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Saturday, April 16, 2022

The Consequences of City Design Decisions

 

The acres in a city’s inventory are a primary source
of its revenue, but not all produce the income needed to equal a city’s average expense per acre. If a city does not understand the economic implications of land use activity and development capacity allocation, it will continue pursuing random projects without the comprehensive strategy needed to lead its physical decisions to foreseeable financial improvement in a revenue and expense equation that determines its quality of life.

Annexation increases the taxable acres within a city’s expanded corporate limits and gives the impression of relief from immediate budget deficiencies. This provides new money to meet current obligations when land is available, but the new revenue from the acres consumed can prove inadequate to meet increasing expense per acre as the city’s infrastructure ages. Repeated annexation ensues with hope as a strategy and sprawl as a result that has no better understanding of the revenue implied per acre of activity and its relationship to the city’s total annual expense per acre. The problem is exacerbated when a city has no land to annex and decline increases as redevelopment for greater revenue meets extensive opposition.

I’m sure there are exceptions to the absolutes I’ve written in the previous paragraph, but I hope they serve to raise the following questions that can lead to an improved awareness of the knowledge we must create and the tools we need to begin addressing a problem that is not limited to a city’s annual accounting summaries and independent silos of professional knowledge.

THE QUESTIONS

Question 1: What does the taxable land in a city’s inventory yield in average revenue per acre?

Answer: A city knows its taxable acres per lot or parcel and the answer is as simple as dividing its total annual revenue by the total number of these acres.

Question 2: What does it cost a city to operate, maintain, improve, and finance a desirable quality of life per taxable acre?

Answer: A city knows its total annual expense including debt service. The answer is as simple as dividing this expense by the taxable acres served.

Question 3: Is a city’s annual expense producing a desirable quality of life?

Answer: This question is complicated by the presence of conflicting opinion. A municipal budget must balance each year, but this is no indication of the physical, social, psychological, environmental, and economic quality of life being provided. In fact, it may include painful budget cuts. Improvement is often a function of the revenue available from the taxable acres and activity present or planned for each parcel within its corporate limits. I doubt that many cities have the relational databases required to understand the relationship of land use activity to land development capacity, intensity and revenue potential to support the quality of life present or desired.

Question 4: What is the revenue yield per taxable acre of activity within a city?

Answer: A city knows the acres occupied and the activity present in most cases, but it rarely knows the total real estate tax, income tax, and other revenue provided by each activity on the acres occupied. The information is contained in separate silos to protect a concept of privacy that prevents the correlation of essential urban economic data. If it could be correlated, it would be a simple matter to divide total activity revenue by the acres occupied to determine its yield per acre; the relationship of activity yield to the city’s annual expense per acre; and the balance of activity, capacity, intensity, and yield needed within municipal boundaries to provide the average revenue per acre needed.

Since a city does not know the yield per acre that can be expected from shelter capacity, intensity, and activity alternatives, the entire process of land use allocation for economic stability depends on a guessing game of annexation and sprawl that seeks elusive balance in the face of inexorable population growth. In other words, a city is like a farmer who cannot estimate the yield he/she can expect from field and crop allocation on land within his/her boundaries.

Question 5: In urban terms, what is a “crop” and what is a “field”?

Answer: A crop is a land use activity that can be specifically identified by standard industrial classification code or grouped by similarity in a zoning code. These zoning groups are referred to as districts rather than fields, and a district may include areas that are placed in more than one city location. Since the economic productivity of district areas may differ by location, each isolated area within a zoning district category is a field that requires a secondary designation to distinguish it from another. This can be as simple as a relational address database that correlates each “field” to its constituent census blocks, tracts, parcel numbers, street addresses, zoning designation and so on. From an urban perspective, information collected by one index that is not related to others is knowledge drowning in a common sea.

Question 6: What is shelter capacity, intensity, and yield?

Answer: Shelter capacity is also referred to as development capacity. It is the gross building area in sq. ft. that is, or can be, placed on an acre of buildable land area. It is a function of the building design category chosen and design specifications adopted.

Intensity is a measure of the capacity introduced per acre, and excessive amounts can produce an undesirable quality of life. Capacity and intensity are important considerations because they define the shelter available to accommodate activity within a given land area.

Yield is the public revenue received per square foot of activity and per acre of land occupied. The mix of capacity, intensity, and activity on acres within a city’s incorporated boundaries determines the financial stability of its land use allocation portfolio. It is a missing store of information per activity that severely limits our ability to balance land use activity, shelter capacity, and intensity with the revenue potential needed to achieve a desired quality of life within sustainable geographic limits.

Question 7: How is the Gross Building Area Capacity of a Given Land Area Predicted?

