 specification values that can be measured.  In my opinion, the physical conditions created by these specification values affect our social, psychological, environmental, and economic quality of life. They combine within each property cell, and every cell combines with others to form the Shelter Division of The Built Domain. This division is served by Movement, Open Space, and Life Support Divisions within a currently pathogenic anatomy that is encouraged by our concepts of annexation within a world without end. My point is that the parking values in cells F33 and F34 are two of these 25 specification values. They are generalizations when related to a specific activity, but they cannot be ignored and deferred to private enterprise as an expedient solution to an intractable problem that currently affects our quality of life and will affect our symbiotic future.

The problem stems from the fact that we have not been able to predict the shelter capacity of land with any degree of accuracy, and capacity is a function of parking requirements. The only certainty is that parking is an inescapable consideration in the age of the automobile.  

Buildings with no on-site parking have deferred their requirements to others in near-by and remote locations. These locations are provided and connected to exempt building activity at public expense in many cases. The parking requirement did not disappear. Its expense was simply shifted. When expense is shifted to the public side of the ledger, it is subsidized by the average revenue received from all municipal acres. If revenue is inadequate to meet expense over time, government is considered profligate. Budget cuts ensue and decline takes another step toward blight. Inadequate parking will continue to add a largely unrecognized burden to surrounding neighborhoods and municipal expense until this relationship is recognized. A city washes it hands of the problem when it defers parking decisions to private enterprise; but expedient solutions have a way of producing unintended consequences, and we cannot continue to consume land and leave our mistakes in an expanding core of blight.

It is time to come to grips with the true shelter capacity of land and its economic implications. Growing populations will never learn to live within symbiotic limits that protect their quality and source of life until they build the knowledge required, and this knowledge will not be produced by the expedient solutions of private enterprise.

---

[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)

Restoring the Health of Cities

The following quotes appeared in an article entitled, “Fates of Rural Colleges, Towns Tied.” The Wall Street Journal, Dec. 22, 2016, page A7.

“Dr. Ditzler arrived in 2014 (Albion College, Michigan) with a record of civic engagement as president of Monmouth College in Illinois. In interviews with trustees, he told them he thought the school could be saved by urging students to use the community as a laboratory to heal real-world problems.”

Dr. Ditzler said, “We can’t survive if this town isn’t healthy.”

If a healthy town is the objective, seeking a prescription from popular opinion is like asking them to cure Bubonic Plague. It’s helpful to know their opinions, but the plague wasn’t understood until cellular awareness produced measureable knowledge expressed in the precise language of biological science. Until then, the general population chose flight from fear. The same flight from urban decline has produced dying cities and a modern phenomenon called sprawl; but we have been unable to progress from observation without a new science. It begins with the realization that a city is not a laboratory. It is an anatomy distinguished by urban and rural phyla containing shelter, movement, open space, and life support divisions. Each division contains specialized cells that currently combine to form areas of shelter, fragments of social open space, and arteries of movement and life support. A cell in this context is a legally defined land area that currently accumulates to create sprawl. Sprawl can only be seen from space, and observation turns a satellite into a microscope that reveals an amorphous shape I’ve called The Built Domain. A shelter cell in both urban and rural phyla of The Built Domain contains a habitable nucleus occupied by a parasitic catalyst. This parasite will continue to produce sprawl that consumes and pollutes its source of life, The Natural Domain, until it functions within geographic and symbiotic limits.

In The Built Domain, a land use plan for cellular growth without shelter capacity and activity correlation simply separates incompatible activity. This 20^th century achievement was called zoning, and was a monumental advance in the march toward human rights; but limited knowledge has partially protected health and safety while producing sprawl. Sprawl seeks a better quality of life (welfare) through expansion and consumption of agriculture. It does not correlate shelter capacity and activity on every acre of land to limit consumption and ensure economic stability. Unfortunately, we have not been able to accurately predict shelter capacity. As a result, we have not measured its presence and evaluated its relationship to activity, location, condition, cost, revenue, return-on-investment, and economic stability in The Built Domain. In addition, we have not been able to measure the intensity, intrusion, and dominance produced by shelter capacity options within urban areas, even though these conditions affect our physical, social, psychological, environmental, and economic quality of life. This means we have not been able to plan its growth with accuracy and confidence.

Shelter capacity is gross building area per buildable acre. Forecasting gross building area options is a function of the shelter design category chosen; the value decisions entered in its design specification template; an algorithm that correlates the values entered; and a master equation that converts an algorithm summary to gross building area predictions. These predictions vary with the floor quantity options being considered. Specification modifications produce a new set of shelter capacity options for the same land area in the blink of an eye.

The underlying point is that gross building area can be occupied by any activity. The type and scope of occupant activity within gross building area produces income tax revenue. It also affects real estate value. Income and real estate tax represent two major sources of public revenue in many states; and total public revenue determines the quality of life that can be provided by government. Every shelter capacity option predicted for the same land area, therefore, has a wide range of related implications for both public and private interests.

