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Thursday, January 25, 2024

Refining the Definition of Density - The Decisions That Determine Density Impact

 I was asked what it would take to build 9 single-family detached residential homes with no further information. I created the forecast model included as Table 1 to explain the information needed to answer the question. It begins with a land area specification in shaded cell F4, since an answer cannot begin without a land area or average gross home area specification.

Normally, a user is expected to enter design specification values in the shaded cells of a forecast model. The values are correlated by an algorithm and processed by a master equation to produce the predictions calculated in its Planning Forecast Panel and Implications Module. A value change in one or more of these shaded cells produces new predictions and implications for evaluation.

In this example I’m filling in the information as a demonstration of shelter capacity evaluation. I entered one total acre in cell F4 and realized that this might have general educational value regarding the term “density”.

The values requested in cells F5-F7 and F9 of the Lot Module in Table 1 are used with subtraction to define the buildable land area in cell F11. It is a critical point, in my opinion, because density calculations based on gross or net land area can give a false, and lower, impression of the density being considered when the land area used for the calculation includes unbuildable area. We live in the density and intensity created on buildable land. The rest is simply a view. It should not be used to distort measurement of the quality of life created on habitable buildable land area.

I entered zero in cells F5-F7 and cell F9 to make the template as generic as possible. I entered 70% in cell F12 because I was told years ago that designers often assume 30% impervious cover as their storm sewer capacity design standard. It may, or may not be accurate, but the 30% value calculated in cell F13 from the value entered in cell F12 is based on this assumption. It could be easily changed to reflect other values if desired.

I entered random values in the Pavement and Building Modules of Table 1 to clarify the type of values expected, except for cell F33. The value entered reflects the inquiry I received. Since the buildable land area in cell F11 remains one acre in cell F11, the dwelling unit quantity requested now represents a density of 9 dwelling units per buildable acre.

The values calculated in the Planning Forecast Panel reflect the implications of the requested density when correlated with the other design specification values entered in the Lot, Pavement, and Building Modules.

The average footprint area (FTP) found in Col. B of the Planning Forecast Panel reflects the implications of the requested density when correlated with the design specifications entered. It does not change with floor quantity because it is the land remaining after all other two-dimensional site plan demands are subtracted. These calculations show that the average footprint remaining is smaller than the garage calculated in cell F27.

The values in cells F28 and F29 were entered to show that it is possible to add bonus dwelling area (BON) over the garage. When this is considered, the additional areas appear in Column C of the Planning Forecast Panel.

Floor quantity (f) is multiplied by footprint area (FTP) and combined with bonus area (BON) to arrive at the total home areas (HOME) calculated in Col. D of the Planning Forecast Panel.

Garage area in cell F27 and accessory building area in cell F31 is added to the home area calculated to arrive at the total building areas (TBA) presented in Col. E of the Planning Forecast Panel. The related total building area percentages of buildable land area are calculated in Col. F.

Gross, net, and buildable land area densities are calculated in Col. G of the Planning Forecast Panel. In my opinion, density is a social measurement that conveys little information about the physical design decisions it is used to represent. These are the decisions that must be correlated before leadership direction can hope to produce what it promises.

The Implications Module introduces physical design measurements based on the correlation of design specification values entered in the template. Shelter capacity (SFAC) in Col. D is found by first multiplying density per buildable area (dBAC) by the total building area values (TBA) found in Col. E of the Planning Forecast Panel. The result is divided by the buildable land area involved in acres to find the shelter capacity involved. This conversion makes all shelter projects measureable and comparable.

When shelter capacity is divided by 43,560 sq. ft. and multiplied by the impervious cover percentage calculated in cell F13, the result is a comparable measure of intensity (INT) that increases with floor quantity as shown in Col. E of the Implications Module.

Intrusion is measured in Col. F of the Implications Module by dividing 5 into the floor quantity under consideration.

The sum of shelter capacity, intensity, and intrusion produces the physical dominance measurements calculated in Col. G of the Implications Module. All of these measurements are based on the shelter capacity (SFAC) values found in Col. D of the Implications Module and are meant to be comparable among any and all shelter design projects and urban design areas.

The Implications Module calculates the correlated impact of any chosen set of design specifications entered in the Design Specification Template of a building design category forecast model. Density is produced by these specifications. It does not lead them and is not comparable unless accompanied by the design specifications involved. In other words, the Implications Module produces the measurements needed to begin assessing and comparing the results produced by design specification decisions. These are the physical design decisions that establish a foundation for the shelter spaces, places, massing, composition, and appearance that is built upon them by all ensuing design decisions.

