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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.


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 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.


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.


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.


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.


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.


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.


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.


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.

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.

Copyright: Walter M. Hosack, 2017. All Rights Reserved

[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.


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.


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.


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.


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.


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.


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.

Copyright. Walter M. Hosack, 2017. All Rights Reserved.

Tuesday, September 5, 2017


The following is a post, a response, and my reply to a LinkedIn conversation that I didn’t want to lose.

THE POST: Another beautiful piece by David Brussat: "Ornament is not merely the jewelry of architecture but its very essence, the expression of a building’s purpose, its aspirations and its place on the street but also in the heart and soul of society."

FIRST RESPONSE: I disagree. Not ornament but rational and sensitive use of site, structure and function are the essence of architecture. (Author note: “rational” and “sensitive” remain undefined matters of opinion that seriously weaken shelter design credibility.)

MY REPLY: I would like to add that architecture is shelter, and shelter is a division within the urban and rural phyla of The Built Domain. The survival of the Built Domain depends on its source of life - The Natural Domain. The decisions that lead to shelter construction and expansion of The Built Domain are currently producing a parasitic disease we call sprawl. It is slowly consuming the face of the planet. The transition from shelter to architecture is a matter of appraisal and opinion at the present time; but architectural design decisions must become part of the correlated, symbiotic decisions and solutions we will need to survive in the future.

Wednesday, August 30, 2017


We will compete to consume until we realize that our definitions of growth and success confuse winning with losing on a planet that demands symbiotic solutions from all of its tenants.

QUESTION: Is sprawl responsible (at least partially) for the flooding in Houston?  

ANSWER: Yes, but it is a term without adequate definition that indicates an inability to correlate the many decisions that lead to failure when independently considered and randomly applied.

Saturday, August 19, 2017

Core Area Restrictions on Shelter Capacity

This is the third essay in a trilogy. The first two were entitled “The Future of Cities” and “Understanding a Building Footprint”.

NOTE: All tables referenced are located after the text 

When parking is required, core area is the buildable land area remaining for shelter and parking after a number of support areas are subtracted from gross land area. Shelter capacity is affected by the building design category chosen, the core land area available, and the building height contemplated. This essay is based on a G1 Design Category that depends on surface parking and building footprint areas that combine to equal the total core land area available. The emphasis here is on available quantity.  It has nothing to do with preliminary or final site plan configuration. This definition of core area makes the formation of shelter capacity equations feasible.
In some cases an architect will know the gross land area available and the objective will be to calculate its gross building area potential - Case 1. (I’ve covered Case 1 in two previous essays entitled, “The Future of Cities” and “Understanding a Building Footprint”.) In other cases the architect will know the gross building area desired and the objective will be to calculate the buildable land area required - Case 2. In some cases the gross land area available and the gross building area objective is known, but this essay is based on Case 2. The answer in both cases depends on the core land area remaining. In Case 2 it is an unknown to be discovered.
Table 1 is related to Case 1. It illustrates the subtraction that leads to the definition of core area in cell F32 and G32 based on the gross land area given in cell F3. (The percentage estimates and calculations in cells F3-F31 lead to the core area estimation in cell F32.)
Table 2 is related to Case 2 and does not begin with a given gross land area. It illustrates the distillation of core area in cell F32 based on the percentage estimates and calculations in cells F3-F31. No square foot land areas are given or calculated.
I introduced the G1 Building Design Category and its Case 1 master equation entitled G1.L1 in “The Future of Cities”.
GBA = CORE * af / (a + (fs))

a –              gross building area square feet permitted per parking space provided

CORE –     buildable land area available for building and parking cover in square feet

f –               floor quantity

GBA –       gross building area potential in square feet

s –              gross parking lot area provided per parking space provided in square feet
The equation solves for an unknown gross building area (GBA) when land area is given, but can be transposed to solve for the core land area needed when a gross building area objective is given:
1)      CORE = GBA / af / (a + (fs))  Transposing master equation G1.L1

2)      CORE = GBA / (a2f + af2s)  Reducing line 1

3)      CORE = GBA / (af * (a + fs))  Reducing line 2
Defining core land area is not the answer to the question posed, however. It is the first step in the derivation:

4)      CORE = CORE% * SHA  When shelter area (SHA) in sq. ft. is known

5)      SHA = SHA% * BLA  When buildable land area in sq. ft. is known

6)      CORE = CORE% * SHA% * BLA  Substituting line 5 for SHA in line 4

7)      CORE = GBA / (af * (a + fs))  Repeat line 3

8)      GBA * ((a + (fs)) / af) = CORE% * SHA% * BLA  Substituting line 7 for CORE in line 6

9)      GBA * (a +(fs)) = CORE% * SHA% * BLA * (af)  Reducing line 8

10)    BLA = (GBA * (a + (fs))) / (CORE% * SHA% * (af))  Transposing line 8 to find Equation G1.B1.BLA
Equation G1.B1.BLA on line 10 is located in cell A38 of Table 2. It is used to calculate the buildable land area options in cells B43-B52 of the table. At this point, the equations in cells C42-L42 are used to calculate additional option columns related to the floor quantity options in cells A43-A52. Shelter capacity, intensity, intrusion, and dominance measurements related to each option are calculated in Columns G-L of the Planning Forecast Panel.
I should again point out that floor quantity above 5 produces rapidly declining gains in gross building area per floor when the G1 Design Category is chosen for shelter construction. This was discussed in “The Future of Cities”.
The buildable land area in cell F9 of Table 2 is estimated to be 82% of the gross land area needed (GLA). An estimate of this gross land area can be simply expressed as:
              GLA = BLA / BLA%
In other words, a GLA estimate can be defined with the following revision to Equation G1.B1.BLA
              GLA = (GBA * (a + (fs))) / (CORE% * SHA% * BLA% * (af))  Master Equation G1.B1
Master Equation G1.B1 is one of 25 related to the building design categories listed in Table 3 and presented in my book, The Science of City Design, CreateSpace, 2016. The derivation of Equation G1.B1.BLA can be found on page 154, lines 62-67. The book, and the second edition of my earlier book entitled Land Development Calculations, can be found on at the following address:

Wednesday, August 16, 2017

Understanding a Building Footprint

I recently wrote an essay entitled "The Future of Cities" that introduced the G1 Building Design Category and its master equation for gross building area that I called (G1.L1):
GBA = CORE * af / (a + (fs))


a –              gross building area square feet permitted per parking space provided

CORE –     buildable land area available for building and parking cover in square feet

f –               floor quantity

GBA –       gross building area potential in square feet

s –              gross parking lot area provided per parking space provided in square feet

The essay explained that when (GBA) is divided by (f), the result is gross building cover area (BCA), also known as building footprint or floor plan. It also noted that (BCA) was equal to 0.1111 of the core land area, but it did not mention the obvious. Eleven percent (0.1111) of a core area is a very small percentage when you consider that core area is the area that remains for building and parking cover after a number of related land areas are subtracted from the gross land area available. It is a surprising statistic, but the formula for maximum potential building floor plan area is one that can give design leadership a simple site planning tool. If maximum floor plan area can be predicted, design results can be easily measured to ensure compliance with leadership intent.

The formula for building cover can be easily derived from the G1.L1 master equation noted above:

Given: BCA = GBA / f

Find: BCA when CORE area is equal to 1.0 in Equation G1.L1:

GBA = af / (a + (fs))                          Equation G1.L1 coefficient

BCA = (af) / (a + (fs)) / f                  Substitute GBA in BCA

BCA = af / ((af) + (f2s))                     Reduce BCA

BCA = a / (a + (fs))                          Reduce BCA to coefficient equation

BCA = CORE * a / (a + (fs))            Reintroduce CORE to form Equation G1.L1.BCA

Remember that Equation G1.L1.BCA only applies to the G1 Building Design Category. When core area is defined by subtraction of estimated land area quantities in a G1 design specification template, the maximum footprint area (BCA) can be found when values are assigned to (a), (f), and (s) in Equation G1.L1.BCA. (The coefficient equation can be useful when presenting options. A sample G1 design specification template explaining the subtraction the leads to core area definition can be found in my essay, “The Future of Cities”. A sample of coefficient evaluation can be found in Table 2 of this essay.)
If you use Equation G1.L1.BCA you will find what every building designer has intuitively observed since automobiles became a G1 site planning topic; but if you are like me, the small percentages will still be a surprise.

