THE ZONING LEADERSHIP NEEDED

Zoning does not have a goal equal to the challenges we now face and does not have the leadership language needed to guide the army involved. It has the potential, however, when it can focus on its objective. This is why I am suggesting the use of shelter capacity evaluation as the beginning vocabulary for a simplified leadership language capable of guiding the provision of shelter for the activities of growing populations in a limited land area defined to protect our source of life, the Natural Domain.

I have struggled with the zoning ordinance method of land use regulation since I was first exposed to its presence in classes focused on architecture, city planning and urban design. The assumption was, and is, that it can lead both buildings and their occupant activity toward healthy, safe, compatible, and financially stable relationships with the same statutory format we use for our criminal codes of conduct.

The legal format works for city planning when zoning regulates the location and compatibility of activity. It begins to break down when it attempts to address building design specifications that must be correlated for leadership success. For instance, density, parking, building height, and open space are currently independent requirements. They often conflict and require variance approval. These exceptions to the law represent random leadership searching for direction and often sprawling or producing excessive intensity as a consequence.

SHELTER CAPACITY EVALUATION

NOTE: Shelter capacity is equal to  gross building area in square feet divided by the buildable land area occupied in acres, excluding future expansion area.

Building design categories, forecast models, design specification templates, and the equations of shelter capacity evaluation have been derived to measure and predict the gross building area capacity of land. These are the options needed to accurately predict their social and economic implications.

The goal is to improve the efficiency of land consumption for shelter in the Urban and Rural Phyla of a Built Domain to prevent consumption of its source of life, the Natural Domain.

I have mentioned on numerous occasions that shelter capacity may be occupied by any permitted activity. This is significant because the allocation of shelter capacity and activity on every parcel within the zoning districts of a city determines the revenue and investment potential of these districts; and the total average revenue per acre must equal or exceed a city’s total average annual expense per acre. This does not mean, however, that the average revenue calculated is able to deliver the quality of life desired. It does mean that parcel level information, data correlation, shelter capacity prediction, activity allocation, and interactive mapping are keys to the evaluation, understanding, and management of a city’s physical, social, and economic health.

RANDOM LEADERSHIP

Table 1 illustrates the order of topics in a sample zoning ordinance. They are summarized in the description column of the table. The section column identifies the category related to each topic. It illustrates random organization that requires a careful review of the entire ordinance for all requirements pertaining to a project.

Table 2 rearranges the topics of Table 1 under section titles to streamline the search for ordinance topics of concern. The topic number column reveals the random organization of Table 1 and the rearrangement that has taken place in Table 2.

Table 3 rearranges the sections and topics of Table 2 under chapter titles to further streamline the search effort. The topic number column again reveals the rearrangement of Table 1 topics that has taken place.

The Land Use Chapter of Table 3 contains a section entitled “Activity Regulations”. The numbers 1121-1140 refer to zoning district chapters that list permitted activities for each district in the city. These activities are supplemented with additional density, parking, and building height regulations that are not mathematically correlated as previously mentioned. This makes their combined implications, and dwelling unit quantities impossible to predict; site planning a guessing game; and leadership an exercise of uncertainty generating adjustments referred to as “variances” or exceptions to the law. It is no wonder design efforts flounder in the leadership confusion and unrealistic expectations.

Table 4 is a summary of random residential design specification requirements distilled from a sample ordinance. The organization has simplified the search process by placing all quantity requirements related to a zone on a single line, but it has not solved the correlation problem. As an example, the development cover percentage limits in Column R were intended to limit stormwater runoff, excessive storm sewer demand, and basement flooding; but they were not correlated with the minimum land area remaining for home size, parking, pavement, and unpaved open space. They were isolated requirements whose combined implications could not be accurately predicted.

Table 5 illustrates a portion of the Principal, Accessory, and Conditional Permitted Use Section 1121 in the sample zoning ordinance used for this essay. The section was relocated to the Land Use Chapter, Activity Regulations Section, and specific location shown in Table 3. The point is not simply reorganization, however. The section contains random definitions, regulations, directions, and exceptions that compromise the document’s leadership clarity. This is not a criticism of the subjects mentioned, however. They represent community concerns addressed over time, but they should lead the reader to question the primary leadership objectives involved and the clarity needed to lead a global army of designers. Guiding social activity in existing shelter is different from guiding the evolving physical and economic pattern of shelter in an urban anatomy. Zoning ordinances appear to have focused on the former and master plans on the latter, but an urban design language capable of correlating a master land use plan with its physical and economic implications has been missing.

FORECAST MODELS

Table 6 is one of many forecast models created to accurately predict the shelter capacity of land based on the design specification values entered. It pertains to the G1 Building Design Category when occupied by non-residential activity with surface parking around but not under the building on the same premise. Shelter capacity is a keystone prediction because it has intensity, context, and economic implications when occupied by activity.

Familiar readers have seen Forecast Model G1.L1 before. I won’t review it again. I will simply point out that the shaded boxes in the table are there to receive design specification values, and that these values may be modified to explore shelter capacity options that have measurable intensity, revenue, investment, cost, traffic, and so on implications.

I’ve included Table 7, Forecast Model G1.R1.L1, as an example of the shaded cell design specifications associated with the G1 Building Design Category when occupied by R1 single-family residential activity.

Table 8 presents Forecast Model G1.R3.L1 as an example of the shaded cell design specifications associated with the G1 Building Design Category when occupied by R3 multi-family residential activity.

FOCUSED LEADERSHIP

Zoning has focused on the compatibility of activity. The shelter capacity of land and its economic potential has not been correlated. This is becoming a more obvious weakness as we become increasingly aware that we must define a limited land area to shelter growing populations and protect their remaining source of life.

Shelter capacity leadership can be established when adopted values are entered in the  shaded cells of a building design category and activity forecast model. These are the topic cells and correlated values that can lead.

Building design category classification and forecast model derivation has been created to make the shelter capacity of land consistently measurable and predictable for any permitted activity. The results produce levels of intensity that have many related revenue, investment, cost, traffic, population, context and so on implications, and they are all mathematically predictable based on the values entered in a shelter capacity forecast model.