I could change any one or more of the design specification values entered in the shaded cells of Table 1, except for the values entered in cells F4 and F33, to arrive at a different set of results and implications without changing the density calculated.

The greatest temptation facing a designer confronted with an inadequate footprint calculation (FTP) would be to reduce the unpaved open space percentage specified in cell F12. This would increase the remaining footprint area calculated in cells B41-B49. It would also increase the intensity measurements calculated in Col. E of the Implications Module - as well as all others in the module. When present or proposed storm sewer capacity is unknown, however, this decision to increase the impervious cover percentage could compromise the available storm sewer capacity. Every plat and project approved by a city, and every variance it grants for building cover and pavement expansion without this impervious cover information runs the risk of adding to a storm water burden that can result in flooding until corrected.

Any number of value changes could be made in the shaded cells of Table 1 that would influence the results calculated in its Planning and Implication Modules. I’m not here to render judgement. I am simply attempting to explain how more rational, fundamental, correlated shelter design decisions can be measured, evaluated, and chosen to lead our pursuit of shelter for all our activities within a Built Domain that must be geographically limited to protect its source of life. We cannot do this with the tools we presently use. They have produced annexation, sprawl, excessive intensity, and a few random success stories in pursuit of mindless growth. It will continue as long as we remain unable to lead shelter capacity for the activities of growing populations within geographic limits drawn to protect their quality and source of life.

Walter M. Hosack: January, 2024



Wednesday, January 10, 2024

Measuring, Evaluating, and Predicting the Shelter Capacity and Economic Potential of Land

 The text referenced by the attached Table of Contents explains the classification concepts and mathematical tools needed to improve the analytical abilities of all public and private sector interests attempting to evaluate, regulate, or predict the development capacity of land and its revenue potential. Development capacity in this context means the gross building area that can be accommodated by a given buildable land area. It is a function of the design specification values and floor quantity options entered in a forecast model related to a given building design category.

When gross building area is divided by the buildable acres occupied, the result is the shelter capacity per acre produced by the design category and specification values chosen. This shelter capacity value makes the development capacity results produced by any set of design specification values comparable. Shelter capacity also has intensity, intrusion, and dominance implications that can be measured, compared, and related to their impact on the surrounding area when shelter capacity can be predicted or measured.

The combination of capacity and intensity measurement combines with activity revenue per sq. foot of gross building area capacity to indicate a project’s contribution to a city’s total average cost per acre to operate, maintain, and improve its benefit to the community. A project may provide more or less than the municipal average required, but the objective is not to target individual contributions. It is to determine the scope of total future contributions needed to improve the city average produced per year. This will take a combined public / private effort that cannot be pursued without a common set of comparable analytical tools. These are listed in the Table of Contents I’m attaching.

The tools are only as good as the specification values used by a building design category master equation. These values require research, measurement, and knowledge formation since they currently depend on individual experience and opinion for selection.

The Table of Contents I’m attaching lists the forecast models I’ve mentioned. They offer the opportunity to improve our leadership ability with the measurement, evaluation, and knowledge formation they enable.

Walter M. Hosack: January, 2024






Saturday, January 6, 2024

City Design for Economic Stability

 There are several prerequisites I need to cover before I get to the title of this essay.

In general, gross building area may be occupied by any activity. It is a product of design specification values and floor quantity choices that combine to produce degrees of shelter capacity per buildable acre occupied.

Shelter capacity (SFAC) is gross building area (GBA) per buildable acre (BAC) of land (SFAC = GBA/BAC). The revenue potential of land is a function of its location, shelter capacity and occupant activity. The sq. ft. of shelter capacity per buildable acre multiplied by the revenue potential of occupant activity per sq. ft. determines the revenue potential of the gross building area and buildable acres occupied.

Shelter capacity quantities produce degrees of intensity. These degrees are equal to shelter capacity times the impervious cover percentage present divided by 10,000. (INT = SFAC*IMP% / 10,000)

The acres allocated to various land use activities are determined by a city’s master plan and zoning plan, but they have not been correlated with the shelter capacity, intensity, and activity options that determine the revenue potential of these acres. This has made economic planning a guessing game. This brief explanation should reveal how little we know about city design for the economic self-sufficiency of cities across the acres that represent its investment portfolio.

