Improving City Planning and the Context of Place

 In my opinion, cities only know where they are. They have a limited concept of where they want to be. They know the annual revenue they receive and if next year’s budget must be reduced, but they do not understand the granular level of their revenue engine and the comprehensive physical adjustments that annexation, economic development, zoning, and redevelopment must produce to comprehensively improve their financial condition – and few things improve without the money required to undertake the effort.

Improvement will begin when the gross building area potential of land can be accurately predicted based on the six building design categories available, since gross building area can be occupied by any permitted activity, and the combination has significant shelter capacity, intensity, intrusion, context, and revenue implications. I have discussed this in many essays. The following is my attempt to summarize.

GROSS BUILDING AREA OPTIONS

Gross Building Area Options (GBA) are a function of the building design category chosen and the values, including floor quantity alternatives, entered in its design specification template. For instance, the G1 Building Design Category equation for gross building area potential uses the values entered in its template to derive the values needed for its equation. (GBA = ((af) / (a+(fs))) * CORE). My point is that shelter capacity and intensity have mathematical definitions that can become part of an improved leadership language. The following are a few points that I’d like to emphasize.

SHELTER CAPACITY

Shelter Capacity (SFAC) is equal to the gross building area present or predicted (GBA) divided by the buildable acres occupied (BAC), excluding future expansion area. It can be used to calculate many implications including, but not limited to, intensity, intrusion, context, and revenue potential.

INTENSITY

Increasing shelter capacity indicates increasing physical intensity. A city has been concerned with the health, safety, and welfare of adjacent activity but it has not been able to accurately measure intensity. It has continued to be a problem without adequate definition. This has led to sprawl seeking to reduce intensity on one hand and excessive intensity seeking to increase revenue on the other. Many cities, if not all, have a limited ability to lead the intensity of shelter construction toward measurable goals capable of consistently repeating success, in my opinion.

Inadequate density and floor area ratio calculations will continue to consume our source of life in a vain search for financial stability until intensity definition and leadership improves. In other words, we have not been able to measure where we’ve been with a leadership language that can be used to chart an accurate course into the future.

BUILDING REVENUE POTENTIAL 

The annual municipal revenue produced by each taxable parcel or block within its jurisdiction is a function of the gross building area present, the occupant activity present, and the revenue produced per square foot. A city may know the gross building area present per parcel. It could record the activity present, but it does not record the revenue produced per square foot of activity on a given buildable land area, and cannot accurately predict gross building area options for a given buildable land area. This means that a city vaguely understands the productivity potential of land under its jurisdiction and cannot accurately evaluate shelter capacity options that can improve its productivity on a comprehensive basis.

Occupant Revenue per square foot is equal to total occupant revenue divided by the gross square feet occupied.

 

Building Revenue per square foot is equal to the sum of its occupant revenue receipts per square foot divided by the number of occupants.

 

Building Revenue Potential per acre of buildable land area is equal to its shelter capacity in square feet times the average revenue potential present or planned per square foot. 

Revenue potential is related to shelter intensity and activity. A city has been concerned with the health, safety, and welfare of adjacent activity but it has not been able to accurately measure intensity. This has led to sprawl seeking to reduce intensity on one hand and excessive intensity seeking to increase revenue on the other. Both have been pursued by government without an accurate ability to correlate the shelter capacity, intensity, intrusion, context, and revenue implications capable of consistently repeating success in my opinion, because cities have had limited information sharing, data management, mapping, and shelter capacity evaluation available. This has significantly limited their ability to comprehensively calculate the shelter capacity and revenue potential of land use decisions in their jurisdictions.

Inadequate density and floor area ratio calculations will continue to consume our source of life in a vain search for financial stability until this leadership improves. In other words, we have not been able to measure where we’ve been with a leadership language that can be used to chart an accurate course into the future.

If a city knows its total average annual cost per taxable acre, it could compare this cost to the annual revenue produced per taxable acre by each of its parcels, blocks, or zones if it had the required data. It is an evaluation that could indicate the leadership decisions needed; but information sharing, data management, mapping, and shelter capacity evaluation are a few of the tools needed to pursue the knowledge required for more informed leadership decisions.

SHELTER CAPACITY EVALUATION

Tegimenics, or shelter capacity evaluation, begins with a series of forecast models meant to measure and predict the gross building area capacity of buildable land based on a building design category choice, a template of design specification decisions, and a column of variable of floor quantity options. Since shelter capacity can be occupied by any permitted activity, the allocation of capacity over an entire city has significant physical, social, psychological, environmental, and economic implications that precede more detailed definition.

TEGIMENICS

The method of calculating shelter capacity and its implications, or Tegimenics, represents a leadership language based on mathematics. It can improve our ability to chart a course for shelter that protects the activities of growing populations on limited land areas defined to protect their source of life, the Natural Domain.