If curbs are crumbling, streets are pot-holed, basements are flooding, water is tainted, and so on; it is not appearance that is the problem. It is the public revenue generated by existing shelter capacity and activity within the city. Reconciling public revenue and private investment objectives by correlating land use allocation, shelter capacity, and occupant activity is an objective of city design. It is meant to expand the concept of architecture, city planning, and human rights to protect the public welfare. However, increasing shelter capacity increases activity that can produce excessive physical intensity, intrusion, and dominance on the site and in the surrounding area. These are specific physical conditions calculated in columns F-J of Table 2 on lines 42-51 that require explanation beyond the scope of this essay, and design is required to correlate their presence with their social, psychological, environmental, and economic implications.

The bottom line is that every urban and rural shelter cell in any government jurisdiction is part of a much larger Built Domain anatomy. The value of a shelter cell is enhanced by decisions that correlate shelter capacity and occupant activity options. These value decisions have been based on location, condition, and opinion in the absence of scientific measurement, evaluation, and knowledge. This has often produced too many acres producing too little revenue; and this is a recipe for the decline of a city. We must be able to accurately predict shelter capacity options for every shelter cell within the Built Domain, and correlate capacity with occupant activity to produce a stable economy that protects our health, safety, and welfare. It is a way to protect public quality of life within a geographically limited Built Domain designed to ensure symbiotic survival.

In a single sentence, we must be able to shelter and serve growing populations within a limited, symbiotic Built Domain that protects their quality and source of life – The Natural Domain. It’s a challenge that won’t be solved in a single generation. Solutions will begin when we recognize the anatomy of the problem and define it with a language that can lead us to knowledge and direction.

Students can help save Albion when they understand the anatomy to be studied and the knowledge that must be acquired with a laboratory research program.

I’d like to repeat a brief explanation of shelter capacity and activity evaluation that I’ve previously written to add a little detail for the students who may be reading this essay. Correlation of shelter capacity and activity with movement, open space, and life support is the key to healthy cities within geographically symbiotic limits, but the key cannot be turned without an ability to measure, evaluate, and forecast shelter capacity options for every shelter cell. These options have a broad array of implications. Correlation will lead the many tactical decisions required to achieve a policy of symbiotic survival with a strategy of city design, but it can’t begin without an address database.

Address Database

An address database correlates a street address with its related parcel number(s), census block, census tract, numbered zoning area, and related zoning category. It is the common planning link for a great deal of related information that must be shared to succeed.

Real estate tax information can easily be assembled by street address, census block, tract, and zone. Income tax information by street address is privileged, but can be assembled by census block or tract and correlated with real estate revenue to provide an essential picture of a city’s economic stability. The objective is to determine the economic productivity of each acre in a city’s land use plan, since the use of these acres determines its ability to thrive.

Table 1 presents a generic example of the acreage allocation and economic productivity of residential acres that may be surprising.

Line 1 recites a number of typical lot areas in square feet. Line 2 converts these areas to acres. Line 3 converts these areas to density statistics. Cell B8 theorizes that the total income and real estate revenue to local government from a 6,000 sq. ft. lot is $4,959. When this is multiplied by the dwelling unit density per buildable acre of 7.26 in cell C3, the total revenue per acre is $36,000 as calculated in cell C8. Cell J14 shows that a density of 1.0 dwelling unit per acre would need to yield $36,000 in revenue to equal the revenue produced by a density of 7.26 dwelling units per buildable acre. A 5 acre lot per dwelling unit would need to yield $180,000 as shown in cell B18 to produce the $36,000 per acre calculated in cell N18. Ten acre per dwelling unit would need to yield $360,000, and a 20 acres per dwelling unit would need to yield $720,000 before they would provide $36,000 per acre to equal the yield from a density of 7.26 dwelling units per buildable acre. In other words, 5 acres per dwelling unit would need to yield 36.3 times the revenue from a 6,000 square foot lot to equal its revenue per acre. This calculation is noted in cell A18. The calculation in cell A20 notes that 20 acres per dwelling unit would need to yield 145.2 times the revenue from the 6,000 sq. ft. lot. The ratios in Col. A would pertain given any starting value in cell B8, and they reveal the implications of decreasing residential density.

If the 5 acre lot produced $32,000 rather than $180,000 in revenue, its yield per acre would be $6,400. This is far less than the $36,000 per acre yield from the 6,000 sq. ft. lot. In fact, the revenue from the 6,000 sq. ft. lot is subsidizing the 5 acre lot when revenue is compared on a per acre basis, and this is the only basis that matters in a city that depends on the use of land area for revenue to protect its health, safety, and welfare.

The point is that a city has a limited number of acres and the revenue from each acre of activity directly affects its economic health. What appears to be a wealthy city of estate homes therefore, can actually be a group of wealthy residents served by a declining city with inadequate revenue. This is a recipe for flight to a newer suburb with less immediate maintenance expense.

