Search This Blog

Wednesday, July 12, 2017

REPLACING DENSITY - Updated


SYNOPSIS: Density is not equal to the leadership language required to define shelter policy and planning strategy within The Built Domain. It is a measure of residential activity that cannot lead the physical results constructed to shelter any activity in the Built Domain. It has caused great confusion, contradiction, disagreement, and distrust within and between those in the public and private sectors. It must be replaced with a language that can more accurately measure the past, evaluate the present, and predict the future. We need a language that can lead us to the goal 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.

NOTE 1: This essay was originally published in September, 2010. This revision is based on the information provided in the book entitled, The Science of City Design, by Walter M. Hosack, 2016 and available from Amazon.com. The equations presented are new and the differences are significant.

NOTE 2: All figures and tables are located at the end of the text.

The development capacity of land is equal to the gross building area that can be constructed per shelter acre available. (Shelter area is calculated in cell F and G17 of Table 1.) Gross building area is a volume that can be occupied by one or more activities given the floor quantity chosen. The percentage of building cover and pavement cover provided per acre is referred to as “intensity”. Intensity is offset by the percentage of unpaved project open space provided. At one end of the intensity spectrum is a small building on thousands of acres. At the other is a high-rise on one acre. In both cases, the square feet of shelter and pavement constructed per acre of land involved is an indication of the physical intensity introduced.

Activity is referred to as “land use”. The relationship of shelter capacity, condition, and social activity to geographic location affects economic stability and social acceptance. In other words, shelter capacity, condition, and location produce levels of physical intensity, social activity, and economic contribution that affect our quality of life within The Built Domain.

The Movement, Open Space, and Life Support Divisions of our Built Domain convert and serve land for the Shelter Division. The square feet of building area and pavement introduced per acre determines the population that can be served, the scope of activity that can be conducted, and the economic contribution that can be expected. The social open space that remains contributes to the quality of life provided within The Built Domain. In other words, the physical, social, and economic characteristics of intensity not only affect the physical, social, psychological, environmental, and economic welfare of a population within The Built Domain; but the survival of its source of life beyond.

Six building design categories encompass most, if not all, of the shelter provided on the planet. They are:

1)      G1: Buildings with surface parking around, but not under the building

2)      G2: Buildings with surface parking around and/or under the building

3)      S1: Buildings with structure parking adjacent to the building on the same parcel

4)      S2: Buildings with underground parking

5)      S3: Buildings with structure parking at grade under the building

6)      NP: Buildings with no parking required

The parking structure options may have supplemental surface parking, but when present, the building is classified by the parking garage configuration present. These building categories may be occupied by any activity group that complies with the local building and zoning codes. The point is that shelter classification begins with the parking design category involved, and each category has shelter capacity limitations that are dictated by parking design specification decisions. For instance, parking design specification decisions have been entered in cells F33-34 of Table 1. Twenty-three other decisions have been entered in the remaining specification boxes of Table 1.

A set of optional percentage decisions are illustrated by the values entered in the boxes of the Land and G1 Modules of Table 1. There are fifteen boxes and each value entered in a box represents a design decision that can be modified to test options. The equations in Col. H of Table 1 convert these decisions to square foot area implications in Col. G. The objective of the algorithm is to identify the shelter area available in cell F17 and the core buildable land area available in cell F32.

The master equation in cell A37 correlates the specification data entered and calculated in the Land and G1 Modules of Table 1 with the floor quantity options entered in cells A42-A51. Shelter capacity alternatives are predicted in cells B42-B51 of the Planning Forecast Panel. The remainder of the panel predicts the implications of the shelter capacity forecasts in Col. B using the secondary equations on line 41. This panel illustrates a few of the many implications that can be forecast as a function of a gross building area prediction.