Answer: I’d like to refer you to Table 1. It shows that the gross building area predictions in Column B of the Planning Forecast Panel are a function of the building design category chosen, the land area given, the 26 mathematically correlated values entered in its shaded boxes, and the equation in cell B39. A change to one or more of these shaded values will change the equation’s gross building area predictions in Column B of the Planning Forecast Panel.

At this point, I’ll simply say that gross building area capacity calculation is not as simple as increasing floor quantity or reducing parking space and setback requirements; even though these are common variance requests that seek to increase the profitability of a given land area. They occur because the correlation required for adequate urban design leadership is not understood.

Question 8: What is a building design category?

Answer: I have written about this extensively, so I’ll try to keep it brief. Shelter is provided for activity by using one or more of six primary building categories around the world. These categories are distinguished by their method of parking provision: (G.1) Buildings with grade parking around but not under the building on the same premise; (G.2) Buildings with grade parking around and under the building on the same premise; (S.1) Buildings with structure parking adjacent to the building on the same premise; (S.2) Buildings with underground parking on the same premise; (S.3) Buildings with structure parking beneath the building on the same premise; (NP) Buildings with no parking provided or required. Buildings with structure parking may include supplemental grade parking lots, but this is not their primary source of parking capacity and classification.

Question 9: What makes development capacity significant?

Answer: I’ve also referred to “development capacity” as “shelter capacity” to distinguish this essential element of survival from the systems of movement, open space, and life support that we build to serve it. We use shelter to protect activity, and the capacity of shelter combines with the value of occupant activity to produce public and private revenue and expense per acre. It also produces physical intensity, intrusion, and dominance that can compromise our quality of life when excessively introduced within the urban pattern.

Our ability to predict gross building area options per acre gives us control over the revenue potential of land and the intensity implied. I can make this claim because gross building area can be occupied by any permitted activity, and various occupant activities produce various levels of revenue per sq. ft. of gross building area capacity. In other words, the allocation of acres, activity and shelter capacity within a city determines its present or planned average revenue per acre, and this average yield must equal a city’s total annual cost to operate per acre. Budget cuts result when this simple equation does not balance and the debate over decline begins.

The challenge is to correlate the revenue produced by shelter capacity and activity with the physical intensity, intrusion, and dominance implied; since these physical, social, and economic implications aggregate across a city’s project acres to produce the revenue and quality of life available. Our current inability to correlate shelter capacity, activity and intensity with its revenue potential and quality of life implications has led to the guesswork and Ponzi solutions we call sprawl, but it is possible to see the future more clearly. I’ll use Table 1 and the G1 Building Design Category to explain in more detail.

TABLE 1

The first objective in Table 1 is to define the buildable land area available. This is calculated using the variables entered in shaded cells F3-F6 and F8. The answer calculated from these entries can be found in cells F10 and G10.

The second objective is to define the shelter land area that remains after an unpaved open space quantity is subtracted from the buildable land area available. The variable percentage chosen has been entered in cell F11 and its quantity equivalent has been calculated in cell G11. The impervious cover area remaining after this subtraction is calculated in cell F12 and G12. This is the land area remaining for building cover, parking cover, and pavement. The optional shared open space percentages in cells F13 and F14 would only be greater than zero when a portion of the total open space entered in cell F11 is shared as common open space serving more than one independent project area. In this example there is no common open space and the buildable land area calculated in cell G10 is equal to the remaining shelter area calculated in cell G17. The impervious cover area available in cell G12 also remains the same in cell G19.

The third objective is to calculate the core project area that will remain for building cover and parking lot area after all other pavement and miscellaneous building cover is subtracted. The design variables entered in cells F23-F29 are subtracted from the shelter area impervious cover found in cell G19 to define the core area remaining in cells F33 and G33 for building and parking cover.

The fourth objective is to define the gross building area permitted, planned or present per parking space in cell A36; and the estimated average parking lot area per space in cell A35 that is allocated or present to serve the space, its circulation drive, and its associated landscape area.

The fifth objective is to define the range of floor quantity options under consideration in cells A44-A53.

The sixth objective is to calculate the range of gross building area options that can be built in the core area remaining. These areas are calculated in cells B44-B53 using the equation in cell B39. It is related to the G1 Building Design Category chosen and predicts the gross building area potential of any given land area based on the variables entered in its shaded cells. A change to one or more of these variables will immediately change the results calculated.

In essence, the equation explains that G1 gross building area increases with floor quantity, and its parking lot area must increase to serve the larger building. Since core land area is the area remaining for building footprint and parking lot after all other present or proposed open space and pavement areas have been subtracted, parking lot area can only increase within this core area when building footprint area declines. However, a smaller building footprint can produce greater gross building area when floor quantity increases. These relationships are shown in the Planning Forecast Panel of Table 1. The gross building area predictions in cells B44-B53 increase at a decreasing rate as floor quantity increases in cells A44-A53; and building footprint area declines in cells C44-C53 to make room in the core area for the increasing parking lot area shown in cells D44-D53. This lot increase is needed to accommodate the increasing parking spaces calculated in cells E44-E53. In other words, the equation in cell B39 and the data in the Planning Forecast Panel of Table 1 describe the fundamental characteristics of the G1 building design category. The characteristics don’t change, but the results forecast will change whenever one or more of the variables entered in the shaded cells of Table 1 are revised.

