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Tuesday, July 16, 2024

A Letter Regarding Shelter Capacity, Land Use Allocation, Data Science, and Design

 


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