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.