The seventh objective is to define the implications of the results calculated in the Planning Forecast Panel of Table 1. The implications of the gross building area forecast in Column B are calculated in Column F of the Implications Module by dividing the buildable acres calculated in cell G10 into the gross building area predictions of Column B in the Planning Forecast Panel. Column F simply explains that the shelter capacity of land in sq. ft. per buildable acre increases with floor quantity at a decreasing rate when all other design specification values in Table 1 remain constant.

Capacity options are converted to intensity options in Column G with the equation in cell G43 of the Implications Module. The column shows that intensity increases with capacity in Column G, but there has been no research to determine the implications of these measurements. It is similar to the lack of knowledge that existed with the first blood pressure measurements.

The increasing floor quantity in cells A44-A53 is converted to a column of intrusion implications with the equation in cell H43. Capacity, intensity and intrusion are converted to a column of project dominance implications with the equation in cell J43. The result is a four-part method of capacity and intensity measurement that can be used to index and evaluate our relationship to the places we create and the shelter that surrounds them.

In other words, the allocation of shelter capacity, activity, and intensity per buildable, taxable acre within a city’s municipal boundaries determines the revenue potential of its land use allocation long before appearance becomes an issue. They are the topics and quantities in a recipe that must be correlated to have a chance of producing a desirable result.

Land use allocation, therefore, is not simply a quest to separate a city’s incompatible activities. It is a financial balancing act that is expected to define, monitor, and adjust the yield from each acre while ensuring that the physical intensity, intrusion, and dominance introduced for the sake of economic stability and financial profitability does not overwhelm the quality of life desired. In the end however, the result cannot respond to population growth with sprawl that threatens to consume its source of life while seeking to preserve its quality of life.

ADDITIONAL OBSERVATIONS

Any building design category may be used to shelter any activity, but the nature of the activity may increase or decrease the gross building area capacity predicted. For instance, Table 2 applies to the G1 Building Design Category when it is used to shelter R3 Apartment activity. The R3 Apartment Module has been added in Table 2 to specify the characteristics of the apartment building under consideration. All values entered in the shaded cells of the Land and Core Modules remain the same as Table 1. The floor quantity options entered in cells A56-A65 of Table 2 also remain the same. The values entered in the shaded cells of the R3 Apartment Module, however, have been added and affect the gross building area results predicted in cells B56-B65.

There are a number of reasons for the increase in the gross building areas predicted in Table 2 when it is occupied by apartment activity, but the simplest explanation is that the gross building area permitted per parking space in cell A35 of Table 1 has increased from 400 sq. ft. to 752.81 sq. ft. in cell J47 of Table 2. This produces a reduced parking lot in the core land area and a corresponding increase in the floor plan area available. When the increased floor plan area in Table 2 is multiplied by the same floor quantity options in Table 1, the larger gross building area options in Table 2 are produced.

It would have been possible to enter 752.81 in cell A35 of Table 1 and arrive at the same gross building area predictions as those in Column B of the Planning Forecast Panel in Table 2 without completing the R3 Apartment Module. This only shows, however, that Table 1 can be used to predict the development capacity of any buildable land area based on the shaded values entered, but additional activity specifications may be required to define the controlling design specification values for a specific land use activity.

FINAL POINT

It is not enough to separate incompatible land use activity in a master plan; depend on annexation to solve planning deficiencies; and include a few hopeful site plan and building design regulations that are often in conflict in a zoning ordinance. These regulations were included to protect our access to light, air, and ventilation within cities, but they have done little to protect us from excessive intensity that is a threat to the “public welfare” we now refer to as our quality of life. Table 1 has revealed a portion of the mathematical correlation involved. Its absence often makes design regulation appear inconsequential and vulnerable to variance requests. However, its invisible presence remains at the heart of the 
leadership needed to shelter growing populations within limited geographic areas that do not sprawl to consume their source of life.

If you are interested in pursuing this topic, you can find all building design categories, equations, and explanations in my book, The Equations of Urban Design, 2020, that is available from Amazon.com. If you are interested in related essays, you can find them in my book, Symbiotic Architecture, 2020, that is also available from Amazon.com. They represent my rough drafts and are not polished publications; but I chose to take no chances with my advancing age, since I felt the content could be a contribution to our continuing presence on a planet that does not compromise with ignorance.