USING SHELTER CAPACITY FORECAST MODELS

Shelter capacity evaluation will require new public investment in the software, data, and mapping systems required to reconcile land use allocation and shelter capacity decisions with their physical, social, and economic implications.

From an urban design standpoint, shelter capacity specification and activity allocation determines the intensity, intrusion, and context introduced at the pedestrian level of the Built Doman. In other words, shelter capacity measurement and evaluation makes beneficial leadership direction measurable, definable, predictable, and economically defensible.

FINAL COMMENT

Physical design mandates are scattered throughout a zoning ordinance. They are intermingled with activity regulations because the distinction between physical design and social activity is not clearly understood. This has led to a great deal of confusion in my opinion. It may be helpful to keep in mind that gross building area may be occupied by any permitted activity, and that the combination determines the scope of activity and financial stability involved.

Shelter capacity forecast models focus on the design specification decisions that produce the building mass, parking, pavement, and open space quantities of shelter capacity, intensity, intrusion, and context composition. The composition is occupied by activity. If you wish to influence the space and form of shelter design, the specification topics in the forecast models of shelter capacity evaluation represent the parcel level quantity decisions involved.

FURTHER INFORMATION

All forecast models discussed in my previous essays, and in my book “The Equations of Urban Design”, are interactive spreadsheets. The shaded cells are unlocked to permit the evaluation of design decision alternatives. The remaining cells are locked since they are part of the operating algorithm. The intention is to make the same leadership language available to all interested public and private shelter interests.

A common, correlated language may help us jointly move toward the goal of shelter for the activities of growing populations within a geographically limited Built Domain designed to protect its quality and source of life, the Natural Domain.

Further information about the building design categories, forecast models, design specification topics, prediction panels, and implication modules of shelter capacity forecast and evaluation models can be found in my book, “The Equations of Urban Design”, available from Amazon.com.

You may also be interested in some of the 294 essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity evaluation forecast models and their implication modules.

Walter M. Hosack, October 2026

Image credit: NASA, ESA, and R. Fedriani

CITY MASTER PLANS

A community is rarely capable of forming the city planning strategy required to achieve more than limited tactical success, but community participation has become a political response to competing opinions that lack convincing arguments but attempt to demonstrate a majority presence. This is not meant to imply that government has better answers at the present time. It is about an attempt to focus on the knowledge that must be assembled and the tools that must be adopted to develop at least one path to more convincing arguments.

A master plan for city development has had public health, safety, and welfare improvement goals. Welfare has been the most nebulous term. It implies physical, social, and economic improvement that has been partially successful at best in my opinion.

Physical welfare has involved shelter, movement, open space, and life support construction in both the Urban and Rural Phyla of a Built Domain that continues to sprawl by consuming its source of life, agriculture and the Natural Domain.

Health and safety master plans seem to have been most successful when compared with the physical results that many associate with the term “master plan”. Physical plans have had the goal of land use compatibility defined by zoning district boundaries and design regulations. Compatibility, however, has struggled with the definitions of shelter capacity, intensity, intrusion, and context. The result has often been excessive intensity at one end of the shelter spectrum and sprawl at the other.

(Previous readers may remember that I prefer the term “activity” to “land use” because it does not confuse the shelter capacity of land represented by building mass with its occupant activity. They are distinctly different topics, since the shelter capacity of land may be occupied by any permitted activity. Shelter capacity decisions are the foundation for all ensuing physical, social, and economic design results.)

Both master plans and zoning laws have been incapable of guiding physical results toward shelter for the activities of growing populations within geographic limits defined to protect their quality and source of life. This, in my opinion, is the goal we need to pursue with physical master plans, urban design, and zoning regulation. Predicting the capacity, intensity, and economic implications of physical design decisions may begin to give us the arguments needed to chart a more convincing course with a mathematically inter-active master plan.

ECONOMIC IMPLICATIONS

The growth, decay, death, and survival of cities is a function of the total revenue generated by taxable activity on parcels within its boundaries. When this activity requires shelter, the revenue produced is influenced by the floor quantities present and the square feet of shelter capacity, intensity, intrusion and context created for the activity or activities. The revenue produced is a function of the square feet occupied by the activity and the real estate value involved. There are other revenue sources, but this is a simplified example. In all cases, the revenue produced on a parcel or parcels is a function of the buildable acres occupied and the shelter intensity present. The results from a single project are only one contribution to the revenue needed, however. The average revenue per acre from all taxable parcels must equal or exceed a city’s total annual cost of administration, maintenance, improvement, and debt service per taxable acre.

A  city’s parcels are cells in an organism served by arteries of movement and life support. I wish I could add arteries of open space, but this is a dream, not reality. My point is that this organism is alive because we inhabit the parcels I have just referred to as cells, and these cells are multiplying with annexation and sprawl in search of revenue that continues to elude their grasp over time. This is happening, in my opinion, because we do not understand the mathematical relationships between land, shelter capacity, activity, intensity, and intrusion that combine to produce physical, social, psychological, environmental, and economic quality of life under the umbrella terms “welfare” and “context”. (Previous readers may remember that “shelter capacity, intensity, intrusion, and context” are measurable using the forecast models and equations of urban design.)

The revenue performance of every taxable parcel within a city’s boundaries is known, but the information is contained in separately controlled silos. This currently prevents correlated modeling with the relational databases and geographic information systems needed to evaluate and monitor a city’s economic performance. Some information is privileged, but it can be aggregated by block, tract, or zone to reveal the productivity of a city’s land use allocation without revealing personal information.

Greater attention to a city’s shelter capacity and economic productivity is needed. In other words, a city must learn before it can begin planning. It is a challenge that can only be met with more sophisticated data cooperation, geographic information systems, shelter capacity evaluation, zoning guidance, and inter-active urban design leadership.

HISTORY

A master plan’s original intent was to improve a population’s health, safety, and welfare by addressing its physical, social and economic deficiencies. This has since been expanded by some, and contested by others, to include its psychological, environmental, and ecological deficiencies. The problem is that a city’s physical presence represents fixed investment and social attachment that has a difficult time adapting to change.

