Sunday, June 18, 2017

The US Architectural Debate Over Beauty and Taste


“I don't think the argument has yet to be successfully made in this thread, that beauty and taste are not the same, or, that the difference is tangible enough to be important. The Kimball is beautiful only to those of a specific taste culture, and even within that taste culture there is going to be disagreement. Gehry's later works are the poster children for this position. They are to some architects very beautiful and to other equally educated architects very ugly. Why? I think it’s because we all carry our own encyclopedias full of pleasurable architectural precedents. These encyclopedias are as unique to us as our fingerprints. Some are heavy in intellectual content, others heavier in the emotional (one could at this point mention Bach vs Beethoven). This is why many academics cringe when student critiques tread into the beauty vs non- beauty arena (or cool vs non-cool). In addition that discussion will ultimately relate to class and privilege (high culture vs low culture) which is sure to distract teachers and students alike from the task at hand. Rather speak of a process, space, relationships, and logic.”

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Stephen Altherr AIA



“RE: Stephen Altherr, I'll grant that beauty and taste are often inappropriately substituted for each other and it rarely matters. But are you also intending to minimize the importance of both? If so, would you like to radically revise AIA design awards programs? Or maybe leave the "design" awards alone and establish a separate architecture awards program? One that privileges process, space, relationships and logic?”

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Mike Mense FAIA



RE: Mike Mense: This implies that process, space, relationships and logic are unrelated to architectural design success. This may be true when the emphasis is on the form and appearance of a building; but it is logic that ignores the hundreds, if not thousands, of invisible decisions required to produce final shelter capacity, intensity, intrusion and dominance that is measureable. It represents logic and priorities that should be carefully considered by all who wish to build architectural knowledge.

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Walter Hosack

Sunday, May 21, 2017

A CAUTIONARY COMMENT


All architects, planners, city officials and residents should be careful of what they propose without a consistent ability to measure and evaluate the consequences. Intuition has never been a substitute for knowledge. It has simply been a catalyst producing both success and failure. Land is an irreplaceable source of life that continues to be squandered by promiscuous experimentation and speculation. Pictures of success and failure do not convey the information needed to repeat the first and avoid the second.

Consistent shelter capacity measurement, prediction and evaluation is defined and explained in my new book, The Science of City Design. It is available in e-book and paperback from Amazon.com.

Monday, May 15, 2017

Shelter Capacity Forecast Offer


I am offering a free shelter capacity forecast model to prove that it is possible to accurately predict shelter capacity options for land before a single line is drawn. These options are presented in a planning forecast panel based on the variables entered in a design specification template. The tool has been written to assist the effort to shelter growing population activity within a limited Built Domain.
If you would like to take advantage of this offer, please respond to wmhosack@gmail.com with the title, “Forecast Model Request”. A copy of the model will be attached to a brief explanation of its use and both will be sent by return mail. This is not a malicious offer. It is intended to introduce one tool in a tool set that can be applied to the use of land for shelter and preservation as a source of life.

I would like to put this tool set in the cloud for common use, but will need a sponsor to achieve the goal. Please note in your reply if you have an interest in the topic.

Saturday, April 15, 2017

What is Architecture? - Three Essays

This is a compilation of three essays I have written in an attempt to answer the question.
It’s a good question. It’s the same one Caesar Augustus asked Vitruvius in Rome centuries ago. There are so many facets that must be reconciled to arrive at an answer! It’s another design problem. We are often distracted by a few high priority topics and compromise with others to arrive at an answer that is not a unifying concept. I think our education has taught us that there are many answers but few exceptional concepts. Intelligence gathering and logical evaluation are key ingredients for a concept that has the potential to increase knowledge.
Architecture is a tactical plan to achieve a shelter objective within a specific project area. It is written and drawn to lead and correlate the work of many contributing technical specialties. Final form and appearance symbolize the complex process and represent current opinion, knowledge and ability. The result is measureable shelter capacity, intensity, intrusion, and dominance that affect our quality of life within and beyond the building.
City design is a strategic plan written and drawn to correlate tactical decisions that combine to affect shelter, movement, open space, and life support within the Built Domain. The strategy leads tactical decisions that affect our physical, social, psychological, environmental, and economic quality of life.
The goal is a declared policy of symbiotic survival that is the only cure for a pathogenic disease on the face of the planet that we call sprawl. To succeed, we must learn to shelter the activities of growing populations within limited geographic areas that protect their quality and source of life – The Natural Domain.
ADDENDUM to “WHAT IS ARCHITECTURE?” 

A concept does not become knowledge until it can repeat success and avoid failure. In architecture, a concept is considered artistic inspiration. Repetition is considered plagiarism. As a consequence, the pursuit of fine art and the fear of plagiarism have led us away from the formation of knowledge that can improve the practice of the entire profession. This will continue as long as fine art is considered to be the answer to the question, “What is architecture?” Only the best is fine art; and fine art is the form, function, and appearance of a complex anatomy. This anatomy is created by an orchestra of technical specialties with a score written, drawn, and conducted by an architect. There are few masterpieces but many compositions. This is architecture, and its greatest strength is a constant search for improvement with logic that always grapples with the unknown. It is the only way to write a score that correlates the performance of an orchestra.
The decisions that set the stage for inspiration are consistent and mathematical. The values chosen determine the shelter capacity of land and the intensity, intrusion, and dominance introduced. These factors can also be measured at existing locations for comparison and evaluation. Architectural form, function, and appearance emerge from these site plan parameters to amplify the quality of life defined at street level. The correlated result symbolizes a culture’s current opinions, knowledge, and ability. This is architecture with a language that can elevate its tactical efforts to the strategic level of city design. In other words, architecture is (can be) a tactical and strategic profession that produces shelter strategy for growing populations. It is served by movement, open space, and life support within a Built Domain that must pursue a policy of symbiotic survival.
A logical, consistent mathematical foundation for ensuing design decisions has never eliminated inspiration. It provides a platform of knowledge to justify design decisions that are presently defended with politically vulnerable opinion.
ON REFLECTION
On reflection, I have ripped my orchestral metaphor for architecture from the drawing board and thrown it into a pile of discarded efforts. The text below is another effort.
Architecture is logic that correlates diverse technical specialists and aesthetic contributions to achieve a shelter project objective. Unfortunately, these project achievements are not led by a strategic language that is able to accumulate knowledge and consistently lead project contributions toward shelter for growing populations within limited geographic areas that protect their quality and source of life – The Natural Domain. The achievement of tactical project objectives without a strategic plan for symbiotic survival will continue to produce pathogenic sprawl, resource depletion, and pollution across the face of a planet that does not compromise with ignorance. Architecture is judged by opinion that determines the building’s status as fine art, but opinion is not equal to the contribution required for symbiotic survival.






