Zoning Influence on Urban Context

 

I recently read some architectural compliments regarding the appearance of a building addition in London. I appreciated the extension of the original style as well, but one comment caught my attention since it addressed a topic that I have attempted to define for a long time. It remarked that, “…it’s all about context”. Since it was a multi-story building covering the entire parcel and surrounded by traffic, I thought the comment was perceptive but couldn’t see the context nearby, except for the traffic.

I do not separate appearance from the external context encountered but have long believed that the shaping of building mass, parking, pavement, and unpaved open space quantities within a site plan establish the foundation for all ensuing external and internal architectural context and style.

The land given for a development project has many shelter capacity options. A context decision can be defined by the building design category chosen and the values entered in its design specification template long before building form, function, and appearance are established.

A capacity option has intensity, intrusion, and context implications that can be predicted mathematically. They can also be measured at existing locations. Presently, we do not correlate shelter capacity calculations with the land area given. We simply determine if the client objective can fit. This has often produced context results intuitively referred to as either “sprawl” or “excessive intensity” in polite terms. The ambiguity of zoning has simply led to arm-wrestling matches in many cases.

As a student, I believed that style and appearance were adequate substitutes for context since sprawl and intensity were client decisions. It was a way to justify the limitations facing these decisions. I have long since agreed with the comment that it is all about context as we attempt to shelter the activities of growing populations in land areas that must be limited to protect their quality of life and our source of life. I would simply add that context results from the correlation of quantity values entered in a building design category template. These are the details that must be addressed to lead many toward context decisions that produce a desirable quality of life in limited land areas that protect their source of life.

INTRODUCTION

Merriam-Webster provided two definitions for “context” on the web.

1)      The parts of a discourse (emphasis added) that surround a word or passage and can throw light on its meaning.

2)      The interrelated conditions (emphasis added) in which something exists or occurs - environment, setting.

Neither definition is capable of physical design leadership. They describe a result from an experience that cannot be measured. Architecture, urban design, city design, city planning, and zoning attempt to create shelter context that sets the stage for a desirable social and economic quality of life, and it can be measured, evaluated, and led in the future.

ZONING

Zoning was the first attempt to define physical context with minimum regulations written to protect public health, safety, and welfare; but welfare has become a term often associated with social programs. In my opinion, the term was intended to mean quality of life for entire populations, but the physical context required could not be adequately defined. This is still the case since zoning regulations, as currently written, are too partial and contradictory to meet the context leadership challenge. The result has too often been sprawling low density development that consumes agriculture; excessive intensity on urban land of greater value in search of increased return on investment; and habitual annexation. I won’t defend this argument since I have discussed the issue in many previous essays.

We need leadership capable of measuring, predicting, and evaluating context options that can shelter the activities of increasing populations within limited land areas that protect their quality and source of life. This requires shelter context definition, measurement, evaluation, organization, design and regulation since sprawl and excessive intensity are not recipes for survival, and we cannot depend on private enterprise to reach this objective without comprehensive leadership.

PREVIOUSLY

I have written extensively about the Urban and Rural Phyla of a Built Domain, and that each contains a Shelter Division served by its Movement, Open Space, and Life Support Divisions.

I have also classified the six building design categories of shelter, including their design specification templates, and have explained the specification value decisions and correlation involved with each template. These correlated specification values have capacity, intensity, intrusion, and context implications that affect our social and economic quality of life; and they must be made within limited geographic areas designed to protect our source of life.

Shelter design leadership involves a building design category choice and a template range of specification value decisions that define a shelter capacity, intensity, intrusion, context, and revenue objective. When successful, the project definition will contribute to an urban design plan for a desirable quality of life within a city that protects its source of life.

Zoning and building codes were our first attempts to protect the public interest in shelter construction after the social reform movement raised the issue long before. City planning addressed two-dimensional land use relationships and compatibility with annexation as its response to unpredictable growth. Building codes addressed health and safety. Urban design now attempts to lead the three-dimensional context that emerges without an adequate leadership language. This context has often been referred to as urban pattern, composition, or texture; but there has been no specific mathematical language applicable to these intuitive design references

ARCHITECTURAL CONTEXT

What I haven’t emphasized in my previous essays is that architectural context can be defined with a mathematical equation. This implication measurement has always been in the forecast models I have discussed, but I labelled the forecast implication “dominance”. I think the term “context” is a far better indication of the implications involved since the measurement will not always indicate dominance.

Architectural context is based on the gross building area measured or predicted for a given buildable land area and is different from urban design and city design context measurement. It is the simplest to explain based on my past essays, however.

Gross building area can be measured in place or predicted based on the design specification values entered for each topic in a building design category template. The values entered are correlated with template algorithms to calculate their combined shelter capacity, intensity, intrusion, and context implications. Changing one or more specification value produces another context calculation for evaluation.

I have discussed the measurements and gross building area predictions related to six fundamental building design categories on many occasions, so I’ll begin with gross building area as a given measurement or chosen prediction from one of the six building design category templates mentioned. The following derivation of a universal equation for architectural context (ACTX) applies to any gross building area measurement or any gross building area prediction found in any building design category forecast model.

DERIVATION

Shelter capacity (SFAC) is equal to gross building area in sq. ft. (GBA) divided by the buildable acres involved (BAC).

              SFAC = GBA / BAC

Physical intensity (INT) is equal to shelter capacity (SFAC) times the impervious cover percentage (IMP%) present or planned divided by 10,000.

              INT = (SFAC * IMP%) / 10,000, substitution produces:

              INT = (GBA/BAC * IMP%) / 10,000, reduction produces:

INT = (GBA*IMP%) / (BAC * 10,000)

Intrusion is the three-dimensional impact produced by floor quantity (f). Its influence combines with intensity to produce a measurement of context (CTX). The equation for intrusion is simply:

              INTR = f/5

I have mentioned that I previously referred to context as dominance in my shelter capacity forecast models; and that the equation remains the same, but I think the term “context” is a far better indication of the implications involved since the measurement will not always indicate dominance.

Architectural context (ACTX) is equal to intensity (INT) plus intrusion (INTR). In other words,

              ACTX = INT + INTR, substitution produces:

              ACTX = ((GBA*IMP%) / (BAC*10,000)) + (f / 5)

The context equation gives you the formula needed to consistently measure, define, compare, evaluate, catalog, and adopt a context decision. It can lead us to an improved quality of life by building a library of leadership knowledge to supplement fine art intuition that leaves us with its owner. In other words, it will be all about the measurable context of shelter capacity and our quality of life in the future.

Walter M. Hosack, October 2024

 

Stormwater and Zoning Plan Review

 

Impervious cover is building and pavement cover that increases the stormwater runoff produced by land in its natural state.

The plat approval process often neglects to record the impervious cover percentage(s) that apply to the storm sewer capacity introduced to serve the parcels created. These percentages may also be missing from the original civil engineering contract documents. I am also guessing that most cities do not have a storm sewer plan that records the storm sewer capacity of every branch and main line within its boundaries - in terms of the maximum impervious coverage percentages that apply. This does not present an immediate problem but introduces an Achille’s heel over time as cities grow and lifestyle standards change. The risk is called street and basement flooding. It can occur when too many room additions and miscellaneous pavement improvements are permitted to exceed the impervious cover percentage originally used to design storm sewer capacity for the lots created– and when Mother Nature does not respect the assumption that a 100-year storm will only occur once in a lifetime. We all understand unanticipated storms, but most are not aware of the relationship between storm sewer capacity and impervious cover limits that require correlation on given land areas.

