Cities and Design: 2017

Thursday, November 2, 2017

Comparing Shelter Design Decisions

Updated from Design Specifications & Shelter Intensity written in 2011

NOTE: All exhibits, tables and figures are included at the end of this text.

I’ve rewritten this essay to correspond with the equations and forecast model format in my new book, The Science of City Design. The equation for intensity in cell G41 of Tables 1 and 2 has also been revised to reflect an improvement in logic and is the basis for a revision to the universal Table of Relative Intensity that is presented as Table 4. These changes first appeared in my essay, “The Single-Family Detached Home Dilemma”. I’m repeating this introduction with a few changes to suit this new title and for its broad applicability.

INTRODUCTION

We call the growth of cities “sprawl”, but know little about the cellular content of this pathogenic organism as it spreads across the face of the planet. We call these cells lots, parcels, acreage and so on. They are created by an army of investors and specialists led by incremental plans for land use, property acquisition, subdivision, engineering, architecture, and sales. The plans produce new cells that multiply to slowly consume land that is our source of life. There has been no realistic discussion of geographic limits for cities because there has been no mathematical ability to predict, evaluate and correlate the shelter capacity of cells within these limits. This has made shelter sprawl a default condition based on annexation that produces new cells and revenue to repeat old mistakes at its leading edge of growth with declining cells in its core.

Shelter capacity is gross building area per acre that can be occupied by any activity, assuming zoning and building code compliance. Sprawl results from population growth that cannot survive without shelter for its many activities, and an inability to correlate shelter capacity and activity with average public revenue and expense per acre over limited municipal land areas. This has prevented us from achieving a desired quality of life within areas that are limited to protect their source of life.

My focus in this brief essay is to discuss and compare the shelter capacity of land for office activity based on two sets of design specification values and the G1 Building Design Category. The effort is based on my belief that we must begin to understand, predict and correlate shelter capacity with activity, revenue, and expense before we can lead the combination to form cities with a desirable quality of life within geographic areas that are limited to protect their source of life.

In order to proceed, I need to explain building design categories and their fit within a Built Domain classification hierarchy that permits shelter measurement, evaluation, prediction and knowledge to be accumulated, organized and taught on a consistent, comparable basis. This has the potential to improve our leadership performance.

Population growth has produced two worlds on a single planet: The Built Domain and The Natural Domain.

The Built Domain is divided into Urban and Rural Phyla that contain Shelter, Movement, Open Space, and Life Support Divisions. Each phylum is distinguished by the significantly different areas associated with the same divisions. (See Exhibit A for a more complete classification outline.)

The Shelter Division in both phyla is served by its supporting Movement, Open Space and Life Support Divisions. Each cell in the Shelter Division contains one of the eight building design categories listed on lines 1-31 of Exhibit B. These categories are classified by their method of parking supply, not their internal activity or external appearance. This makes it possible to reconcile an infinite number of unique buildings into a common, limited set of classification categories.

FORECAST MODEL G1.L1

Forecast model G1.L1 on line 2 of Exhibit B will be used to define and compare two distinctly different projects.

Typical Office

Table 1 illustrates the G1.L1 Forecast Model and pertains when gross land area is given. It is occupied by office activity in this example. The values entered in the forecast model are measurements that pertain to the one story office project illustrated by Figure 1. Fifteen variable specification topics are identified with boxes in two design specification modules. The Land Module begins on line 2. The Pavement Module begins on line 23. Each box in a module must receive a specification value to define the two-dimensional site planning characteristics of a proposal. Ten specification boxes in cells A42-A51 of the Planning Forecast Panel receive floor quantity options that represent three-dimensional alternatives. These values complete the information needed by the master equation in cell A37.

In other words, fifteen two-dimensional specifications in the Land and Pavement Modules of Table 1 are correlated with the ten floor quantity options in Col. A of the Planning Forecast Panel to produce the line item options in the forecast panel. A change to one or more of the design specification values entered will produce a new forecast of implications in the Planning Forecast Panel.

Land Module

The Land Module in Table 1 is based on a given gross land area of 4.2 acres in cell F3. The module subtracts a number of potential demands on the gross lot area given to arrive at the buildable lot area calculated in cell F10. An unpaved open space percentage is entered in cell F11 and the remaining impervious cover is automatically calculated in cell F12. The impervious cover percentage is used to calculate the amount of buildable land that can be devoted to building and pavement cover in cell M19.

Pavement Module

The seven specification values entered in this module are used to calculate the amount of social and service pavement planned or present around the building. The total pavement area is calculated in cell F31 and it too reduces the amount of impervious cover remaining for building and parking lot area.

Core Area

Core area is the amount of buildable land area remaining for building footprint and parking lot area. It is calculated in cell N32 and is one of the values needed by the master equation in cell A37.

Master Equation

The master equation in cell A37 requires values for a, s, and f in addition to the core area found in cell N32. The value (a) is the gross building area planned or permitted per parking space provided and is entered in cell F34. The value (s) is the gross parking lot area permitted or planned per space provided and is entered in cell F33. The floor quantity (f) required by the master equation is represented by the ten floor quantity options (f) entered in cells A42-A51.

Gross Building Area Forecast

The gross building area options forecast in cells B42-B51 are based on the twenty-five design specification values entered in Table 1. A change to one or more of these specification values will produce a new forecast. All additional line item predictions in the Planning Forecast Panel are derived from these values using the secondary equations noted on line 41. The predictions in columns C-E are a small fraction of those possible when accurate gross building area predictions can be calculated.