Table 1 illustrates the 16 decisions required to expose options and lead the G1 Design Category toward a desired objective. A change to one or more of the specification values in Table 1 will produce a new forecast of options in Col. A of the Planning Forecast Panel, and hundreds of options can be predicted in a very short time. The point here is that the gross building area predicted can be occupied by any permitted activity, and that a single density requirement is not a substitute for the 16 decisions required to lead performance toward a desired objective.

The gross building area options forecast in Col. B of the Planning Forecast Panel are used to produce the shelter capacity forecast in Col. F. These capacity options are used to calculate intensity, intrusion, and dominance measurements in Columns H and J. These four measurements are like the first blood pressure readings. They indicate the impact level present or proposed. I can only hope that continued measurement and evaluation will lead to impact parameters that can improve urban health, safety, and welfare.

Intensity options are defined by stating the design categories and specification values being considered. A leadership decision establishes an objective by defining the design category and specification values selected for further architectural definition and context refinement. Before refinement, however, the impact selection and its 16 specification decisions represent a massing definition. When massing compositions are combined, the product is referred to as urban form; and a plan for urban form determines the shelter capacity of a Built Domain. Design specifications and impact measurements make it possible to evaluate, diagnose, and prescribe urban form one project at a time. When a Built Domain is geographically limited, the quality of life within these limits will be a function of the definitions chosen in relation to the population size involved -- and the natural environment preserved.

A DESIGN PRINCIPLE

The G1.L1 equation in Table 1 reveals a design principle when the gross building area values in Col. B of the Planning Forecast Panel of Table 1 are mapped. It can be formally expressed in the following terms:

When the G1 Design Category is considered, the rate of increase in gross building area declines at an accelerating rate as the number of building floors increase.

Figure 1 illustrates this principle and clearly shows the dramatically decreasing rate of increase in gross building area as building height pushes above five floors. Figure 1 is based on the provision of 40% open space. If this were reduced to 15%, the efficiency profile in Figure 1 would show the same rapidly decreasing rate of increase in development capacity, but start at a higher point on the Y-axis. In fact, any change to design specification values will alter the intensity and context created, but its impact remains a matter of opinion because it has not been measured and evaluated.

Figure 1 confirms the intuition of many designers and converts this intuition to knowledge that is a function of the Table 1 forecast model. The context implications of design specifications, including open space requirements, and the intensity options produced remain to be explored; but there is another point to be made. Figure 1 demonstrates that planning and design issues can be expressed in mathematical terms. This has the power to persuade in a political environment that cannot be avoided. It also improves our ability to collaborate with the science of others; since the land our planet can donate to shelter, and the shelter capacity of this land, is becoming an issue of survival.

Figure 1 was based on the gross building area permitted per parking space (a) being less than the gross area estimated per parking space (s) and 40% unpaved open space. This is not always the case, and Figure 2 is based on (a) being greater than (s) and 15% unpaved open space. The design principle still applies, but the results produced are dramatically different when these values are modified. A comparison of these results should explain why the gross building area permitted per parking space and the impervious cover proposed are two of the most common points of public and private disagreement.

Figure 2 shows that gross building area potential is significantly increased when (a) is greater than (s). The rate of gross building area increase has not flattened out at 10 stories, and gross building area potential begins at 85,630 sq. ft. rather than 38,577 sq. ft. When surface parking is planned or required, however; the risk of inadequate parking space quantity is significantly increased when (a) is greater than (s).

When the five story gross building area is subtracted from the one story gross building area in each figure, the differences become more apparent. In the case of Figure 1, the total gain for 1-5 stories is 17,145 sq. ft. The total gain for 5-10 stories is 3,278 sq. ft. In the case of Figure 2, the total gain for 1-5 stories is 79,043 sq. ft. The total gain for 5-10 stories is 21,749 sq. ft. Above 5 stories, the gross building area gain per additional floor declines and becomes increasingly less cost-effective in both cases.

