The first ambiguity is an unspecified percentage of the acre
that is available for shelter construction. This immediately makes physical
intensity an unmeasurable quantity. As an example, portions of the acre may be
required for public right-of-way. In this case a “gross acre” is reduced to an
available “net area”. Portions of the net area may be consumed by ravines,
protected wetlands, streams, and so on. The remainder then becomes a “buildable
land area”. Portions of the buildable area may be devoted to common open space
shared by a number of dwelling units. In this case the remainder becomes a
“shelter area”. A density calculation or regulation that does not accurately define
the area on which it is based introduces uncertain intensity, ambiguity, and
argument.
The second ambiguity is an unspecified maximum dwelling unit
area for the quantity permitted per acre. This problem is easiest to visualize
by considering the same dwelling unit on decreasing land areas. The result is
increasing amounts of physical intensity, intrusion, and dominance, but we have
been unable to calculate or measure these implications. We have simply formed
opinions based on individual perception.
The following discussion will explain the measurement topics
that are required to adequately define density and predict future implications
in the leadership detail required. The template used will address one building
design category occupied by one activity group. The format is similar, but not
identical, for all forecast models related to six building design categories
that are occupied by a wide variety of activity groups around the globe. The
alternative is simply a continuation of the methods that have brought us
annexation, sprawl, and continuing consumption of both agriculture and the land
of our natural domain. I have frequently explained this category classification
in the past and will avoid duplication here for the sake of brevity.
Density does not lead shelter design decisions. It is a
product of them. The broad design discretion permitted by the concept, and the
lack of correlation among its variable determinants, has produced random
results fashioned with opinion. Annexation and sprawl symbolize the continuing
leadership confusion with excessive land consumption. This isn’t the first time
I’ve said this, but I keep trying to simplify the explanation.
It takes a correlated set of design value decisions to
determine density, and these measurable decisions have shelter capacity,
intensity, intrusion, and dominance implications that can be measured. I intend
to explain one set in this brief essay. Many optional design specification values
are not desirable, but this remains to be proven with evaluation of accurate, measureable
analysis. The objective is simple and probably controversial. We must learn to
live within a geographically limited Built Domain that shelters the many
activities of growing populations while protecting their quality of life and their
source of life – the Natural Domain. We cannot do this with a random approach
that depends on opinion without an adequate foundation of acquired knowledge.
I’m going to explain density by leading you through the 51 measureable
design specification decisions that lead to this conclusion in the example I
have chosen. It will also show that these decisions produce measureable capacity,
intensity, intrusion, and dominance implications that we either enjoy or endure
within the Shelter Division of our cities. Correlation of these decisions is
the key. Quality of life and economic potential are outcomes encouraged by the
right decisions.
THE FORECAST MODEL
The following example begins with a given gross land area, a
given building design category, and apartment activity as the given occupant
group. If you have read my earlier work you will recognize the G1.R3.L1
Forecast Model included as Table 1. The notation “G1” refers to all buildings
served by surface parking around but not under the building on the same
premise. The notation “R3” refers to gross building areas subdivided to contain
three or more single floor apartment “flats” for residential activity. The
notation “L1” indicates that gross land area must be given.
Currently, activities are grouped under the term “land use
category” rather than “activity group”. This has confused the distinction
between a building design category and an occupant activity. This essay is
based on a shelter classification system that contains six building design
categories occupied by most, if not all, activity groups around the planet. A
building design category may be occupied by an activity. It is the correlation
of shelter capacity with activity on land that determines the economic
potential of the land as well as the physical intensity introduced. We have had
to rely on opinion and rules of thumb to assess these opportunities. Opinion is
enough to debate the merits of fine art; but only enough to start the
measurement and evaluation needed to proceed with an effort to build transferrable
knowledge regarding shelter capacity, intensity, and economic stability.
Land Module
This explanation begins with the Land Module in Table 1. Gross
land area given in shaded cell F3. An unbuildable land area percentage is
requested in cell F4. The area percentages to be set aside for existing
conditions to remain and future expansion are requested in cells F5 and F6.
Subtraction produces the net land area percentage remaining in cell F7. The
percentage of net land area estimated for public right-of-way is requested in
cell F8. Subtraction of this area from net area produces the buildable land
area remaining in cell F10. The percentage of buildable land area to be set
aside for unpaved open space is requested in cell F11. The impervious cover
remaining for building cover and all other pavement is found in cell F12 by
subtracting the value entered in cell F11 from 100%. Portions of the project
area unpaved open space and impervious cover remaining in the buildable land
area may be devoted to common area serving more than one building in a larger
project area. If so, the percentages of buildable land area contemplated are
requested in cells F13 and F14. Common space allocation, when introduced,
reduces the impervious cover and unpaved open space percentages of buildable
land area remaining. These reductions, if present, are shown in cells F15 and
F16. The sum of the impervious cover and unpaved open space percentages remaining
in cells F16 and F17 produce the remaining project shelter area in cell F17. Finding
this value is the objective of the Land Module.
Core Module
The objective of the Core Module is to subtract all
additional estimated miscellaneous impervious cover percentages that reduce
total impervious cover percentage in the shelter area. Subtraction finds the
core area remaining for building cover and surface parking in cell F32.
Defining this core area makes the derivation of a master equation capable of
predicting gross building area options for the core area feasible.
The master equation is located in cell B51, but the values
(a), (f), and (s) in the equation remain to be defined. The value (f)
represents floor quantity. The values under consideration are entered as
options in cells A56-A65. The value (a) represents the gross building area
square feet that may be constructed per parking space provided. The value (s)
represents the average parking lot square feet per parking space planned or
provided. Both are found using the R3 Apartment Module.