Saturday, April 8, 2017

Townhouse & Apartment Density Exposed


As a young architect and city planner in local government I was asked to assist in the evaluation of a townhouse development and the density proposed. I soon realized that my undergraduate and graduate education in architecture and city design had left me with more opinions than knowledge, and that these opinions were based on those of my professors. They could only be defended with logic that often failed to persuade in the face of political, social, psychological, and economic opposition. This led to my search for a credible leadership language capable of accumulating knowledge that could convince those beyond the walls of the profession. It began with my effort to replace educated trial and error intuition with knowledge built on a mathematical language that I knew was at the heart of initial design evaluation and decision. If successful, I believed that this language would have more persuasive power in the public arena of competing debate, and would form the basis for a new language and science of city design. This science now addresses the universe of building design categories, but this essay will only address my original question that was formed years ago. It concerns reasonable density levels for townhouse (R2) and apartment (R3) activity groups that occupy the G1 Building Design Category. (The G1 category encompasses all buildings served by a parking lot adjacent to one or more sides of a building. It does not include G2 buildings served by a parking lot that extends under a building.) The forecast models used in this essay represent the answer to my original struggle with density and are entitled G1.R2 and G1.R3.

TOWNHOUSE DENSITY

As used in this discussion, townhouses are single-family dwelling units that are attached to one or more additional units but not stacked above a dwelling unit. Table 1 illustrates forecast model G1.R2 and contains a Land Module, Shelter Module, Forecast Module, and Density Module. The first three modules contain design specification boxes. The modules perform automated calculations based on the specification values entered. The results provide the data needed by a master equation to predict density options for evaluation in the Density Module.


Land Module

This module begins with the gross land area entered in cell F3. It distills the shelter area (SHA) percentage of gross land area (GLA) remaining for building footprint, service pavement, and project open space in cell F12 by subtracting percentage estimates for the topics represented by cells F4-F6, F8, and F10-F11. Eighty-two percent of the gross land area remains in cell F12 for shelter area after these topic estimates are subtracted.

Shelter Module

Values are entered in sixty Shelter Module specification boxes, beginning on line 15 and ending on line 27, to mathematically define the project proposal. The values entered in each box can be altered to create proposal options for evaluation. This is also true for the seven boxes in the Land Module and the nineteen boxes in the Density Module.

Forecast Module

The values entered in the Shelter Module are converted to square foot predictions on lines 38-42 of the Forecast Module. Since the townhouse proposal contains a mix of dwelling units defined in cells A23-A27 of the Shelter Module, the objective of the Forecast Module is to convert the values calculated for this mix to the data on lines 38-42 of the Forecast Module, and the mix averages noted on line 45. The goal of the Forecast Module is to calculate the total average impervious cover per dwelling unit (AVGIMPD) in cell J43 from the mix definition areas calculated in cells A38-L42 of the Forecast Module. The average values on line 43 are used to calculate the AVGIMPD value in cell J43.

Density Module

The objective of the Density Module is to forecast density options in cells F53-F71 based on the unpaved open space values entered in cells A53-A71. The equation in cell B52 is used to calculate the average land area required per dwelling unit (LDU) in cells B53-B71 as the unpaved open space (UOSD) increases in cells A53-A71. The remaining shelter area calculated in cell G12 is then divided by each succeeding LDU value in cells B53-B71 to find the number of potential dwelling units in cells E53-E71. The shelter area densities calculated in cells F53-F71 are based on the shelter area available in acres and the dwelling unit quantities calculated. Shelter area is used foe he density calculations because this is where people will live and this is the immediate density they will experience. Density per buildable land area (BLA), net land area (NLA), and gross land area (GLA) could also have been calculated; but these calculations would represent increasingly ambiguous statistics.

Density Implications

The density forecast in cell F53 is much greater than the density forecast in cell F71 because the unpaved open space percentage of land area per dwelling unit has increased from 5% to 95% in cells A53-A71. An increased unpaved open space percentage means that more total land is required per dwelling unit, and a fixed shelter area (SHA) can accommodate fewer of these larger land areas.

Impervious cover is equal to 100% minus the unpaved open space percentages entered in cells A53-A71. It has declined from 95% to 5% in cells A53-A71 as the unpaved open space percentage has increased. If the storm sewer capacity available can accommodate runoff from 30% impervious cover without storm water detention, this would mean that 70% unpaved open space would be required and the project would be limited to a density of 6.18 dwelling units per shelter acre as noted in cell F66. Most townhouse developers would not be satisfied with this limit. In this case, they could introduce a storm detention system that would permit a higher impervious cover percentage; or revise the project proposal values used to define the project in the Land and Shelter Modules of the Design Specification Template.

If a developer wanted to reach the density of 10.3 dwelling units per shelter acre in cell F62, cell A62 indicates that the storm sewer system would need to accommodate 50% impervious cover based on the project specification values entered in the Land and Shelter modules. If 50% impervious cover sewer capacity were too demanding and the density was still an objective, the eighty-six design specification values entered in the Land, Shelter, and Density modules could be adjusted to produce another design option, or a storm detention system could be introduced. The question of reasonable density that produces a desirable quality of life would remain, however.

The underlying point is that all design specification values entered in each box of Table 1 are correlated to produce the results in the Density Module. A change to one or more of these values will produce a new forecast of options. Neglecting attention to one or more of these topics and values will produce arbitrary leadership. Neglecting correlation of these values will produce contradiction and confusion.

There is another question. Does the shelter area density of 10.3 dwelling units per shelter acre produce undesirable intensity? The corresponding shelter capacity (SFAC) noted in cell H62 is 13,985 sq. ft. per shelter acre. The intensity calculated in cell J62 is 0.161. The dominance calculation in cell L62 adds an intrusion measurement equal to floor quantity divided by five in cell K53 to the intensity measurement in cell J62. The dominance result measures the impact of building mass, pavement and height within the project area. The value calculated in cell L62 is 0.499. These intensity and dominance calculations are measurements without a quality of life scale based on research at the present time. An acknowledged scale would begin to indicate how well the proposal would protect the population’s physical, social, psychological, environmental, and economic welfare. The scale does not exist at the present time because existing conditions have not been measured and evaluated. As a result, the intensity and dominance calculations in Columns J and L of the Density Module are like early blood pressure measurements. They also began without an accepted reference scale based on a database of research to explain their meaning. The equations on line 52 make consistent measurement feasible, however, and comparison with existing condition measurements will produce knowledge to support negotiation and opinion in the offices and arenas of city design debate.