Shelter Capacity Options

Shelter capacity (SFAC) is equal to gross building area divided by the buildable acres occupied. It is predicted in cells F42-F51 of Table 1 based on the equation in cell F41. It is a prerequisite required by the intensity equation in cell G41 and is defined by the following equation when buildable land area (BLA) is expressed in sq. ft.:

SFAC = GBA / BLA / 43560. This can be reduced to:

SFAC = GBA * 43,560 / BLA

Intensity Correlation

Intensity (INT) is the relationship of building mass and pavement to unpaved open space on a given land area in the Shelter Division of both the Urban and Rural Phyla of the Built Domain. The intensity equation in cell G41 of Table 1 produces the column of intensity options from G42-G51. There is no attempt to pass judgement on the intensity statistics presented in Col G, but I will compare the results to the intensity options produced by the corporate office building specified in Table 2.

Corporate Office

The values entered in Table 2 are measurements that pertain to the four story corporate office project illustrated by Figure 2. The green open space in Figure 2 is significantly greater than that in Figure 1. Table 2 uses the same G1.L1 forecast model and specification format because both buildings fall into the same design classification category, but the values entered in Table 2 define a completely different set of context relationships. I won’t bother repeating the format explanation used for the typical office covered in Table 1 because the format remains constant. It is the values that change in Table 2.

When appearance is ignored in Figures 1 and 2, the relationship of building mass and pavement to unpaved open space is called intensity. Intensity can be measured with the equation in cell G41 of Tables 1 and 2. The intensity options for Figure 2 are presented in cells G42-G51 of Table 2. The four-story option on line 45 identifies the characteristics produced by its primary design specification decisions.

COMPARATIVE SHELTER CAPACITY and INTENSITY

The acres within a city are its raw material. The shelter capacity potential of each acre combines with occupant activity to determine the economic productivity of each acre. From a public perspective, the average yield per acre of municipal land area must equal or exceed its average expense to avoid budget reductions. However, the push to increase shelter capacity per acre to increase its yield per acre can produce excessive intensity that detracts from the quality of life a city is attempting to afford. This means we need an improved method of measuring, evaluating and correlating shelter capacity with occupant activity to improve our quality of life and protect our source of life. The decisions at this land allocation level produce intensity, revenue and context quantities that represent leadership decisions awaiting refinement by talent.

Comparison

The design specification values in Table 1 define the project illustrated by Figure 1 and are repeated in Col. C on lines 3-34 of Table 3. The design specification values in Table 2 define the project illustrated by Figure 2 and are repeated in Col. D of Table 3 on lines 3-34.

The planning forecast table at the bottom of Table 3 displays the gross building area, shelter capacity and intensity options that were available in Tables 1 and 2. The highlighted lines in the Planning Forecast Panel indicate the massing options chosen. (“Massing” is the relationship of building mass, service pavement, social pavement and unpaved open space in a given project, neighborhood, district, city, or regional area.)

The design decision options that were available for Figures 1 and 2 are repeated in the Planning Forecast Panel of Table 3 beginning on line 41. The options chosen for Figures 1 and 2 are highlighted. A simple comparison documents the obvious and not so obvious. The gross building area illustrated by Figure 1 is much smaller than the provided by Figure 2 because the initial land areas available were quite different and the ensuing design specifications did not cancel the advantage of a larger land area. The shelter capacity (SFAC) for Figure 1 is greater that Figure 2. This means that more gross building area per buildable acre has been provided by Figure 1. It also means that Figure 1 has an intensity level that is 4.3 times the level of Figure 2.

The point is that shelter capacity and intensity can now be measured, evaluated and predicted using a consistent building design category classification system and design specification format, and that comparison can be used to build knowledge that will be needed to shelter growing populations within a geographically limited Built Domain that protects their quality and source of life – The Natural Domain.

Table of Relative Shelter Intensity

Shelter intensity is like blood pressure. Both readings fall within a matrix of possibilities. Their location within the matrix indicates the level of patient health present. The difference is that shelter capacity and intensity have never been measured, evaluated and predicted; nor has a common matrix been established as a consistent frame of reference. Table 4 is a sample Table of Relative Shelter Intensity that can be extended to encompass the full range of possibilities. The highlighted values locate Figures 1 and 2 within this table and represent two of the relatively infinite number of G1 possibilities that can be created by modifying the values entered in a G1.L1 Design Specification Template. One of the great challenges facing the 21^st century and its current definitions of growth and success will involve the definition of acceptable shelter capacity and intensity levels within land use allocation plans that organize capacity, intensity and activity areas to produce economically stable aggregations capable of affording a desirable quality of life within a geographically limited Built Domain.

PARKING LOT COMPARISON

The parking lot areas shown in Figure 2 are often expanded to increase shelter capacity at the expense of project open space because every additional parking space justifies an increase in gross building area. Unpaved open space may also be reduced to increase the number of spaces provided. This increases shelter capacity and intensity, but decreases the project’s contribution to a city’s quality of life.

When a low value for the gross parking lot area planned or permitted per space (s) is entered in a design specification template, the parking lot design must use the entire area for pavement. Higher values for (s) include internal area for landscape improvement to reduce parking intensity. The internal parking lot open space implied by the value (s) combines with building cover and all remaining service and social pavement to produce total project impervious cover. This is offset by the unpaved project open space remaining and determines the relationship of people to the project intensity created.

The value (s) for Figure 2 is low. This indicates that only pavement can be provided for the parking lot. However, the unpaved open space percentage is high. These statistics result from the fact that every parking bay is separated by a project open space finger that is included with the total unpaved open space provided. These fingers reduce the collective intensity of parking and provide a separate pedestrian route to the building entry for every parking space. Another statistical way of accomplishing the same design objective would consider the open space fingers part of the parking lot area. This would increase the total parking lot area provided per space (s) and result in a reduced percentage for the remaining unpaved open space quantity that is not part of the parking lot design. In other words, the same project could be represented by either approach, but the latter approach would place more emphasis on the relationship between pavement and open space within a parking lot perimeter.