I was once told by a civil engineer that single-family residential developers request or expect storm sewer capacity design based on 30% impervious cover. I recognize that this is a generalization, but I have not forgotten the comment. It helped me understand street and basement flooding as well as the need for relief sewers over time. A limited impervious cover percentage reduces the initial storm sewer pipe size and development cost involved but can require public expense for a new parallel system to increase capacity in the future.

The engineer’s comment was based on a separated storm and sanitary sewer system. A combined sewer serves both in the same pipe and receives stormwater through open street inlets. It was considered a public health innovation at the time, but ensuing street and basement flooding of combined waste revealed its weakness. The systems still exist in older neighborhoods but are now prohibited in most, if not all, new developments for rather obvious reasons.

The problem of sewer separation has been resolved. The cost of installed storm sewer capacity remains an issue involving the first cost of capacity to a developer versus a potentially long-term public demand for additional capacity. The demand represents a transfer of responsibility from the private to public sector involving significant public expense, disruption and inconvenience. It is a relatively easy problem to overlook. New development produces new revenue that appears to increase public income until its age begins to demand additional revenue for maintenance, improvement, and debt service. Excessive impervious cover that is not correlated with underground storm sewer capacity is simply one example of the problems that can occur when plan review efforts focus on land use compatibility rather than building design categories, design specifications, shelter capacity evaluation, and the context implications that emerge from the mathematical correlation involved.

To wrap up this brief storm sewer discussion, a community cannot easily compare a development request to the storm sewer capacity available unless: (1) It can calculate the total impervious cover percentage being proposed, and (2) It has recorded the storm sewer capacity installed throughout the city. If it can’t make the comparison between proposal and capacity, plan approval and economic development can create, or multiply, an invisible problem that may produce unexpected future public obligations.

The strategic issue in physical design is not regulation with independent “thou shall not” stipulations. These are tactical directions that are functions of strategic correlation and leadership direction. The term adopted by physical designers to indicate strategic correlation has been urban design and city design. Unfortunately, the leadership language required to lead the army of designers involved has been missing until now.

I won’t dwell on the language since I have discussed it many times in previous essays. I’m simply using a storm sewer example to describe its application. Several specification topics in a building design category forecast model involve impervious cover percentages. The most significant is the amount of unpaved open space present or planned since it determines the remaining buildable area, or impervious cover, that may be used for building cover, parking, and miscellaneous pavement. When the unpaved open space percentage is subtracted from 100%, the remainder should equal the storm sewer capacity present or planned.

This comment is meant to paint a broad picture and does not account for more detailed engineering calculations that can affect the final impervious percentage adopted. When the initial values do not match however, it is an indication that the topic deserves more attention. My point is that a variance departure from a forecast model specification should assume greater significance since it represents a breakdown in the correlation required to lead a single project toward a greater objective.

Storm sewer capacity is simply one of the more obvious systems that can be affected by promiscuous approval of variances from a zoning ordinance. They can easily disrupt a carefully defined leadership plan when it exists, but their effect is difficult to discern when there is no mathematically correlated plan in place. Reasons for variance disapproval can be agonizing when there is no correlated justification for a single regulation.

A storm sewer has simply been a convenient example in this essay since capacity is an established engineering calculation. The other specification topics in a forecast model do not benefit from the same amount of research and may involve acceptable ranges, but the point is not tactical mandates for single specification topics. It is the correlation required to lead physical design toward shelter capacity and intensity objectives that protect the activities of growing populations within geographic limits defined to preserve both their quality and source of life. It cannot be unconditional surrender of the planet. It must be symbiotic survival.

Walter M. Hosack: September 2024

Photo by Jondal

Minimum Design Standards in Zoning Regulation

 

The picture associated with this essay is intended to illustrate a possible motivation for design standards but is not even close to the worst tenement examples that can be found throughout history.

Minimum mathematical design standards in a zoning ordinance are independent regulations that have often attracted excessive conflict and variance requests to reconcile the expectations created by their conflicting stipulations. Design regulations do not stand alone like separate offenses in a penal code. Their mathematical standards must be correlated within the text to consistently achieve given physical, social and/or economic objectives.

The intent of minimum design standards is to protect the public health, safety, and welfare with the least regulation of free enterprise possible. It is a simple goal statement, but goals are often too general to solve complex problems. They require additional definition with more precise language capable of correlating the strategies and tactics required to reach them. It took science centuries to make headway in its conflict with opinion and needed a precise language of definition, classification, measurement, evaluation, and success to support its arguments.

LANGUAGE

Classifying building design categories and deriving a precise, correlated language of shelter capacity evaluation represents my attempt to introduce a leadership language of measurement, evaluation, definition, and decision to the relatively infinite spectrum of desirable and undesirable design topic choices that determine the pattern, form, and intensity of the places we inhabit outside the shelter we occupy. The language represents a strategic method of precise communication that is needed to lead the design decisions of many away from the undesirable options currently encouraged by the concept of “minimum design standards” in a zoning ordinance. The entire concept of independent, uncorrelated mathematical regulations has too often contributed to sprawl, excessive intensity, and economic instability. 

PROBLEM

Allocation of site plan areas and building height decisions on every parcel of occupied land are the invisible foundation for results in architecture, urban design, landscape architecture, civil engineering, and so on. This allocation is often the product of minimum design standards and private enterprise motivation that has frequently led us to produce random sprawl and excessive intensity. These “density decisions” often represent expectations from investors reading the mathematically uncorrelated regulations in a zoning ordinance. They symbolize our confused attempt to lead the physical design decisions that consume land to shelter activity.

Building design category classification has been nonexistent. Some prominent design topic specifications remain unlisted and unspecified. Those that do exist remain mathematically uncorrelated. This makes the term “minimum design standards” a hollow phrase lacking the substance and correlation needed to avoid random results and inconsistent success. It was the best we could do at the time.

The mathematical specifications of zoning regulation are a perfect example of an incomplete, uncorrelated, and contradictory language with an admirable goal. For example, when a designer is faced with the associated density, building height, parking, and setback requirements of a zoning code, it can often be difficult, if not impossible, to reach a client’s permitted density expectations given his/her desired dwelling unit mix and average dwelling area - even with excessive pavement. The inability to reconcile these criteria prompts a desire to request variances. In these cases, the requests reflect an inability to correlate client density and design expectations with zoning regulations that are not mathematically interactive and not available for option evaluation during joint discussions.

The bottom line is that mathematical zoning regulations are a collection of independent, uncorrelated requirements that often conflict in practice when married to more detailed client intent. This inevitably leads to variance requests that are, in essence, negotiations needed to reconcile these conflicts and contradictions with inconsistent decisions.

Most, if not all, governments lack the data science and mathematical language needed to measure, predict, evaluate, and correlate the shelter capacity, intensity, and activity that grows on their incorporated land. This cannot continue. It must be consciously allocated and monitored to produce the revenue needed to adequately protect the health, safety, and quality of life of its population over time. From this perspective I have called the city a farm with zones of shelter and activity that must produce a minimum average economic yield per acre that equals or exceeds its cost per acre to operate, maintain, improve, and serve its debt. It must do this without consuming its source of life using annexation as an expedient but life-threatening solution. The concept of minimum design standards leading the decisions of private enterprise will not get this done. It’s time for data science and shelter capacity evaluation, and implication measurement.