APARTMENTS

As used in this discussion, apartments are one-story dwelling units that are connected and stacked within a larger gross building area envelope. Table 2 illustrates apartment forecast model G1.R3. It contains a Land Module, Shelter Module, G1 Module, Apartment Module, and Density Module. The first four modules contain design specification boxes. The modules perform automated calculations that lead to the density options predicted for evaluation in the Density Module.



Land Module

This module begins with the gross land area entered in cell F2. It distills the shelter area (SHA) percentage of gross land area (GLA) remaining for building footprint, service pavement, and project open space in cell F11 by subtracting percentage estimates for the topics represented by cells F2-F5, F7, and F9-F10. Eighty-two percent of the gross land area remains in cell F11 for shelter land area after these estimates are subtracted.

G1 Module

The G1 module contains four specification boxes that receive miscellaneous project service and social pavement percentage estimates. These estimates are used to calculate the shelter area remaining for building and parking cover in cell G19.

Apartment Module

Specification values are entered in twenty-eight Apartment Module s boxes, beginning on line 23 and ending on line 33, to mathematically define the project. The values entered in each box can be altered to create proposal options for evaluation. This is also true for the seven boxes in the Land Module and the twenty-nine boxes in the Density Module.

The values entered in the G1 and Apartment modules define the mix of dwelling units proposed in cells A29-A33. The objective of the Apartment Module is to calculate the mix averages on line 35, and in particular, the average dwelling unit area (ADU) in cell D35.

Density Module

The objective of the Density Module is to forecast density options in cells C42-M60 based on the unpaved open space values entered in cells A42-A60 and the floor quantity options on line 40. The density options calculated are based on the shelter land area available (SHA) because this is where people live and this is the immediate density they will experience. Density per buildable land area (BLA), net land area (NLA), and gross land area (GLA) could also have been calculated; but these calculations would represent increasingly ambiguous statistics.

Density Implications

The density forecast in cell C42 is much less than M42 because the floor quantity has increased from 1 to 100 stories, but a building cover calculation would have to confirm if the remaining building footprint area is feasible. This is beyond the scope of Table 2, since it is focused on density; but is included in the G1.R3 spreadsheet of city design.

The density forecast in cell C42 is much greater than the density forecast in cell C60, however, because the unpaved open space percentage of land per dwelling unit has increased from 5% to 95% in cells A42-A60. This means that the core land area available for building cover and parking cover in Col. B of the Density Module has declined in response to the increasing open space in cells A42-A60. This declining core area can accommodate fewer average dwelling unit areas (ADU’s), which produces a decline in achievable density. The reader should note that the core area declines in Column B until it becomes unrealistically small for both building and parking cover, however; and densities decline in cells C42-M60 in response to increased unpaved open space in Column A until they no longer represent an apartment densities.

Impervious cover is equal to 100% minus the unpaved open space percentages entered in cells A42-A60. If the storm sewer capacity available can accommodate runoff from 60% impervious cover without storm water detention, this would mean that 40% unpaved open space would be required. As a result, a five story building is limited to a density of 16 dwelling units per shelter acre for a five story building as noted in cell G49. If the storm sewer capacity were not this great, the five story density would decline as noted in cells C50-C60, or a storm detention system would be required to justify the impervious cover percentage.

If a developer wanted to reach the density of 20 dwelling units per shelter acre in cell G46, the storm sewer system would need to accommodate 75% impervious cover based on the project specification values entered in the Land, G1, and Apartment modules. If 75% sewer capacity were too demanding and the density was still an objective, the floor quantity in cell G40 and the values entered throughout the design specification template would have to be re-examined. The 25% unpaved open space in cell A46 would also have to be examined for excessive intensity.

The underlying point is that all specification boxes are correlated in Table 2, and the values entered in each box are correlated with the UOSA values in cells A42-A60 to produce the results in the Density Forecast Module. A change to one or more of these values will produce a new forecast of options. Neglecting attention to one or more of these topics and values will produce arbitrary leadership. Neglecting correlation of these values will produce contradiction and confusion.

There is another question. When does apartment density produce undesirable intensity?

Intensity

Table 3 presents related intensity calculations for each of the density values in cells C42-M60 of Table 2. For instance, the density of 16.0 in cell G49 of Table 2 is based on the design specification values entered in the Land, G1, and Apartment modules above; and the 40% unpaved open space area in cell A49. Table 3 calculates that this represents an intensity of 0.258 in cell G9. Cell G9 in Table 3 calculates that the density of 20.0 in cell G46 of Table 2 will produce an intensity of 0.403 based on the design specification values entered in the Land, G1, and Apartment modules of Table 2 and the 25% unpaved open space area entered in cell A46 of Table 2.



Intensity is a calculation in the dark at the present time. A reference scale supported by a database of research measurement would indicate how well the proposal would protect the population’s physical, social, psychological, environmental, and economic welfare (“quality of life”). The scale does not exist at the present time because existing conditions have not been measured and evaluated. As a result, the intensity calculations in in Table 3 are like early blood pressure measurements conducted to build a database of knowledge. Consistent measurement of existing conditions is feasible with a design specification template, however, and comparison will produce knowledge to support negotiation and opinion in the offices and arenas of city design debate.

Dominance

A dominance measure is equal to the sum of an Intensity measure and an intrusion measure. Intrusion is measured by dividing floor quantity by five. The quotient is added to the intensity calculation in Table 3 to form the dominance measurements in Table 4. If you locate cells G31 and G34 in Table 4, you will see that the intensities calculated in Table 3 have dominance measurements of 1.258 and 1.403 when five story building intrusion is considered.



Therefore, the densities of 16.0 and 20.0 produced by the design specification in Table 2 have associated intensity measurements of 0.258 and 0.403 in Table 3. They have dominance measurements of 1.258 and 1.403 in Table 4 that represent the sum of intensity and intrusion measurements.
The implications surrounding these measurements are yet to be determined, but their significance lies in the ability to measure, since it can lead to knowledge.

