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.
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.
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.
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.
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 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.
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 (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.
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.
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 21st 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.
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.
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.
Copyright: Walter M. Hosack, 2017. All Rights Reserved