CORRELATION

Few, even in the design professions, recognize the full scope of mathematical correlation required to consistently lead shelter options and decisions in a desired direction. I pointed out the scope of initial urban design specification decisions for one building design category in my previous essay. For those interested, the scope of possible specification combinations for the G1 Building Design Category was shown to be 5.31404665706133 x 10¹⁴⁷⁰⁶ or 5.31404665706133 times 10 to the power of 14,706. In fact, the scope produces the problem. Both ends of the spectrum are undesirable but permitted under the concept of minimum design standards. We call one end of the spectrum “sprawl” and the other “excessive intensity” but have been unable to mathematically define the implications of either through an organized and consistent definition, measurement, evaluation, prediction and decision process. We have had to rely on conflicting opinions and opposing motivation that produces what we seek to avoid.

SHELTER CAPACITY EVALUATION

The objective of city planning and zoning has been to protect the public health, safety and welfare from the individual freedom to compromise these benefits in the pursuit of profit. There are countless pictures of unhealthy, unsafe, and inadequate shelter from centuries of neglect that symbolize where we have been and still are in many places.

In my opinion, success in our efforts to protect health has been the most successful because we have developed a precise diagnostic language as a foundation, and it keeps improving. Our efforts to protect safety have produced partial success with the evolving language, opinions, strategies, and tactics of jurisprudence. Our efforts to protect our social and economic quality of life in the cross currents of cultural conflict, economic motivation, public opinion, and political leadership will continue to fail without a more precise language that can adequately monitor and shelter growing activity within limited geographic areas.

Minimum design standards in a zoning ordinance do not represent the design language needed to guide a global army of designers toward a strategic objective. The objective is shelter to protect the social and economic activity of growing populations within a geographically limited Built Domain defined to protect their quality and source of life. The goal is not unconditional surrender of the planet. It is symbiotic survival for the planet’s entire population.

The language of shelter capacity evaluation can supplement the concept of minimum design standards and contribute to the measurement, evaluation, and accurate direction needed to protect our land’s ability to sustain the built and natural worlds on a single planet.

Walter M. Hosack: August 25, 2024

Quantifying the Complex Foundation of Shelter Design Decisions

 

The Language Needed to Measure Urban Design Decisions

The shelter capacity of land has been estimated and more land has been acquired when needed by converting/consuming agriculture, undeveloped areas, and/or natural settings. The entire concept of master planning has assumed that annexation can adjust for mistaken land use allocation and population growth.

Growing populations cannot survive without shelter for their many activities, but it seems obvious that land is not infinite and must be shared with the Natural Domain to protect our source of life from eventual consumption.

Surveying defines land areas. It does not define the shelter capacity of land or its environmental significance. This has made land a commodity. The result has been the lack of general recognition that the land areas we define must be consciously managed, conserved, protected, preserved, and shared as a source of life. The lack of a common, consistent language of mathematically correlated shelter capacity evaluation has produced inconsistent decisions leading to sprawl, excessive intensity, and random land consumption.

A honeybee knows better. It builds limited shelter; grows in limited quantities; feeds in limited areas; and pollinates in return for consumption. It responds to the Law of Limits on a planet that responds to a universe beyond our comprehension. We have yet to create a language of shelter capacity evaluation that can build any segment of comparable knowledge or contribution, and the planet does not compromise with ignorance.

INTRODUCTION

Shelter capacity is first a function of the building design category chosen among six in the Shelter Division of the Built Domain. Until now, shelter has never been classified by mathematically useful building design categories. The design specification decisions related to each category and occupant activity have never been comprehensively identified or correlated with the algorithms needed to measure and/or predict shelter capacity, intensity, intrusion, and context options for any given area.

The shelter capacity of a given land area is a function of the building design category forecast model chosen; the values entered in its design specification template for each topic listed; and the floor quantity options considered. The result is a correlated mathematical prediction of shelter capacity options in sq. ft. per acre and the intensity, intrusion, and context implications related to each.

Shelter capacity decisions determine the scope of activity that can be contained within the gross building area per buildable acre measured, planned, or predicted. The nature of this activity combines with shelter capacity and intensity to determine the revenue and investment potential of the buildable land area occupied.

The correlation of mathematical decisions and floor quantity options in a design specification template produces gross building area options and related shelter capacity, intensity, intrusion, and context implications. These implications are measurements of the physical relationships involving building mass, parking, pavement, and unpaved open space that combine with movement, open space, and life support systems to form the places within our Built Domain.

ECONOMIC DEVELOPMENT IMPLICATIONS

An informed allocation of capacity, intensity, and activity within a city can make the evaluation of financial stability more than an annual guessing game. It will, however, require the participation of data science and the correlation of many related data silos with the leadership calculation and evaluation of shelter capacity alternatives. It is the only way to provide shelter for growing populations within limited geographic areas defined to protect and preserve their quality and source of life. It is a fundamental physical issue.

The consistent measurement of shelter capacity, intensity, activity, and revenue from every acre within a city makes the evaluation and accumulation of knowledge feasible. The implications are significant. The knowledge will offer the opportunity to mathematically correlate and monitor a city’s land use allocation plan. This will make it possible to produce and maintain an average economic yield per acre equal to or greater than a city’s expense per acre. The implied objective is to establish, afford, and maintain financial stability that can produce a desirable quality of life within limited geographic areas.

SHELTER CAPACITY DESIGN DECISIONS

I’m including a brief example of shelter capacity forecasting in Table 1. It will be quite repetitious for previous readers but will provide an example of a tool that can be used at joint meetings of planners, investors, developers, and advisers to mutually evaluate options, reach decisions, and define objections before the expense of graphic evaluation begins. In fact, hundreds of spreadsheet options can be evaluated in the time it would take to sketch one.

The entire collection of forecast models is meant to introduce a mathematical language of correlated design specifications to replace comparable but partial and mathematically uncorrelated zoning regulations. Consistent measurement and evaluation of existing conditions based on a comparable, correlated set of design specification topics can build knowledge regarding their implications and future leadership parameters.

TABLE 1

I have explained Table 1 many times, so I’ll keep it brief. The table is a forecast model that applies to the CG1L building design category. This category includes all buildings served by a surface parking lot around, but not under, the building on the same designated premise.

The shelter capacity options in cells F44-F53 of Table 1 are predicted from the specification values entered in its shaded cells. The results may be occupied by any permitted activity. The scope of activity is affected by the shelter capacity measured, predicted, planned, and/or available.

The correlation of capacity, intensity, and activity produces a context measurement that combines with location to determine the revenue potential of the land area involved. The allocation of these relationships on every taxable parcel/acre of land within a city’s boundaries determines its total average revenue per acre. This must equal a city’s total annual operating, maintenance, improvement, and debt service expense per acre, or budget cuts ensue. The public reaction to the municipal services provided is a measure of its context allocation success and ability to explain its decisions.

Lines (a-e) identify the forecast model in Table 1. Line (g) identities the Design Specification Template. Line 2 identifies the Land Module in the specification template. The shaded cells in the module identify the locations requiring design specification decisions. The values entered are simply for illustration. The text to the left of the values explains the topic. Column G converts all values to their sq. ft. equivalents.