THE POINT

Figures 1 and 2 document a relationship we have intuitively understood for quite some time. Greater parking space requirements (a) and greater parking areas per space (s) reduce the area available for building footprint and unpaved project open space. This reduces gross building area potential. Unpaved open space is consumed to increase parking areas and gross building area options. (Gross building area may be occupied by any residential or non-residential activity.) Parking variances are sought to reduce the parking requirement (a) when open space consumption does not provide enough additional parking to justify a gross building area objective. (There may be no objective. It may be a simple attempt to maximize gross building area potential given the cost of the land.)

Parking requirements have little research to defend them and can easily be challenged by the experience of a current applicant’s operations. Unfortunately, successful appeals can leave deficient parking for a future building owner. In the worst cases, it can contribute to economic decline, deteriorating condition, and inadequate public revenue from the acres consumed within a city’s boundaries.

Figures 1 and 2 are based on the design specification data in Table 1. The (a) value in Table 1 has been modified to produce Figure 2. The example illustrates the influence of parking requirements on gross building area potential, but this is not the underlying point of the discussion.

The results in Table 1 could not have been predicted by a residential density regulation; and if they cannot be predicted, they cannot be led to produce results that avoid excess and decline. Table 2 lists the design categories and forecast models that can enable us to speak in the language required to lead shelter toward solutions that protect our quality of life within a geographically limited Built Domain that protects our source of life. In other words, residential density is a product of design specification decisions. It does not make them nor provide design leadership. Table 3 presents a Built Domain classification system that incorporates the generic design categories of Table 2.

BACKGROUND

Our ability to shelter populations and activities within a limited built environment will depend on our ability to balance the artificial world of our presence with the natural world of our planet; and on our ability to balance a growing population with the average intensity required. This is an emerging awareness tormented by conflicting opinion; but fortunately, intensity and impact can be predicted. The options forecast however, have context implications that remain to be explored; and research is required to avoid the oppression intensity and impact can produce.

The prediction of shelter options will improve when we can quickly forecast the entire spectrum of intensity alternatives that meet an open space specification; since open space offsets intensity and is the weight that produces balance within our built environment. It is also the foundation of a natural environment that suffers our presence at its discretion. In other words, it is all about design with space – since open space must be present before details can be introduced -- and success will depend on our ability to forecast the implications of intensity options that preserve its presence. We have learned however, that simply adding open space is not an answer; and we need  a scientific method that can  measure context, evaluate implications, forecast alternatives, and express decisions in precise terms. At this point, vocabulary will become language with the power to lead the shape and form of our built environment to the limits demanded by its silent partner -- and to the quality of life deserved by its inhabitants.

Architecture has always sheltered the activities of its period and been a product of the knowledge and opinions available. It is no accident that the current sprawl of architecture reflects our confused relationship to the land. Opinion has produced indiscriminate regulation and the land is compromised by the process. We are distracted by the details of compatibility, construction and appearance — not to mention ownership and sovereignty; but intuition is looking beyond the environment we build to include the environment we consume. Balancing these two worlds will depend on our ability to understand impact and offer options within limits that meet our strategic goals.

Architecture, landscape architecture, city planning, and regional development have borrowed from the knowledge of others, but need a common language with greater ability to coordinate the efforts of many while multiplying success over time. Until then, the language of others will continue to substitute opinion for knowledge in the search for leadership of the built environment. The goal is to prevent this artificial presence from consuming a natural gift that constantly adjusts in reaction to a universe of forces. Our responsibility is to recognize that cities are one of the forces to be reconciled, that the shelter we build reflects the level of awareness  we achieve, that shelter within limits requires an improved understanding of the intensity and impact options involved, and that symbiotic survival is the goal. Intuition is again required – and leadership is needed when anticipation must substitute for proof.