Sunday, March 19, 2017

Adapting Our Cities to Reality


We have been in a position of weakness surrounded by the power of tooth and claw for thousands of years, and have had to dominate without conscience to survive. Success has given us time to pursue non-lethal competition. It mimics our survival efforts with incomplete rules that substitute for conscience. Competition without conscience is war by another name. It can make the concept of democracy a casualty.
A superior predator that does not respect its species will not survive the carnage - until it recognizes the symbiotic policy of the planet. It is an axiom we have ignored within the perimeters of partial safety we have created. This safety has encouraged us to compete with the planet for land as our need for shelter grows with success. Growth is considered success, and it has expanded the urban pattern into amorphous, pathogenic sprawl surrounded by contaminated water. The two are contained within a plastic bag of atmosphere that accumulates the heat and pollution generated by growth and success. The combination threatens the gift we have been given. How much more will it take for the ultimate predator to recognize that the planet cannot be dominated?
It is we who must adapt, and the contributions of many are required. I have written The Science of City Design to address the issue of shelter. It provides a language capable of measuring, evaluating, and expressing land use decisions in mathematical terms of shelter capacity, intensity, intrusion, and dominance. You will learn that these terms and their definitions can lead site planning and shelter quantity decisions to form an improved quality of life over time. The goal is to shelter the activities of growing populations within a limited Built Domain that protects their quality and source of life - The Natural Domain. It is one of many precise languages written to convert opinion to knowledge. Its use will require adaptation that is a challenge to dominating, predatory power promoted by competitive instinct. As always, our competing instincts are the issue. Future decisions will reveal if we recognize the policy of a planet that demands symbiotic behavior from a predator that must adapt to its stewardship responsibility.

Photo courtesy of NASA



Tuesday, March 7, 2017

Graduating from the Floor Area Ratio


The floor area ratio FAR is a zoning regulation originally created to protect public health, safety, and welfare from excessive construction in urban areas. It is a project measurement equal to gross building area divided by gross land area in square feet. A floor area ratio of 5, for instance, means that 5 acres of gross building area may be constructed on one acre of gross land area. The simplicity of the regulation is attractive, but its simplicity inadequately leads the decisions that combine to determine shelter capacity, intensity, intrusion, and dominance within projects, neighborhoods, districts, cities, and regions.  

CORRELATION

I’ll make my point with Table 1. It is a forecast model constructed to predict shelter capacity in square feet of gross building area per buildable acre of land when no parking is required. There are eight boxes in the Land Module and five boxes in the NPL Module. The values entered in these boxes may be modified at will and represent design specification decisions. These decisions are correlated to find the maximum core area available for a building floor plan in cell G32 using the architectural algorithm in cells H3-H33. The core area found in cell G32 is used by the master equation in cell A35 to predict gross building area options in cells B40-B49. These options are based on the floor quantity alternatives entered in cells A40-A49.



The shelter capacity options related to the gross building area predictions in Col. B of the Planning Forecast Panel are calculated in cells D40-D49 using the equation in cell D39. Shelter capacity is expressed in building sq. ft. per acre.

Massing ratios related to the gross building area options in Col. B of the Planning Forecast Panel are calculated in Col. E. These ratios are used by the equation in cell F39 to calculate the intensity represented by each gross building area option in Col. B of the Planning Forecast Panel.

Related intrusion measurements are calculated in Col. G. They are used to calculate dominance options in Col. J of the Planning Forecast Panel using the equation in cell H39.

Finally, the floor area ratio representing each gross building area option in Col. B of the Planning Forecast Panel is calculated in Col. J using the equation in cell J39.

The point is that the floor area ratios calculated in Col. J of the Planning Forecast Panel react to the specification decisions entered in the 23 boxes of the NPL forecast model. The floor area ratio does not lead them, and our emphasis on the ratio as a leadership tool has produced confusion, argument, conflict, and the application of legal opinion based on the precedent of mistaken assumptions. I’ll make my point with one issue.

In my opinion, the most significant topic omitted from floor area regulation is the provision of social open space for people at street level. The opposing argument has contended that social open space is a public benefit that should be purchased at public expense. The open space specification in cell F11 of Table 1 is zero percent in cell F11 to begin an evaluation of these two positions. The value represents a developer’s attempt to maximize leasable building area on a given, high-cost urban land area. If the floor area ratio limit for Table 1 is 19, the design specification predicts that a 20 story building will produce 823,776 sq. ft. of gross building area and a floor area ratio of 18.91. I could have adjusted the specification values to make the floor area ratio exactly 19 in cell J47, but left it so I could point out that predictions will change whenever one or more specification values are modified in Table 1.

Table 2 has revised the zero percent value in cell F11 of Table 1 to 32.18%. All other specification values from Table 1 are held constant in Table 2. The 32.18 percentage has been entered to make the floor area ratio in cell J49 of Table 2 identical to that in cell J47 of Table 1. A comparison shows that the same floor area ratio and gross building area can be achieved when 32.18% of open space is provided for pedestrian relief at street level, but the trade-off is an increase from 20 stories in Table 1 to 30 stories in Table 2. The additional stories represent additional cost to reach an equal gross building area. In the past an increase in height was considered a bonus in return for social open space at the pedestrian level, but the calculations in Table 2 show that ten additional floors produce gross building area parity.

It could be argued that a bonus would involve negotiations for building height in excess of ten stories to compensate for the cost of increased building height. It could just as easily be argued that the floor area ratio of 16 was a reasonable limit; that social open space has been ignored as an essential part of the effort to protect public health, safety, and welfare within urban pattern and form; and that the deficiency should not be allowed to continue. I do not intend to resolve the argument. I only wish to point that it can be debated on a more credible foundation of measurement, evaluation, prediction, and knowledge. Cooperation between public and private interest will not be secured until all parties can sit around a table discussing options with a common language that can accurately predict implications.



GROSS BLDG AREA

In most cases a developer will know the land area involved, but in some cases he or she will be exploring the buildable land area needed to serve a given gross building area objective when a floor area ratio is given. Table 3 has been constructed to answer this question. If a floor area ratio of 16, a gross building area objective of 850,000 sq. ft. and a 30% social open space objective are given in addition to the other specification values noted, the master equation in cell A36 and the secondary equations in row 40 of the Planning Forecast Panel predict that 1.212 buildable acres will produce a floor area ratio of 16.10 in cell K49 when a 25 story building is chosen in cell A49. A slight modification to the specification values entered in the NPB Module of Table 3 could reduce 16.10 to a precise floor area ratio value of 16 in cell K49. The entire specification would represent a public/private agreement.



Table 4 shows that when no open space is provided in cell F10, the same gross building objective and floor area ratio can be reached on the same land area with only 17.5 building floors. The floors needed to compensate for the 30% public open space dedication in Table 3 would be a subject for negotiation as mentioned previously.