The Core Module in Table 1 begins after the Land Module. The shaded cells in the Core Module continue to designate design specification locations. The CORE value found in cell F33 is correlated from all specification values entered in both modules. It is converted to a sq. ft. value in cell G33, and is needed by the master equation in cell B39. Parking specification values are entered in shaded cells B35, B36. Optional floor quantity values are entered in cells A44-A53. All specification values entered are correlated for use by the master equation to find the gross building area options in cells B44-B53 of the Planning Forecast Panel. All other predictions in the Planning and Implication Modules are functions of these gross building area predictions.

CONTEXT

The values in cells J44-J53 of Table 1 are context measurements. They are a function of the capacity, intensity, and intrusion options calculated in the preceding columns. I originally designated the column as containing dominance values (DOM) but have since come to believe that context measurement (CXT) is a better title indicating the entire range of options that can result from a design specification.

DESIGN SPECIFICATION DECISIONS

There are 27 shaded design specification topics in Table 1. The first is a given land area that can be of any size. Eleven of the ensuing topics in the Land and Core Modules involve percentage decisions that can range from 0-100%. The values in cells F27-28 and A35-36 of the Core Module involve integer decisions and a more limited range of options. The column of floor quantity options in Column A44-53 is often limited by a zoning ordinance, but the potential list of choices can range beyond 100. I’ll make my point in the ensuing paragraphs.

Each specification topic requires a mathematical entry/design decision even if it is zero. Changing one or more values assigned to any shaded specification topic produces revised results in the Planning Forecast Panel and Implications Module. I’ll ignore the whole number topics and the given land area. I’ll limit the floor quantity range of choices to 100 to simplify this explanation.

The 12 topics involving decisions ranging from 1-100 in Table 1 represent a relatively infinite spectrum of low to high intensity combinations associated with the CGL1 building design category, which is the simplest of the six building design classifications. Twelve specification topics times 100 potential options each produces a great number of potential combinations. The factorial of 1200 is 6.3507890863e+3175. This can also be written as 6.3507890863 x 10³¹⁷⁵, or 63507890863+3165 more digits. If I added an estimate of 2360 for the potential fixed number specification options in the model, the total potential design choices would be 4560 and the potential number combinations would be 5.31404665706133 x 10¹⁴⁷⁰⁶.

This is the first time I have come to recognize the true complexity of the physical design decision process, the experience required to navigate these options, and the scope of research/knowledge required to improve a leadership language that currently uses intuition, talent, contradictory regulations, and missing information to produce random results. We need to more thoroughly understand the implications of the options involved and improve our ability to comprehensively, consistently lead these decisions toward desired outcomes within geographic limits designed to protect both our quality and source of life.

LEADERSHIP CHALLENGE

The design specification values entered in the shaded cells of Table 1 are examples of the decisions that must be correlated and led to consistently achieve desired results from the CG1L building design category. Without leadership, the options available to every owner, developer, real estate investor, architect, landscape architect, urban designer, civil engineer, city planner, and so on are too vast to expect results capable of consistently avoiding sprawl, excessive intensity, and continuing consumption of land that is also our source of life.

Table 1 represents one forecast model that can be used to measure and evaluate our past physical design performance, build knowledge, and improve results with a leadership language based on the mathematical knowledge acquired. It is one model in a city design portfolio of models. The portfolio choices are not a substitute for architectural form, function, and appearance decisions. They precede them. The topic values involved are meant to lay an urban design foundation of building mass, parking, pavement, and unpaved open space quantity decisions. These define massing composition/relationships that will be refined during the ensuing phases of design and construction.

City design is a strategic concept meant to achieve the goal of sustainable, symbiotic survival. Urban design defines an objective that must be achieved to move toward the goal. The specification topics in shelter capacity evaluation represent a leadership language. The value decisions assigned require mathematical correlation. These invisible decisions can lead many others to produce the visible, physical, three-dimensional form, function, and appearance of shelter that symbolizes the entire scope of knowledge acquired.

FOUR TOPICS

Four topics in Table 1 deserve special mention.

Unpaved Open Space

Cell F11 is a critical but often ignored specification. The 30% unpaved open space specified determines the amount of impervious cover that will produce stormwater runoff. In this example, the related storm sewer capacity must be able to accommodate the runoff from 70% impervious cover. This relationship has often been ignored for many reasons. One of which is the pipe size cost to accommodate the demand. Cell F11 is included to attract attention to this important planning/engineering coordination issue.

Area per Parking Space and Associated Circulation Drive Area

Cell A35 is another topic often ignored and included here to gain design attention. The sq. ft. planned per parking space and its related circulation aisle can be minimized to eliminate landscape relief and increase the parking spaces provided. The debate over function and appearance versus parking capacity affects achievable gross building area and needs careful consideration and commitment based on convincing research.

Number of Parking Spaces

Cell A36 is one of the most hotly contested topics in zoning regulation. It defines the number of parking spaces required for a given land use category and building area. The argument generally surrounds an applicant’s proposed activity and the number of parking spaces the activity requires. It often involves a conflict between experience and regulation that ignores the fact that parking deficiencies will apply to future owners. These deficiencies may affect the value/revenue potential of the land and building(s) to both the city and future owners. It is another fundamental topic that needs careful leadership attention, but the demands of a specific activity will always make a general regulation controversial.

Building Height

Cells A44-A53 display a limited range of building height options that can be changed with a few keystrokes to examine the implications of other options. It is another typical zoning regulation that is often hotly contested, but with a limited understanding of the implications. These are shown in the Implication Module of Table 1, but it is like reading blood pressure readings with no prior diagnostic history. It is no wonder that fear attends increasing building height proposals at the present time.

All building height options are not undesirable. If they were there would be no shelter for man. The potential range may suffer from generalizations that come with a lack of measurement, evaluation, and debate. There is much to learn regarding the social and economic quality of life produced by building design categories, design specification choices, and related floor quantity decisions that define the form and fabric of the Shelter Division in our Built Domain.

OBSERVATIONS

We have depended on market forces to determine the scope of shelter capacity required by growing populations. Growth has been met with supply given the assumption that land is a commodity without end. Municipal economic deficiencies have been met with the annexation of land for new revenue that may again prove inadequate as the annexation ages, prompting more annexation and sprawl. Encircled cities worry that they have no land for annexation to compensate for budget deficiencies.

We have not learned how to correlate shelter capacity, intensity, activity, and location to produce economic stability within limited geographic areas that protect our quality and source of life; but we cannot continue indefinitely on our random path without finding a solution. It will inevitably involve data science, and the formation of shelter capacity strategy based on the correlation of technical knowledge from many related professional disciplines.

Walter M. Hosack: August 2024

The Language of Shelter Capacity and Context Evaluation

The choices that will determine the land we consume to shelter growing populations on a finite planet. 

Cities have not been prepared to monitor, evaluate, or plan the economic performance of their shelter capacity, intensity, and activity pattern/form beginning at the parcel, zone, and census block/tract level of their incorporated areas. This has limited their ability to allocate shelter capacity, intensity, and activity to achieve the balance needed to plan/monitor and achieve financial stability. They have had to rely on annual budget estimates based on experience. This is one reason why cities attempt to maintain unincorporated corridors of land for annexation that can provide new revenue to meet expenses that often proves inadequate over time as age, maintenance, and demand for services increase. It is an inadvertent Ponzi scheme that has emerged based on inadequate measurement, evaluation, prediction, design, and use of land and shelter capacity within their jurisdictions. 