More open space means less shelter capacity given the same design specification, but we have not been able to predict the options available; and when you cannot predict you cannot anticipate nor plan for coexistence. Building design categories and design specification values are at the heart of the shelter issue. Zoning regulations represent a 20th century attempt, but they have been incomplete and uncorrelated. The algorithms and equations in The Science of City Design have been written to correlate this interaction, but context research and analysis is needed to define value limits that will offer lifestyle options while protecting our health, safety and quality of life.

OBSERVATIONS

I hope Tables 1 and 2 have made it clear that it takes at least fifteen correlated design specification values and one building height value to accurately predict a G1.L1 option with the master equation in cell A37, and that this knowledge opens up a vast number of square foot related predictions. Two of these options have been compared in Table 3.

CONCLUSION

This text has been modified, but first appeared in my essay “The Single-Family Detached Home Dilemma”.

This essay has focused on site plan quantities defined by the values entered in a design specification template. This is a tactical project issue. The strategic question involves the cellular aggregations that combine to form neighborhoods and districts within a city. The land use allocation of shelter capacity, activity and intensity must produce average revenue per acre that meets or exceeds its average expense per acre for operations, maintenance, improvement, and debt service without excessive intensity. Strategic answers will require data accumulation, correlation, and land management that is beyond the scope of this brief essay. Physical, social and financial balance is feasible, however, when specification templates are linked to each parcel of land within a city and correlated with other data sources to form a complete picture of a city’s current physical, social, and financial condition. This will permit comprehensive evaluation and adjustment with the credibility required to convince others. Planning leadership for a sustainable future cannot proceed without a scientific bridge capable of relating population and activity to its shelter imperative on a planet with limited resources and symbiotic demands.

We have been preoccupied with growth to counter risk and threat since the beginning of time. This is the origin of the admonition to be fruitful and multiply. We have been successful. It is time to recognize that success from growth is the enemy of balance, and we must adapt to a new level of symbiotic responsibility. The planet is programmed to seek its own balance. I think we intuitively understand that the same law applies to us, but it requires anticipation without proof by extinction. This is a requirement of faith by any name. In fact, faith-based names have distracted us from reality. God has given us the planet. This power has not assigned ownership. It has assigned responsibility. It is up to us to define what that means and adapt accordingly.

Wednesday, October 18, 2017

The Single-Family Detached Home Dilemma

NOTE: All exhibits and tables are located at the end of this text.

We call the growth of cities “sprawl”, but know little about the cellular content of this pathogenic organism as it spreads across the face of the planet. We call these cells lots, parcels, acreage and so on. They are created by an army of investors and specialists led by incremental plans for land use, property acquisition, subdivision, engineering, architecture, and sales. The plans produce new cells that multiply to slowly consume their source of life, the planet. There has been no realistic discussion of geographic limits for cities because there has been no mathematical ability to predict, evaluate and correlate the shelter capacity and activity of cells within these limits. This has made shelter sprawl a default condition based on annexation that produces new cells and revenue to repeat old mistakes at its leading edge of growth - with declining cells multiplying in an expanding core of blight. Single-family detached housing has been on the front line of this random advance, and it has been led with incomplete, uncorrelated direction that has frustrated leadership credibility and authority.

Shelter capacity is gross building area per acre that can be occupied by any activity, assuming zoning and building code compliance. Sprawl results from population growth that cannot survive without shelter for its many activities, and an inability to correlate shelter capacity and activity with average public revenue and expense per acre over defined municipal areas. This prevents our ability to achieve a desired quality of life within areas that are limited to protect their source of life.

My focus in this brief essay is to discuss: (1) the anatomy of cities, (2) the cellular category we call single-family detached housing, (3) the list of single-family cellular contents I refer to as design specification topics, (4) the mathematical relationship of single-family design specification topics, (5) the shelter capacity options produced when topic values are modified, and (6) the measureable intensity levels produced by correlated topic value decisions. The effort is based on my belief that we must begin to understand, predict and correlate shelter capacity with activity, revenue, and expense before we can lead the combination to form cities with a desirable quality of life that are limited to protect their source of life.

One of two building design categories can be chosen to shelter single family residential activity. In order to proceed, I need to explain these categories and their fit within a Built Domain classification hierarchy that permits shelter measurement, evaluation, prediction and knowledge to be accumulated, organized and taught on a consistent, comparable basis that has the potential to improve our leadership performance.

THE ANATOMY of CITIES

Population growth has produced two worlds on a single planet: The Built Domain and The Natural Domain.

The Shelter Division in both phyla is served by its supporting Movement, Open Space and Life Support Divisions. Each cell in the Shelter Division contains one of the eight building design categories listed on lines 1-31 of Exhibit B. These categories are classified by their method of parking supply, not their internal activity or external appearance. This makes it possible to reconcile unique buildings into a common, limited set of classification categories. The residential activity groups listed below line 33 in Exhibit B represent six of the many activity groups that can occupy a limited list of building design categories.

Single-family detached residential activity is designated R1 and can occupy either the G1 or G2 Building Design Category. Table 1 applies to the G1 Building Design Category when it is occupied by R1 activity and gross land area is given. This table will be used to address discussion topics 2-6 previously mentioned.

SINGLE-FAMILY DETACHED HOUSING

The Reference Panel on lines 2-5 of Table 1 recites the characteristics of seven common single-family lot sizes in columns C-J. These lot sizes will be used as references for the remainder of this essay. Column C represents an escape from earlier 15-30 by 100 foot or less lots created when land ownership and the automobile made flight from a high density urban core feasible. These small lots are now part of inner cities. They could not compete with the larger 50x120, or 6,000 sq. ft., lots created in first ring suburbs and noted in Column C.