Struggles for freedom establish new relationships among men, but over-simplify their relationship to a planet within a universe that is a gift from infinity. We may be free to own the land, sea and air, but we are not free to abuse it and its inhabitants in the silent court that prevails. Our knowledge is limited, our vocabulary is inadequate, and our language is ineffective; but our vision must restrain an instinct to control or be dominated that has become a threat to the planet. It is time to follow the road from intuition to science again; and many sciences must collaborate to lead the shape, form, and intensity of cities toward the harmony needed. Density is not equal to the leadership required. It does not control the team of horses involved and must be replaced with algorithms that can correlate the forces in play. Nothing less than symbiotic survival is at stake, and we must again prove that we are equal to the threat success has produced by providing the leadership required.










Saturday, July 1, 2017

Zoning Conflict & Opportunity


This is an attempt to understand the relationship of individual residential zoning regulations, the reasons why they often conflict to produce ambiguous shelter design leadership, and their improvement potential.

NOTE: I suggest printing this essay so you can place the tables next to the text for reference. Tables 1-3 document the conflict. Tables 4-7 are forecast models that present an algorithmic alternative. They are part of a comprehensive portfolio implied by Table 8, and eliminate conflict by automatically correlating independent regulations to reveal their combined implications. They represent the formation of a new leadership language that can lead a response to the issue of shelter for the activities of growing populations within a Built Domain that is geographically limited to protect their source of life, and is designed to protect their quality of life. The models represent one small step toward the absolutely essential goal of symbiotic survival. This is a document you must be prepared to study. It is not meant to be easy reading on the editorial page. It is meant to stimulate your interest in a new science - the Science of City Design.

SINGLE FAMILY ZONING

Table 1 is a collection of residential zoning regulations distributed through the chapters of one zoning ordinance. Lines 14-29 apply to single family residential lots. Lines 31-91 are written for multi-family buildings, but also permit 1-4 family housing.

Minimum lot areas per zone are noted in column F. Building height regulations are noted in columns C-E. Maximum net densities are noted in column H. Lot width, depth, and setback requirements are noted in columns J-P. Parking requirements are noted in column Q.

None of these requirements are correlated. Each is independent and their combination has often produced conflict and contradiction that has defeated consistent design leadership. The dilemma is most easily explained by asking one question:

1)      Is it possible to achieve the net densities permitted in column H given all of the remaining independent requirements on any given line of Table 1?

Table 2 lays the ground work for an answer by calculating the implications of the zoning requirements in Table 1. Column HH gives the impression that the total gross building area potential for each zone is more than adequate. Column JJ shows that unpaved open space is a quantity that remains after all impervious cover topics are subtracted. It is not a requirement. It is a left-over quantity and cell JJ14 reveals a typical contradiction. The 3 acre R1 zone is intended to be the lowest density zone in the city; but when the independent line item requirements in Table 1 are analyzed, cell KK14 shows that they permit the highest percentages of two-dimensional building and pavement cover (impervious cover) in the community. This means that the lowest density is permitted to produce the greatest intensity.

The collection of requirements on line 14 of Table 1 also permit the greatest amount of three-dimensional gross building area as shown in cell HH14 of Table 2. Homes in the R1 zone are expected to be larger; but the maximum 158,610 sq. ft. shown in cell HH14 is far greater than needed for a single family detached residential home and contradicts the low density intent. Column JJ in Table 2 also shows that total left-over yard areas increase as density increases. This exposes another contradiction of expectations.

Column KK also reveals a more dangerous permitted condition. A residential storm sewer is often designed to accommodate the runoff from 30% impervious cover, but the actual percentages are often omitted from the public record. The percentage reduces initial pipe size and construction cost, but may not be correlated with zoning requirements that govern site plan preparation for building cover, pavement, and yard area quantities. Column KK in Table 2 shows that all permitted site plan impervious cover percentages in the column exceed 30%. Problems can begin when storm sewer design capacity percentages are not correlated with zoning ordinance regulations and recorded on approved plats. When permitted impervious cover excesses multiply along branch and trunk sewer lines with limited storm water capacity, flooding becomes inevitable and continues until a city can afford to construct relief sewers. In other words, the impervious cover percentage limits permitted for site plans in column KK should not exceed the design capacity of the storm sewer system present, planned, or permitted.