I should mention at the outset that shelter capacity is the square feet of gross building area present or planned per buildable acre. It may be occupied by any activity permitted by a local zoning ordinance. The objective is to correlate/balance measurable quantities of shelter capacity, intensity, and intrusion that combine to form context for activity within a city. Successful allocation/correlation/balance can produce economic stability and a desirable quality of life. If the physical context designed/produced is undesirable however, the occupant activities within and around cannot help but be compromised and endured at best.

We have not been able to measure, evaluate, predict, define, correlate, or lead the capacity, intensity, intrusion, and context characteristics of shelter mass, parking, pavement, and unpaved open spacehat combine to form shelter on parcels within the organisms we refer to as cities, regions, and conurbations. Without consistent, accurate measurement, prediction, and design we cannot lead.

I have previously referred to the measurement and prediction of “context” as “dominance” in my essays and forecast models. In either case it is the sum of shelter capacity, intensity, and intrusion measurements for a given buildable land area. A context measurement in a forecast model includes all quantity measurements of building mass, parking, pavement, and unpaved open space in a project area. I have changed the reference because I believe “context” is a better indication of the conditions created by the sum of the correlated physical design decisions and implications involved.

The language and algorithms of shelter capacity evaluation are needed before we can use data science to improve the design specification values for building design categories. These design specifications combine to form the Shelter Division of cities. Data science can improve the knowledge behind the values entered in the design specification template of a shelter capacity forecast model.

Keep in mind, however, that this essay addresses the Urban and Rural Phyla of the Shelter Division of the Built Domain. These cells are served by arteries of movement, open space, and life support. (Public open space arteries are more of a dream than reality at the present time.)

The growth of a city is driven by shelter demand, but its health, safety, and quality of life depend on the correlated allocation of shelter capacity, intensity, intrusion, and activity that combines on land to produce context within every cell of the urban anatomy. This can become excessive without design leadership formed from the measurement and evaluation of previous context specifications and decisions. The physical form and appearance that emerges from this effort will symbolize our ability to create desirable, sustainable, symbiotic relationship with our source of life. Anything less will resemble the unlimited growth of a parasite.

LEADERSHIP LANGUAGE

Our planning focus has been limited by the language we use to define options and lead the design decisions that define shelter strategies for individual parcels within cities. We have attempted to lead these innumerable project efforts with a zoning language that has not been equal to the mathematical correlation required. The result has been contradiction, confusion, and argument that has often led to variance requests and approvals attempting to resolve contradictions and disagreements with decisions that provide inconsistent design leadership at the cellular level of urban formation. The attempt to form an urban anatomy without data science and consistent cellular design leadership is a recipe for mutant formation and continuous annexation of our source of life for shelter that is only one of the essential ingredients needed to survive.

PHYSICAL DESIGN

Shelter design is involved with the correlation of knowledge required to define shelter strategy for construction at the project level of the Built Domain. Shelter projects become tactical elements in a larger Shelter Division strategy whose projects combine to form a three-dimensional shelter context served by arteries of movement, open space, and life support within the anatomy of a Built Domain. (Arteries of open space are more of a dream than reality.) Unfortunately shelter strategy can be compromised by its mathematically uncoordinated zoning regulations. Sprawl and excessive intensity often result.

Physical designers, including architects, refer to a greater level of strategic context correlation as urban design or city design depending on the scale involved. Correlation of building design categories and design specification values on parcels within these areas produces shelter capacity, intensity, intrusion, context, and economic stability alternatives. The conscious allocation of these alternatives on every parcel within cities produces context that has revenue, investment, and quality of life implications.

The correlation of shelter capacity, intensity, and activity within cities is a complex physical, social, and economic issue that cannot be adequately addressed without the participation of many related disciplines including data science, but it cannot begin without a language that can consistently translate data evaluation into a language capable of leading physical context design decisions toward the physical, social and economic context results required to provide shelter for growing populations within limited geographic/environmental limits that protect their quality and source of life.

FINE ART

In my opinion it has been a fundamental mistake to consider the correlation of knowledge required to define the strategy and tactics of shelter definition an architectural fine art. The effort has always been an applied science spinning off engineering specialties as its knowledge has increased over centuries; but engineering serves strategic design decisions. It does not make or correlate them.

The term “fine art” implies that we must rely on observation, talent, and intuition to solve the problem of shelter for growing populations on land that must be shared to protect our environmental source of life. Fine art is a reference to the physical form and appearance that emerges from client mandates and invisible design decisions for shelter construction based on intuitive logic and often contradictory zoning regulations.

I’ve never been sure if the term “function” in the historic phrase “form follows function” referred to the floor plan created or to the correlation of floor plan and engineering systems that must be correlated to produce function at the time. The phrase has been attributed to Mies van de Rohe and it was probably associated with the appearance of his fine art. In my opinion, the phrase can now be interpreted to have far more significance when the shelter decisions behind appearance become recognized for their sustainable, symbiotic, environmental importance.

ARCHITECTURE

Architects have been focused on the project definition of owner aspirations, shelter objectives for a given activity, and the correlation of all related technical and professional knowledge required to define a strategy for shelter construction. Correlation has rarely been recognized or advertised because the emphasis on fine art has given the impression that architects are artists. It is a key word, however. Correlation within architecture is a leadership/management function that defines strategic direction in phases it refers to as “programming” and “schematic design”. Correlation is gaining significance as we begin to realize that the increasing demand for shelter must be correlated with the shelter capacity of land, the intensity introduced, the functions involved, and the activity planned to protect and preserve our source of life. In my opinion, the correlation of physical design knowledge to produce desirable shelter capacity context within geographic/environmental limits will become increasingly important as shelter demand for the activities of growing populations increases.

It seems obvious that land on a finite planet is limited and that our need to consume land for shelter must be balanced against our need to preserve land and the environment as a source of life for ourselves and our specie partners. This is where familiarity with consultant correlation, shelter capacity evaluation, and context implications becomes a greater asset to the entire population, but it must expand beyond the project orientation of architecture. In fact, the correlation of all physical design disciplines related to the term “context” will become more essential as shelter capacity becomes a greater issue that can now be mathematically measured, evaluated, predicted, adjusted, and guided to produce shelter for the activities of growing populations within geographic/environmental limits defined to protect their quality and source of life.

ECONOMIC DEVELOPMENT

The combination of shelter capacity, intensity, and activity on land determines the revenue and investment potential of the context per buildable acre created. These considerations take their place next to our historic concerns for the compatibility of adjacent activity to protect our health and safety. In municipal terms the allocation of shelter capacity, intensity, and activity per buildable acre within its land area determines the total annual yield it receives to support its operations, maintenance, improvements, and debt service. From this perspective, the allocation of context within municipal boundaries takes on much greater significance; but it will require much greater emphasis on the data assembly needed to build the knowledge required for design specification decisions that will be essential to a sustainable, symbiotic future.