The 6,000 sq. ft. lot typically contains a one-car detached garage in the rear yard with a long access driveway that passes by the house and through the rear yard. Social activity in the rear yard is compromised by the garage and driveway presence. Fences often magnify rear yard insufficiency in an effort to improve privacy.

The 60x120 foot lot in column D was an attempt to offer an alternative to the smaller lots in Column C. It typically contains a two-car garage that is either attached or detached. Detached garages still require extended driveways and both still detract from a slightly larger rear yard. Attached garages preserve the rear yard and require shorter driveways. Both still seek to introduce rear yard privacy with fences on occasion.

Variance requests to expand home sizes with additions, add outdoor social pavement, or connect to detached garages are often requested by owners of Col. C-E lots. These variance requests reflect attempts to adapt to changing lifestyle expectations with over-development and excessive impervious cover on inadequate lot areas. This in turn can overwhelm storm sewer capacity when repeated along a shared storm sewer line.

The 90x120 or 12,000 sq. ft. lot in Column G seems to provide enough land area to meet current mainstream expectations regarding home size, garage capacity, social pavement, service pavement, and privacy but variance requests to expand can still reduce the unpaved open space percentage that serves installed storm sewer capacity. Fence installations decline in quantity when not prohibited.

The lot sizes in Columns G-J indicate increased affluence and privacy. In general, increasing lot size increases the scope of sprawl per dwelling and the movement, open space, and life support systems that must be extended to serve it.

All lot sizes are subject to the impervious cover percentage limits associated with installed storm sewer capacity. It is in a developer’s interest to minimize initial sewer capacity and impervious cover potential to serve only the initial installation in an effort to reduce cost. When this occurs, it eliminates future home expansion potential and places unpaved open space at risk of future expansion requests that seek to exceed the impervious capacity of the storm sewer. It is in the public interest to record initial impervious limit information for future reference when variance requests are submitted, but this critical information is often overlooked, rarely compiled on a city-wide basis, and unavailable for comparison with measured impervious cover requests during variance proceedings.

The bottom line is that unpaved open space percentages and impervious cover percentages are critical planning topics that must be recognized and will be included with this discussion.

DESIGN SPECIFICATIONS

Table 1 illustrates the G1.R1.L1 Forecast Model listed on line 36 of Exhibit B. Sixteen variable specification topics are identified with boxes in three design specification modules. The Lot Module begins on line 9. The Garage and Accessory Building Module begins on line 21. The Pavement Module begins on line 31. Each box in a module must receive a specification value to define the two-dimensional site planning characteristics of a housing proposal. Nine specification boxes are provided in Col. A of the Planning Forecast Panel to receive floor quantity options. These values complete the information needed by the master equation in cell A44. It converts the maximum first floor area found in cell G40 into nine home area options in cells B50-B58 based on these values. In other words, sixteen two-dimensional specifications in the Land, Garage and Pavement Modules of Table 1 are correlated with the nine floor quantity options in the Planning Forecast Panel to produce the line item options presented in the forecast panel. A change to one or more of the design specification values in the three modules, or a change to one of the floor quantity options in the Planning Forecast Panel, will produce a new forecast of implications in the Planning Forecast Panel.

Lot Module

The Lot Module in Table 1 is based on a given lot size of 6,000 sq. ft. or 0.13774 acres in cell F10. The module subtracts a number of potential demands on the gross lot area given to arrive at the buildable lot area calculated in cell F17. An unpaved open space percentage is entered in cell F18 and the remaining impervious cover is automatically calculated in cell F19. The impervious cover percentage is used to calculate the amount of buildable land that can be devoted to building and pavement cover in cell G19.

Garage and Accessory Building Module

The five specification values entered in this module are used to calculate the amount of impervious cover that is, or will be, consumed by garage and accessory buildings in cell G29. This reduces the amount of impervious cover remaining for first floor home area.

Pavement Module

The five specification values entered in this module are used to calculate the amount of social and service pavement planned or present around the home. The total pavement area is calculated in cell G38 and it too reduces the amount of impervious cover remaining for first floor home area.

Home Footprint

When the available footprint area in cell G40 is multiplied by the floor quantity options in cells A50-A58, the master equation in cell A44 calculates gross home area options in cells B50-B58, including any bonus area above the garage. If cells F25-F27 are zero, there is no bonus area and the reduced home area options calculated in cells C50-C58 will match the home area options calculated in cells B50-B58.

The buildable land area remaining for building footprint was found in cell G40 by subtracting the total support building and pavement areas found in cell G39 from the total impervious area available in cell G19. The remaining first floor or footprint area of 528 sq. ft. was the first indication of an outdated lot area. The footprint was a function of the 30% impervious cover available and the design specification values entered. The impervious cover percentage limits future expansion, and I’ve seen more than 60% permitted by variance approval when the storm sewer capacity is unknown. It’s very difficult to say no to your neighbors when opinion cannot be answered with fact.

Shelter Capacity Options

Shelter capacity (SFAC) is equal to total building area (TBA) in sq. ft. divided by buildable lot area in acres (BLAC). When buildable lot area (BLA) is expressed in sq. ft.:

SFAC = TBA / BLA / 43560. This can be reduced to:

SFAC = TBA * 43,560 / BLA

Home capacity per buildable acre (HCAC) does not include garage and accessory building area. It is presented in Column G of the Planning Forecast Panel of Table 1 but does not give an accurate impression of the total building area contribution to site plan intensity. Total building area (TBA) includes garage and accessory buildings in col. D and is used for this purpose. Shelter capacity options are based on total building area (TBA) and presented in Column H as one element of the intensity equation in cell J48. Both capacity and intensity statistics are related to the floor quantity options in Column A.