Saturday, August 12, 2017


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

The future of a city is directly related to the intelligent use of land within its corporate boundaries. These acres produce yield in the form of revenue - and intensity in the form of perception. Yield per acre has often been inadequate to meet a city’s average cost per acre to operate, maintain and improve. Excessive intensity has often produced physical, social, psychological, environmental, and economic stress generally referred to as inadequate quality of life. Stress has produced sprawl in search of quality at an expanding suburban perimeter.
Expansion often involves annexation, and it can repeat past land use allocation and shelter capacity mistakes in its search for new revenue to solve immediate problems. The increasing cost of maintenance and improvement over time for the new land is ignored until age requires more annexation for new money to balance increasing budget demand. The result can be an unbalanced allocation of shelter capacity and activity within a municipal land area that unwittingly multiplies the burden on an increasingly deficient public revenue stream, or yield per acre. This parasitic growth pattern is a Ponzi scheme that is slowly consuming and polluting its source of life – a limited Natural Domain that does not compromise with ignorance.
The source of the disease we call sprawl is our inability to predict levels of shelter capacity per acre that contain activity producing enough revenue to support municipal expense, even when introducing excessive intensity in some cases. Our ability to accurately predict the shelter capacity of land per acre and correlate this capacity with its revenue and intensity implications remains a random result of marketing decisions based on individual interpretation. This has produced sprawl that will not be contained without a bridge language that can correlate shelter capacity, activity and revenue with its intensity and its quality of life implications. This does not mean that every acre within a geographically limited municipal area must meet or exceed its average cost per acre for municipal operations, maintenance, and improvement. It means that we need a bridge language to correlate average revenue from all shelter capacity and activity present or planned per acre with its average municipal expense per acre. In other words, we need an accurate ability to measure, predict, and lead shelter capacity decisions toward the goal of balanced activity within a geographically limited Built Domain that protects its quality and source of life. We now have a bridge language capable of correlating shelter capacity measurement and prediction with its physical, social, psychological, environmental and economic implications.
Project site plans and building mass combine to produce shelter capacity. The relationship of shelter capacity to movement, open space and life support within a city determines the physical intensity, intrusion, and dominance perceived at any scale of city design. Physical intensity combines with social activity to produce economic performance. This performance supports the quality of life present or planned for a city. The aggregation of cities produces a Built Domain that is currently sprawling to consume its source of life - The Natural Domain. Sprawl is produced by an arbitrary and expanding demand for shelter from a growing population. These populations consume excessive amounts of land and resources to satisfy the demand because they have not been able to accurately correlate shelter capacity with activity to form beneficial, balanced physical, social, and economic relationships.
The purpose of this essay is to introduce one equation from a portfolio of 26 listed in Exhibit A. They are bridge equations that can be used to link shelter capacity measurements, predictions, options, and decisions to a wide variety of implications related to their square foot measurements and predictions such as, but not limited to, shelter capacity, cost, yield, population, traffic, open space, life support, return on investment, and so on. They can also be used to link a wide variety of disciplines influenced by shelter capacity options such as city planning and design, architecture, landscape architecture, civil engineering, urban geography, sociology, psychology, ecological science, real estate investment, traffic engineering, and so on. In other words, the series of bridge equations listed in Exhibit A, and their related design specification templates, can be used to guide city design measurement, evaluation and prediction toward the formation of city planning and design decisions that will produce knowledge when results are evaluated.
The bridge equation to follow is listed in Exhibit A. It is one in a series written to fill a measurement, evaluation, conclusion, and prediction gap. This gap has prevented more rapic accumulation of city design knowledge and the formation of options that can be chosen to lead our efforts toward a symbiotic future.
Shelter capacity is gross building area in square feet divided by the total number of buildable acres occupied. I have referred to these acres as gross, net, buildable, shelter, and core areas. Table 1 begins with gross acres in cell F3 and illustrates the subtraction that leads to net area in cell G7, buildable area in cell G10, shelter area in cell G17, and core area in cell G32. Core area is the land area remaining for building floor plan and parking support when parking is required.
Gross building area in a project is converted to shelter capacity per buildable acre, but should not be confused with land use activity. Activity can occupy any gross building area, assuming building code compliance. The scope of activity that can be sheltered is a function of the gross building area present of planned per acre. If building capacity per acre does not shelter enough activity to produce adequate revenue per acre, capacity must either increase or be offset by the revenue from other activities to meet a city’s annual cost to operate, maintain, and improve. In other words, the scope and type of activities sheltered per acre within a city must combine to meet or exceed the average revenue required per acre to support a city’s desired quality of life. If the relationship is inadequate, budget cuts will ensue and the conversion of agriculture through annexation will be considered. Building capacity is shelter capacity and it is a function of building design category and design specification decisions that produce gross building area options. Revenue is a function of the activity sheltered within gross building area in addition to the real estate value introduced.
The downside to a capacity-activity relationship occurs when excessive capacity produces excessive intensity in a project or larger urban area. Cells G42-J51 calculate the intensity, intrusion, and dominance implications of the shelter capacity options in cell F42-F51. (These capacity calculations are a function of the gross building area options predicted in cells B42-B51.) I have no idea if the intensity options in Column (G) are excessive. This definition is a challenge for future research. I have simply provided a method of measuring physical intensity, predicting gross building area options at the cellular (project) level of city formation, converting gross building area measurements to their shelter capacity implications, and calibrating perception with capacity, intensity, intrusion, and dominance statistics that have physical, social, psychological, environmental, and economic implications.
When a surface parking lot around, but not under, one or more buildings is used to satisfy parking demand on a given land area, the building design category is referred to as “G1” and gross building area options for the land area given can be defined with Equation G1.L1.