CONCLUSION

When social open space was introduced in Tables 2 and 3, the intensity and dominance calculations in columns F and H of the Planning Forecast Panel dropped from those calculated in Tables 1 and 4. There is no research that defines acceptable levels of intensity and dominance, but the ability to measure these conditions brings us closer to the knowledge needed to protect public welfare and improve quality of life within urban areas.

At the present time, most cities are woven together with ribbons of sidewalk and torrents of traffic. In the most extreme cases, these rivers flow between canyons of artificial stone and glass governed by skyplane regulations that attempt to ensure light, air, and ventilation penetrate to street level. In other cases, the sidewalk is omitted and replaced by a parking lot that qualifies as a front yard. In both cases, it has been our method of protecting the public health, safety, and welfare with minimum standards that are now coming into question. Why is the public being protected with government standards meant to keep them alive with a minimum quality of life (welfare)? The measurements of shelter capacity, intensity, intrusion, and dominance in Tables 1-3 represent a method of calibrating “welfare” so that research can begin to produce the knowledge needed to define minimum standards for livable cities.

The physical intensity, intrusion, and dominance of shelter, movement and life support within cities is offset by social open space. The result is referred to as urban form composition. We have yet to write the first score in this composition with a language that can lead the orchestra. The result has been discordant practice as virtuosos independently tune their instruments.

The first step is to recognize that a language is needed. The second is to recognize that cities must be woven together with social open space before they can begin to protect a population’s physical, social, psychological, environmental, and economic welfare.

Tables 1-3 were included to illustrate how open space negotiations can begin when assumptions are replaced with accurate measurement and calculation. The debate concerns the need for this open space to protect the public welfare, and the public/private share of this expense. These are political questions that require additional knowledge, and I do believe that answers are needed. The Science of City Design[1] has been written to encourage you to explore these questions with a credible language. It can lead us to a geographically limited Built Domain capable of protecting our quality and source of life -- the Natural Domain.



[1] Hosack, Walter M., The Science of City Design, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com)

Thursday, March 2, 2017

Improving the Influence of City Planning & Design


Public appointments and elections are based on the concept that reasonable men and women can make reasonable decisions in the absence of conclusive knowledge. When uncorrelated zoning regulations conflict with site planning reality, as they often do, the officials appointed and elected face variance requests and render decisions to resolve conflict based on project details that defeat consistent leadership direction. When faced with annexation requests, they have even less ability to accurately analyze the area’s potential to offset a municipalities shared expense per acre for administration, maintenance, improvement, and debt service as both increase in age.
Opinion did not cure the Black Plague and it will not cure pathogenic urban sprawl. Sprawl consumes agriculture and The Natural Domain in a failing attempt to surround an expanding core of blight and decay. It will continue until we begin to define the cellular structure of its anatomy in a language that can lead us to prescribe consistent, reliable, and credible treatment.
Planning commissions, councils, and mayors depend on their planning staffs, but the staff does not have the language needed to define problems, conduct research, build knowledge and convincingly defend recommendations. They must rely on conflicting regulations. This makes them servants rather than leaders of opinion; and the result is often distorted logic, political leverage, and faulty assumptions that lead to arbitrary decisions by elected and appointed officials. These decisions remind me of the considered opinions that defended blood-letting as a medical cure. A common, correlated leadership language capable of defining problems and solutions is needed.
There are now two worlds on a single planet, and The Built Domain is slowly being recognized as pathogenic sprawl that is a threat to agriculture and The Natural Domain. A correlated, scientific language of city design is needed to study a physical anatomy that will grow without restraint until a cure for this disease is found. This is not a problem that can be solved with the logic of opinion until it is supported by the science of city design. Every profession has had to invent a specifically relevant language to build knowledge, lead others, and convince popular opinion of the benefit. Architecture, city design, and city planning are no different. They are just behind as the public consequences grow.

Monday, February 27, 2017

Updating a Comprehensive Plan


A comprehensive plan update will suffer from later inattention until it is linked to a city’s economic welfare. In other words, a city is a farm and every acre within its boundaries combines to produce an average yield per acre. This yield must meet or exceed a city’s average expense per acre as operating, maintenance, improvement, and debt service expense increase with age. Annexation of acres for new revenue often repeats past mistakes by assuming that the new income will not be reduced by the increasing expense of aging. As expense increases, a city with fixed income is often accused of profligacy when seeking to increase revenue in response. Budget cuts ensue and decline takes one more step toward blight.

As the journey continues, decline becomes visually obvious and flight from fear begins as annexation attempts to surround disease. The disease expands and the city fights to protect annexation corridors and avoid encirclement by surrounding suburbs. This occurs time and again across the nation because a city does not recognize that it is a farm and must understand the yield from each of its acres over time. It becomes more severe when a city is surrounded by suburbs and must meet the increasing expense of aging with inadequate development capacity and activity allocation. At this point redevelopment and increasing taxation become unwelcome visitors met with skepticism, cynicism, assumption, opinion, prejudice, disrespect, and obdurate behavior resistant to change. A comprehensive plan cannot meet these objections with credible solutions until it can explain and correlate land use allocation, shelter capacity, occupant activity, and economic productivity. A new mathematical language and science of city design is required to credibly defend comprehensive plan recommendations.

Arguing for a Science of City Design


These are slides from a presentation that argues for new tools to empower our approach to the growth of cities and the shelter they serve.

THE PROBLEM

Growing populations are currently building shelter for a wide range of activities in a pathogenic pattern of sprawl that is slowly consuming agriculture and our source of life – the land of The Natural Domain.  This continues because we have not been able to accurately predict the development capacity of land given the current disorganized nature of shelter design decisions and regulation.

THE OBJECTIVE

The challenge is to predict our capacity to shelter human activity within limited geographic areas defined to protect our quality and source of life – The Natural Domain.

THE APPROACH

(1)    Comprehensively list the shelter design categories available and their related specification topics;

(2)    Mathematically correlate specification topic relationships; and

(3)    Predict the gross building area potential of land based on the design category chosen and the values assigned to its specification topics.

THE DESIGN CATEGORIES

Six primary design categories may be occupied by any activity group. A category forecast model includes two specification modules and a forecast panel. An activity module is added to the category specification when it is tailored to a specific activity group.

THE FORECAST MODELS

A forecast model is written to predict answers to a question based on the specification values entered. A change to one or more values produces optional answers for comparison, evaluation, and direction.

THE QUESTIONS

1)      How much gross building area can be constructed on a given land area?

2)      How much buildable land area is needed to accommodate a given gross building area?

THE RESOURCES
Table 1 is a current list of forecast models. The Design Category Group can be occupied by any activity. The Activity Group addresses residential activity that occupies the G1 Category of buildings.