As an example, a home with 2,000 sq. ft. of total building area on ¼ acre equals a shelter capacity of 8,000 sq. ft. per acre. The same total building area on 1/8 of an acre represents shelter capacity of 16,000 sq. ft. per acre. This correlates land consumption with its shelter potential, and is one element of the intensity equation in cell J48. If the occupant activity on both land areas produced equal revenue per sq. ft., the 1/8 acre lot would produce greater yield per acre but introduce much greater intensity.

INTENSITY IMPLICATIONS

The acres within a city are its raw material. The shelter capacity potential of each acre combines with occupant activity to determine the productivity of each acre. From a public perspective, the average yield per acre of municipal land area must equal or exceed its average expense to avoid budget reductions. The push to increase shelter capacity per acre to increase yield can produce excessive intensity that detracts from the quality of life a city is attempting to afford, however. This means we need an improved method of measuring, evaluating and correlating shelter capacity with occupant activity because decisions at this land allocation level produce intensity, revenue and context quantities that represent leadership decisions awaiting refinement by talent.

Intensity (INT) is the relationship of building mass and pavement to unpaved open space on a given land area in the Shelter Division of both the Urban and Rural Phyla of the Built Domain. The intensity equation is noted in cell J48 of Table 1. There is no attempt to pass judgement on the intensity statistics presented in Col J of this table, but I have mentioned that the lot size given in cell F10 is less competitive than the other options available to this activity group on line 2 of the Reference Table. It also has the highest density as shown on line 5.

Two and one-half stories has been a commonly accepted limit for building height on suburban residential lot areas. Table 1 presents the intensity produced by a 2.5 story building in cell J53 based on the sixteen values entered in the design specification boxes above. The history of this lot size and the intensity produced by the 2.5 story home specified provides a glimpse of the measureable specification topics that can be compared, evaluated and used to build leadership knowledge in the pursuit of sustainable cities with symbiotic potential and a desirable quality of life.

OBSERVATIONS

I hope Table 1 has made it clear that it takes at least sixteen correlated design specification values and one building height value to accurately predict a single-family detached housing option with the master equation in cell A44, and that this knowledge opens up a vast number of square foot related predictions. A few of these have been included in the Planning Forecast Panel of Table 1.

Zoning

Incomplete, independent and uncorrelated specifications called zoning regulations often require choices among contradictions. When this occurs, it requires variance approval to reconcile the choices made. The variances approved are considered precedent setting, but they simply add confusion when there is no comprehensive correlation of all regulations that combine to affect shelter capacity and intensity. Contradictions in any endeavor simply frustrate consistent leadership direction.

Home Size

Home sizes and lot sizes represent fixed decisions that can last for centuries. Changing circumstances require adaptation that cannot be accommodated easily, if at all. I chose the 6,000 sq. ft. lot in Table 1 to add this point to the discussion. I could have chosen the 3,150 sq. ft. lot on page 23 of my book, The Science of City Design, but this would have been too extreme for a brief discussion. The point is that both were desirable escapes from the punishing density of central cities at one point in time. Time passes however, and outdated home size can combine with outdated movement, open space, and life support infrastructure to introduce intransigent decline. In some limited cases this has been reversed when old neighborhood attributes become desirable again; but for most, cities are saddled with decline they have yet to solve with improved tools, knowledge and political determination.

Encircled Cities

Encircled cities without annexation potential often face budget reductions and decline or increased taxation. The consequences of encirclement have become apparent and have encouraged others to protect their annexation corridors into agriculture and the Natural Domain. It is an unhealthy formula that begins with a lack of data correlation that can lead to knowledge and adjustment. Improvement will require that currently isolated data centers be linked to a relational database with shelter forecast models that make land management evaluation feasible and defensible.

Comparison of Intensity Implications

I’m introducing Table 2 to make another point. The land area given is 0.34435 acres, or 15,000 sq. ft. and is generally referred to as a 1/3 acre lot. The impervious cover limit calculated in cell F19 is 4,500 sq. ft. when 70% unpaved open space is required in cell F18. This is the same open space percentage entered in Table 1, but the percentage produces a significantly higher impervious cover limit than the 1,800 sq. ft. in Table 1 because the lot size is greater.

The same number of garage spaces and garage cover is provided in Table 2, but a bonus habitable area over the attached garage has been provided in cell F27 based on the specification values entered in cells F25-26. After building cover and pavement are subtracted, the remaining impervious cover available for home footprint is 2,718 sq. ft. in cell F40.

Based on the values entered in the design specification template of Table 2, the 2.5 story home noted in cell A53 has a total home area potential of 7,034 sq. ft. This is calculated in cell C53 using the master equation in cell A44, and is significantly greater than the maximum home area calculated in Table 1 for a 2.5 story home on a 6,000 sq. ft. lot.

A 7,034 sq. ft. home on a 15,000 sq. ft. lot would be far greater than normal, but the 15,000 sq. ft. lot permits home expansion over time with a 30% storm sewer capacity. It simply permits too much. If, or when, the maximum home size is constructed; it would produce an intensity of 0.613 as calculated in cell J53 of Table 2 and be compatible with its neighbors. The intensity calculated for the 6,000 sq. ft. lot in cell J53 of Table 1 is only 0.287, but the 1,319 sq. ft. maximum home size is now considered less desirable.

Variances

The maximum home size permitted by 30% impervious cover on the 6,000 sq. ft. lot in cell B53 of Table 1 may be less than desirable; but if the neighborhood is desirable, it can prompt variance requests for building additions and pavement that exceed 60% impervious cover. Under these circumstances, shelter capacity will increase to 44,714 sq. ft. per buildable acre, intensity will increase to 2.535, and the potential for flooding will increase when adjacent neighbors demand equal treatment along the same sewer line.