Table 3 measures the implications of Tables 1 and 2. The underlying question is the meaning of the measurements. For instance, the most obvious implausibility is on line 14. It pertains to the low density R1 zone, but permits some of the greatest shelter capacity (SFAC), intensity (INT), intrusion (INTR), and dominance (DOM) measurements in the table because of the zoning regulations in Table 1. This is a classic example of inadequate or nonexistent correlation that can occur between zoning regulations and city design results.

The measurements in Table 3 imply two additional questions:

2)      What measurements and percentages are desirable?

3)      How can regulations be correlated to avoid leadership contradictions?

I won’t attempt to answer Question (2). It will require site plan measurements and evaluation of hundreds, if not thousands, of existing site plans and building mass relationships before conclusions can be reached with the credibility required for public acceptance. When accepted, these conclusions will establish desirable, correlated parameters with the potential to lead the design and construction of shelter for the activities of growing populations within a geographically limited Built Domain. This will protect their quality and source of life – The Natural Domain.

Correlation is the objective of Table 4 and the answer to Question 3. Cell F3 defines the actual land area involved for this example. Cell F12 defines the shelter area available for “improvement” in cells F12-G12 after the percentages entered in the boxes of the Land Module produce quantities that are subtracted. (Any value entered in a box within the table is a variable that may be changed to explore options.)

Cells F15 through F19 define the design standards being tested. Line 23 introduces additional design decisions that apply to the proposal.

Line 38 calculates the implications of all design values entered in the boxes of the Land and Shelter Modules. Line 43 presents these calculations. The impervious cover value representing the sum of these building and pavement cover decisions is presented in cell J48. The bonus room above the garage is added in cellK38. Garage and accessory building areas are added in cell L38 to produce total building area (TBA) in cell L38. All of these values are presented on line 43.

Cells A53 to A74 contain unpaved open space percentage options. The shelter area density that can be achieved in column F of the Density Module is a function of the average impervious cover per dwelling unit value (AVGIMPD) presented in cell J43 and the unpaved open space per dwelling unit value (UOSD) chosen in column A of the Density Module. (One minus the UOSD% in column A should coincide with the storm sewer capacity present, planned, or permitted.)

The density results in cells F53 to F74 serve to explain that density is not a leadership tool. It is a result of the 45 correlated design decisions displayed in the boxes of Table 4. The choice of design values in these boxes is up to you until research defines better parameters. Table 4 is simply an algorithmic tool that correlates these decisions to give you the vocabulary and language needed to lead shelter design decisions toward your design objectives.

The total impervious cover required for the home specified on line 23 of Table 4 is presented in cell J43. When this 2,700 sq. foot area is combined with the 9,300 sq. ft. of unpaved open space in cell B68, a 12,000 sq. ft. lot is produced containing the 77.5% of unpaved open space, or 9,300 sq. ft., noted in cell B68. This total complies with the minimum lot area required by the R6 zone. Column D in the Density Module also shows that the home would fit in five other zones when the unpaved open space percentage in column A is adjusted as noted. If you look at column EE in Table 2, however, the impervious cover pertaining to these zones in the current ordinance is substantially greater. So who is right? If the impervious cover capacity of the storm sewer is 30%, line 66 in Table 4 is right and Table 2 represents serious excess.

I should also mention that line 29 in Tables 1-3 was rejected by the community in 1968 as a minimum living standard. It permitted 53% impervious cover and the desire for larger home sizes on these small lots led to variance requests that were often permitted. These variances increased impervious cover, reduced open space, and eventually led to the need for a relief sewer at public expense. These variance approvals were often combined with additional variance requests to reconcile conflicting regulations. The combination of increasing intensity, decreasing open space, and inadequate infrastructure eventually led to rejection of the R7a zone on line 29 of Table 1, but left the lots as a lesson that was not fully understood.