Table 2 is a sample of a completed G1 Forecast Model. It contains a Land Specification Module, a G1 Specification Module, and a Planning Forecast Panel. The values entered in the boxes of the specification modules represent design decisions that can be modified for comparison and evaluation. The implications of a mathematically correlated set of design specification decisions are presented in the Planning Forecast Panel.

Column A in the panel is a specification column of optional building heights. Columns B-E forecast the design implications of a full set of optional specification decisions. Column F forecasts shelter capacity per acre of land consumed. It is a key measurement of the land use efficiency being proposed by the design specification. When a city has a limited geographic area, the efficient allocation of shelter capacity and occupant activity determines the total revenue available to support operations, maintenance, improvement, debt service, and quality of life.

Columns G-J calculate the intensity, intrusion, and dominance implied by the shelter specification. They are quality of life measurements that will build knowledge with continued use.



THE IMPLICATIONS

1)      Gross building area predictions are relevant to real estate evaluation and private enterprise economics.

2)      The allocation of shelter capacity and activity per acre determines public revenue potential and municipal economic stability.

3)      Evaluation of the intensity, intrusion, and dominance produced by a design category specification will produce quality of life knowledge and improvement.

CONCLUSION

The solution to a problem begins with a language that can express concepts, define options, measure implications, evaluate results, and build knowledge. The argument for a science of city design[1] is an argument for a language that can begin the search for shelter solutions to the problem of symbiotic survival. Shelter solutions, however, are only one of the many essential answers required.



[1] Hosack, Walter M., The Science of City Design, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com. Available in paperback from CreateSpace)

Monday, February 13, 2017

Surface Parking Limits on the Shelter Capacity of Land


A surface parking lot must expand to increase parking space quantity. An increased quantity increases permitted gross building area (GBA), but decreases the land remaining for building footprint (BCA). The conflict is resolved by either increasing the number of building floors associated with the reduced building footprint, or adjusting other areas of the site plan. This rather simple relationship has caused endless debate because surface parking requirements affect the shelter capacity of land, and their credibility is often challenged by the history of a specific activity at a specific location. This essay will ignore activity and drill down to understand the specification topics, values, and relationships that determine parking lot area and reduce shelter capacity for any activity on any land area.
Basics
A parking requirement specifies the square feet of gross building area (GBA) permitted per parking space provided. For instance, a parking requirement of 250 means that 250 sq. ft. of gross building area may be constructed for every parking space introduced.
Figure 1 plots the increase in gross building area (GBA) potential for a 5 story building as the parking requirement declines. (Keep in mind that a parking requirement of 600 is less restrictive than a requirement of 250 because more GBA is permitted per parking space provided.) The x-axis increments represent this decline in GBA restriction. The increase from 5,912 sq. ft. to 41,382 sq. ft. of GBA shows the dramatic impact of parking requirements.
Figure 2 plots the increase in GBA potential per floor of building height as increased amounts of GBA per parking space are permitted along the x-axis. The increase from 4,966 sq. ft. to 41,382 sq. ft. shows the combined impact of parking requirements and building height options.

The increases plotted in Figures 1 and 2 can be found in Table 1. They serve to explain why parking requirements and building height options are hotly debated across the table in every planning office of the nation. Frustration prevails because the accurate prediction options and implications is not a common practice.
Line (cd) in Figure 2 shows that GBA increases decline with each floor of increased building height; and that height increases above 2 stories produce declining increases in GBA. This make these height options increasingly less cost effective when all other design specification values remain constant.
Line (ab) shows that 15,000 sq. ft. of GBA can be achieved with a 1 story building when 1 parking space is required per 600 sq. ft. of GBA, and with a 5 story building when 1 parking space is required for every 275 sq. ft. of GBA. If you look at 20,000 sq. ft. of GBA on the y-axis in Figure 2, you’ll see that it cannot be achieved with a 1 story building; given the design specification values involved. Design specifications will be explained in the section to follow.
The point is that parking requirements and building height options play a significant role in determining the shelter capacity of core land area; that shelter capacity can be occupied by any activity; and that one design category equation makes it possible to calculate its GBA potential on any core land area. (The G1 Design Category is being used for this example and applies when surface parking around, but not under the building, is chosen as a parking design solution.)
Design Specifications and Core Area
The design specification decisions in Table 2 are represented by the values entered in the boxes of Column F. Calculating core area in cell F32 is the objective, since this is the land remaining for building footprint and surface parking after percentage estimates for all other site plan areas have been subtracted.
Cell F34 in Table 2 specifies the parking requirement (a) under study, and cell F33 specifies the total surface parking lot area per parking space (s) estimated. The master equation in Table 2 uses the (a) and (s) values entered; the core area calculated (CORE); and the building height options entered in cells A42-A51 to calculate the GBA options in cells B42-B51. The GBA options from cell B7 to L11 in Table 1 were found by modifying the (a) value entered in cell F34 of Table 2. These (a) value alternatives were noted in cells B6-L6 of Table 1.
The value (a) is only one of 25 specification boxes in Table 2, and a change to one or more of the values entered will produce a different set of GBA options in Col. B. All values were held constant as the (a) value was modified to produce the GBA options from cell B7 to L11 in Table 1.

The Specification Value (s)
The value (a) entered in cell F34 of Table 2 is a straight-forward parking requirement that restricts shelter capacity. The accuracy of all parking requirements is a matter of continuing debate. It results from their effect on GBA potential and the lack of research available to justify the values involved. The only certainty at this point in time is that parking is needed for the transition to sheltered activity, and can be provided in either remote or adjacent locations.
The value (s) is equal to total parking area, excluding loading area, divided by the number of parking spaces provided. The value is easy to find when a site plan can be measured, but difficult to predict. The 18 specification decisions that combine to create the value (s) are shown in the boxes of Table 3. Each of these decisions is a variable that can be modified to alter the results calculated in cells C15-K20. The objective is to find the values in column K. The calculated result in cell K15 shows that the (s) value entered in cell F33 of Table 2 is based on a 90 degree parking layout decision.