If low intensity on a small lot produces less intensity when the impervious cover limit is respected, but much greater intensity when variances are granted to exceed this limit, how should lot size be addressed for a building design category and activity group that consumes the most land per occupant sheltered in urban areas? Keep in mind that lot size has been a major contributor to both inner city blight and suburban sprawl. A free market has sought relief from excessive intensity with this residential concept, but it rarely produces enough revenue per acre to offset a city’s average expense per acre over an extended period of time without increased taxation and budget cuts.

Unpaved Open Space Implications

If I prepared tables for ½ acre and 1 acre lots with similar 30% unpaved open space specifications, theoretical shelter capacity and intensity for a 2.5 story home would continue to increase from the 15,000 sq. ft. lot in Table 2. The ½ acre lot would produce 24,381 sq. ft. per acre and an intensity of 0.731. The one acre lot would produce 26,892 sq. ft. per acre and an intensity of 0.807, but these intensity measurements are going in the wrong direction. An increasing lot size is expected to produce less intensity.

The intensity increase occurs because the 70% unpaved open space provision has not been increased with the increasing lot sizes. If it isn’t, 30% impervious cover on a larger lot size will permit greater potential shelter capacity and intensity per acre. This doesn’t happen because maximum potential home sizes are rarely built on larger lots, but the intent to decrease intensity by increasing lot size is left to chance.

Home Sizes

I’m including Table 3 to illustrate an obvious design principle. The table is based on a given home area with an unknown lot area to be found. The Lot Module explains that the land area basis for calculation is 70% unpaved open space and 30% impervious cover. A number of specification values have been entered in the Building Module to arrive at a total home area objective of 2,148 sq. ft. in cell F23. The 100 sq. ft. accessory building area entered in cell F24 is added to the home area to find the total building area of 2,728 sq. ft. in cell F25. The specification values entered in the Pavement Module are used to find the driveway and parking pavement areas in cell F34. These values complete the information needed by the master equation in cell A37. (I should mention that this master equation is equal to the equation on page 48, line 56 of my book[1], but it does a better job of differentiating building cover from pavement cover.)

The Planning Forecast Panel predicts that a one story home with the specification values entered would require a 12,000 sq. ft. lot in cell B43, and that this would produce an intensity of 0.297 with a shelter capacity of 9,901 sq. ft. per acre. A 2.5 story home would only need a 7,761 sq. ft. lot as shown in cell B46, but would produce an intensity of 0.362 and a shelter capacity of 12,054 sq. ft. per acre. In other words, the trade-off for greater shelter capacity per buildable acre is increased floor quantity and greater intensity. The choice is a very serious issue because the management of shelter capacity, intensity and context for all building design categories and activity groups will determine our ability to correlate our presence on a planet with limited capacity.

Setback Lines

Someone may comment that intensity hasn’t been left to chance because front, side and rear yard setback requirements increase with lower density zoning districts, and this hasn’t been taken into account. I have empirically found that setbacks increase yard areas with increased dimensions, but these dimensions do not consistently reduce shelter capacity and intensity. They only appear to be correlated and may be occupied by buildings and pavement that reduce their off-setting benefit. From a designer’s perspective, setbacks are primarily useful for building alignment when desired, fire separation when adequate, and privacy when generous. They are no substitute for adequate unpaved open space quantities defined and correlated with design specifications that establish the format for shelter capacity, intensity and context refinement.

Intensity Correlation

Table 4 shows how intensity increases in cells F12-17 when shelter capacity per acre increases in cell B12-17. The intensity noted in cell F12 is related to the 6,000 sq. ft. lot introduced by Table 1. Cell F17 is based on a similar specification when a one acre lot is given. The intensity statistics are going in the wrong direction because the design specifications for all lots have been held constant, and a larger lot with the same impervious cover percentage will produce greater building and pavement area that results in greater potential intensity. This can be easily corrected when an unpaved open space percentage is increased with lot size in a design specification template, or when other adjustments are introduced to reflect the lifestyle associated with increased lot sizes. This resolves one issue, but it does not begin to address the excessive consumption of agriculture and the Natural Domain for increasing lot sizes.

CONCLUSION

This essay has focused on site plan quantities defined by the values entered in a design specification template. This is a tactical project issue. The strategic question involves the cellular aggregations that combine to form neighborhoods and districts within a city. The land use allocation of shelter capacity, activity and intensity must produce average revenue per acre that meets or exceeds its average expense per acre for operations, maintenance, improvement, and debt service without excessive intensity. Strategic answers will require data accumulation, correlation, and land management that is beyond the scope of this brief essay. Physical, social and financial balance is feasible, however, when specification templates are linked to each parcel of land within a city and correlated with other data sources to form a complete picture of a city’s current physical, social, and financial condition. This will permit comprehensive evaluation and adjustment with the credibility required to convince others. Planning leadership for a sustainable future cannot proceed without a scientific bridge language capable of relating population and activity to its shelter imperative on a planet with limited resources that demands symbiotic relationships.

[1] Hosack, Walter M., The Science of City Design, CreateSpace, 317 pages, 2016

Monday, September 25, 2017

Shelter Capacity, Intensity & Context Leadership

NOTE: All tables, exhibits and figures are placed at the end of this text.

A planning design specification can be used to lead shelter capacity, intensity and context results within a Built Domain that must be geographically limited to protect its source of life, The Natural Domain. This approach is not based on the qualitative evaluation of form, function and appearance. It is based on the measurement, evaluation, prediction and adoption of correlated topic quantities that produce shelter capacity, intensity and context within a Built Domain that must be limited to protect its source of life from sprawl.

A design specification template begins with a comprehensive list of site planning topics related to a building design category. Values assigned to these topics are mathematically correlated with an algorithm and master equation to predict shelter capacity, intensity, and open space options within a single project area. Single project definitions are then aggregated to form neighborhood, district, city and regional context definitions.