CONCLUSION

It is now mathematically possible to accurately predict the shelter capacity, intensity, intrusion, and context implications surrounding a chosen building design category and related template of design specification decisions. The result is a mathematical forecast of physical design options and implications based on the specifications and range of floor quantity choices entered in the template. These choices represent context options that must be served with sustainable, environmental support solutions. 

It is also possible to measure the design specification decisions related to an existing building and enter them in a related building category template to measure the existing context and evaluate the implications of its design specification decisions to improve our knowledge regarding shelter design decisions.

OBSERVATIONS

Shelter context begins at the parcel level of cities with building mass, parking, pavement, and unpaved open space. The allocation of parcel capacity and intensity across the buildable acres of a city combines with permitted occupant activity to determine a city’s financial stability. The complex correlation required for economic success and an affordable quality of life within environmental boundaries will include data science and improved government cooperation. Success will continue to depend on our ability to advance knowledge with improved tools, research, measurement, evaluation, correlation, and leadership choice.

Goals are generally simple statements that require complex strategies and tactics for achievement. Strategies and tactics are the invisible, complex foundations for success. The WWII goal of unconditional surrender comes to mind. The strategy commenced in N. Africa. One of its many objectives was Operation Overlord, or Normandy. The tactics required to achieve all objectives were innumerable and the cost unimaginable.

With growth as the topic, I’d like to suggest that one objective can only be shelter for the activities of growing populations within geographic/environmental boundaries defined to protect their quality and source of life. The goal is symbiotic survival. The strategy continues to be contested. Tactics will depend on improvement in the tools available.

A Letter Regarding Shelter Capacity, Land Use Allocation, Data Science, and Design

 

I read your article and noticed your invitation to write. You mentioned quantitative fluency, data visualization, ethical responsibilities, and transdisciplinary interaction with analytics and data science.

I have something to offer in this regard that concerns the evolution of cities. In my opinion, plans to shelter the activities of growing populations must be designed to protect their quality and source of life within geographic/environmental limits. Our current efforts are producing parasitic, suffocating sprawl and blisters of excessive intensity across the face of the planet. The solution will undoubtedly involve transdisciplinary interaction, but it cannot begin without the classification system, mathematics, forecast models, and implication measurements that will constitute the leadership language of shelter capacity evaluation and leadership.

I am attaching a brief essay entitled, “Shelter Capacity, Land Use Allocation, Data Science, and Design” that outlines my approach to shelter capacity evaluation. Its algorithms, master equations, and forecast models will depend on convincing data entry values that improve on the intuition and anticipation of talent, education, and experience. The result will be transferable shelter knowledge that only measurement, data science, and a transdisciplinary research approach can provide.

Leadership away from excessive land consumption for shelter to protect “human good” will require that we ask, “…whether we can do something and whether we should.” Convincing arguments will depend on the forecast models of Shelter Capacity Evaluation and the values provided by data science research from many related physical, social, psychological, environmental, ecological, and economic disciplines. Future shelter leadership decisions will depend on the knowledge that all can provide, and a new shelter science may emerge from this correlated effort.

The essay I’m attaching briefly mentions the classification system, mathematical tools, and forecasting models needed to support the research, education and implementation required to lead both public and private shelter decisions toward a realistic relationship with the land and seas of the planet. These tools will depend on the work of transdisciplinary data science to build credibility for the forecasting values entered and adopted to lead shelter away from the threat of excessive environmental consumption, contamination, and ecological destruction.

The goal is symbiotic survival. We must learn to build the tactical tools and strategic knowledge required to succeed.

BACKGROUND

I am an alumna with 5-year Bachelor and 2-year Master of Architecture degrees granted in 1966 and 1968. The Master of Architecture degree was converted from a Master of City Design degree after the city design program under Professor Rudolf Frankel was abandoned.

There has been a lack of city design knowledge that can lead investment, design, and construction of shelter away from the sprawl and excessive intensity it often produces. The correlation of data science with the new classification system, forecast models, algorithms, and master equations of shelter capacity evaluation can provide the leadership direction we need to avoid the continuing, excessive consumption of land that is our source of life.  

I have derived the equations of shelter capacity evaluation and explained their forecast model application in over 220 essays on my blog at www.wmhosack.blogspot.com. I have also written three books and one second edition on the subject. They can be found at McGraw-Hill and on Amazon.com. I published an earlier version of these forecast models on a CD with McGraw-Hill. It was too often copied and is now outdated by the equations I have derived and documented.

I would like to offer these forecast models on a subscription basis. The leadership values entered, however, will only be as good as the knowledge transdisciplinary data science research and visualization can provide over time. The common language, comparative potential, and research opportunity represented by the equations and forecast models of Shelter Capacity Evaluation is complete; but I lack the ability to include them in a software subscription package that can be offered to any interested pubic or private entity associated with the planning, design, investment, and/or regulation of our Built Domain. I cannot overstate the potential market, educational contribution, and leadership potential represented by a transdisciplinary approach to shelter capacity evaluation. We must learn to shelter the activities of growing populations in limited environmental areas designed to protect both our quality and source of life.

I hope you have the time to read the brief essay I’ve attached.

 

SHELTER CAPACITY, LAND USE ALLOCATION, DATA SCIENCE and DESIGN

 

The entire spectrum of shelter capacity options for a given land area has not been mathematically predictable in a reasonable and affordable amount of time. This has produced estimation, annexation, sprawl, excessive intensity, unending argument, and unrestricted consumption of agriculture and our Natural Domain.  The growth of shelter capacity demand for our increasing activity, however, will force us to more efficiently allocate the capacity of land to shelter activity within geographic limits designed to protect our quality and environmental source of life.

At the present time, shelter capacity evaluation is a function of experience and estimation based on a property survey that defines the area available, not the area required for the project intended. At this point the argument over shelter capacity begins using the terms “density” or “floor area ratio”. (My previous essays have explained why these terms define results but do not correlate the design specification topics, values, and decisions required to consistently lead the shelter design process toward desired options.) The ensuing uncertainty surrounding these poorly defined objectives has often produced sprawl and excessive intensity that continues to consume the face of our Natural Domain and the Agricultural Phylum of our Built Domain.

Data science will be unable to meaningfully address the relationship of population growth and its need to shelter expanding activity with the limited land and resources available until it can correlate the shelter capacity of land with its social and economic implications in a reasonable amount of time. Its promise and the equations of shelter capacity evaluation can make this possible, however.

We have been unable to measure physical intensity and unable to accurately predict the shelter capacity of land for any land use activity until now. This has prevented us from correlating the relationship of shelter capacity to activity, intensity, revenue, investment, and quality of life on buildable land within limited urban areas.

LAND USE ALLOCATION

A city’s investment portfolio begins with the taxable land within its boundaries. The allocation of shelter capacity, intensity, and activity on every parcel determines its average economic productivity per acre and the quality of life this combination can afford. These are the relationships we have been unable to consistently and successfully map, predict, correlate, and monitor within a city’s corporate limits because we have been unable to accurately measure or predict shelter capacity, intensity, activity, and economic productivity options on a given parcel or parcels for six fundamental building design categories. The fallback result has been unlimited annexation attempting to reconcile economic imbalances and quality of life deficiencies with increasing consumption of agriculture and its source of life, the Natural Domain. We will continue to pursue annexation that produces inadequate revenue to equal increasing expense over time until we can accurately calculate, correlate, monitor, and lead the shelter capacity, intensity and activity relationships that determine our financial stability and quality of life.