GBA = CORE * af / (a + (fs))

a –              gross building area square feet permitted per parking space provided
CORE –     buildable land area available for building and parking cover in square feet
f –               floor quantity
GBA –       gross building area potential in square feet
s –              gross parking lot area provided per parking space provided in square feet

The detailed discussion surrounding this equation can be found in Chapter 6 of my book, The Science of City Design, published by CreateSpace in 2016 and available on (The derivation of the equation can be found on page 154. It permits shelter capacity options to be accurately predicted for any given land area when the G1 Design Category is the shelter design choice.) The equation predicts shelter options based on the values entered in its design specification and correlated for use in this master equation. The shelter design options produced can be evaluated based on accumulated and evolving knowledge. The goal is to protect a growing population’s quality of life while limiting its consumption of land that is its source of life.
The equation depends on an accurate definition of core area, which is the land remaining for building and parking cover after percentage estimates are subtracted for all other site planning topics and quantities. An example of a G1 core area calculation is presented in Table 1. The table begins with the gross land area given on line 3. Core area is found on line 32 by subtracting percentage estimates for the intervening site planning topics listed.
Figure 1 charts the gross building area (GBA) results predicted by Table 1. It is discussed in detail in Chapter 6 of my book, and is presented here to illustrate a fundamental characteristic of the G1 Building Design Category. The increase in G1 gross building area capacity produced by increasing floor quantity on a fixed core land area rapidly declines as a surface parking lot expands to justify the increase and the core land area remaining for building footprint (BCA) shrinks in response. (A building footprint is multiplied by floor quantity to increase gross building area potential until parking lot expansion makes the footprint too small to be useful. There is also a point when the increase in gross building area per floor becomes too small to be justified given the cost of increasing the number of floors.) The point of failure is a matter of investment opinion, but appears to occur at either the 4 or 5 floor mark in Figure 1. This figure is based on the values entered in the design specification template of Table 1 and is heavily influenced by the open space percentage entered in cell F11. A change to this percentage will influence the point where the curve begins on the y-axis when all other specification values remain constant. I’ve made this point in previous essays and only repeat it here to indicate why I have limited all spreadsheets in Table 2 to a floor quantity range of 1 to 5 stories.
When the core value in Equation G1.L1 is equal to 1, the gross building area potential of any G1 core land area is indicated by the values entered in the equation coefficient, (af / (a + (fs)). This makes it possible to present a broad range of gross building area options for any G1 building on a single page. For example, spreadsheet (A) in Table 2 is based on an s-value of 400 as noted in cell C5. (An s-value is equal to the total area within a parking lot perimeter, including landscaping, divided by the number of parking spaces provided. The a-values on line 10 in spreadsheet (A) represent the total gross building area permitted per parking space provided.) The spreadsheet shows that gross building area coefficients increase as the gross building area (a) permitted per parking space increases on line 10 and floor quantity increases in cells B11-B15. It also shows in cell R15 that a 5 story building with a parking requirement of 1,000 can be 15 times the size of a 1 story building with a parking requirement of 50. This statistic and the entire spreadsheet gives a glimpse of the advantages that accrue when a parking variance to a less restrictive requirement is approved and the risk of excessive intensity is increased.