A specification template within a forecast model is shown on lines 3-34 of Table 1. It defines the project shown in Figure 1 and includes land and building modules with topic lines that introduce assigned and calculated values. A box is used to designate an assigned value. One or more of these assigned values may be modified in a specification to evaluate the options predicted in the Planning Forecast Panel shown on lines B42-E51. The floor quantity values entered in cells A42-A51 of the panel are part of the design specification and may also be modified to test optional decisions.

Table 1 pertains to the G1 building design category and requires that the gross land area be given in cell F3. The G1 Design Category classification pertains to all buildings that use surface parking around, but not under, the building to serve occupant activity. (Exhibit A presents the complete building design category list with its related forecast models.)

The percentage variables entered in the design specification boxes of Table 1 are used to calculate land areas that are subtracted from the gross land area given to arrive at the core land area remaining for gross building footprint and parking lot area. This core area value is calculated in cell G32 of Table 1.

As a parking lot expands to serve increased gross building area within a fixed core area, building footprint area shrinks to make room and floor quantity increases to accommodate the increased gross building area. This relationship is defined by the master equation in cell A37. Parking lot design variables are entered in cells F33 and F34 to satisfy two of the values required by the equation. The last value required is floor quantity, and quantity options (f) are entered in the boxes of cells A42-A51 to satisfy the equation. Gross building area options are calculated in cells B42-B51 using the master equation in cell A37. These options represent keystone data. When gross building area options can be predicted in square feet, a wide array of related project and planning implications can be calculated.

Exhibit B is a diagram of the site plan hierarchy that is subtracted to find the core area remaining for building footprint and parking lot area.

The design specification values in cells B42-G51 of Table 1 are correlated to produce project and planning forecast implications. These predictions change when one or more design specification values are modified. The forecast values presented in the Planning Forecast Panel of Table 1 are some of the many that may be calculated and they fall into two categories. Cells B42-E51 represent project design implications. Cells F42-G51 represent corresponding planning implications.

The design specification in Table 2 defines the project shown in Figure 2. The format of the specification is identical to Table 1, but different specification values define the impact of Figure 2 and will be used for comparison after an explanation of the following common characteristics. This explanation uses Table 1 as a frame of reference.

PROJECT IMPLICATIONS

The gross building footprint predictions in Col. C of the Table 1 Planning Forecast Panel, and the gross parking lot predictions in Col. D, are quantity predictions that combine to form the core area of a site plan. (Do not confuse these quantities with a completed site plan illustration. The focus here is on quantity prediction, not site plan arrangement. Quantity predictions may be subdivided and separated in a final site plan arrangement, but their sum must equal the category sum forecast.)

The increasing floor quantities in Col. A of the Planning Forecast Panel produce corresponding increases in gross building are in Col. B. These areas must be accommodated within the constant core area calculated in cell G32 of the design specification. The increasing gross building areas are served by the increasing surface parking areas calculated in Col. D. This means that the building cover area in Col. C declines to make room for the increasing parking lot area. Gross building area increases with increasing floor quantity in Col. A, however. Increasing floor quantity multiplies the decreasing building footprint area to produce larger gross building areas. I’ve previously mentioned that this G1 design characteristic produces a steady decline in total gross building area as floor quantity increases. Five floors is a realistic limit for this building design category, even when design specification values are modified to increase the core area available because the same decline curve simply begins with a greater gross building area.

PLANNING IMPLICATIONS

The gross building area options in cells B42-B51 of Tables 1 and 2 are converted to a common, comparable index called shelter capacity in cells F42-F51.

Shelter Capacity (SFAC)

Shelter capacity is equal to gross building area divided by the buildable acres consumed. The equation is noted in cell F41 of Table 1. Buildable land area (BLA) is calculated in cell G10. Shelter capacity is a comparable statistic that can be used to improve land use planning and economic development decisions within limited geographic areas. These limitations will become essential when we realize that the life-sustaining Natural Domain must be protected from sprawling consumption by The Built Domain.

Keep in mind that gross building area can be occupied by any activity, assuming building code compliance. Gross building area combines with occupant activity to produce public revenue per acre and private return on investment per building square foot. I’ll use the generic term “yield” to indicate these financial implications. Average yield per acre and per square foot must exceed average expense to ensure both public and private prosperity. In other words, shelter capacity per acre combines with activity to produce average yield per acre. When a city summarizes yield from all of its acres, the average revenue must meet or exceed its average expense per acre to avoid budget reductions. This means that we must recognize the importance of every acre on the planet and improve our methods of shelter capacity prediction, correlation and limitation in the search for a sustainable, symbiotic future.

Intensity (INT)

We intuitively know that excessive gross building area and parking can overwhelm a neighborhood with building height, mass, pavement, movement, and activity; but have not had an adequate method of measuring, evaluating, and predicting this presence. If we can’t measure, we can’t determine when the measurements represent excess. The secondary equation in cell G41 of the Planning Forecast Panel has been provided to measure the intensity implications of the shelter capacity options calculated in Col. F. Keep in mind that a shelter capacity statistic in Col. F represents the combined impact of all design specification values entered, and will change when one or more of these values are modified.

The intensity results produced in cells G42-G51 calibrate intensity without passing judgment. At the present time they simply sit within the parameters of an intensity yardstick. The entire yardstick is presented in Table 5 and referred to as the Theory of Relative Shelter Intensity.