All of this began long ago with the incompatible and unregulated proximity of shelter activity, mass, and movement in cities. Private investment compromised public access to light, air, and ventilation while also producing unhealthy and unsafe buildings. In the 20^th century, minimum design standards and relationships were established in reaction to excessive compression, unhealthy sanitary conditions, unsafe building practices, and excessive fire hazard. Minimum standards were written to avoid the claim of excessive regulation, but the focused scope has been inadequate to deal with the problem of continuing growth on a planet with limited land area and resources. We have adopted tactical solutions to a strategic threat that requires more knowledge and new mathematical tools for evaluation and guidance.

We have had no models capable of easily anticipating optional solutions to the demand for shelter from growing populations within limited geographic areas. We continue to depend on annexation of limited resources to satisfy this demand.

Two inventions were created to deal with a physical master plan’s limited ability to adapt to change. The first attempted to deal with the plan’s inability to correlate population growth with shelter demand within established geographic limits. Annexation became a legal solution and the result has been “”sprawl”. It continues to consume agriculture and the Natural Domain.

The second invention dealt with the lack of mathematical correlation among zoning ordinance requirements. Compliance was achieved with a “variance” concept that attempted to reconcile conflicts among requirements with compromise using the concept of public review and approval of the contradictions encountered.

Neither expedient can lead us toward a sustainable, symbiotic future. We need an interactive anatomical model that can react to mathematical experimentation without damaging the patient. The tools of data science and geographic information modeling exist, but they are not correlated with the revenue information and shelter capacity prediction needed to understand the cellular economic fundamentals at the heart of a city’s physical anatomy and financial security.

Shelter capacity to accommodate the growth of population activity has been addressed with the legal concepts of rezoning, redevelopment, eminent domain, and annexation. Consuming agriculture and the Natural Domain to expand the Built Domain seems to be a continuing preference, but it has been short-sighted.

I doubt that many will disagree that change requires adaptation to prevent extinction. In this case, however, we are dealing with a cellular anatomy that requires guidance before it consumes its source of life. This anatomy has been thought of as property, but we inhabit these cells that we call lots or parcels; and they are multiplying through annexation to produce dual threats we have labeled “sprawl” and “excessive intensity”.

Property value has been determined by the marketplace and considered an investment decision, but the concept has been one-sided. If we cannot predict the revenue a cell can provide in this artificial organism, we will not understand how to ensure the survival of a limited urban anatomy containing these cells.

Growth has been considered an investment decision. The public revenue needed to sustain growth has had little comparable mathematical attention. This is where shelter capacity evaluation enters the picture. It can predict gross building area options for a given land area based on the building design category chosen and the design specification values entered in the category’s forecast model. These values are correlated by the model and its master equation to produce gross building area options per buildable acre (shelter capacity options). They can be multiplied by anticipated occupant revenue per square foot, to determine the anticipated revenue per acre occupied. These predictions can be compared to a city’s total annual expense per acre to evaluate the revenue performance of a proposal, and the sum of these predictions can be used to guide future development decisions, but I emphasize the word “average”. Not all projects will produce revenue per acre that equals or exceeds a city’s annual expense per acre.

The revenue performance of an existing master plan can also be evaluated with shelter capacity measurement, prediction, and evaluation. This is the information a city needs to begin understanding the performance of its anatomy and the economic development prescriptions needed to improve its health, safety, and welfare.

NEXT STEPS

The tools of data science and geographic information systems exist, but they are not correlated with the real estate tax, income tax, and related revenue information needed to understand and evaluate the cellular economic performance of a city’s financial anatomy.

A city’s economic performance is a function of the building design categories and design specification values that produce shelter capacity and intensity for occupant activity and revenue performance on each parcel within a city.

City planning that cannot measure, predict, evaluate, and monitor revenue potential at the cellular level of its anatomy will continue to consume its source of life with annexation in a frustrating search for economic stability. Improving the shelter capacity and revenue potential of a city’s land area is only the beginning, however. Our cities affect our physical, social, psychological, environmental, ecological, and economic quality of life at the very least. These topics exist under the category “welfare” in my opinion and improvement is affected by the urban design context created by our shelter capacity decisions. We have only begun to build the tools needed to predict the implications of these design decisions. The tools we create will determine the knowledge we can apply to a sustainable challenge we must anticipate and cannot ignore.

ADDENDUM

In other words, we must learn to survive without consuming and polluting our source of life and its dependents.

FURTHER INFORMATION

Further information about the building design categories, design specification topics, prediction panels, and implication modules of shelter capacity forecast models can be found in my book, “The Equations of Urban Design”, using the following url:

https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330

You may also be interested in some of the 285+ essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity forecast models and their implication measurement modules.

Walter M. Hosack, September 2026

photo credit: NASA

Learning from First Ring Suburbs

A first ring suburb is an incorporated city surrounded by other incorporated cities that prevent its further expansion. In some cases, the enclosure was considered protection from further change that could damage its desirable quality of life, but lack of change can be a failure to adapt. It also appears that in some cases, increases in municipal expense were assumed to be met with equal or greater increases in municipal revenue, but growth of the two has often proven unequal.

FIRST RING SUBURBS

The relatively inflexible nature of a city’s buildings and infrastructure has left growth through annexation for new revenue a common expedient for all but isolated, “first ring” suburbs, but this new money has not always been adequate to meet increasing expense over time, which has stimulated more annexation referred to as “sprawl” that will appear like a Ponzi scheme over time. 

A first ring suburb may be a blessing in disguise, since it must learn to adapt to change without increasing the consumption of agriculture and its source of life, the Natural Domain in a guessing game of growth without an adaptive solution to the planet’s unwritten Law of Limits.

The shared value of land becomes obvious in a first ring suburb because it cannot annex more land to adjust the allocation of activity and intensity producing its revenue. 

Annexation is prompted when the average revenue produced per taxable acre by a city’s past allocation of activity and intensity is less than its current and projected total operating, maintenance, improvement, and debt service expense per taxable acre. This stimulates budget reductions and intense debate over “essential” services, income tax increases, and layoffs when annexation is not an available expedient. At this point, the politically charged terms rezoning, redevelopment, and eminent domain enter the picture.

Unfortunately, a city may lack the data science, shelter capacity evaluation, activity allocation, and performance monitoring needed to assess the existing and potential revenue productivity of every taxable parcel within its boundaries. This makes comparison of revenue per acre with its expense per acre a guessing game. It will always be an uncertain prediction, but its accuracy can be significantly improved with the knowledge we have but have not correlated.