The design specification values (l), (a), and (e) in Cells J3-J5 of Table 3 are shown in Figure 3 as dimensions of a parking lot bay. (A “bay” includes a circulation aisle and parking spaces on both sides of the parking aisle.) A parking lot may also contain parking stalls, service stalls, and circulation aisles in addition to those found in parking bays. It may also contain landscape islands to relieve the sea of asphalt. The design specification values (C%) and (L%) in cells J7-J8 of Table 3 are introduced to estimate their presence in this example. The values chosen show that a utilitarian parking lot is planned with little amenity. Parking space angle and circulation aisle options are entered in cells A15-B20 of Table 3, and each value affects the gross and net parking lot areas predicted in cells H15-J20. The number of parking spaces in one row of a bay must be estimated in Cell J6 of Table 3 to forecast parking lot area. The 10 spaces entered in Table 3 produce an average of 406 sq. ft. per space in cell K15. Thirty spaces produce an average of 389 sq. ft. and 5 spaces produce an average of 432 sq. ft. when all other specification values remain constant. Understanding this range of areas can be helpful when choosing the value to enter in cell F33 of Table 2.

The objective is to forecast average parking lot area per space in cells K15-K20 of the Planning Forecast Panel in Table 3. The value in cell K15 has been chosen for entry in cell F33 of Table 2 because it is related to a 90 degree parking angle. The area options in column K are calculated from the values entered in Columns A and B of the Planning Forecast Panel and the values entered in Cells J3-J8. A change to one or more of these values will produce a new forecast.
The point of this exercise has been to explain the scope of design specification decisions that must be correlated to produce the value entered in cell F33 of Table 2. The decisions entered in Table 3 could use refinement, but the underlying purpose is to explain the many related decisions that stand behind the production of a single parking estimate (s), and the major role this value plays in the forecast of GBA options in Table 2.
Surface Parking Coefficients
I’ve created Table 4 to illustrate the impact of (s)-value options on gross building area potential (GBA). The results are based on the surface parking equation GBA=(af/(a+fs))*CORE. When CORE is equal to 1, gross building area potential is represented by the coefficient in this equation. It becomes a function of optional (a), (f), and (s) value decisions, and expresses GBA potential as a multiple of the core area available.
Table 4 places optional (s)-values in boxes above six matrices labeled 350-800. Each matrix locates (f) values on the y-axis and (a) values on the x-axis. A larger (s)-value indicates that more parking lot area is provided per parking space. This increased average area may result from increased landscaping; more generous parking space and circulations areas, or both.

Cell L18 is part of matrix 400 in Table 4. It shows that a 5 story building with a parking requirement (a) equal to 1,000 sq. ft. of GBA per parking space can yield a total GBA equal to 1.667 times the core area available. This is possible when the parking lot contains an average of 400 sq. ft. per space (s). (The maximum building footprint area would be equal to 1.667 / 5 times the core area.) In contrast, cell B14 shows that a one story building and a parking requirement of 100 sq. ft. of GBA per parking space will yield total GBA equal to 0.200 times the core area available when (s) is equal to 400.
In matrix 800, if 100 sq. ft. of GBA (a) is permitted per average parking space (s) equal to 800 sq. ft.; the parking lot will grow much more rapidly that gross building area. This ratio limits GBA potential to 0.111 times the core area as shown in cell B50 of Table 4. If 1,000 sq. ft. of GBA is permitted per average parking space of 800 sq. ft., cell L54 shows that the ratio produces GBA equal to 1.000 times the core area for a 5 story building. If you compare the results in matrix 800 to those in matrix 400, the differences in GBA potential illustrate the impact of the (s) and (a) decisions represented. The significance of the values entered in cell F33 and F34 of Table 2 may now be more apparent.
Line 50 in Table 4 illustrates a typical trade-off decision related to the G1 surface parking design category that is not immediately apparent. In the G1 category, gross building area potential declines when average parking lot area per space (s) increases and all other design specification decisions remain constant. In many cases, more parking lot area per space indicates greater landscape provisions. These provisions soften the impact of asphalt pavement, but fewer parking spaces reduce GBA potential in the G1 Design Category. This places landscape provisions at a distinct disadvantage. It has been exacerbated because comparative options and implications have been limited by the time required to manually prepare alternate site plans. Table 2 was introduced to explain how GBA options can be forecast, compared, and evaluated by changing one or more values in its design specification template. The (s) and (a) parking values represented two of these design decisions. Tables 3 and 4 have explained the implications of choice among these values. The mathematical format involved will not eliminate argument and debate over GBA implications when landscape provisions are considered, but it can eliminate confusion and distrust around a table that has had to depend on intuition, assumption, and opinion for evaluation and conclusion. In fact, confusion surrounds every specification value entered in Table 2 at this time. This has severely compromised the leadership potential of all public and private sectors responsible for the provision of shelter for the activities of growing populations within a geographically limited Built Domain that protects their quality and source of life – The Natural Domain.

Friday, February 10, 2017

Strategic Architecture


Architecture collects and correlates isolated information to reconcile complexity and confusion with logic and talent. The form, function, and appearance of a building symbolize this complicated process. The increasing focus on fine art emphasizes appearance, but does not transfer knowledge for improvement by future generations.

This is not an attempt to abandon fine art. It is an attempt to place it in the context of a creative process that can be taught. Talent will always die with the owner. Knowledge can be inherited, and improvement will enhance the contribution of exceptional talent and its many peers.

An architect is not an engineer, although it could be argued that he/she engages in systems engineering. This is a fancy term for creation of a logical strategy that correlates the contributions from many related technical disciplines. The result is project completion, but this is no longer the goal. Project completion represents the cellular formation of an artificial environment across the face of a planet that is no longer a world without end.

Architecture has been occupied with schematic design for shelter at the cellular level of The Built Domain, and this has contributed to an unlimited, pathogenic anatomy we call sprawl. If you believe that we must learn to shelter the activities of growing populations within a limited Built Domain that protects their quality and source of life – The Natural Domain, then you may agree that architecture has an expanded role to play. It involves strategic planning for schematic design within a limited Built Domain, and this has the potential to protect the public interest. Strategic architecture involves the science of city design,[1] and it can be taught, improved, and inherited. The form, function, and appearance of schematic design that rests on its foundation will begin to symbolize a new Symbiotic Period of human awareness.



[1] Hosack, Walter M., The Science of City Design, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com)

Saturday, January 28, 2017

Abdicating Surface Parking Requirements


Parking requirements have been considered a function of occupant activity since the introduction of zoning regulations. The concept has maintained that more intense activity requires more parking spaces. For instance, 1 parking space might justify 50 gross sq. ft. of restaurant activity or 200 gross sq. ft. of office activity. The concept, however, has produced two intractable problems: (1) The requirements are averages that are not tailored to the needs of a specific enterprise, and (2) The requirements do not solve pre-existing conditions that flood neighboring areas with incompatible overflow parking demand.