Based on my experience, unpaved open space on a given lot or land area is a by-product and not a conscious zoning requirement adopted to protect a city’s storm sewer capacity and quality of life. The minimum amounts needed to function as a relief from intensity and a contribution to a city’s health, safety and quality of life has often been considered a “taking” of property value; but who is taking what from whom? The lack of knowledge regarding the value of unpaved open space and the arbitrary nature of uncorrelated zoning requirements leaves an entire city at the mercy of uninformed regulations and variance approvals.

Forty-five values have been entered in the boxes of Table 4 and have been correlated by an algorithm and master equation to produce the results in its Density Module. The specification values entered are interactive and one or more may be modified to produce different results in the Density Module, but the underlying point is that correlated zoning requirements are the key to effective city planning and design leadership.

A measurement system has been introduced in columns H-L of the Table 4 Density Module to calibrate the implications of correlated zoning requirements. Line 66 shows that the minimum preferred single family residential standard in the R7 zone produces 15,379 sq. ft. of gross building area per shelter acre, an intensity of 0.106, intrusion of 0.4, and dominance of 0.506 per shelter acre when the minimum unpaved open space percentage is 70 and the total home area in cell K43 is 2,598 sq. ft.

Cell H66 in Table 4 reveals a contradiction with cell GG28 in Table 3. Table 4 shows that the R7 zone on line 66 can produce 15,379 sq. ft. of shelter area per acre based on its design specification. Table 3 shows that the R7 regulations on line 28 of Table 1 can produce 36,421 sq. ft. of total shelter area per acre. The intensity represented is 0.446, intrusion is 0.5, and dominance is 0.946. Keep in mind, however, that Table 3 represents unintended consequences produced by uncorrelated zoning regulations.

The answer to Question 1 is that achieving a net density limit produces random results when the 45 leadership decisions in the boxes of Table 4 remain ignored or uncorrelated. The density options in column F of Table 4 are based on these 45 correlated decisions. In other words, density is a social measurement that is a product of many physical design decisions.

Question 2 remains to be answered with the measurement, correlation, and evaluation of existing projects based on the consistent topics of a shelter capacity and intensity forecast model.

In response to Question 3, zoning regulations can be correlated to avoid leadership contradictions and achieve leadership objectives with shelter capacity and intensity forecast models.

MULTI-FAMILY ZONING

Lines 32-91 in Table 1 were originally written to address multi-family residential shelter options that I’ll generically refer to as townhouses and apartments. “Townhouses” are horizontally connected single-family residential dwelling units that are not stacked. “Apartments” are connected and stacked dwelling units within a gross building area envelope.

Townhouses

Table 5 is similar to Table 4, except for lines 23-27 and lines 38-42. Design value options have been entered in lines 23-27 to reflect the diversity of bedroom options often available in townhouse configurations. (These additional values could also be changed to reflect home size options in a residential subdivision.) Lines 38-42 calculate the implications of lines 23-27. Lines 53-71 correlate these implications with a master equation to produce the results in the Density Module. The density options related to these correlated design decision values are displayed in cells F53-F71 of the Density Module.

Column F in the Density Module of Table 5 illustrates that density is a function of the 67 optional design values entered in the Land and Shelter Modules of Table 5, and a choice among the unpaved open space percentages entered in column A of the Density Module. If 5% open space is considered, a density of 21.33 dwelling units per shelter acre can be achieved as noted in cell F53, but this is based on a limit of 5% unpaved open space. If 50% open space is provided, a density of 11.23 dwelling units per shelter acre is achieved on line 62 based on the design specification in the Shelter Module. The point is to illustrate that correlated open space percentages and design specifications produce the density limits in column F of Table 5. Keep in mind that each open space increment in cells A53-A71 has a companion storm sewer capacity percentage equal to 1-UOSD% in cells B53-B71. An engineering standard does not necessarily represent an open space provision that protects our physical, social, psychological, environmental, and economic quality of life, however. The measurements in columns H-L of the Density Module have been created to measure these implications.