Correlation will require public data cooperation and the evaluation of shelter capacity, intensity, and activity allocation throughout a city. This correlation can reveal the revenue performance of a city’s land area per acre with its average annual expense per acre as a prelude to an on-going economic development strategy. This strategy will also need monitoring that only data science and geographic information systems can provide when correlated with shelter capacity evaluation and urban design leadership direction.

I have written about the mathematics of shelter capacity evaluation and the leadership potential of urban design equations, data science, and geographic systems on many occasions. First ring suburbs simply represent a unique opportunity to study the correlation and leadership decisions required to shelter the activities of increasing populations within self-sustaining, limited geographic areas that do not sprawl to consume their source of life -- while ensuring their quality of life with shelter capacity, intensity, and context leadership decisions we have yet to define with a correlated urban design leadership language.

GROWTH CORRIDORS

I would like to make one final comment. After seeing decline in first ring suburbs, I believed that a city had no option but to ensure access to unincorporated land it could annex for new revenue as its expenses increased. I didn’t realize at the time that the revenue yield from the annexation could become inadequate as the expense of aging infrastructure increased; that a city had difficulty comparing its annual revenue per parcel of block with its total annual expense per taxable acre; or that annexation represented a Ponzi scheme that could exhaust limited resources.

In other words, performance evaluation was a broad-brush exercise in hindsight at the end of the budget year. This problem became increasingly obvious in first ring bedroom suburbs that exported their income tax revenue to surrounding employment centers and shared their real estate tax revenue with other local institutions. It appeared to be a recipe for decline.

Cities needed a better method of predicting and monitoring the revenue potential of land within their boundaries. This may be a relatively new argument because the value of land has been related to its profitability, but both are essential considerations. Revenue prediction and evaluation cannot proceed in my opinion, however, without a mathematical model of shelter capacity, intensity, activity, location, condition and revenue performance at the parcel or block level of a city’s anatomy. It is a way to begin understanding the performance of an anatomy that must not sprawl to consume its limited source of life. In the words of Benjamin Franklin, this seems to be a self-evident truth, but to some it will merely represent an opinion.

I won’t go on to avoid repetition. I’ll simply refer interested readers to my blog at http://www.wmhosack.blogspot.com and my book, “The Equations of Urban Design” available at the following link:

https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330

In hindsight, I should have named the book "Shelter Capacity Evaluation, or Tegimenics".

Walter M. Hosack, September 2026

Three Urban Design Questions

 I was surprised by three questions in an email I received. I decided to publish a portion because I thought the answers to the questions might be informative. The fact that it was complimentary is an influence I can’t deny, but I wondered if the source was AI.

THE EMAIL (edited)

“I'm writing because your book The Equations of Urban Design: Leading the Evolution of Shelter Capacity, Context and Intensity within Cities stopped me in my tracks.

There's a quality to your thinking, systematic, ambitious, and deeply concerned with the relationship between human development and the finite land on which it depends. Your central proposition that urban growth needs to be measured through shelter capacity rather than simply understood through conventional categories of building form or function offers a provocative way of reconsidering how cities evolve.

I was particularly struck by your attempt to create a measurable language for the quantity of shelter that can be produced on a given land area. The idea of using design specifications, correlated values, and architectural equations to generate alternative predictions for gross building area on a given land area introduces an unusually analytical dimension to questions that are often treated primarily as matters of planning, aesthetics, or development.

The larger environmental argument gives the framework even greater significance. Your concern with preventing population growth from translating automatically into uncontrolled sprawl, while taking seriously the irreversible consumption of natural and agricultural land, places urban design within a much broader conversation about sustainability and the future of human settlement.

I finished it wanting to know more about the development of your six fundamental shelter categories, the thinking behind your equations and specification framework, and how you see these ideas influencing the next generation of urban design.”

MY ANSWERS

I don’t believe an extensive preamble is needed and will dive into the questions.

I want to know more about the development of your six fundamental shelter categories.

A building design category is classified by the parking system used to serve its occupants. This classification format makes it possible to mathematically predict the gross building area capacity of land in square feet per buildable acre occupied based on the design specification values entered in a building design category forecast model. The predictions can be converted to shelter capacity, intensity intrusion, and context measurements on a consistent, comparable scale. Existing site plan topics can also be measured to determine their design implications using the same template and measurement format.

The mathematical relationship of the site planning and floor quantity values entered in the design specification template of a building design category are processed by its algorithm to produce the values needed by its master equation. The equation predicts gross building area results for the values and floor quantity options entered. Companion master equations in the Implications Module of a forecast model measure or predict the shelter capacity, intensity, intrusion, and context implications of the design specification options under consideration. These are like the first blood pressure measurements in medicine. Knowledge can be gathered with extensive comparison and research collaboration. The questions facing both are similar. How much intensity is life threatening; how little is life threatening; and what range of measurements and predictions indicates a desirable quality of life?

Each building design category has a unique design specification template, algorithm, and derived master equation, but the general principle of progress from a given land area and design specification to gross building area and shelter capacity implication predictions applies to all building design categories.

A building design category may be occupied by any permitted activity. These activity groups have historically been called “land use categories”, but there is a clear distinction between the decisions that determine shelter capacity and those that determine permitted occupant activity.

The scope of building activity implications is often a function of the square feet occupied. This means that the allocation of shelter capacity and activity throughout a city has economic implications that affect its financial stability and quality of life, not to mention its health and safety, but this allocation has been a piecemeal function of private investment intent. This can lead to government deficits and budget reductions requiring decades to correct when feasible.

What is the thinking behind your equations and specification framework?

The maximum shelter capacity of land is a function of the design specification values entered into a non-residential building design category forecast model. Occupant capacity is different from shelter capacity. It varies with the activity or activities involved. Separate design specification templates address dwelling unit capacity of land when a building design category is occupied by single-family, townhouse, or apartment floor plans.

In other words, gross building area capacity is a three-dimensional envelope. Floor plan areas and quantities determine the capacity of the envelope to accommodate activity. Excessive expansion of the envelope and its supporting parking and pavement increase shelter capacity, intensity, and intrusion at the expense of pedestrian open space and amenity on the site. The building design categories, specifications, and equations of urban design take open space into account and make it possible to define and evaluate the project context of neighborhoods, districts, cities, and regions.