Shelter capacity is the sq. ft. of gross building area present or planned per buildable acre assigned to the project. Shelter capacity divided by 43,560 times the impervious cover percentage present per buildable acre is a measure of the physical intensity introduced. Shelter capacity forecast models can measure and/or predict the gross building area alternatives associated with any given land area, building design category, and values entered in its design specification module. The result is a series of gross square foot options related to a list of building height alternatives entered in the forecast model. These options are converted to shelter capacity, intensity, intrusion, and physical dominance measurements with implication equations. Like the first blood pressure readings, only research can indicate the quality of life implied by the conditions measured or proposed; and only more accurate measurement can lead our cities in the right direction.

DATA SCIENCE

At this point data science must enter the picture. Gross building area is a physical measurement that has many social, economic, and engineering implications. For example, construction cost per sq. ft. is a relatively common multiplier that is correlated with the scope of occupant activity present or proposed to determine an estimated budget. Profit potential per sq. ft. of leased or rented space for activity is another rather common rule of thumb in the commercial real estate industry. The average municipal revenue produced per sq. ft. of activity category located within a city is relatively, if not completely, unknown. This makes the allocation and correlation of shelter capacity, intensity, activity, intrusion, and dominance plans or predictions with its revenue potential an economic development guessing game.            

The ultimate objective is to correlate the anticipated revenue and investment yield per square foot of activity with the quantity of activity that should be allocated per buildable acre of land within established city limits to ensure an adequate average revenue yield per total taxable municipal acre. The underlying objective is to ensure that these square foot quantities do not compromise a project’s quality of life and that of the surrounding area with excessive physical intensity, intrusion, and dominance. At this point we will be able to correlate social and economic stability with the three-dimensional shelter compositions that emerge to shelter our quality and source of life within environmental limits. (I have defined measurable “intrusion” and “dominance” in many of my previous essays.)

CORRELATION

There are now two worlds on a single planet. Continuing growth of the Built Domain is still a relatively unrecognized carcinogenic threat to our source of life, the Natural Domain; even though sprawl appears to be recognized as undesirable. The threat continues because the shelter capacity of land, the options available, and the geographic limits of a sustainable Built Domain are all matters of opinion and leadership disagreement. The only way to debate opinion is with research, measurement, prediction, and successful decisions. Shelter capacity evaluation makes physical measurement of capacity, intensity, intrusion, and dominance implications feasible.

Data science can make measurement of average activity revenue per square foot of gross building area a new chapter of economic knowledge. These physical and economic measurements can be correlated with their intensity, intrusion, and dominance implications to make quality of life within geographic limits a measurable topic of environmental research and economic stability.  

IMPLICATIONS

In the past, many assumed that the supply of land for the Built Domain was unlimited. The perception of many has changed, however; and this has led some to recognize that land consumption is subject to the planet’s unwritten Law of Limits. We will continue to challenge these limits until we can more accurately and consistently predict the shelter demands of growing population activity; and correlate these demands with limited geographic areas, building design categories, and shelter capacity options that can be mathematically correlated to protect our quality and source of life. It is a tall order, but data science that cannot predict the shelter capacity of land to accommodate data demand without sprawl and excessive physical intensity will continue to assume that this is a world without end. 

OBSERVATIONS

Gross building area per buildable acre may be occupied by any activity in conformance with local planning and building regulations. The compatibility and appearance of activity within a city has been our preoccupation, but the scope and taxable value of activity per buildable acre determines its physical, social, and economic contribution to a city’s quality of life. A simple comparison can illustrate my point.

First, divide a city’s entire annual expense by the taxable acres within its boundaries. This reveals the city’s current cost per acre to operate, maintain, improve, and serve its debt. Second, divide the total revenue a city receives from any single-family residential lot by the lot area in acres. (Do not include the revenue the lot delivers to its school system, library, county, and so on.) Finally, compare the two results to see if the residential lot produces more or less than the city’s total expense per acre. This exercise can be conducted for any activity and every parcel in a city to determine the average economic productivity of its land area. The correlation of Shelter Capacity Evaluation and Data Science can introduce this ability to monitor economic productivity and its impact on a city’s quality of life. The correlation can become the foundation for future city design within environmental limits defined to protect our quality and source of life.

CONCLUSION

In my opinion, we must eventually eliminate our dependence on annexation and continued consumption of agriculture and the Natural Domain. Annexation has been a Ponzi scheme demanding new money to cover increasing costs at the expense of our source of life. When in place, the correlation of shelter capacity evaluation and data science will enable us to monitor and correlate a city’s financial performance with the physical presence and social quality of life it delivers.    

Walter M. Hosack: July 16, 2024

THE LEAP FROM OPINION TO KNOWLEDGE - Building knowledge to support city planning, urban design, landscape architecture, and architectural opinion

 

Our methods of property description have not been followed with an accurate and consistent ability to quickly appraise desirable shelter capacity options for occupant activity on these land areas. The result has been arbitrary approximation and promiscuous consumption of land. It continues because the ability to mathematically correlate shelter capacity, occupant activity, physical intensity, and economic performance on a given land area has been non-existent. It has been a matter of hope, opinion, and experience with random results ranging from sprawl to excessive intensity. Shelter capacity, intensity, and activity relationships can produce economic stability and a desirable quality of life within a geographically limited master plan area; but it requires leadership with mathematical tools and correlated databases that encourage research, measurement, evaluation, decision, and direction. This has been our method of proceeding from opinion to knowledge throughout history. Opinion will continue to demand more land from the Natural Domain and the Agricultural Phylum of the Built Domain until knowledge helps us understand the Urban Phylum and its place on a planet that will not compromise with ignorance.

 
I have written about these mathematical tools in many essays on my blog at www.wmhosack.blogspot.com and on Linked-In. Earlier versions of the forecast models involved were included on CDs in my first two books. The latest and most useful forecast models remain to be published as one of my future projects.

I have been searching for a single paragraph that could encompass the work I have undertaken and its motivation. The first paragraph above is my latest attempt. 

Walter M. Hosack: June 2024

Shelter Science

Shelter is one of four divisions in both the Urban and Rural Phyla of our Built Domain. It is served by its Movement, Open Space, and Life Support Divisions, and is essential to our survival; but continues to consume our source of life as it sprawls across the face of the planet in an unrestrained belief that land is a commodity. It is a situation that cries out for a more scientific approach to the provision of land for shelter capacity as populations grow and migration patterns continue. (Shelter capacity is gross building area in sq. ft. per related buildable acre.)

Six design categories are all that is needed to begin objective classification of buildings in the Shelter Division. They currently consume land without accurate mathematical correlation to the actual shelter capacity of land, the activities contemplated. The intensity implied, and the public revenue potential per acre consumed.

The land consumed for shelter is at best an approximation related to the parcel or parcels available. Continued land consumption for an expanding Built Domain is leading to increasing recognition that more sustainable solutions must be found to make better use of an essential resource subject to competing demands. Efficiency of land use has been an agricultural preoccupation that is becoming an urban mandate. We have often been concerned with the compatibility of adjacent activity but relatively helpless in the face of expanding sprawl.