Apartments

Table 6 is a variation of Tables 4 and 5. It has been adapted to address the unique nature of apartment design decisions. The Land Module calculates the shelter area available in cells F12 and G12 based on the values entered in its boxes. The G1 Module identifies the net shelter area available in cells F20 and G20 after a number of miscellaneous site plan topic values are entered and subtracted. The Apartment Module defines the “mix” of bedroom types, percentage allocations, and habitable areas under study in cells A30-C34. The building efficiency percentage entered in cell F36 is used to convert habitable area to gross building area per dwelling unit type in cells D30-D34. The garage and parking lot spaces planned per dwelling unit type are entered in cells E30-F34. The design averages representing the dwelling unit mix are calculated on line 36. These are correlated with the open space percentage options in column A and the building height options on line 44 of the Density Module to produce the density options in cells C46-M64. (The correlation is executed with a master equation.)

Table 6 illustrates the number of density options that can be produced from one design specification when unpaved open space and floor quantity options become variables. The specification is represented by the values entered in the boxes of the Land, G1, and Apartment Modules of Table 6. The unpaved open space options have been entered in cells A46-A64. Floor quantity options have been entered in cells C44-M44. Density options are located in cells C46-M64. A choice is made by finding the intersection of an unpaved open space percentage and a floor quantity option. The density located represents the correlation of 68 design specification decisions in the Land, G1, and Apartment Modules plus the unpaved open space and floor quantity decisions in the Density Module. Intensity and Dominance measurements corresponding to the density options found in Table 6 are calculated in Table 7.

The point of this apartment exercise is to show that the density of 34.85 permitted in cell G74 of Table 1 is questionable given a complete design specification containing 70 decisions. It cannot even be found in cells C46-M64 of the Density Options Module in Table 6. In addition to this, the intensity and dominance measurements calculated in Table 7 indicate that many of these choices are not desirable; but this conclusion is based on my opinion, and it will only convince others when supported by consistent measurement and evaluation of many existing multi-family residential apartment projects based on a standard specification vocabulary and language.

OPPORTUNITY

Compilation, correlation and consistency of planning data evaluation can yield city design knowledge. This is the opportunity implied by Tables 4-7. Table 8 has been created from Table 4 by removing all calculation line items. The data entry boxes remain to form a questionnaire for the G1.R1 Activity Group. The intent is to use this modified forecast model to record existing and proposed shelter project data for evaluation. If the residential activity topics were removed, it would e a questionnaire for the G1 Design Category. (The gross building area options for a design category can be used to shelter any activity.)

A completed questionnaire represents a project data record. Record values can be entered in a related forecast mode. Tables 4-7 have been examples of forecast models that calculate shelter design and impact implications. For instance, columns B-F in Table 4 calculate design implications based on 23 design decisions and 22 floor quantity choices. Many more design implications could be calculated, but these have been presented as examples.

Columns H-L in Table 4 calculate the impact represented by the 23 design decisions and 22 floor quantity options in the table. Impact is measured by calculating the shelter capacity, intensity, intrusion, and dominance represented by the design specification and each floor quantity option in the Design Module. The data in the module implies a question:

        What impact parameters on the 22 lines of the Density Module are undesirable?
Given the incomplete and conflicting nature of current zoning regulations, this remains a land owner driven decision without a correlated city design strategy and land use policy. Project records, evaluation, and city design forecasting can begin to answer the question when all members of the shelter design and construction community begin to use a common, cloud-based method of preliminary planning and evaluation. I have the models if someone wishes to invest in the application.