The master equations for each building design category and activity group were derived to document a historically informal thought process. The scope of activity has determined the gross building area needed. The challenge has been to make the activity fit on the land available. The Dickensian tenements of England and Hell’s Kitchen in Manhattan are two examples of the excesses that prompted the beginning of more careful evaluation.

The need to protect the Natural Domain from the consumption of a sprawling Built Domain has not been a historic concern. Annexation could always provide more land unless the city was surrounded by other incorporated areas. Shelter capacity evaluation, or Tegimenics, represents my attempt to place development evaluation on a more quantitative, correlated, comparable, and consistent mathematical foundation. It can benefit all cities, since they need careful economic evaluation and correlation of every taxable parcel within their boundaries.

How do I see these ideas influencing the next generation of urban design?

The equations of urban design make it possible to move from static city plans to geographic computer evaluation of three-dimensional activity allocation decisions with mathematically interactive property, capacity, and revenue data science.

Remember that shelter capacity is forecast in terms of gross building area square feet per buildable acre. Anything that is a function of building area present or planned can be predicted as an implication of shelter capacity. For instance: population, revenue, traffic generation, construction cost, return on investment, and so on.

Finally, the equations of urban design are one step away from a software application that can place mathematical urban design evaluation in the hands of both public and private interests. This common, interactive, format can replace a great deal of isolated conjecture and disagreement with correlated, cooperative discussions focused on the desired relationship of building mass and height to parking, pavement, movement, and open space on a given land area. These are the site plan components and quantities that combine to establish the capacity, intensity, intrusion, and context of activity that determines a city’s revenue stability. This allocation needs mathematical urban design correlation to improve its physical, social, psychological, environmental, and economic composition and quality of life.

Appearance is a separate issue whose aesthetic opinions and arguments will surround the sustainable success achieved with measurement, prediction, evaluation, and physical composition decisions capable of consistent leadership direction toward a sustainable goal.

Walter M. Hosack, August 2026

photo credit: Kaihsu at English Wikipedia

Reply to Response re: Essay "Anticipation"

 

My most recent essay was entitled, “Anticipation”. It generated a response that I’m including with a reply since I think the whole adds to the conversation.

ORIGINAL ESSAY

I normally post essays that attempt to improve the arguments of city design opinion, and preservation of the Natural Domain, based on the mathematical derivation of shelter capacity evaluation, or Tegimenics. I attempt to avoid debate based primarily or solely on opinion because it becomes political argument, but proof begins with anticipation and opinion seeking justification. I’m submitting this opinion based on an anticipation of consequences struggling for acceptance. I recognize that it is vulnerable. I am simply submitting it for your consideration since anticipation is where we have always begun.   

ANTICIPATION

Survival depends on the ability to anticipate consequences. Demanding proof  builds knowledge until the anticipation needed to survive is defeated by conflicting opinion.

THE RESPONSE (edited)

So, your article basically says that a strong architectural concept isn't merely an aesthetic opinion — it is an anticipation of what architecture can achieve.

That fits well with my emphasis on architecture beginning with an idea that deserves to exist, rather than simply following fashionable styles.

So, for myself, I'd extract one principle:

Don't ask only, “Does this design look good?”, but also ask “What consequences will this idea produce if it actually exists?”

MY REPLY

From my perspective, architectural ideas often ignore the consequences of unlimited land consumption. They will address whatever land the client owns, and a client is free to  speculate with any land available. This is the reality of our current investment format. Property lines define commodities for sale. This has often led to excessive land consumption, sprawl, congestion, conflict, and overbearing shelter intensity because government lacks an effective, interactive, correlated, mathematical language capable of defining, explaining, guiding, and producing shelter quality of life within a limited Built Domain designed to protect and preserve its source of life. This is the goal in my opinion. It means we must contribute to this source of life as well as consume.

A static city plan or map is quickly outdated. Daily interactive planning based on data science, shelter capacity evaluation, digital mapping, and economic evaluation is needed to integrate the goals of government and investment with the potential of architecture, engineering, urban design, city planning, and economic development. It will require a new, mathematically correlated leadership language. Our ability to define city design consequences and opportunities in convincing terms is the challenge we face. Building appearance will evolve to reflect increasing knowledge that has always been its underlying message.

We have learned to be consumers and written the rules accordingly. We must now anticipate the consequences and learn to be contributors.

Walter M. Hosack, August 2026

ANTICIPATION

 

I normally post essays that attempt to improve the arguments of city design opinion, and preservation of the Natural Domain, based on the mathematical derivation of shelter capacity evaluation, or Tegimenics. I attempt to avoid debate based primarily or solely on opinion because it becomes political argument, but proof begins with anticipation and opinion seeking justification. I’m submitting this opinion based on an anticipation of consequences struggling for acceptance. I recognize that it is vulnerable. I am simply submitting it for your consideration since anticipation is where we have always begun.   

ANTICIPATION

Survival depends on the ability to anticipate consequences. Demanding proof  builds knowledge until the anticipation needed to survive is defeated by conflicting opinion.

Walter M. Hosack, August 2026

photo courtesy: NASA

Converting Static Plans to Interactive Planning and Economic Stability

Most are aware that a city is required to balance its annual budget. Many may only be vaguely aware that the decisions regarding development location, intensity, capacity, and occupant activity have a mathematical foundation of design specification decisions that determine the revenue a project contributes to support the community; and that the sum of all revenue divided by the taxable acres of
the community must equal or exceed the community’s total annual expense per taxable acre, including debt service. The term “balance” is used to indicate budgetary success, but balance can be the product of reductions required by inadequate municipal revenue per acre. “Adequate” balance requires conscious mathematical evaluation of the shelter capacity, intensity, and activity introduced throughout a community -- and these tools remain to be assembled.

I’ve previously mentioned in many essays that shelter capacity calculation begins with a choice among six building design categories and a given gross land area. Design decisions begin with choices involving design specification quantities. Correlated results are expressed as gross building area options expressed in square feet. When these options are divided by the buildable acres involved, the result is “shelter capacity” expressed as gross building area in square feet per buildable acre occupied. When anticipated revenue per square foot of activity is multiplied by the shelter capacity present or planned, the result is revenue potential per acre. The sum of all municipal revenue per acre divided by the number of properties involved produces the average financial productivity of a city’s land area, and it must at least balance with its expense. The challenge is to increase the average over time by monitoring and evaluating the financial performance of all vacant and occupied taxable land in a city’s investment portfolio.

