I read your article and noticed your invitation to write. You mentioned quantitative fluency, data visualization, ethical responsibilities, and transdisciplinary interaction with analytics and data science.
I
have something to offer in this regard that concerns the evolution of cities. In
my opinion, plans to shelter the activities of growing populations must be
designed to protect their quality and source of life within
geographic/environmental limits. Our current efforts are producing parasitic,
suffocating sprawl and blisters of excessive intensity across the face of the
planet. The solution will undoubtedly involve transdisciplinary interaction,
but it cannot begin without the classification system, mathematics, forecast
models, and implication measurements that will constitute the leadership
language of shelter capacity evaluation and leadership.
I am
attaching a brief essay entitled, “Shelter Capacity, Land Use Allocation, Data
Science, and Design” that outlines my approach to shelter capacity evaluation.
Its algorithms, master equations, and forecast models will depend on convincing
data entry values that improve on the intuition and anticipation of talent,
education, and experience. The result will be transferable shelter knowledge
that only measurement, data science, and a transdisciplinary research approach can
provide.
Leadership
away from excessive land consumption for shelter to protect “human good” will
require that we ask, “…whether we can do something and whether we should.” Convincing
arguments will depend on the forecast models of Shelter Capacity Evaluation and
the values provided by data science research from many related physical,
social, psychological, environmental, ecological, and economic disciplines.
Future shelter leadership decisions will depend on the knowledge that all can provide,
and a new shelter science may emerge from this correlated effort.
The
essay I’m attaching briefly mentions the classification system, mathematical
tools, and forecasting models needed to support the research, education and
implementation required to lead both public and private shelter decisions
toward a realistic relationship with the land and seas of the planet. These
tools will depend on the work of transdisciplinary data science to build
credibility for the forecasting values entered and adopted to lead shelter away
from the threat of excessive environmental consumption, contamination, and
ecological destruction.
The
goal is symbiotic survival. We must learn to build the tactical tools and
strategic knowledge required to succeed.
BACKGROUND
I am
an alumna with 5-year Bachelor and 2-year Master of Architecture degrees
granted in 1966 and 1968. The Master of Architecture degree was converted from
a Master of City Design degree after the city design program under Professor
Rudolf Frankel was abandoned.
There
has been a lack of city design knowledge that can lead investment, design, and
construction of shelter away from the sprawl and excessive intensity it often
produces. The correlation of data science with the new classification system, forecast
models, algorithms, and master equations of shelter capacity evaluation can
provide the leadership direction we need to avoid the continuing, excessive
consumption of land that is our source of life.
I
have derived the equations of shelter capacity evaluation and explained their forecast
model application in over 220 essays on my blog at www.wmhosack.blogspot.com. I have also written three books and
one second edition on the subject. They can be found at McGraw-Hill and on
Amazon.com. I published an earlier version of these forecast models on a CD with
McGraw-Hill. It was too often copied and is now outdated by the equations I
have derived and documented.
I
would like to offer these forecast models on a subscription basis. The
leadership values entered, however, will only be as good as the knowledge
transdisciplinary data science research and visualization can provide over
time. The common language, comparative potential, and research opportunity
represented by the equations and forecast models of Shelter Capacity Evaluation
is complete; but I lack the ability to include them in a software subscription
package that can be offered to any interested pubic or private entity
associated with the planning, design, investment, and/or regulation of our
Built Domain. I cannot overstate the potential market, educational
contribution, and leadership potential represented by a transdisciplinary approach
to shelter capacity evaluation. We must learn to shelter the activities of
growing populations in limited environmental areas designed to protect both our
quality and source of life.
I
hope you have the time to read the brief essay I’ve attached.
SHELTER
CAPACITY, LAND USE ALLOCATION, DATA SCIENCE and DESIGN
The entire spectrum of shelter capacity options for a
given land area has not been mathematically predictable in a reasonable and
affordable amount of time. This has produced estimation, annexation, sprawl,
excessive intensity, unending argument, and unrestricted consumption of
agriculture and our Natural Domain. The
growth of shelter capacity demand for our increasing activity, however, will
force us to more efficiently allocate the capacity of land to shelter activity
within geographic limits designed to protect our quality and environmental
source of life.
At the present time, shelter capacity evaluation is a
function of experience and estimation based on a property survey that defines
the area available, not the area required for the project intended. At this
point the argument over shelter capacity begins using the terms “density” or
“floor area ratio”. (My previous essays have explained why these terms define
results but do not correlate the design specification topics, values, and
decisions required to consistently lead the shelter design process toward
desired options.) The ensuing uncertainty surrounding these poorly defined
objectives has often produced sprawl and excessive intensity that continues to
consume the face of our Natural Domain and the Agricultural Phylum of our Built
Domain.
Data science will be unable to meaningfully address the
relationship of population growth and its need to shelter expanding activity with
the limited land and resources available until it can correlate the shelter
capacity of land with its social and economic implications in a reasonable
amount of time. Its promise and the equations of shelter capacity evaluation can
make this possible, however.
We have been unable to measure physical intensity and
unable to accurately predict the shelter capacity of land for any land use
activity until now. This has prevented us from correlating the relationship of
shelter capacity to activity, intensity, revenue, investment, and quality of
life on buildable land within limited urban areas.