In both cases, land is the underlying issue. In new construction, a parking requirement can reduce the land available for a building footprint and the gross building area that can be constructed. In existing areas, there may be no land available to provide adequate parking. There will never be a perfect parking solution given the two problems noted, but the lack of perfection is not an excuse to ignore a fundamental problem as proposed in the following quotation:

Off-street parking should be a business decision, not a government decision.

Business is not motivated by the public interest, and I will argue that adequate parking for successive owners has significant public implications. It may help to begin by explaining the place of parking in a site plan and the design specification values that combine to produce its need for land.

New Construction

All land areas contain various percentages of four ingredients: (1) Unbuildable land area, (2) Buildable land area, (3) Common, or shared, buildable land area, and (4) Shelter land area. When common areas are not provided, buildable land area is equal to shelter land area.

Shelter land area contains various percentages of five ingredients, and one or more of these percentages may be zero: (1) Unpaved open space, (2) Service pavement, (3) Social pavement, (4) Parking pavement, and (5) Building footprint. When shelter is the issue, the first three layers are subtracted from the shelter area remaining to find the core area available for parking pavement and building footprint. The ratio between parking and footprint area combines with floor quantity to determine gross building area potential.

In other words, parking quantity determines the gross building area that can be constructed. Each additional parking space permits additional gross building area, but reduces the surface land area remaining for the building footprint. The building increases in height with a smaller footprint to accommodate the increased area permitted; but the relationship between parking and footprint stops producing meaningful increases in gross building area above five stories, when all other design specification values remain constant.

The shelter capacity of land is the gross building area that can be constructed per shelter acre. It is a function of design specification decisions that are correlated by an architectural algorithm for use in a master equation. The equation pertains to the design category under consideration and predicts gross building area options based on four variables:

1) The gross building area permitted per parking space (a), also known as a parking requirement.

2) The number of building floors under consideration (f).

3) The estimated gross parking lot area per parking space, (s).

4) The core land area available for parking lot and building footprint area after estimates for all other site plan areas have been subtracted (CORE).

The Design Specification Template in Table 1 pertains to the G1 Surface Parking Design Category and illustrates the calculation of core area in cell F32. The parking requirement (a) is entered in cell F34. An estimate of gross parking lot area per space (s) is entered in cell F33. Building floor quantity options (f) are noted in cells A42-A51. The master equation in cell A37 predicts gross building area options related to building height options in cells B52-B51. This is the point when the impact of a parking requirement becomes clear - and the point when it becomes vulnerable to variance requests when it does not produce a desired gross building area. This is not the only option, however. Since there are 25 specification boxes in the table, values can be modified to pursue change in many ways, but the design specification template in Table 1 is not in common use. In its absence, the expedient owner choice has been to reduce the parking provided to increase gross building area, but this can sacrifice its usefulness to successive owners and its public revenue potential over time. Since the city is essentially a farm, the yield from each of its acres determines the quality of life it can afford to provide.



Table 2 is based on a core area of 24,829 sq. ft. and an estimate of 400 sq. ft. per parking space. It presents a range of parking requirement options (a) on line 4. When these values are entered in cell F34 of Table 1, the table produces the gross building area options displayed in columns B-Q. If an owner had a choice among the parking requirements listed on line 4, most would choose the regulation that produces the desired gross building area with the least building height. The number of parking spaces might prove inadequate, but they would choose to live with the result and hope for the best. This is not necessarily in the public interest, however. A failing activity leaves a vacant building with inadequate parking that consumes potentially productive acres. Parking is an essential ingredient in this equation and its impact is felt long after the original owner’s departure.

In other words, a building owner is a temporary investor in shelter for activity on a given land area; and may also be a total or partial occupant of the premises. The building represents a permanent source of public revenue that fluctuates with location, condition and succeeding occupant activity. Under these circumstances, a privately owned building is a public resource that can be compromised by a parking quantity that proves insufficient for future activity. The City of Buffalo, NY has chosen to make parking quantity a business decision. We will never understand the impact until knowledge emerges from the adoption of scientific measurement, evaluation, and forecasting techniques.[1]

Pre-Existing Conditions

A city is an anatomy that grows at the cellular level of property ownership, and it surrounds its defects when there is land to annex. Unfortunately, a sprawling city does not learn to correct its mistakes and control its tendency to consume and pollute the land that is its source of life. In a way, sprawling cities represent an attempt to return to the farm where open space is abundant and equipment can be stored conveniently. Property in a surrounded city cannot expand, and density is magnified by increasing movement and decreasing open space donated to parked cars.

It is inevitable that business would attempt to serve residents in these areas under the deficient conditions created by the automobile, but decline is inevitable when intensity exceeds the limits of tolerance for those who can afford to escape. Columns G-J in Table 1 show that physical intensity, intrusion, and dominance are functions of 25 specification values that can be measured.  In my opinion, the physical conditions created by these specification values affect our social, psychological, environmental, and economic quality of life. They combine within each property cell, and every cell combines with others to form the Shelter Division of The Built Domain. This division is served by Movement, Open Space, and Life Support Divisions within a currently pathogenic anatomy that is encouraged by our concepts of annexation within a world without end. My point is that the parking values in cells F33 and F34 are two of these 25 specification values. They are generalizations when related to a specific activity, but they cannot be ignored and deferred to private enterprise as an expedient solution to an intractable problem that currently affects our quality of life and will affect our symbiotic future.

The problem stems from the fact that we have not been able to predict the shelter capacity of land with any degree of accuracy, and capacity is a function of parking requirements. The only certainty is that parking is an inescapable consideration in the age of the automobile.  

Buildings with no on-site parking have deferred their requirements to others in near-by and remote locations. These locations are provided and connected to exempt building activity at public expense in many cases. The parking requirement did not disappear. Its expense was simply shifted. When expense is shifted to the public side of the ledger, it is subsidized by the average revenue received from all municipal acres. If revenue is inadequate to meet expense over time, government is considered profligate. Budget cuts ensue and decline takes another step toward blight. Inadequate parking will continue to add a largely unrecognized burden to surrounding neighborhoods and municipal expense until this relationship is recognized. A city washes it hands of the problem when it defers parking decisions to private enterprise; but expedient solutions have a way of producing unintended consequences, and we cannot continue to consume land and leave our mistakes in an expanding core of blight.
It is time to come to grips with the true shelter capacity of land and its economic implications. Growing populations will never learn to live within symbiotic limits that protect their quality and source of life until they build the knowledge required, and this knowledge will not be produced by the expedient solutions of private enterprise.


[1] Hosack, Walter M., The Science of City Design: Architectural Algorithms for City Planning and Design Leadership, CreateSpace, 2016. (Available in paperback and e-book versions from Amazon.com)