R3 Apartment Module
I mentioned at the beginning of this essay that density
expression does not specify the average dwelling unit area (ADU) used to
produce the density involved. It also omits the values (s) and (a) from its
definition. These omissions can produce a wide range of shelter capacity,
intensity, intrusion, and dominance results. The R3 Apartment Module has been used to find
these values and make the prediction of gross building area (GBA) options
feasible with the use of the master equation in cell B51.
The dwelling unit types planned are entered in cells A41-A45.
The percentage allocation for each type is entered in cells B41-B45. The
habitable area planned for each is entered in cells C41-C45. These habitable
areas are increased by the efficiency factor entered in cell F37 to determine
the estimated gross building area required for each habitable area in cells
D41-D45. The average dwelling unit area involved (ADU) is calculated from the
data entered and calculated in cell D47.
The number of garage spaces planned for each dwelling unit
type is entered in cells E41-E45. The number of parking spaces planned for each
dwelling unit type is entered in cells F41-F45. The average parking area per
parking space for all dwelling units planned (a) is calculated in cell J47.
The value (s) is a design variable decision entered in cell
F36. The value chosen has a great deal to do with the landscape quality
anticipated for the parking lot.
I’ve already mentioned that master equation value (f) is represented
by a series of floor quantity options entered in cells A56-A65.
The master equation in cell B51 is the product of an
extensive derivation that is not included for the sake of brevity.
At this point I hope it is clear that design value decisions
must be entered in the 51 shaded cells of Table 1 before their density
implication can be accurately calculated by the master equation in cell B51. Omitting
this information introduces too much ambiguity for adequate leadership within a
limited Built Domain that must be constrained from consuming its agriculture
and source of life.
Planning Forecast Panel
The gross building area (GBA) options calculated in cells
B56-B65 of Table 1 have been the objective of this forecast model, and they are
a function of the values entered in the shaded cells of Table 1. A change to
one or more of these values would produce different forecast results since they
are all correlated. This should indicate the sensitivity of the correlation
that has been managed with instinct, intuition, and talent for centuries. When these
gross building area options are divided by the buildable acres involved, the
options that result are presented as shelter capacity (SFAC) options in cells
J56-J65.
The calculation of gross building area options for a given
land area makes any number of related predictions feasible. A few are
calculated with simple arithmetic in Columns C-H of the Planning Forecast Panel
as examples of this potential. I won’t spend time with them since they are relatively
self-explanatory.
Implications Module
I’ve previously mentioned that an inability to accurately
calculate gross building area and shelter capacity per buildable acre can
result in estimations that either waste land or produce excessive intensity on
inadequate land area. The Implications Module introduces a method of measuring
shelter capacity, intensity, intrusion, and dominance that will be produced by
a given or measured set of design specifications.
An example set of specifications has been entered in the 51 shaded
cells of Table 1. The implications calculated in Columns J-M of the
Implications Module are like the first blood pressure measurements. We will not
understand their meaning until we measure and evaluate a test group of project
areas to understand the unwritten knowledge they convey.
I’ve included density per shelter acre (dSHAC) and density
per gross acre (dGAC) in Columns M and N to show how density implications are a
product of the leadership decisions entered in the 51 shaded cells of Table 1. As
an isolated requirement without the specifications provided, it is simply too imprecise
to lead these decisions toward a desired objective.
Dwelling Unit Forecast Panel
The forecast panel beginning on Row 67 of both Tables 1 and 2 is provided to help assess the design implications of the design specification values entered and the floor quantity entered in cell B70. The rounded dwelling unit quantities calculated on Row 71 are intended as a guide, not as a floor plan solution.
Postscript
I’m going to ask you to imagine for a
moment. If you, your client, or an applicant filled in the values requested in
the shaded boxes of Table 1 on paper, you could enter them in the digital
template illustrated to determine their implications. If prior research and
evaluation had defined capacity, intensity, intrusion, and dominance targets,
the specification could either be approved or modified with a few keystrokes to
meet them. This doesn’t mean that all differences of opinion regarding the
values entered can be resolved without recourse to a Zoning Board of Adjustment.
It simply provides a more objective, efficient, and comprehensive common
platform for evaluation by all parties involved.
Unpaved
Open Space – Stormwater
This is a topic that has been
largely ignored in the quest to increase the permitted number of dwelling units
on a given land area with the least expense. If I reduced the unpaved open
space percentage specified in shaded cell F11 of Table 1 to that shown in Table
2, the dwelling unit quantities in Column D of the Table 2 Forecast Panel
increase along with the densities calculated in Columns M and N of the
Implications Module. The impervious cover percentage in cell F11 also increases.
Density approval of the increase
requested can often overlook the storm sewer capacity required by the increased
impervious cover. Later variance approvals for more impervious cover on the
same lots can easily increase the problem. The conflict between public benefit and
private expense should be obvious. I won’t expand on the issue since I’ve
discussed it in previous essays. I note it here because it is one reason for
the unpaved open space percentage requested for evaluation in cell F11 of Table
1, and the resulting maximum impervious cover percentage that is calculated in
cell F12. These values would apply to all future variance requests as well. If
a city defines these percentages and insists on recording these decisions to
protect its infrastructure, it will need to depend on accurate site plan review
of the percentages requested in the future.
Cell Aggregation
Table 1 is a design specification
for a single project area, or cell, in the Shelter Division of our Built Domain.
Cells aggregate to form an urban anatomy we call cities in a Built Domain we
have failed to recognize as a parasite. The challenge is to measure and design
every existing and proposed cell in this domain using forecast models to
conserve land and encourage economic stability with the same intensity that we
devote to weather evaluation. The anatomy of the Built Domain has not been born
in symbiotic harmony with the planet. It has grown under mistaken assumptions.
City design with authority is the only remedy available.
Walter M. Hosack: June, 2023
No comments:
Post a Comment