LAND USE ALLOCATION
A city’s investment portfolio begins with the taxable
land within its boundaries. The allocation of shelter capacity, intensity, and
activity on every parcel determines its average economic productivity per acre and
the quality of life this combination can afford. These are the relationships we
have been unable to consistently and successfully map, predict, correlate, and
monitor within a city’s corporate limits because we have been unable to
accurately measure or predict shelter capacity, intensity, activity, and
economic productivity options on a given parcel or parcels for six fundamental
building design categories. The fallback result has been unlimited annexation
attempting to reconcile economic imbalances and quality of life deficiencies with
increasing consumption of agriculture and its source of life, the Natural
Domain. We will continue to pursue annexation that produces inadequate revenue
to equal increasing expense over time until we can accurately calculate,
correlate, monitor, and lead the shelter capacity, intensity and activity relationships
that determine our financial stability and quality of life.
Shelter capacity is the sq. ft. of gross building area
present or planned per buildable acre assigned to the project. Shelter capacity
divided by 43,560 times the impervious cover percentage present per buildable
acre is a measure of the physical intensity introduced. Shelter capacity forecast
models can measure and/or predict the gross building area alternatives
associated with any given land area, building design category, and values
entered in its design specification module. The result is a series of gross
square foot options related to a list of building height alternatives entered
in the forecast model. These options are converted to shelter capacity,
intensity, intrusion, and physical dominance measurements with implication equations.
Like the first blood pressure readings, only research can indicate the quality
of life implied by the conditions measured or proposed; and only more accurate measurement
can lead our cities in the right direction.
DATA SCIENCE
At this point data science must enter the picture. Gross
building area is a physical measurement that has many social, economic, and
engineering implications. For example, construction cost per sq. ft. is a
relatively common multiplier that is correlated with the scope of occupant
activity present or proposed to determine an estimated budget. Profit potential
per sq. ft. of leased or rented space for activity is another rather common
rule of thumb in the commercial real estate industry. The average municipal
revenue produced per sq. ft. of activity category located within a city is
relatively, if not completely, unknown. This makes the allocation and
correlation of shelter capacity, intensity, activity, intrusion, and dominance plans
or predictions with its revenue potential an economic development guessing
game.
The ultimate objective is to correlate the anticipated revenue
and investment yield per square foot of activity with the quantity of activity
that should be allocated per buildable acre of land within established city
limits to ensure an adequate average revenue yield per total taxable municipal
acre. The underlying objective is to ensure that these square foot quantities do
not compromise a project’s quality of life and that of the surrounding area
with excessive physical intensity, intrusion, and dominance. At this point we
will be able to correlate social and economic stability with the three-dimensional
shelter compositions that emerge to shelter our quality and source of life
within environmental limits. (I have defined measurable “intrusion” and
“dominance” in many of my previous essays.)
CORRELATION
There are now two worlds on a single planet. Continuing growth
of the Built Domain is still a relatively unrecognized carcinogenic threat to our
source of life, the Natural Domain; even though sprawl appears to be recognized
as undesirable. The threat continues because the shelter capacity of land, the
options available, and the geographic limits of a sustainable Built Domain are
all matters of opinion and leadership disagreement. The only way to debate
opinion is with research, measurement, prediction, and successful decisions. Shelter
capacity evaluation makes physical measurement of capacity, intensity,
intrusion, and dominance implications feasible.
Data science can make measurement of average activity
revenue per square foot of gross building area a new chapter of economic
knowledge. These physical and economic measurements can be correlated with
their intensity, intrusion, and dominance implications to make quality of life
within geographic limits a measurable topic of environmental research and
economic stability.
IMPLICATIONS
In the past, many assumed that the supply of land for the
Built Domain was unlimited. The perception of many has changed, however; and this
has led some to recognize that land consumption is subject to the planet’s unwritten
Law of Limits. We will continue to challenge these limits until we can more
accurately and consistently predict the shelter demands of growing population
activity; and correlate these demands with limited geographic areas, building
design categories, and shelter capacity options that can be mathematically
correlated to protect our quality and source of life. It is a tall order, but
data science that cannot predict the shelter capacity of land to accommodate
data demand without sprawl and excessive physical intensity will continue to
assume that this is a world without end.
OBSERVATIONS
Gross building area per buildable acre may be occupied by
any activity in conformance with local planning and building regulations. The
compatibility and appearance of activity within a city has been our
preoccupation, but the scope and taxable value of activity per buildable acre determines
its physical, social, and economic contribution to a city’s quality of life. A
simple comparison can illustrate my point.
First, divide a city’s entire annual expense by the
taxable acres within its boundaries. This reveals the city’s current cost per
acre to operate, maintain, improve, and serve its debt. Second, divide the
total revenue a city receives from any single-family residential lot by the lot
area in acres. (Do not include the revenue the lot delivers to its school
system, library, county, and so on.) Finally, compare the two results to see if
the residential lot produces more or less than the city’s total expense per
acre. This exercise can be conducted for any activity and every parcel in a
city to determine the average economic productivity of its land area. The
correlation of Shelter Capacity Evaluation and Data Science can introduce this
ability to monitor economic productivity and its impact on a city’s quality of
life. The correlation can become the foundation for future city design within
environmental limits defined to protect our quality and source of life.
CONCLUSION
In my opinion, we must eventually eliminate our
dependence on annexation and continued consumption of agriculture and the
Natural Domain. Annexation has been a Ponzi scheme demanding new money to cover
increasing costs at the expense of our source of life. When in place, the
correlation of shelter capacity evaluation and data science will enable us to
monitor and correlate a city’s financial performance with the physical presence
and social quality of life it delivers.
Walter
M. Hosack: July 16, 2024
No comments:
Post a Comment