We have not been able to mathematically predict the gross building area potential of buildable land area under any given set of design specifications. This has meant that we have not been able to consistently and accurately predict the shelter capacity of a land use allocation plan. It is a critical point, because the intensity of activity placed on a buildable acre of land determines its revenue potential, but excessive intensity can produce misery. Inadequate attention to the relationship of shelter capacity to intensity and activity produces annexation and sprawl attempting to solve an immediate budget deficit. There is no way to resolve this guessing game without improved knowledge and forecasting ability.

I have shown in my essays and books that we can mathematically predict gross building area, shelter capacity, and intensity options for a given buildable land area based on a given building design category and value options entered in the category’s design specification template. This is only a one piece of the puzzle however.

We do not know the average revenue potential per sq. ft. of various occupant activities. A building can be occupied by any activity, but we are not presently able to correlate shelter capacity and intensity with the revenue potential of various activities to produce a desired revenue stream from the square feet and acres occupied.

The lack of shelter capacity forecasting ability and revenue knowledge per sq. ft. of occupant activity means that a city cannot correlate its two-dimensional land use allocation plan with its three-dimensional revenue potential. Annexation and excessive intensity will continue their search for new revenue to solve immediate budget deficits until our mathematical measurement, evaluation, and prediction of revenue potential per acre of shelter capacity and activity allocation makes it possible to predict longer term solutions.

TABLE 1

I’d like to begin explaining myself by introducing Table 1. It applies to all buildings served by a grade parking lot around but not under the structure on the same premise when gross land area is given. The building design category is referred to as G1. The Design Specification Template in this table itemizes the topics whose quantities are used to produce shelter capacity and intensity predictions.

Land Module

The measurements entered in the gray cells of Column G in Table 1 are those of the project entitled Bradenton Office. They are the traditional square foot measurements of architecture. Subtraction is used to define a new area I’ve referred to as “shelter area remaining” in cell G17 of the table. It is composed of impervious cover in cell G19 and unpaved open space in cell G20. The amount of impervious cover available in G19 is found by subtracting the amount of unpaved open space in cell G11 from the buildable land area available in cell G10. It also represents the storm sewer runoff capacity required. The corresponding percentages in Column F track the quantity allocations measured in Column G.

Core Module

The objective of the seven gray boxes in cells G23-G29 in Table 1 is to identify all miscellaneous pavements that reduce the impervious cover remaining for parking lot and building footprint area. The sum of these miscellaneous impervious areas is located in cell G30. It is subtracted from the impervious area available in cell G19 to find the impervious area remaining in cell G33. This is the core area (CORE) that is available for surface parking and building footprint area. This definition makes the creation of master equations for the prediction of gross building area options within a defined core area feasible. Table 2 will explain this in more detail.

Two-hundred and sixty parking spaces were provided in the Bradenton site plan for an average of 420.5 square feet per space as calculated in cell A35. The parking space quantity provided was equal to a provision of one space for every 250 gross square feet of building area. This is calculated in cell A36. The floor quantity involved was noted as 3 in cell A46.

Planning Forecast Panel

The Bradenton footprint consumed 21,667 square feet of its core area as noted in cell C46. The three floors noted in cell A46 transformed the footprint into 65,000 square feet of gross building area as noted in cell B46. The remaining 109,330 square feet of core area was used for the parking lot measured in cell D46.

The 65,000 sq. ft. gross building area noted is a generalized measurement referred to as building mass. Mass is equal to floor plan area times floor quantity when floor plan area is defined by a simplified building perimeter that ignores architectural enhancement. The result is an indication of building volume, or mass, that encloses all detail and combines with pavement to form impervious cover. It is offset by the unpaved open space quantity provided in cell F11.

Implications Module

The implications of the massing and impervious cover just measured are calculated by the equations in cells F43–J43 of the Implications Module. The first of these equations explains that the specification values entered in the gray cells of Table 1 combine to produce 12,428 square feet of shelter area per buildable acre. This is referred to as shelter capacity. The second explains that the shelter capacity calculated represents an intensity of 0.752 in cell G46. The third explains that the 3 story height produces an intrusion value of 0.6, and the fourth explains that the sum of intensity and intrusion produces a dominance value of 1.352. This is the point where evaluation can begin based on objective classification, measurement, and comparison of the place created.