If a yield of $36,000 per acre is not adequate to maintain a desired quality of life in our theoretical city, annexation for additional residential land use will bring new money without initial maintenance expense that appears to solve the current problem, but will prove to be an unwise use of land over time. A city has no way of understanding these relationships when it does not have an address database, related information that is shared by others, correlating software programs, and an adequate geographic information system.

Evaluation

Revenue evaluation involves the acres a city devotes to each independent zoning area; the specific activity in each cell within the area; and the shelter capacity present, planned or permitted per acre. (Keep in mind that a cell may be a fraction of an acre.) Revenue calculation is a function of the planned or permitted sq. ft. of activity per acre times the average revenue expected per square foot of activity. The amount of activity that can be accommodated per acre is a function of shelter capacity design. Shelter capacity per acre within urban and rural areas can be correlated with land use allocation for activity, movement, open space, and life support by city design to protect our health, safety, and quality of life.

Identifying every activity group in a city and its revenue implications per square foot can be too extensive to undertake and monitor, so I’m offering a short-form solution. Imagine the real estate property map of any city with each zoning area represented by a number and transparent color indicating its zoning category. All property tax-exempt areas are in white. Subtract the tax-exempt areas to find net acres per zoning area. Divide the total real estate tax produced per zoning area by the gross and net area calculated to find the real estate tax revenue per acre per area. Summarize the zoning area information by zoning category.

Next, divide the income tax revenue from each zoning area by its gross and net land area to find the income tax revenue per acre from each area. Summarize the zoning area information by zoning category. Add all real estate and income tax revenue from all zoning categories and divide by the total net and gross acres in the city. The result is real estate and income tax revenue yield per gross and net acre from all zones. Divide annual revenue from all other municipal sources by a city’s gross and net land area to find other financial yield per gross and net acre. Add all real estate tax revenue, income tax revenue, and other revenue to find total municipal revenue and divide it by a city’s gross and net acres to find a city’s average revenue per gross and net acre.

Finally, divide the city’s total annual expense by its gross and net acres. Compare its gross and net annual revenue per acre to its total annual expense per gross and net acre. The two should be equal, but this does not necessarily indicate an adequate quality of life. A city is required to balance its annual budget and cuts may have been required. Next, subtract the city’s total expense per gross and net acre from the gross and net revenue received from each zoning area. Zoning areas with negative results are being subsidized. The results may show that residential areas are being subsidized by non-residential areas. It is not unusual, but the extent of subsidy is one indication of a city’s economic stability.

There is one fundamental question behind this financial evaluation. Does the population feel the programs and services provided are both needed and adequate? This is a public policy question they are able to answer. When a majority agrees with the quality of life desired, the debate over cost and benefit becomes focused on the cost to provide desired benefit; and the perception of a wasteful government can be ameliorated but not eliminated. If a program is desired but the service is inadequate, a city’s revenue per acre is inadequate and additional funds must be found with city design and economic development based on an understanding of land use allocation and shelter capacity.

Conclusion

At this point it should be obvious that land use allocation in a master plan and zoning map is a partial cure for unhealthy cities. It is a two dimensional answer to a three dimensional question. A building shelters activity and can be remodeled to serve other activities. I’ve called gross building area per buildable acre shelter capacity. It is a function of building height and area on a given buildable land area and it determines the scope of activity that can be sheltered per acre. Shelter capacity and activity per buildable acre determine the revenue produced per acre. Every activity has an average yield per acre based on the square feet of shelter provided, but we have not collected activity revenue per building square foot information. This has made it impossible to accurately evaluate the economic implications of shelter capacity options for a given buildable land area; but activity allocation and shelter capacity combine to determine the public revenue potential of a buildable acre, and the economic potential of a city’s incorporated acres.

When a city can correlate zoning areas and activities with shelter capacity options and revenue potential, it will be in a position to evaluate economic alternatives and credibly defend planning recommendations designed to restore its health.

I’m including Table 2 as an example of shelter capacity prediction so you’ll have a visual frame of reference, but won’t spend a lot of time repeating what is included in my book.

Table 2 has been created to represent the G1 building design category. This category includes all buildings served by a surface parking lot around, but not under, the building. The values entered in the boxes of the Land and G1 Modules in Table 2 represent specification value decisions that can be adjusted to test alternatives. The core area found in cell G32 is multiplied by a master equation to find the gross building area options in cells B42-B51. Since every square foot has public revenue and private return-on-investment implications, an accurate forecast of gross building area potential in Col. B, shelter capacity potential in Col. F, and their intensity, intrusion, and dominance implications in columns G-J represent extensive options for restoring economic stability when correlated with occupant activity. This correlation is an essential pre-requisite for the urban and rural health of any city within The Built Domain.

Please note that there are 15 specification value decision entered in the Land and G1 Modules of Table 2 and 10 entered in Col. A of its Planning forecast Panel. If one or more of these 25 specification values is modified, new gross building area options will appear in Col. B of the Planning Forecast Panel for evaluation.

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.

---

[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.

---

[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)