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Tuesday, December 27, 2022

Confronting Sprawl with an Adequate Language

 


City planners, architects, urban designers, landscape architects, zoning specialists, and many others concerned with the use of land have been preoccupied with the compatibility of adjacent activity and the oppression, disease, and crime stimulated by the overcrowding of buildings and populations within municipal land areas for quite some time. This has produced a series of independent stipulations within zoning ordinances that lack the mathematical correlation needed to form a successful leadership language. The extensive number of variances granted to often conflicting stipulations serves to prove the point. Sprawl symbolizes the leadership confusion. Fortunately, sprawl is slowly being recognized as a symptom of disease. The microscopic cause is a growing population’s need for shelter on a planet with limited resources. The cure will depend on our agreement with this observation and our ability to identify the shelter options available. This will require a new leadership language with vastly improved diagnostic potential.

It may be a surprise to learn that there are only six shelter options available when classification is based on the parking solution employed rather than the style applied, and this makes shelter capacity prediction for limited land areas feasible. It also helps to recognize that: (1) shelter is simply gross building area that may be occupied by any activity when it conforms to local building code requirements; (2) shelter quantity for any and all activity is a function of the gross building area that is placed on a given land area; (3) gross building area per acre is shelter capacity; (4) shelter capacity can be increased with floor quantity options that are one of a number of initial decisions that must be correlated; (5) shelter capacity options represent levels of measurable intensity; (6) current intensity levels are accidentally created with design stipulations that remain incomplete and uncorrelated; (7) intensity management with comprehensive, correlated design value decisions is needed to shelter growing populations within geographic limits prescribed to protect their quality and source of life; (8) intensity management topics apply to all buildings; and (9) the social activity within a building does not determine the physical intensity introduced but it may magnify the impact.

Building classification by style has distracted us from these fundamental observations for centuries. I’ve written about these six building design categories many times, and repeat them here simply as a reminder. They are: (1) G1 buildings with grade parking around, but not under, the building;(2) G2 buildings with grade parking around and under the building; (3) S1 buildings with adjacent parking structure on the same premise; (4) S2 buildings served by underground parking structures; (5) S3 buildings with parking structures above grade under the building; (6) NP buildings with no parking required. I have also included a set of shelter capacity and property demand forecast models for independent parking garages (PG) in a book I will mention at the end of this essay even though I don’t consider them buildings for human habitation unless dictated by an emergency.

My emphasis on parking rather than building style and appearance stems from my effort to accurately forecast the gross building area capacity of an acre of land when floor quantity options are correlated with the other pivotal decisions involved. These are the options for growing populations that we are expected to balance within limited geographic areas to share the planet with all that depend on it for survival. It is a deceptively simple proposition. It is complicated by the number of opinions, variables and decisions that must be correlated. Our mistake has been to overlook some of these decision topics and consider the remainder independently.

Shelter capacity forecasting depends on the simple subtraction of design specification values. They are entered in the shaded cells of a forecast model related to a chosen building design category and given land area. This subtraction proceeds from the given land area to the core area remaining for building and parking area. Subtraction is performed by an embedded algorithm that correlates all values entered to arrive at the core area remaining. A master equation related to the building design category calculates a range of gross building area options for the land area given, topic values entered, and range of floor quantity options introduced. A change to one or more of these values changes the gross building area predictions calculated by the forecast model. These are the shelter capacity options available for the land area given based on the design specification values entered. The intensity represented by each prediction is calculated with a separate equation noted in the model.

The forecast model format and its mathematical foundation introduce a comprehensive, correlated leadership language that can also be used to accurately measure existing physical conditions. The evaluation measured and recorded can then be used to lead future design specification decisions toward intensity levels and relationships that improve our ability to shelter growing populations within geographic limits. We cannot do this without a language that has the potential to lead with fundamental, comprehensive shelter design specifications. These decisions can no longer be left to the discretion of a marketplace that will consume land without limits because they cannot predict the consequences. It is now possible to predict the options available and evaluate the consequences implied with the organized measurement, evaluation, and documentation needed to build knowledge long before appearance becomes an issue.

TABLE 1

I have included Table 1 in many essays and am repeating it here as an example of a complete, correlated set of design specification topics and values for the G1 Building Design Category. I am also repeating text from an earlier essay to amplify its message.

There are 26 shaded cells in Table 1 for the G1.L1 forecast model. Each shaded value entered in a cell is correlated by an algorithm, and master equation in cell J47, to produce the gross building area options in cells B44-B53. I mention this to make the point that regulating each shaded value independently is a hopeless exercise without the leadership potential needed to produce total average revenue per acre equal to or exceeding a city’s average expense per acre without annexation or budget reductions over time.