The consumption of land for shelter has often produced random sprawl and excessive intensity because the tools needed to measure, correlate, predict, and lead the design and construction of shelter capacity within limited land areas are either missing or uncorrelated. We have attempted to lead the planning and physical design decisions that produce our cities with a legal format steeped in our social history of independent commandments. The result has often been leadership contradiction and confusion because physical design requirements are not independent social regulations. The values assigned to their topics must be correlated with mathematical algorithms before a set of value decisions can efficiently use limited geographic areas to shelter the activities of growing populations when the goal is to protect both their source and quality of life.

A set of correlated design specification values entered in the forecast model template of a building design category defines the shelter capacity, intensity, intrusion, and dominance implications planned or measured. These value topics have been partially recognized but have remained incomplete and mathematically uncorrelated. Shelter science can begin when they are consistently listed, measured, correlated, and evaluated for each building design category and activity group. This can build the knowledge needed to understand, improve, and lead the results produced.

Fortunately, the shelter topics involved can be expressed with equations. The relationship of these equations can be defined with algorithms. This is the mathematical foundation for the building form, function, and appearance that grows from these decisions. The mathematical relationships between shelter and land have always been there, but we have been slow to recognize their underlying presence in the forest of more tactical design decisions that reside within specialties we call architecture, landscape architecture, urban design, city design, and city planning. There is, however, a foundation of mathematical decisions that can be correlated to define the shelter capacity, intensity, intrusion, and dominance of shelter desired long before it grows from the land; and it can be used to lead shelter growth within limited geographic areas. This collection of building mass, parking, pavement, movement, open space, and life support has often been referred to as an urban pattern or composition; but these terms give the impression of organization when the results have more often been scattered sprawl and/or unmeasurable intensity, intrusion, and dominance. Science can begin when measurement becomes feasible.

SHELTER DIVISION CLASSIFICATION

The Shelter Division of a city contains six building design categories classified by the parking that serves them. They are: (1) Buildings with surface parking lots around, but not under, the building on the same property (G1); (2) Buildings with surface parking around and under the building on the same property (G2); (3) Buildings with an adjacent parking garage on the same property (S1); (4) Buildings with underground parking on the same property with or without supplemental surface parking (S2); (5) Buildings with structure parking under the building on the same property with or without supplemental surface parking (S3); and (6) Buildings with no parking required (NP).

The definition of the six building design categories just mentioned is expanded with the design specification topics listed in their forecast models. These topics receive values that are either measured or entered for evaluation of the option represented.

Table 1 presents an example of the G1.L1 forecast model. It pertains to the G1 Building Design Category when the buildable land area in acres is given in cell F3. Think of the listed specification topics and values entered or measured as the characteristics of a species. When topic values are processed by the algorithm in the design specification template of the table, the master equation in cell B39 uses the results to calculate gross building area options in cells B44-B53 that are related to the floor quantity options entered in cells A44-A53. For instance, a five floor building on line 48 of Table 1 is predicted to produce 24,226 sq. ft. of gross building area given all specification values entered in its Design Specification Module. A change to one or more of these values will produce a new set of implication predictions.

The G1 building is further classified by the shelter capacity, intensity, intrusion, and dominance calculated in the Implications Module of Table 1. The five floor option, for instance, has a shelter capacity of 13,939 sq. ft. per buildable acre; an intensity rating of 0.836, a vertical intrusion rating of 1.0, and an overall physical dominance rating of 1.836. If the projected total revenue potential from its occupant activity were $10.00 per gross sq. ft., total revenue of $13,939 could be divided by the 1.738 buildable acres calculated in cell F10 to predict a total revenue potential, or yield, of $8,020.14 per buildable acre. Comparing this to a city’s total annual expense per buildable acre would reveal its place in a city’s total revenue investment portfolio.

In other words, the land is more than a commodity to a city and its use is more than a socially compatible consideration. The combination of permitted shelter capacity, intensity, activity, and economic potential are an investment in its future. Decisions regarding the allocation of shelter capacity, activity, and intensity in its urban design plan determine the quality of life it can provide.

HOW MUCH LAND IS NEEDED

A shelter capacity question does not always involve the potential of a given land area. The buildable land area needed for a given gross building area objective is also a question that can arise.

The answer begins with the selection of a building design category forecast model. In this case I’ve again chosen the G1 Building Design Category but am using Table 2 to address the question. It contains forecast model G1.B1 and uses the same shaded cell designation for design specification values. The optional values entered are used to further define the question with a complete description of the classification characteristics proposed.

Table 2 is based on the gross building area objective entered in cell A34. The values entered in the remaining gray cells represent one set of correlated design specification options, and a change to one or more of these values will produce a new forecast of necessary buildable land area alternatives in cells B44-B53. These alternatives are related to the floor quantity options entered in cells A44-A53 and are converted to buildable acre options in cells E44-E53.

The implications of the values entered in Table 2 are calculated in its Implications Module. This makes it possible to measure and compare the mathematical physical design decisions that determine the shelter pattern, spaces, and composition of cities with their social and economic implications long before building appearance becomes an issue.

THE MASTER EQUATIONS

The master equation in cell B39 of Table 1 is one of a number derived to predict gross building area implications from a set of design specification values entered in the gray cells of a building design category forecast model. I’ve only shown one in Table 1 and one in cell B39 of Table 2. The entire Table of Contents is presented as the last exhibit in this essay. It is not included to display the master equations, however. They require greater explanation related to their forecast models. It is included to show classification of the Shelter Division by building design category and activity group.

A building design category is occupied by an activity group. The combination may require that additional design specification topics and values be added to its forecast model when it is amended to address a specific activity group. The Residential Activity Group in the Table of Contents illustrates the forecast models that address an activity group when it occupies the fundamental building design category options listed above.

In other words, gross building area is subdivided to serve an activity group. The shelter capacity, or gross building area per buildable acre, of the land area remains the same; but the internal capacity of the gross building area to serve a specific activity group will be affected by the group’s floor plan requirements. Gross building area is determined by the design specification values entered in a building design category’s design specification template. The shelter capacity of land and the intensity options considered are a function of these values. These are the strategic shelter design decisions that combine with movement, open space, and life support decisions to determine the spaces, places, and building mass that surrounds us in an urban pattern that cannot be permitted to consume our source of life.

The internal capacity of gross building area is a function of the activity’s program of floor plan requirements. This is the beginning of tactical architectural design decisions that are correlated to produce the form, function, and building appearance we recognize.

The master equations related to each building design category pertain to every potential activity group that may occupy the category. They make it possible to measure and forecast the implications of correlated mathematical design decisions in a fraction of the time it takes to prepare one schematic drawing; and the time-consuming drawing has always been limited to an intuitive, visual understanding of the implications depicted.

There are many activity groups that remain unrepresented in the attached Table of Contents, but group specifications only relate the capacity of gross building area to serve the demands of a specific activity. Keep in mind that gross building area may be occupied by any activity. The shelter capacity of land is a function of the gross building area present or planned. The scope of present or planned shelter capacity, activity, condition, and location of gross building area on land determines the value of the buildable acres to a city’s revenue investment portfolio; and the land’s ability to contribute to a city’s quality of life. The ultimate objective is to provide an economically balanced city design model of shelter capacity and intensity to finance the activities of growing populations within geographically limited areas defined to protect both their quality and source of life.

W. Martin Hosack: April, 2024