Shaping Urban Pattern, Form, and Space for Shelter Capacity and Economic Stability within Limited Geographic Areas

 Urban Pattern, Form, and Space -- Learning to Live Within Limits

I’ve mentioned in some previous essays that I believe our goal must be to shelter growing populations within limited geographic areas that contain economically correlated urban design compositions of shelter capacity, intensity, and occupant activity. In my opinion, it is the only way we can avoid random, sprawling, and excessive consumption of agriculture and the Natural Domain. We cannot do this until we can mathematically measure, predict, evaluate, and lead shelter capacity, intensity, and physical context for activity toward economic stability within these limits.

This is why I have pursued the mathematical language of shelter capacity evaluation and have discussed its evolution in 260+ essays on my blog at www.wmhosack.blogspot.com. The more recent have also been published on LinkedIn. The effort has been summarized in my book, The Equations of Urban Design, that is available on Amazon.com. I regret the title, which should have been “Shelter Capacity Evaluation”, since the book is not about the algorithms and equations embedded in shelter capacity forecast models. It is about a template format and design specification topics related to six building design categories that enable the consistent definition, evaluation, and prediction needed for shelter knowledge accumulation and leadership direction.

We will continue to struggle with sprawl and excessive intensity until we can quickly and efficiently calculate shelter capacity options and their implications based on improved information sharing, data science, mapping evaluation, and mathematical correlation of shelter capacity, intensity, and activity options with their economic implications. The result can be correlated decisions in a language capable of consistently leading our design efforts toward the physical pattern, form, and spatial solutions required for financial stability and quality of life within sustainable geographic limits.

Shelter density is an attempt to define a cake with a partial recipe of unmixed, uncorrelated ingredients. Is it any wonder that the result often fails to satisfy? Table 1 is my initial attempt to illustrate the correlation required for consistent leadership success. It illustrates a language and format of correlated mathematical expression that can help us measure existing conditions, evaluate shelter options, build knowledge, and pursue leadership direction in terms that can produce consistent success.

TABLE 1

Table 1 applies to the G1.R3 Residential Activity Group.* All zoning ordinances contain some of the shaded cell topics in the Land and Pavement Modules of Table 1, but I doubt that most if not all of the ordinances contain the entire list; and I doubt that those included are mathematically correlated to expose their combined implications and/or contradictions.

*G1.R3 refers to the residential apartment activity group (R3) when served by surface parking around, but not under, the building(s) on the same premises (G1).

The shaded topics in all three modules of Table 1 are interrelated and mathematically correlated to either measure or predict the implications presented in its Planning Forecast Panel and Implications Module. A simple density limit has been entered into cell F4 and the number of dwelling units it represents has been calculated in cell F5. This entry and calculation do not determine the specification values entered in the template’s remaining shaded boxes, however. This is the point. Any set of values can be entered in the remaining shaded boxes. The embedded template equations calculate the planning and implication results that will respect the density limit given, even though some results will be far less desirable than others, some will be unbearable, and some will be impossible. In other words, density does not lead to design specification decisions, but it can lead to some very undesirable results.

A brief glance at the shaded boxes in Table 1 should indicate the number of variable design decisions involved. Results calculated in the table’s planning and implication modules will change whenever one or more of the shaded values in its Land and Pavement Modules are modified, but are all options desirable? For instance, lower open space quantities in cells A45-A53 produce larger gross building areas and greater potential return in cells B45-B53, but are lower unpaved open space areas desirable? I could ask the same question about any number of the shaded cell values entered, since any value or combination of values would produce different results.

I don’t believe that arbitrary results have ever been the objective. They happen because the equations of urban design have not been derived to predict shelter capacity options and implications that can lead to evaluation and establish parameters that define a healthy, contained urban anatomy. One that is not a parasitic threat to its host. The fact that they now exist does not mean that the effort is over. It has just begun. The Planning and Implication Modules in Table 1 have been provided to assist the effort and are included for every building design category and activity group in The Equations of Urban Design.

At this time, we can calculate the planning and implication results produced by templates of design specification values for classified building design categories like the one presented in Table 1. I have mentioned in other essays, however, that looking at Table 1 results is like looking at the first blood pressure readings. The reader will have no grasp of the health indicated or the parameters needed. (The impossible results are shown in parentheses.) New research is required. The result can be a language capable of consistently leading our design efforts toward the physical pattern, form, and spatial solutions required for financial stability and quality of life within sustainable geographic limits.

Walter M. Hosack, November 2025