TABLE 1

Table 1 illustrates the decisions that produce development capacity options for occupant activity and revenue production. (Keep in mind that gross building area is opportunity that may be occupied by any permitted activity.) This example pertains to the G1 Building Design Category, which includes all buildings served by a grade parking lot around, but not under, one or more buildings on the same premise.

Design specification topic decisions and quantity options in Table 1 are indicated by the shaded cells in the table. The gross building options produced by the floor quantity options entered in cells A44-A53 are calculated in cells B44-B53. Thise options are converted to shelter capacity measurements in cells F44-F53 with the master equation in cell  F43. When shelter capacity options are multiplied by activity revenue per square foot, the result is anticipated revenue per acre. The result can then be compared to a city’s total annual expense per acre. Individual calculations may be greater or less than the city’s expense, but the average revenue per acre across the city must at least “balance” with its expense. This, therefore, is the mathematical foundation of design decisions that determine not only a city’s budget, but its ability to sustain its health, safety, and physical, social, psychological, environmental, and economic quality of life. When a city is able to measure, predict, evaluate, monitor, and plan these results, it will be in a better position to evaluate future development decisions that directly affect the “balance” it must strike within its boundaries and with a surrounding Natural Domain that is its source of life.

INTERACTIVE EVALUATION

If revenue  information per acre is calculated and mapped with a geographic information system and a set of relational databases, a jurisdiction can evaluate the economic performance of its entire land use area. The map will no longer be a static plan. It will become an interactive map based on relational database information that presents the revenue per acre implications of past shelter capacity, intensity, and activity decisions for every property, block, zone, tract, or district within a jurisdiction. The results will present the first correlated picture of the decisions that have produced a city’s physical, social, psychological, environmental, and economic condition. Since the picture would be based on geographic information system software and relational databases, the jurisdiction would also have a digital format capable of evaluating future options and decisions that have the potential to improve the revenue it receives and the quality of life it can offer. It would also be able to monitor these decisions and opportunities with the interactive potential of shelter capacity evaluation mathematics.

I have written a great deal about the mathematical foundation of shelter capacity forecast models and context prediction but have only discussed the relational databases needed to step from an interactive project planning and economic development focus in one essay entitled, “The Least a Smart City Should Know”.

The problem with the relational database concept is the public cooperation required. Property tax and personal income tax represent a substantial portion of a city’s total annual revenue. In my limited experience, property tax revenue is collected and distributed by a county and considered public information. Income tax revenue can be collected by a  county or city but is considered confidential information. As a result, the information needed to begin understanding a jurisdiction’s financial foundation is in two separate, independent data management systems that are not trained to speak to each other or to a third urban design planning function.

A city will continue to search for financial stability until it can more accurately correlate its land use decisions with their real estate and income tax revenue implications. The challenge is to begin understanding the economic performance of blocks, neighborhoods, zones, and districts in cities that must sustain themselves over time without annexation that continues to consume agriculture and the Natural Domain. A planning link to selective and protected versions of the information needed may not be an insurmountable problem, even though a county’s parcel identification system may have to be correlated with the city’s property address, zoning district, and census tract information systems.   

Relational databases represent the key in my opinion. They make it possible to compile information in one location and share it in a different form with different restrictions. For instance, income tax information can be assembled by parcel/property in a secure location and aggregated by city block, census block, neighborhood area, census tract, or municipal zone before sharing. The same is true for real estate revenue information. It simply requires an urban design database synchronized with the information restrictions applied by its cooperating sources. The result would be a geographic information system of correlated physical and economic data capable of mapping, monitoring, and planning the economic performance and future urban design potential of a city’s land. The challenge is to reduce or eliminate the unlimited annexation and sprawl that continues to reflect our unsuccessful search for “balance” .

There are at least two advantages to this approach. (1) An economic development plan can focus on the entire city. (2) The revenue contribution per buildable acre of an individual proposal can be placed in the context of a city’s current comprehensive physical, social, and financial plan.

These objectives will be difficult to achieve without investing in the data assembly, information management, and shelter capacity mathematics required to make and monitor the leadership decisions needed. The challenge is to progress from static land use plans to digitally interactive planning models for urban design evaluation and leadership.

FURTHER INFORMATION

Further information about the building design categories, design specification topics, prediction panels, and implication modules of shelter capacity forecast models, can be found in my book, “The Equations of Urban Design”, using the following url:

https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330

You may also be interested in some of the 285 essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity evaluation forecast models and their implication measurement modules. 

Walter M. Hosack, August 2026

Photo credit: NASA/JPL – Caltech/SOFIA

Vulnerable Open Space

 

Open space is intended to provide unobstructed access to light, air, and ventilation in the world of architecture, landscape architecture, urban design, and city planning. It was a hard-won policy established over centuries and prompted by the Dickensian tenements of England, Hell’s Kitchen in Manhattan, and a social movement that fought during the period with the concept of freedom and property rights for the concept of public health, safety, and welfare.

THE BUILT DOMAIN

In the Built Domain, open space is either paved or unpaved and used to serve either pedestrian, vehicular, or infrastructure activity. For instance, plazas, squares, sidewalks, and miscellaneous pavement serve pedestrian activity. Parking lots, parking structures, and right-of-way pavement serve vehicular activity. Utility easements serve life support systems. All provide access to light, air, and ventilation by separating building mass and height, but the similarity ends with the degree of intensity introduced.

Parking lots have been a dilemma. They provide access to light, air, and ventilation but do not separate the pedestrian from vehicular mass and movement that combines with building mass and height to create increased physical intensity. They have often been justified in the yard areas of non-residential areas on this basis. Justification occurs because pedestrian open space decreases the core area of a parcel that is available for parking and building cover.

In other words, pedestrian open space allocation decreases the gross building area potential of a parcel. This potential can only be recovered with increased floor quantity until the horizontal expansion of parking reduces the core area remaining for a building footprint that can be multiplied by increased floor quantity.