Table 5 is a complete departure from Table 1.2 presented on page 16 of The Science of City Design. (Hosack, Walter M., CreateSpace, 317 pgs., 2016. Page 16, and the related tables on pages 166 and 188, should now be considered outdated.) The change to the intensity, intrusion and dominance calculations on page 16 was prompted as I prepared comparative Tables 3 and 4 in this essay. The initial calculations made with the older algorithm produced conflicting comparisons in this essay that revealed a logical error. I have simplified the equation and improved its logic by discarding the concepts of intrusion and dominance that are already reflected by shelter capacity calculations. The result is Table 5. It is a simple yardstick that indexes the results produced by a correlated set of design specification values. This makes comparison and evaluation of design specification results feasible. Knowledge quickly follows the ability to measure and evaluate.

Summary

Tables 1 and 2 are represented a building design category chosen from Exhibit A for evaluation of a given land area. Core area was distilled from gross land area by subtracting the percentage values assigned to a series of site plan topics in a design specification template. Gross building area options were predicted with a master equation after additional parking and floor quantity values were entered in the G1 Module of the specification. Gross building area predictions were divided by the constant buildable acres calculated to produce shelter capacity measurements per acre. These measurements could be compared to those from other projects. These calculations were converted to their intensity equivalents using the secondary equation in cell G41 of Tables 1 and 2.

The intensity measurements presented in cells G42-G51 are similar to early blood pressure measurements. The measurements were meaningless until a database of comparable measurements with related evaluation was compiled. When shelter capacity and intensity calculations follow the same path, the result will be a credible bridge language that can defend intuition, talent, opinion and experience. The language will represent a scientific method for accumulating city design knowledge that can also be taught without excessive reliance on intangible artistic intuition and talent.

EVALUATION of COMPARABLE MEASUREMENTS

Table 1 presented a design specification template containing values related to Figure 1. Table 2 presented the same template with values related to Figure 2. These comparative measurements make evaluation on a quantitative basis feasible. This separates opinion regarding building form, appearance, and beauty from design specifications that determine shelter capacity, intensity and context within the Shelter Division of The Built Domain. In other words, a recipe precedes a cake but is not a substitute for successful execution and pleasing appearance.

Recipes apply to every shelter cell we define with property lines, but the ingredients and quantities of cellular matter have not been comprehensively listed and consistently measured to evaluate their impact on the urban and rural context we inhabit. We have spent more time with microscopes than with telescopes that observe this growing organism from space, and have been distracted by appearance. This has permitted these cells to multiply in random carcinogenic patterns we call sprawl.

OPINION

Cellular recipes have been referred to as planning design specifications in this essay. Existing undocumented cellular specifications can be measured and evaluated to build knowledge regarding their implications. The cellular project knowledge acquired will have consistent leadership potential when it is combined to create plans for the space, mass, pavement and intensity characteristics of shelter within neighborhoods, districts, cities and regions. This will permit the design of contained cities composed of living cells that are economically correlated within limited geographic areas to protect their source of life.

There is no mystery to site plan quantity decisions. They simply require research to improve knowledge and gain credibility that will stimulate fine art within a shelter sanctuary served by movement, open space and life support that constantly reminds us of the gift we have been given and the obligation implied.

COMPARISON

The design specifications and forecast panels of Tables 1 and 2 represent the appearances presented in Figures 1 and 2. The Planning Forecast Panels in Tables 3 and 4 are repeated from Tables 1 and 2 to reduce the statistics presented. The statistics in cells A4 and G11 of Table 3, and the statistics in cells A28 and G38 of Table 4 have been placed within Table 6.

Table 3 shows that the appearance of Figure 1 is represented by a shelter capacity of 9,288 sq. ft. per acre in cell F11 and impervious cover of 67.5% in cell A4. The intersection of these two values in Table 6 reveals an intensity measurement of 0.627. This is the same measurement calculated in cell G11 of Table 3 and cell G42 of Table 1.

Table 4 shows that the appearance of Figure 2 is represented by a shelter capacity of 6,935 sq. ft. per acre in cell F38 and impervious cover of 19.0% in cell A28. The intersection of these two values in Table 6 reveals an intensity measurement of 0.132. This is the same measurement calculated in cell G38 of Table 3 and in cell G45 of Table 2.

As a frame of reference, many single family residential subdivisions are designed with a storm sewer capacity equal to 30% impervious cover. This reduces initial infrastructure cost but limits future expansion potential. If one buildable acre contains 5,000 sq. ft. of total gross building area, and is limited by a storm sewer capacity of 30%, the intersection of these two values in Table 6 reveals a maximum intensity measurement of 0.150.

The Figure 1 intensity of 0.627 is well above the low density residential intensity of 0.150. The Figure 2 intensity of 0.132 is lower than this suburban intensity. The context impression left by Figure 2 is often referred to as an “office park”.

When I visually compare the parking, pavement, open space and building mass of Figure 1 to Figure 2 without evaluating building form and appearance, I prefer Figure 2. It has 25% less shelter capacity per acre however, and the capacities are not further apart because Figure 2 is a four story building. In other words, more land is used to produce shelter in Figure 2, and land is a finite resource that is our source of life. It is not a commodity that can be owned, consumed, polluted and discarded without consequences.

If you prefer Figure 2, it means that more land must be used to shelter activity within a geographic area. If geographic limits are accepted to protect our source of life from sprawl, population growth and its activities will require city design decisions that balance shelter intensity and context within these limits. These are inescapable relationships. Tables 1 and 2 are simply tools that make credible evaluation feasible.

Building capacity, intensity and context shelters the many activities of growing populations. I have raised the issue to alert you that this is now a finite planet. It is no longer a world without end that can shelter unending growth, and we have a responsibility to plan accordingly. I have given you a tool set in my book, The Science of City Design. It can be used to evaluate options because shelter is currently expanding to consume our source of life. The disease is called sprawl. When inspecting sprawl from a satellite, we need to look no further than the inhabitants of shelter to find the active cause of this disease on the face of the planet. The words growth, success, progress, capacity, intensity and context take on new meaning from this perspective.