I’ve written about facets of shelter capacity evaluation on many occasions. For the interested reader, these essays are located on my blog at www.wmhosack.blogspot.com. The more recent are also on LinkedIn. The entire concept is collected in my book, “The Equations of Urban Design”. It is available on Amazon.com. In hindsight, I wish I had titled the book, “Tegimenics, the Science of Shelter Capacity Evaluation”, but this has been a journey of incremental discovery seeking an intuitive destination. It has led to leadership language capable of measuring, evaluating, and defining shelter capacity options that can be part of any sustainable, symbiotic solution to the puzzle of our presence on the planet.

CONCLUSION

I am suggesting that shelter capacity design begins with the measurement, prediction, evaluation, and selection of desirable site plan quantities. These quantity decisions establish the foundation for the shelter pattern, form, function, and appearance that is molded from its recipe. The result is context of place. This combination of strategic and tactical leadership can be used to protect our physical, social, psychological, environmental, and economic quality of life within geographic limits, but it will depend on a commitment to funding and improving the information sharing, data management, mapping, and shelter capacity evaluation needed to expand the knowledge available.

Walter M. Hosack, January 2026

Photo credit: Jacek Halicki

The Shelter Correlation Needed for a Sustainabe Future

The distribution of taxable activity in buildings throughout a city, and the real estate value of these buildings, is a primary source of revenue per acre. This yield must contribute to a city’s total annual expense per acre, but a city does not calculate its revenue on this basis. This has led to a disconnect between the land use compatibility objectives of city planning and the revenue objectives of local government. It has led, in my opinion, to many revenue-deficient land use plans and decisions when compared to their long-term public expense. The relationship of land use acres to revenue is easily overlooked, however, when excess and deficient contributions per acre are merged into the total annual revenue received by a city. This leads a city to overlook the fact that the shelter capacity of land combines with its occupant activity to determine the revenue the city receives, and too much land can be devoted to too little revenue within a limited municipal area. This can lead to annexation when land is available and stagnation or redevelopment when it isn’t. This has led me to search for a better method of measurement, prediction, and evaluation because shelter capacity determines the scope of feasible economic activity, and more accurate predictions can lead to less land consumption.

THE CITY

A city is a collection of shelter options with varying degrees of capacity served by arteries of movement, open space, and life support. The scope and variety of occupant activity permitted by zoning and shelter capacity determines a city’s revenue potential. The physical context and appearance of this capacity symbolizes its quality of life.

Attention to building, parking, pavement, and open space context has often been referred to as urban design, but the social, psychological, environmental, and economic implications of these physical design decisions have rarely been correlated with these measurable shelter capacity, intensity, intrusion, and context implications.

THE NEED

The sustainable provision of shelter on the limited land of our planet will depend on our ability to accurately predict the shelter capacity of this land. We need to limit its consumption to protect its source of life, the Natural Domain. A more accurate ability to calculate shelter capacity in a limited Built Domain is needed to serve the activities of growing populations and conserve their source of life, the Natural Domain.

A city is a collection of shelter capacity decisions served by arteries of movement, open space, and life support on defined land areas that can be occupied by any permitted activity. The mathematical measurement, prediction, arrangement, and correlation of shelter capacity, intensity, and activity can form the quantitative basis for further city design evaluation on limited land areas.

THE ATTEMPT

The shelter capacity of land is its gross building area potential per buildable acre. It is a function of calculations based on a building design classification system and choice, values entered in the category’s design specification template, and a column of optional floor quantity entries. I have written about these forecast models on many occasions and will avoid repeating myself by referring the reader to these essays on my blog at www.wmhosack.blogspot.com and to my book, “The Equations of Urban Design”, available on Amazon.com.

THE OPINION

The distribution of shelter capacity and occupant activity among a city’s taxable acres determines the revenue a city receives and the quality of life it can provide, but the contribution from every taxable parcel has never been calculated or mapped based on the land consumed; nor has its revenue per acre been compared with the total annual cost of municipal government per acre – to my knowledge. This has made it difficult, if not impossible, to correlate the capacity and use of land with its revenue potential and quality of life within sustainable, symbiotic geographic limits. This competence will require improved information sharing, data management, shelter capacity prediction, mapping evaluation, urban design assessment, and scientific correlation before city design can become more than unlimited land consumption.

THE OPPORTUNITY

In other words, when revenue productivity from gross building area can be measured or predicted per acre for every parcel or block within a city; when it can be geographically mapped; and when it can be compared to a city’s total annual cost per acre; the economic implications of a city’s land use decisions will become apparent, and future planning decisions will be better informed.

