Design Decisions That Determine Apartment Density

 

An apartment is a one floor leased or rented dwelling unit that may be subdivided from any one of six building classification categories. The apartment activity group is designated R3 and often referred to as a land use category.

Land use is social activity that occupies a physical shelter classification, and social activity is served or subjected to the intensity of the physical shelter and surroundings provided.

A building design category is classified by the primary method of parking used to serve its occupant activity.

A G1 Building Design Category includes all buildings served by a grade parking lot around, but not under, the building on the same premise.

Apartment density is the product of 42 initial design decisions when a G1 Building Design Category is subdivided to create R3 dwelling units. Ten of these decisions are often limited by local zoning regulations. The remaining 32 are discretionary. The combined decisions may not produce a dwelling unit quantity greater than that specified by a density limit in a zoning ordinance (without public variance approval). Density does not lead these 42 decisions however. It is a product of them, and correlation of these decisions to respect a density limit depends on instinct, intuition, and opinion referred to as talent at the present time. Consistent success will remain arbitrary and elusive until we can accurately predict the results produced by these 42 decisions and lead them to produce shelter for growing populations within limited geographic areas defined to protect their quality and source of life.

The 42 apartment decision topics are identified in Table 1 with a gray tone. Ten zoning requirement topics are designated with solid black lines around their respective gray cells, but the values entered are not consistently mandated in all zoning ordinances. The values entered in the 32 remaining gray cells are discretionary. The 42 values involved have been mathematically correlated in the Table 1 forecast model to produce results in its Planning Forecast Panel, Implications Module, and Dwelling Unit Forecast Panel. If one or more of the gray cell values is modified, the results calculated will adjust in response.

If we look at the 3 story building specified in cell A58 of Table 1, the correlation of the 41 related gray cell values entered above produces the results summarized on line 58 and the density calculated in cell N58. Any change to one or more of the gray cell values entered will produce a revised set of implications in the forecast model.

Density is a very inaccurate measure of the shelter capacity, intensity, intrusion, and dominance produced on a given land area by the 42 correlated design decisions itemized in Table 1, however; because the number of dwelling units permitted may be any size and pavement may be permitted in many required yard areas. The result can easily become excessive quantities of impervious cover threatening existing storm sewer capacity and surrounding quality of life. These lifestyle outcomes can now be measured with the equations in cells H50 and H51. Their conclusions are presented in columns K and L of the Implications Module based on the values entered in the gray cells of Table 1.

Zoning intent has been to leave at least 32 of the values entered in the gay cells of Table 1 flexible as long as the density limit is not exceeded, but this sacrifices the leadership needed to ensure that shelter capacity, intensity, intrusion, and dominance do not become excessive on the land area subject to these 31 decisions, since the intent behind these decisions is not necessarily in the public interest.

The combination of building mass, pavement, and unpaved open space quantities that emerge on a given land area are a function of the 42 site planning / massing design decisions entered in the gray cells of Table 1. This collection of decisions could be called a quantity recipe for an urban design site plan. These quantities are mathematically correlated by the equations in the forecast model to produce the intensity calculations included in the Implications Module of Table 1; and many different levels of density and intensity can be created by adjusting the values assigned to these 42 topics. The lack of itemization and correlation of these values has led to the random and often excessive intensity levels we attempt to escape in every sprawling Built Domain we have created.

POSTSCRIPT

It would be a simple matter to discuss any project values entered in the gray cells of Table 1 with all public and private parties involved at a common round table. The established mathematical relationships of the forecast model would quickly determine the development capacity of the land based on the mandatory and discretionary values entered. The focus would then center on the alternatives created and the implications produced by adjusting the discretionary values entered. The mandatory values could also be examined for variance opportunities. Decisions would be based on accumulating knowledge formed by measuring and evaluating these topics at existing locations to determine shelter capacity, intensity, intrusion, dominance, and density to be emulated or avoided with reasonable assurance that success could be duplicated and failure avoided. This would convert contentious disputes over isolated zoning requirements to a common focus on the correlated site plan / massing values that can correlate the development capacity of land with its intensity, intrusion, dominance, density, and quality of life potential.

I have deleted most of the equations in Table 1 to simplify the illustration and have omitted a detailed discussion of the Building Design Category and Residential Activity Group classification mentioned in this brief essay. If you are interested, these equations and discussions can be found in my book, The Equations of Urban Design, which is available from Amazon.com. (I discovered an error the cell N55 equation of Table 14.2 and Table 14.5 that will be corrected in future editions to conform to this essay.)