The shaded cells in Table 1 are not intended to replace an entire zoning ordinance. They are intended to replace independent design specification topics with the correlation needed to lead shelter capacity toward its intended intensity and occupancy goals. (See “The Disorganized Zoning Ordinance”)

Gross building area prediction is the first objective in Table 1. The other predictions in the Forecast Panel add initial detail needed by a designer. The Implications Panel measures the consequences of the values entered in the Design Specification Template. The final intensity and dominance columns of the Implications Panel measure the results produced by the correlated shaded cell values, and resulting gross building area predictions, to make evaluation and knowledge accumulation feasible.

It should be obvious that language and knowledge is limited by the vocabulary available. Shelter intensity has been a term without adequate definition ever since its presence was recognized with instinct, intuition, awareness, and observation. Density and the Floor Area Ratio have been easy to measure but they have missed many of the controlling topics that must be correlated to provide the shelter massing and intensity leadership that forms a pattern for our quality of life. Current zoning stipulations have simply led to variance appeals and sprawling annexation patterns in search of a mirage called “physical, social, and economic balance”.

EXCERPTS FROM “LAND USE and DEVELOPMENT CAPACITY CORRELATION” (with modifications)

“I’ll close by including Table 1 as an example of an urban design forecast model that applies to all buildings served by an adjacent parking lot on the same premise. It is called the G1 Building Design Category and is the most common category used to shelter activity in many parts of the world -- when parking is required.

The gray cells in Table 1 indicate design specification topic locations. The values entered are mathematically correlated for use by the master equation in cell J47. A change to one or more of the design specification values entered will modify the results produced. The point is that these specification values are not independent and isolated. They represent combinations that must be correlated -- and illustrate the interactive relationship of building design decisions.

The ten floor quantity options entered in gray cells A44-A53 complete a set of design specification options. The master equation in cell J47 predicts their gross building area implications in cells B44-B53. The Planning Forecast Panel predicts further design implications using the equations on line 43. The shelter capacity, intensity, intrusion, and dominance impact of these options is calculated with the equations on line 43 of the Implications Module. I am not providing an evaluation of these impact measurements since this is a hypothetical example; but measurement, evaluation, and accumulated knowledge is the leadership promise offered by this system of building classification, design specification, planning prediction, implication measurement, and evaluation.

ADDITIONAL OBSERVATIONS

The public revenue implications of the gross building area forecast in Table 1 is easiest to explain by looking at the options predicted in cells B44-B53. If $10 of revenue were expected per sq. ft. of gross building area, the total annual revenue would range from $48,843 to $73,511 depending on the floor quantity chosen. Since the buildable land area noted in cell F10 is 100% of the gross land area given in cell F3, the total revenue projections would be divided by 5.230 acres to find the revenue potential per acre provided by the city’s inventory. This would range from $9,339 to $14,055 per acre. A simple comparison with the city’s annual expense per acre would indicate the contribution or subsidy implications of the land and building options contemplated.

The results that evolve from fundamental design specification decisions have been overlooked for centuries; and overdevelopment and oppression are not easily overcome when economic hardship is claimed -- until the examples become too extreme to ignore during the debate that ensues. The Implications Module in Table 1 illustrates one method of measuring the impact of gross building mass and composition on our quality of life within the urban fabric we create. When these measurements are combined with the financial evaluation mentioned in the paragraph above, it will become easier for a city to evaluate the combined impact of its shelter design decisions. A city that understands these implications for every parcel within its jurisdiction is a city that is prepared to evaluate the land use and urban design decisions that will affect its future.

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

CONCLUSION

“I hope I have shown that it is entirely possible to mathematically correlate land consumption with gross building area capacity, activity, economic potential, and quality of life within limited geographic areas when the leadership topics for each building design category classification are comprehensively defined and correlated with the algorithms, value decisions, and master equations required. The goal is to define a limited Built Domain without wandering consumption. I think we all understand at some level of comprehension that limits are required. It remains to define them and the path required with a language that can lead us to consistent results.

I have contributed the conceptual framework and technical information needed to continue this discussion in my book, “The Equations of Urban Design”. It is available on Amazon.com but the title may have been an unfortunate choice since the book is not consumed with equations. They are simply the foundation on which the conceptual, predictive, measurement, and evaluation format is based. I have also published over 190 essays regarding this topic at my blog www.wmhosack.blogspot.com. It has been visited by over 32,000 readers.

There is a lot of work to be done to reach the only goal that matters. Symbiotic survival is not an option. It is a mandate that will not be met until our habitat ceases to be a threat to ourselves and its source of life – the Natural Domain.”

Escape to Mars will simply prolong our mistaken assumptions regarding land ownership prerogatives, shelter capacity, and population growth.

Walter M. Hosack: December, 2022

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