THE CHALLENGE

It sounds simple enough, but we have not been able to accurately predict the shelter capacity of buildable land area, and we do not know the annual revenue that can be expected from various occupant activities. An investor can calculate the anticipated profit from an occupant activity, but an investor can sell a mistake. A city has far less ability to predict its risk and protect its investment. It is left with the result.

THE FOCUS

I have focused on deriving an accurate method of predicting the shelter capacity of land and calculating the physical implications of the predicted options. The definition of revenue potential per square foot of occupant activity is information that remains to be assembled unless I am mistaken. If it is available, it can be easily multiplied by predicted or measured shelter capacity options to find the revenue options implied.

THE OPORTUNITY

Shelter capacity measurement and prediction, or Tegimenics, can anchor the correlation of research and knowledge needed to lead us to the goal of life within symbiotic limits.

THE EXAMPLE

I’ll borrow Table 5 from my previous essay, now labelled Table 1, to create a simple example of shelter capacity evaluation. Table 1 is based on the information given at the top of the table and the design specification quantities entered in its gray cells. The gross building area predictions that result are calculated in cells B44-B53.

I have arbitrarily entered a square foot revenue prediction in cell K43 of Table 1. It is meant to represent total real estate, income, and other revenue related to the gross building area predicted. Multiplying this by the gross building area predictions calculated in cells B44-B53 produces the revenue predictions in cells K44-K53. (A square foot revenue prediction based on measurements from other similar activities would obviously be a better choice.) If this were repeated for every parcel in a city’s inventory, a picture of its current productivity and future potential would emerge, and the ability to evaluate and map alternatives would require a few keystrokes.

CONCLUSION

My point has been to illustrate the usefulness of gross building area predictions produced by shelter capacity algorithms and design specification templates when they are combined with other information related to these Tegimenic measurements, predictions, and implications.

Walter M. Hosack, January 2026

Correlating Zoning Design Standards

 NOTE: The shelter capacity of land is equal to the gross building area in square feet present or planned divided by the buildable project area in acres, except for future expansion area. The quantity introduced has many related implications such as but not limited to the scope of -- occupant activity, traffic generation, population capacity, revenue potential, construction expense, and return on investment implied by the square feet introduced.

Zoning ordinance regulations depend on itemized, independent standards that are not mathematically correlated in many if not all cases. A residential density limit that cannot be reached by the combination of applicable parking and floor quantity limits involved is a common current example. This has often produced contentious arguments, permitted exceptions, inconsistent precedent, excessive intensity, and sprawl that has limited its zoning effectiveness as a leadership language.

Shelter design depends on quantity decisions that become the foundation for all ensuing site plan organization, building form, and final appearance decisions. In a sentence, initial site planning quantity decisions such as parking area, pavement area, unpaved open space area, floor quantity, building volume, and final appearance have been intuitively evaluated and created for centuries, but the mental correlation involved has been considered a fine art endeavor. As a result, it has escaped the underlying mathematical definition that makes knowledge, prediction, evaluation, and accurate leadership guidance feasible.

Mathematically correlated design specification standards produce shelter capacity, intensity, intrusion, and context implications that can be measured for evaluation and predicted for future planning and urban design guidance. It has been my intent to define the terms shelter capacity, intensity, intrusion, and context with mathematical specification values and template forecast models for a building design category classification system. The templates have been created to provide the mathematical format required for consistent measurement and prediction of shelter capacity, intensity, intrusion, and context implications based on the values entered. This format can lead the efforts of many toward shelter for the activities of growing populations within the sustainable, symbiotic geographic limits that are required.

THE PROBLEM

Table A from “The Disorganized Zoning Ordinance” is repeated at the end of this text. The point was to show that the organization of itemized standards in a zoning ordinance were disconnected when compared to the five chapter and nine section reorganization suggested in Table 2. The underlying motive at the time was to relocate all applicable design standards that were often buried with unrelated text throughout the ordinance.

Table 3 includes a sample dissection of a partial section in the sample ordinance chosen. The table illustrates the heavy lifting required to convert a section of the sample to the structure illustrated by Table 2.

Each topic in Col. B of Table 3 is dissected and referenced to the Table 2 sections that pertain, but the itemized format remains. The related Table 2 sections are noted in Col. A of the table. Some additional notes are also included.

Table 4 illustrates the distillation of all design standards from the sample ordinance, and they were not all found in one location. The result is a Table of Design Standards. It displays all relevant standards for one zone on one line in one consolidated location for ease of reference and consistency of application. Lack of adherence to a standard, however, still represents an itemized offense requiring variance approval by a Board of Zoning Adjustment.

Table 4 may represent a consolidated improvement over scattered design requirements in a zoning ordinance, but it does not correlate these complex standards to indicate their combined implications and realistically achievable gross building area results. At the present time each collection of line-item limits represents a puzzle that must often be solved with exception variances in some, if not many, cases. This is not leadership with a goal. It is regulation with an unknown future.

