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Tuesday, March 20, 2012

Introduction to Intensity

Architectural recommendations are difficult to defend when there is disagreement, but decisions affect our sustainable future as certainly as sprawl is consuming our source of life. I originally approached this problem with a desire to understand multi-family residential density. I intuitively felt it was an inaccurate measurement, encouraged over-development, and ignored the issue of sprawl. (See “Replacing Density”; “The Limits of Shelter Capacity”; “Improving the Argument for Architecture and City Design”; and “Context, Capacity and Intensity”) I eventually realized that project open space was a significant element in development capacity calculations and intensity evaluation, but an ignored factor in density regulation. It was the lime missing from the sailor’s diet. This meant that open space would remain a remnant of project design for all land use categories until its development capacity implications could be forecast to permit evaluation, consider alternatives, and justify requirement.

My interest in this topic stemmed from my belief that we simply did not understand “intensity”; could not measure its spectrum from under-development to over-development; could not forecast the spectrum; and as a result could not discuss the issue in terms that could lead development to improved results within limits that protected its source of life. My efforts have produced a method of development capacity evaluation and a vocabulary of intensity that I will attempt to briefly explain, since it has the potential to structure research, define conclusions and defend decisions that are presently vulnerable to attack by opinion. 

Shelter falls into three generic building families and each family uses one of three generic parking systems. Tables 1.1, 1.2 and 1.3 identify these families and parking systems. They also identify the design categories that lead to specific intensity forecast models based on the information given. I’ve called these intensity models development capacity forecast and evaluation models because they predict rows of intensity options related to building height alternatives in their planning forecast panels. 

In effect, Tables 1.1, 1.2 and 1.3 represent decision trees that lead to forecast model identification. Values are entered in the design specification template of a model to produce intensity option predictions in its forecast panel. Changing a value changes a forecast. Switching models changes the design premise.  (These tables are presented at the end of this essay to avoid the interruption they would produce here.) 

Residential and non-residential forecast models CG1L and RG1L are attached as examples labeled Tables 2 and 3. They represent two of forty listed in Tables 1.1, 1.2 and 1.3. The full collection predicts results for all generic parking solutions, including no parking. The approach allows all affected parties to focus on a design vocabulary that defines initial intensity options and shapes all future project direction. 

When evaluating intensity options, a user can alter values in the design specification template of a forecast model to compare results in the design category represented.  He or she can change models to compare design premise or, parking category, options. The result is a strategy based on design premise and specification values that have leadership potential and flexibility. 

It should be apparent after a glance at the design specification templates in Tables 2 and 3 that research is required to identify the implications of design specification values, since many will produce unsatisfactory results in the model’s forecast panel. The research, however, will support recommendations and add credibility to the decisions taken.  


Land use and shelter intensity allocation will determine our ability to live and thrive within geographic limits that protect our natural source of life.

Project open space reduces intensity but cannot be ignored, and is included as a conscious entry in all design specification templates.

The planning forecast panels in Tables 2 and 3 predict rows of gross building area options related to building height alternatives when project open space is specified. These capacity options are related to an intensity index INT in the right hand column that takes the form (f.S). The prefix (f) indicates the number of building floors involved. The suffix (S) indicates the percentage of project open space provided within the buildable area. Optional indexes with more detail are discussed in my book. The result is a forecast of intensity options based on an entire set of interactive design specification values.

We need shelter for survival, but total building area must be provided for growing populations within sustainable limits that do not contain excessive intensity. The composition of gross building area, pavement and project open space is shelter. When shelter combines with the movement, open space and life support divisions of our built environment, the composition determines our physical, social, psychological and economic health, safety and welfare.

Exceptional talent will always produce signature buildings that bookmark our progress toward a sustainable future, but design matters because architecture and city design are essential parts of a symbiotic correlation we have called evolution.

Competition produces extinction when correlation is absent. Competition may permit an individual or group to extend its lifespan, but correlation permits the species to survive over time periods beyond comprehension. It not about competition to consume. It's about a correlation of forces that permits continued competition without extinction. This is symbiotic awareness and the correlation of shelter with survival has entered a new dimension of competition where domination is failure.

I have purposely tried to keep this a brief introduction to intensity. For those interested in reading more, there is an extensive collection of free essays on my web site. The 40 forecast models mentioned can be found on a CD attached to my book: Hosack, Walter Martin, Land Development Calculations v.2, The McGraw-Hill Book Companies, 2009.


Table 2 Development Capacity Forecast Model CG1L


Table 3 Development Capacity Forecast Model RG1L

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