I have written three essays entitled, "Design Decisions That Determine Apartment Density”; “Design Decisions That Determine Townhouse Density”; and “Design Decisions That Determine Single-Family Detached Housing Density”. They were written to identify the design topics whose values must be mathematically correlated to lead residential shelter capacity toward intensity combinations that avoid overcrowding and sprawl.
There are 27 gray cell entries in Table 1 that represent
decisions collected in 3 modules entitled, “Land”, “Lot”, and “Building”. Gross
land area is given in cell F3 and the objective of the table is to predict the
average number of lots and gross home area options that can be constructed on
the land area given under the conditions specified by the gray cell values
entered and mathematically correlated. These predictions can be found in the
Planning Forecast Panel at the bottom of the table, and they will change
whenever one or more of the gray cell values are modified in the spreadsheet.
The Land Module in Table 1 pertains to traditional
subdivision plans that provide no common open space for shared public amenities
as noted by the 0% values entered in cells F13 and F14. If percentages had been
entered in these cells, the remaining shelter area would have declined as a
percentage of the buildable area available, but the impervious cover limit
calculated in cell F12 would have remained for every lot subdivided from the
smaller shelter area.
The 10 gray cell values entered in the Lot and Building
Modules of Table 1 are used to find the first floor footprint area remaining on
the lot area given in cell F23 after all other allocation is subtracted. This footprint
area is found in cell F46. It is multiplied by the floor quantity alternatives
entered in gray cells A55-A63 to find average gross home area options for the
given lot area in Column B of the Planning Forecast Panel.
This footprint, or first floor area in cell F46 may seem low
for a 9,000 sq. ft. lot, but it is a function of the 30% storm sewer capacity calculated
in cell F12 from the 70% unpaved open space entered in cell F11. It is not only
low. The area is a limit that includes all future expansion. This should
indicate the critical importance of a subdivision feature that is often
overlooked until storm sewer flooding produces a need to supplement the
developer’s limited contribution with a public relief sewer. I cannot overstate
the need to take the value entered in cell F11 seriously for this reason, along
with the implications calculated in cell F12 and the related implications in
the Planning Forecast Panel of Table 1. If the storm sewer capacity calculated
in cell F12 had been greater, the lot area entered in cell F23 could have been
reduced while producing an equal or greater footprint area. This would have
produced greater shelter capacity per buildable acre and reduced land consumption
for the most desired dwelling unit configuration on the planet. The downside is
that too great a decrease in the value entered in cell F11 would increase the
intensity calculated in Column H of the Implications Module until it prompted a
flight similar to that of the original suburban migration.
Estimated lot quantity for the recipe entered in Table 1 is found in cell C55 of the Planning
Forecast Panel by dividing the average lot area given in cell F23 into the
shelter area remaining in cell G17. Three additional columns of predictions are
also included in the Planning Forecast Panel.
The Implications Module in Table 1 is the last feature of
the Table 1 forecast model. The shelter capacity of the land area given is related
to the floor quantity options entered in Column A. The results are used by the
formula in cell H53 to produce the related intensity values in Column H. These calculations
measure the relationship of building mass and pavement to unpaved open space when
floor quantity options change in Column A and the remaining gray cell values entered
are constant. Any change to one or more of the gray cell values entered will
produce a revised planning forecast and set of implication measurements.
The intrusion measurements calculated in Column J translate
the floor quantity options entered in Column A to a compatible four-part measurement
system.
The measurements calculated in Column K of the Implications
Module combine the capacity, intensity, and intrusion measurements of Columns
G-J into a consolidated statement of project dominance options. In other words,
a project dominance value in this example is produced by correlating 18 design decisions
that do not exist in isolation and must be coordinated to provide correlated leadership
direction for the three physical fronts of shelter design.
From a city design perspective, land use planning with design
specification correlation can optimize the use of land to shelter any activity,
and is the key to correlating capacity, activity, intensity, and economic
stability within limited geographic areas.
CONCLUSION
I hope that I have made the significance of comprehensive,
coordinated design value decisions apparent. Our current concept of minimum,
independent zoning regulations cannot lead us toward the shelter capacity and
activity allocation needed to protect the physical, social, psychological,
environmental, and economic welfare of growing populations within geographic
limits that protect their source of life. We depend on shelter for survival but
it consumes land that is our source of life. We are expected to discover the
correlation required.
I have deleted most of the equations in Table 1 to simplify the illustration and have omitted a detailed discussion of Building Design Categories and Residential Activity Group classification that I have mentioned in earlier essays. 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. The subdivision chapter in this book considers two fundamental Traditional and Clustered subdivision questions in depth:
1) What lot quantity and average home area
options can be accommodated in a subdivision when gross land area and
minimum lot area are given?
2) What minimum lot area, shelter area and
buildable land area is needed for a subdivision when lot quantity and
average home area objectives are given?
A third question is a variation of Question 1.
3) What average lot area and home area options
are available to a subdivision when gross land area and lot quantity
objectives are given?
A fourth question is solely devoted to cluster subdivisions.
4) How is average home size affected when lot
quantity remains constant in traditional and clustered subdivision plans for
the same gross land area?
The answers to these questions can be examined in
spreadsheets I have called forecast models. The values assigned are like a
musical score. The symphony produced will remain a function of the talent
available. The objective is to eliminate the dissonance produced when a
score and conductor are missing.