CONCLUSION
All calculations have been based on the G1 Building Design Category. It represents buildings served by parking around, but not under, a building. Classifying buildings by parking system permits an infinity of appearance and activity options to be organized into 6 building design categories: G1, G2, S1, S2, S3, and NP. A design category is occupied by one or more activities to form an activity group, but activities are a social consideration. The gross building area available to shelter these activities is the product of a physical design specification containing many correlated decisions. These decisions directly affect the massing, pavement, and open space fabric of the projects, neighborhoods, districts, cities, and regional areas we occupy. Our success in designing this fabric contributes to the quality of life we create.

You have just read about the G1.R1 (single-family), G1.R2 (townhouse), and G1.R3 (apartment) activity groups. The S1.R3 activity group represents an apartment building served by an adjacent parking garage on the same property. The parking capacity of the S1 garage influences the gross building area potential of the site. Gross building area is subdivided by an apartment design specification to determine the apartment capacity of the gross building area. If an S1 design category building became an initial design decision, the Table 6 forecast model would be replaced by another. The floor quantity options in the new model would be changed, and the density options calculated would increase significantly. These optional building categories are not anticipated by the density regulations in Table 1. This omission, and the omission of unpaved open space specifications, means that a developer may seek to achieve these permitted high densities with a surface parking lot. The attempt can produce a sea of asphalt around a tall building with no open space relief in sight and little attention to storm sewer capacity.
POSTSCRIPT
I have used a number of terms in the Conclusion without definition. Table 9 places them in context with a Built Domain classification system that includes an explanation of their meaning.


TABLE 9: Classification of The Built Domain






A
B
C
D
1


Definitions:

2



The Built Domain: All physical creations of man on planet Earth
The Natural Domain: All of planet Earth, except The Built Domain
Phylum: one of two elements of The Built Domain
Division: one of four components of a Phylum
Cohort: a primary unit of a division encompassing similar, but not necessarily compatible, activities
Category: A primary unit of a cohort with a unique physical feature such as, but not limited to, a parking system
Group: A unit within a category containing similar activities or functions
3
Phylum


Urban, Rural
4

Shelter Division

5


Cohort
Residential, Non-residential
6


Category
G1: Surface parking around, but not under, building
G2: Surface parking around and under building
S1: Structure parking adjacent to building on same premise
S2: Structure parking underground
S3: Structure parking at grade under building
NP: No parking required
7


Group
R1: Single-family detached, unstacked residential
R2: Single-family attached, unstacked residential
R3: Single family attached, stacked residential (apartments)
NR: Non-residential occupant activities are too extensive to separately itemize, and may require customized design specification templates.
8


Characteristics
Location: Address and parcel number(s)
Capacity: Gross building area in sq. ft. per acre
Impact: Intensity, Intrusion, Dominance, Density
Class: Appearance or Style: a designation from architectural history and landscape history can be debated but is helpful.
Code: Use group, construction class, and occupancy limits: This level of detail is difficult to gather. It is optional for this reason, but essential for a complete library of information.
9

Movement Division

10


Cohort
Roads, railways, air traffic, water traffic, subways, bikeways, sidewalks, and so on
11


Category
Airborne, terrestrial, aquatic, and subterranean
12


Group
Intercontinental railways, short-haul railways, international airlines, local airlines, intercontinental shipping, local ferries, intercontinental tunnels, local subway systems, and so on
13


Characteristics
Location
Function: (e.g., local, collector, arterial and freeway road systems)
Service Level: level of demand or design
14

Open Space Division

15


Cohort
Federal, state, regional, local and private
16


Category
Preservation, participation, defense, and buffer
17


Group
Campgrounds, day visits, lodges, proving grounds, and so on
18


Characteristics
Location
Function: active, passive, restricted, or prohibited use
Service Level
19

Life Support Division

20


Cohort
Agriculture, energy, communication, health and safety
21


Category
Airborne, terrestrial, aquatic, or subterranean
22


Group
Farms, hydro-electric dams, sewer systems, water systems, power systems, communication systems, medical systems, food systems, and so on
23


Characteristics
Location
Function: active, passive, restricted, or prohibited use
Service Level