If you compare the coefficient calculated in cell G15 of spreadsheet (A) to the coefficient calculated in cell G27 of spreadsheet (B), you’ll see that the coefficient for a 5 story building declines from 0.5556 to 0.3846. This occurs because the s-value in cell C17 has increased to 600 from 400 in cell C5. This indicates that more parking lot pavement and/or landscape area has been provided per parking space introduced. A smaller gross building area is permitted by the reduced number of parking spaces that can be provided.
The coefficient in cell G27 is approximately 30% less that the coefficient in cell G15. This is a 30% decrease in 5 story gross building area potential when the parking lot area provided per space increases from 400 to 600 sq. ft. When the increase reflects additional landscape area to relieve pavement intensity, more general questions are implied.
When should shelter capacity be limited by an unpaved open space requirement (OSAU in cell F11 of Table 1) to relieve the intensity, intrusion, dominance, and impervious cover introduced by building mass and pavement, and what percentage should be required?
There is no consistent answer to this question at the present time, except for the limits required by storm sewer capacity design that are generally unknown and/or ignored. We have not accumulated the measurements and evaluation needed to distill knowledge and demand relief. The only impression I have at the moment is that the percentages will vary with the activity sheltered, but even this raises a question. When you look beyond a site plan and specific activity, how much unpaved open space should be woven into the urban fabric to relieve intensity and offset stress in the cities we build?
Building cover (BCA) is another term for building footprint or building floor plan. A building cover coefficient is equal to a gross building area (GBA) coefficient divided by the floor quantity (f) related to the coefficient. For instance, the gross building area coefficient for a 5 story building and a parking requirement (s) of 250 is noted in cell G15 as 0.5556. The maximum building cover coefficient is 0.5556 / 5, or 0.1111. If the available core area were 100,300 sq. ft. as shown in cell G32 of Table 1, the maximum GBA potential would be 55,726 sq. ft. and the maximum footprint would be 11,145 sq. ft. (These values can be calculated with a coefficient or found in Table 1.) If either area is insufficient to satisfy a client’s architectural program of rooms, spaces and relationships, the values entered in the Land Module and G1 Module of the design specification in Table 1 would have to be adjusted; and these adjustments might require zoning variance requests. In these cases, the altered values would be debated and the adequacy of their defense would depend on the logic, research, and accumulated knowledge supporting each value.
A city’s total buildable land area is restricted by corporate boundaries that make each acre a limited resource - and its permitted activity list an investment in the city’s economic future. Annexation is a losing exercise if the additional acres are not devoted to shelter capacity and activity that can maintain or improve a city’s average revenue per acre over a time period that includes the land’s increasing cost of maintenance and improvement.
The capacity, intensity, revenue and expense associated with each acre of municipal land has not been measured or predicted because a mathematical bridge has not been available to correlate shelter capacity, activity, and revenue with intensity and appearance in a timely manner. Equation G1.L1 is one example of the bridge language and science of city design that can be used to correlate reality with perception to preserve land as a source of life.