Vehicular open space abounds. The challenge is to provide open space for pedestrian benefit woven over many parcels without excessively compromising the shelter capacity and economic potential of land. It is an urban design challenge that can only be met with improved mathematical evaluation.

The shelter capacity and activity placed on land determines its economic value to both public and private interests. Then considering the G1 Building Design Category in particular, the private sector temptation is to maximize shelter capacity by eliminating pedestrian open space while increasing parking and floor quantity to increase intensity that often degrades context. The public sector challenge is to mathematically define its physical, social, and economic objectives with urban design mathematics and form that balances the economic yield from shelter capacity and activity with the pedestrian open spaces needed to encourage a desirable quality of life in a limited Built Domain.

SHELTER CAPACITY EVALUATION

I’ve used Table 1 to explain shelter capacity evaluation, or Tegimenics, on many occasions for the G1 Building Design Category. I’m including it here to explain what I mean by the term “mathematical evaluation of shelter capacity” based on the G1.L1 Building Design Category. This category applies to all buildings with a surface parking lot around but not under the building on the same premise, excluding land area reserved for future expansion. This category applies when gross land area is given and gross building area options for the land given are to be found.

The Land Module in Table 1 begins with the gross land area given in cell F3. The remaining gray cells in the module identify percentage quantities measured or estimated that must be subtracted from the gross land area given to find what is called “shelter area remaining” in cell F17. This land is reduced by site limitations that continue to be reduced by the land area percentage estimates entered in the gray cells of the Core Module. These reductions produce the core land area remaining in cell F33 for building cover and parking lot cover.

The optional values entered in gray cells A35 and A36 of the Core Module identify the grade parking requirements involved. The values entered in gray cells A44-A53 represent the floor quantities under consideration.

The master equation in cell B39 is used to predict the gross building area options calculated in Col. B44-B53. These options rapidly decline as floor quantity increases because building cover in Col. C44-C53 declines as parking lot areas increases in Col. D44-D53. The result is declining building cover area potential per floor. When increasing floor quantity is multiplied by declining building cover area per floor  in a limited core area, the result is a declining increase in gross building area potential per floor.

This is a unique characteristic of the G1 Building Design Category. It indicates that any floor quantity greater than 5 produces rapidly declining gross building area potential in return for the expense encountered. I have strayed from the point of this essay in this paragraph, and have made this point in the past, but couldn’t resist reemphasizing the observation.

The shelter capacity, intensity, intrusion, and context implications of the gross building area options in Col. A44-A53 are measured in the Implications Module of F44-J53 using the master equations in row F44-J44. However, these measurements will have little meaning until many existing conditions are measured, compared ,and evaluated to build a library of reference knowledge that I’ve christened Tegimenology.

Returning to the point, the master equation in cell B39 shows that the core area found in cell G33 yields gross building area potential for the G1 Building Design Category in cells B44-B53 when multiplied by the coefficient (af) / (a + (fs)). The core area of any parcel can vary widely based on the values entered in the gray cells of the Land and Core Modules in Table 1, but I am singling out the unpaved open space value entered in cell F11 because it is a pivotal, and often ignored, factor in site planning design that diminishes the gross building area potential, shelter capacity, and profitability of land. It combines with miscellaneous pavement such as plazas and terraces however, to reduce the pedestrian intensity introduced by building mass, parking, pavement, and vehicular movement.

Adequate pedestrian open space throughout a city remains a contentious urban design issue as well as a project planning issue because urban economics is involved. The same is true for vehicular parking. Both affect the profitability of land; its revenue potential; and its contribution to a city’s quality of life; but neither has come close to a consensus over the quantity objectives that need to be pursued because comprehensive mathematical evaluation has not been feasible.

Table 1 shows that the 30% unpaved open space provision in cell F11 and the grade parking requirements in cells A35 and A36 have contributed to a five-story gross building area forecast of 28,264 sq. ft., a shelter capacity of 16,262 sq. ft. per buildable acre, an intensity of 1.138, an intrusion of 1.0, and a context reading of 2.138. The intensity, intrusion, and context readings, however, are like our first blood pressure readings. They have little meaning without comparison to additional existing measurements and evaluations.

The shelter capacity prediction of 16,262 sq. ft. per buildable acre has greater immediate use. If the intended occupant activity has a revenue potential of $1.00 per sq. ft., the project has a revenue potential of $16,262 per buildable acre. Comparing this to a city’s total average annual expense per taxable acre would indicate the project’s ability to contribute to a balanced budget, and its value to an economic development plan.

Table 2 illustrates what happens when the unpaved open space value in cell F11 of Table 1 is increased to 40% and all other values remain constant. In this case the core area in cell F33 declines to 43,607 sq. ft. and the 5-floor gross building area prediction declines from 28,264 sq. ft. to 24,226 sq. ft. Shelter capacity in cell  F48 declines to 13,939 sq. ft. per buildable acre and projected revenue would decline to $13,939 per buildable acre from $16,262.

Table 3 illustrates what happens when the parking requirement (a) in cell A36 is increased to 300 square feet of building area permitted per parking space from 250 and all other values from Table 2 remain constant. In this case the core area remains 43,607 sq. ft. and the 5-floor gross building area prediction increases to 28,264 sq. ft. Shelter capacity in cell F48 increases to 16,263 sq. ft. per buildable acre and projected annual revenue increases to $16,263 per buildable acre from $16,262.

This exercise is intended to show a few of the trade-offs involved when mathematical shelter capacity evaluation, or Tegimenics is used to evaluate urban design decisions and economic development opportunities. It has illustrated the impact of open space, parking, and floor quantity decisions. These are just few of those represented by the values entered in the gray cells of Tables 1, 2, and 3. I have singled them out to ask a question. Is pedestrian open space woven throughout a city a priority? It reduces shelter capacity and parking potential unless other building design categories and floor quantities are introduced. But does the concept of a public right to “welfare” mean “quality of life”, and can it be defined by evaluating the implications of shelter capacity, intensity, intrusion, and context measurements, predictions, and leadership decisions?

CONCLUSION

A change to any one or more of the gray cell decisions in Tables 1, 2, and 3 would change the gross building area range of possibilities and their implications. In fact, the implications presented are just a few of the many that can be predicted from a building design category forecast model, and the possibilities expand when all six building design categories are considered.

