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Thursday, January 25, 2024

Refining the Definition of Density - The Decisions That Determine Density Impact

 I was asked what it would take to build 9 single-family detached residential homes with no further information. I created the forecast model included as Table 1 to explain the information needed to answer the question. It begins with a land area specification in shaded cell F4, since an answer cannot begin without a land area or average gross home area specification.

Normally, a user is expected to enter design specification values in the shaded cells of a forecast model. The values are correlated by an algorithm and processed by a master equation to produce the predictions calculated in its Planning Forecast Panel and Implications Module. A value change in one or more of these shaded cells produces new predictions and implications for evaluation.

In this example I’m filling in the information as a demonstration of shelter capacity evaluation. I entered one total acre in cell F4 and realized that this might have general educational value regarding the term “density”.

The values requested in cells F5-F7 and F9 of the Lot Module in Table 1 are used with subtraction to define the buildable land area in cell F11. It is a critical point, in my opinion, because density calculations based on gross or net land area can give a false, and lower, impression of the density being considered when the land area used for the calculation includes unbuildable area. We live in the density and intensity created on buildable land. The rest is simply a view. It should not be used to distort measurement of the quality of life created on habitable buildable land area.

I entered zero in cells F5-F7 and cell F9 to make the template as generic as possible. I entered 70% in cell F12 because I was told years ago that designers often assume 30% impervious cover as their storm sewer capacity design standard. It may, or may not be accurate, but the 30% value calculated in cell F13 from the value entered in cell F12 is based on this assumption. It could be easily changed to reflect other values if desired.

I entered random values in the Pavement and Building Modules of Table 1 to clarify the type of values expected, except for cell F33. The value entered reflects the inquiry I received. Since the buildable land area in cell F11 remains one acre in cell F11, the dwelling unit quantity requested now represents a density of 9 dwelling units per buildable acre.

The values calculated in the Planning Forecast Panel reflect the implications of the requested density when correlated with the other design specification values entered in the Lot, Pavement, and Building Modules.

The average footprint area (FTP) found in Col. B of the Planning Forecast Panel reflects the implications of the requested density when correlated with the design specifications entered. It does not change with floor quantity because it is the land remaining after all other two-dimensional site plan demands are subtracted. These calculations show that the average footprint remaining is smaller than the garage calculated in cell F27.

The values in cells F28 and F29 were entered to show that it is possible to add bonus dwelling area (BON) over the garage. When this is considered, the additional areas appear in Column C of the Planning Forecast Panel.

Floor quantity (f) is multiplied by footprint area (FTP) and combined with bonus area (BON) to arrive at the total home areas (HOME) calculated in Col. D of the Planning Forecast Panel.

Garage area in cell F27 and accessory building area in cell F31 is added to the home area calculated to arrive at the total building areas (TBA) presented in Col. E of the Planning Forecast Panel. The related total building area percentages of buildable land area are calculated in Col. F.

Gross, net, and buildable land area densities are calculated in Col. G of the Planning Forecast Panel. In my opinion, density is a social measurement that conveys little information about the physical design decisions it is used to represent. These are the decisions that must be correlated before leadership direction can hope to produce what it promises.

The Implications Module introduces physical design measurements based on the correlation of design specification values entered in the template. Shelter capacity (SFAC) in Col. D is found by first multiplying density per buildable area (dBAC) by the total building area values (TBA) found in Col. E of the Planning Forecast Panel. The result is divided by the buildable land area involved in acres to find the shelter capacity involved. This conversion makes all shelter projects measureable and comparable.

When shelter capacity is divided by 43,560 sq. ft. and multiplied by the impervious cover percentage calculated in cell F13, the result is a comparable measure of intensity (INT) that increases with floor quantity as shown in Col. E of the Implications Module.

Intrusion is measured in Col. F of the Implications Module by dividing 5 into the floor quantity under consideration.

The sum of shelter capacity, intensity, and intrusion produces the physical dominance measurements calculated in Col. G of the Implications Module. All of these measurements are based on the shelter capacity (SFAC) values found in Col. D of the Implications Module and are meant to be comparable among any and all shelter design projects and urban design areas.

The Implications Module calculates the correlated impact of any chosen set of design specifications entered in the Design Specification Template of a building design category forecast model. Density is produced by these specifications. It does not lead them and is not comparable unless accompanied by the design specifications involved. In other words, the Implications Module produces the measurements needed to begin assessing and comparing the results produced by design specification decisions. These are the physical design decisions that establish a foundation for the shelter spaces, places, massing, composition, and appearance that is built upon them by all ensuing design decisions.

I could change any one or more of the design specification values entered in the shaded cells of Table 1, except for the values entered in cells F4 and F33, to arrive at a different set of results and implications without changing the density calculated.

The greatest temptation facing a designer confronted with an inadequate footprint calculation (FTP) would be to reduce the unpaved open space percentage specified in cell F12. This would increase the remaining footprint area calculated in cells B41-B49. It would also increase the intensity measurements calculated in Col. E of the Implications Module - as well as all others in the module. When present or proposed storm sewer capacity is unknown, however, this decision to increase the impervious cover percentage could compromise the available storm sewer capacity. Every plat and project approved by a city, and every variance it grants for building cover and pavement expansion without this impervious cover information runs the risk of adding to a storm water burden that can result in flooding until corrected.

Any number of value changes could be made in the shaded cells of Table 1 that would influence the results calculated in its Planning and Implication Modules. I’m not here to render judgement. I am simply attempting to explain how more rational, fundamental, correlated shelter design decisions can be measured, evaluated, and chosen to lead our pursuit of shelter for all our activities within a Built Domain that must be geographically limited to protect its source of life. We cannot do this with the tools we presently use. They have produced annexation, sprawl, excessive intensity, and a few random success stories in pursuit of mindless growth. It will continue as long as we remain unable to lead shelter capacity for the activities of growing populations within geographic limits drawn to protect their quality and source of life.

Walter M. Hosack: January, 2024



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