If city planning and urban design leadership is desired, the ability to correlate diverse requirements is needed to produce gross building area options that can reach shelter capacity, intensity, intrusion, and context goals without inconsistent exceptions that compromise the quality of life desired.

THE SUGGESTION

Conceiving a method of measuring, evaluating, and correlating site plan quantity decisions has been my objective, since quantities are the foundation for all ensuing physical design, and we must move beyond the puzzles represented by Table 4 before we can provide the shelter portion of a sustainable, symbiotic goal.

Those of you who have read my previous essays know that I began by classifying two worlds on a single planet, The Natural and Built Domains. I theorized that the Built Domain anatomy contained Urban and Rural Phyla, and that each phyla contained a Shelter Division served by arterial divisions of Movement, Open Space, and Life Support, even though I admitted that arteries of open space in the Built Domain were more of a dream than reality.

I continued with the theory that shelter classification contained only six building design categories based on the parking system adopted, and that each responded to a specification template of topic variables that could be mathematically correlated to produce measurable and predicable gross building area, shelter capacity, intensity, intrusion, and context implications. Implications could then be evaluated with a mathematically correlated leadership language, and knowledge could replace the presently itemized opinions of zoning.

This meant that mathematical shelter capacity, intensity, intrusion, and context planning prescriptions could be used as a language that could lead shelter formation and organization toward protection of a city’s physical, social, psychological, environmental, and economic health, safety, and quality of life.

THE G1.L1 FORECAST MODEL

I’ve used Table 5 on many occasions for many reasons. I’ll use it here to illustrate the point I’ve just made regarding architectural quantity correlation. Table 5 predicts the gross building area potential of a given buildable land area, excluding future expansion area, when using surface parking around but not under the building. The option is referred to as the G1 Building Design Category.

The first thing to recognize is that occupant activity occupies capacity and may be limited by the quantity available. For example, capacity is a function of the design specification values entered into the gray cell topics of the Table 5 template. These template topics vary with the building design category and activity group involved.

Table 5 involves generic topics for the G1 Building Design Category. It is unencumbered by specialized activity group functions that require additional template topics, such as residential activity. The generic shelter capacity of land is predicted in cells B44-B53. This is determined by the design specification values entered and mathematically correlated in the forecast model. A change to one or more of the values would produce a new prediction of gross building area options in cells B44-B53. This would also produce a revision to the capacity, intensity, intrusion, and context implications calculated in cells F44-J53.

Any value entered in a gray cell of Table 5 is a variable. For instance, the parking values entered in cells A35 and A36 are the most common since they change with the occupant activity involved and affect the gross building area that can be produced. The floor quantity values in cells A44-A53 may also be limited or expanded to influence gross building area potential.

The unpaved open space percentage entered in cell F11 is a variable that has often remained unspecified in a zoning ordinance since it can also limit achievable density, shelter capacity, and intensity, but this is a serious mistake. It should at least be correlated with the storm sewer capacity available, since inadequate correlation can contribute to capacity overload without more sophisticated engineering modifications.

Table 5 differs from Table 4 because it is based on an algorithm; and it immediately responds to the variables entered in its shaded cells with a measurement of their implications in its Forecast Panel and Implications Module. This means that design specification options capable of achieving the same shelter capacity objective could be easily explored by rebalancing the variables involved. This balancing discussion could even occur at joint public/private conferences with the model as the center of attention.

If I’ve made my point, the interactive concept of correlated shelter capacity evaluation illustrated by Table 5 can replace the static regulation of Table 4. In fact, it has the potential to amend regulation with cooperation among all parties concerned with the provision of shelter for population activity. I have only provided a glimpse, however. Table 5 is one in a series of forecast models that represent a suggested method of measuring and predicting the shelter capacity, intensity, intrusion, and context implications of design specification decisions. This is information that could be used to build knowledge. The entire suggestion is presented in my book, “The Equations of Urban Design” that is available on Amazon.com. I’m including its Table of Contents as Table 6. The book discusses the building design categories, activity groups, and forecast models that use embedded equations to provide shelter capacity predictions for evaluation and guidance with a few keystrokes.

CONCLUSION

Some form of shelter capacity measurement and prediction is needed to build the knowledge and defend the guidance required to protect populations within geographic limits that recognize our responsibility to protect our source of life. Our current methods of zoning regulation are an inadequate response to the threat represented by annexation, excessive intensity and sprawl based on inadequate knowledge and mistaken assumptions. It will continue to consume agriculture and the Natural Domain until a leadership language equal to the knowledge and guidance required is pursued. I have simply made one suggestion in a discussion that deserves pursuit in my opinion.

Walter M. Hosack, January 2026