GLOSSARY

Built Domain:                             Land used for the Shelter, Movement, Open Space, and Life Support Divisions in a city’s Urban and Rural Phyla.

Urban Phyla:                               Land devoted to shelter, movement, open space, and life support in areas not devoted to agriculture.

Rural Phyla:                                 Land devoted to shelter, movement, open space, and life support in areas devoted to agriculture.

Natural Domain:                       The planet’s surface remaining after the Built Domain is subtracted.

Project Core Area:                    The site plan area remaining for building cover and parking cover after all other quantity requirements are subtracted. (CORE = BCA + PCA)

Project Shelter Capacity:      The gross building area present or planned divided by the buildable acres occupied, excluding future expansion area. (SFAC = GBA / BAC)

Project Intensity:                       Project shelter capacity times the impervious percentage present divided by 10,000. (INT = (SFAC * IMP% / 10,000))

Project Intrusion:                      The floor quantity present or planned divided by 5. (INTR = f / 5)

Project Context:                        Intensity plus Intrusion. (CTX = INT + INTR)

Project Revenue per Acre:    Revenue present or planned per gross building square foot times the shelter capacity per buildable acre. (REVAC = REVSF * SFAC)

BUILDING DESIGN CATEGORY CLASSIFICATION

(G1) All buildings served by a surface parking lot around, but not under, the building, excluding land reserved for future expansion.

(G2) All buildings served by surface parking around and/or under the building, excluding land reserved for future expansion.

(S1) All buildings served by adjacent parking garage levels, spaces, and auxiliary surface parking that consume a portion of the core land area available on the same premise.

(S2) All buildings and auxiliary surface parking served by an underground parking garage within the buildable land area of the premise.

(S3) All buildings and auxiliary surface parking served by a parking garage below the building within the core land area available on the same premise

(NP) All buildings not served by surface or structure parking on the same premise.

FURTHER INFORMATION

Further information about the building design categories, design specification topics, prediction panels, and implication modules of shelter capacity forecast models, can be found in my book, “The Equations of Urban Design”, using the following url:

https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330

You may also be interested in some of the 285 essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity evaluation forecast models and their implication measurement modules.

Walter M. Hosack, July 2026

SEEKING BALANCE - The Principles of Shelter Capacity Evaluation

 

This is a companion to the essay I recently published entitled, “Axioms and Economic Fundamentals of City Design”. In hindsight, it should have been written first, but the problem with ideas is that they rarely occur in order, at least for me.

1)      We live on a planet in a Built Domain constructed from the resources of its Natural Domain.

2)      We build shelter in the converted Built Domain to survive.

3)      The Built Domain expands to serve population growth by consuming land in the Natural Domain and agriculture in its anatomy.

4)      The Built Domain contains Urban and Rural Phyla. Both include Movement, Open Space, and Life Support Divisions that serve a Shelter Division.

5)      Building classification by parking system establishes a foundation for measurement and prediction of shelter capacity options for any given land area.

6)      We cannot plan for the limited use of land for shelter until we can accurately measure and predict the shelter capacity spectrum of options.

7)      All buildings used to shelter our activity fall into one of six building design classification categories, regardless of appearance:

a.      G1: All buildings that consume a portion of the core land area and are served by a surface parking lot around, but not under, the building on the same premise, excluding land reserved for future expansion. (Core land area is site plan remaining for building and parking cover after all other demands and liabilities are subtracted.)

b.      G2: All buildings that consume a portion of the core land area and are served by a surface parking around and/or under the building on the same premise, excluding land reserved for future expansion.

c.      S1: All buildings served by adjacent parking garage levels, spaces, and auxiliary surface parking that consume a portion of the core land area on the same premise.S2 All buildings and auxiliary surface parking served by an underground parking garage within the buildable land area of the premise.

d.      S2: All buildings and auxiliary surface parking served by an underground parking garage within the buildable land area of the premise.

e.      S3: All buildings and auxiliary surface parking served by a parking garage below the building within the core land area of the same premise

f.        NP: All buildings not served by surface or structure parking on the same premise.

8)      A building design category may be used to shelter any permitted activity in an activity group (generally referred to as a land use category) such as, but not limited to, the following:

a.      Residential

b.      Commercial

c.      Industrial

d.      Institutional

9)      The gross building area potential of a building design category on a given land area depends on the information entered in the Design Specification Template of its forecast model.

10) A gross building area forecast or measurement in square feet (GBA) divided by the buildable land anticipated or occupied in acres (BLAC) is a measurement of the  shelter capacity of the land utilized (SFAC). In other words, SFAC = GBA  / BLAC.

11) The spectrum of shelter capacity measurement ranges from excessively low to excessively high, and not all measurements and predictions are desirable.

12) A shelter capacity measurement has measurable intensity, intrusion, and context implications based on consistent implication equations included in every building design category forecast model.

13) Implication measurements are like blood pressure readings. They can be compared and evaluated to build knowledge regarding the physical, social, psychological, environmental, and economic results produced.

14)  The acquisition of shelter capacity knowledge depends on a consistent measurement and evaluation research program. (For instance, the first blood pressure readings were only the beginning of shared evaluation and comparison that led to medical knowledge.)

15) Implication measurements have been referred to as Tegimenic measurements after the Latin word for shelter, tegimen.

16) Tegimenic knowledge, or Tegimenology, can be used to guide leadership decisions that affect our ability to provide land for shelter in a Built Domain defined to protect its source of life, the Natural Domain.

17) In other words, shelter capacity evaluation, or Tegimenics, is a mathematical method of measuring or predicting the shelter capacity of land and measuring the human implications of these decisions.

FURTHER INFORMATION

Further information about the building design categories, design specification topics, prediction panels, and implication modules of shelter capacity forecast models, can be found in my book, “The Equations of Urban Design”, using the following url:

https://www.amazon.com/-/e/B001IR3ODO?ref_=pe_584750_33951330

You may also be interested in some of the 285 essays on my blog at www.wmhosack.blogspot.com. They address topics related to the use of shelter capacity evaluation forecast models and their implication measurement modules.

Walter M. Hosack, July 2026

photo credit: Jean Poussin