The project I chose for this example is located on a street with low pedestrian and vehicular volumes. If the volumes were greater, the intensity of 0.752 could have been multiplied by a factor greater than 1 for each mode and level of adjacent traffic. In fact, the basic intensity value could be multiplied by a number of related factors such as sound pressure level and air quality to refine the sophistication of the measurement.

I do not intend to offer an evaluation of the measurements presented in Table 1. My objective is to demonstrate that it is possible to classify and consistently measure the places we create for evaluation, knowledge accumulation, and consistent leadership definition. Conclusions will always remain in the realm of opinion. The challenge is to give these opinions greater credibility with the method of knowledge formation employed.

Economic Implications

We will continue to blindly pursue annexation and isolated economic development projects in an attempt to plug annual budget shortfalls until we understand the revenue implications of shelter capacity, intensity, and activity combinations on every parcel within the boundaries of our master and zoning plans. Until this time, both annexation and economic development will continue to have short term frames of reference that cannot measure their comprehensive contribution to a city’s long term economic stability.

If I knew the total real estate, income, and miscellaneous tax revenue from Bradenton’s 65,000 sq. feet of gross building area I’d be able to make a more compelling presentation regarding its contribution to its city’s long term economic stability. As it is, I can only present the opportunity since the data and knowledge required is scattered in several independent silos that frustrate correlated city design evaluation.

If total Bradenton revenue were known, it could be divided by its gross building area to determine its revenue yield per sq. ft. This is the first piece of the puzzle. The shelter capacity of the Bradenton project has been calculated in cell F46 of Table 1 as 12,428 sq. ft. per buildable acre. If this shelter capacity were multiplied by Bradenton’s activity revenue potential per square foot, the product would indicate the project’s revenue per buildable acre. This is the second piece of the puzzle. It is interesting but becomes significant when compared to a city’s total average revenue yield per buildable acre.

The puzzle involves a simple question. Does the Bradenton revenue yield per buildable acre provide more or less that the city’s average annual cost per buildable acre to operate, maintain, and improve the city for all of its residents? The question’s objective is not to target the performance of a single project, however. Individual performance can be confidential information that is aggregated by block, tract, zoning district, and so on to answer the same question.

The objective is to produce a picture of a city’s financial performance that can be adjusted to produce an average revenue yield per acre equal to a city’s average cost per acre. This does not mean that all activity must yield a revenue surplus. It means that the surplus and deficits must combine to produce the average revenue required. It all depends on how a city allocates it land use activity, shelter capacity, and physical intensity to produce yield in the form of revenue. At this point, a farmer knows more about his land than a city.

TABLE 2

Table 1 presented the capacity and intensity implications of one set of project measurements related to a given land area and three story building. Table 2 uses the same given land area, but illustrates the options that can be predicted when percentage values replace the square foot measurements entered in the gray cells of Table 1. Percentages equal to the areas presented are entered in the gray cells of Col. F in Table 2. Their square foot implications are forecast in Col. G and can be compared to Table 1.

The master equation entered in cell B39 of Table 2 applies to Building Design Category G1 and has been added to predict gross building area options for the floor quantity options entered in cells A44-A53. The ability to accurately predict gross building area options in cells B44-B53 will become increasingly important as we attempt to coordinate shelter capacity with intensity, activity, location, and economic potential in geographic areas that are limited to protect our source of life.

The existing Bradenton Office project is classified by the data on line 46 of Table 2, but the table illustrates that an unlimited number of shelter capacity options were available during the Bradenton planning stage. Floor quantity choices are only one example of the options that were available. In addition, the gross building area calculations change whenever one or more of the gray cell specification values is modified. Rapid calculation of these options will become increasingly helpful as we attempt to balance shelter demand for activity with the quality of life produced by increasing intensity and economic potential per buildable acre. These are the strategic decisions that will be required to avoid a continuation of sprawl and its promiscuous consumption of land in both the Built and Natural Domains. Tables 3 and 4 have been created to illustrate how these options can be created with a few keystrokes.

TABLE 3

I haven’t changed the land area under consideration in Table 3 in order to facilitate comparison with Tables 1 and 2, but have adjusted three primary points of discussion. The amount of unpaved open space planned in cell F11 has been reduced to 25%. The amount of parking lot area per space has been reduced to 400 sq. ft. in cell A35 (This means that little landscape area and minimum parking lot dimensions will be provided within the parking lot perimeter.), and the parking requirement in cell A36 has been reduced to one space for every 300 square feet of gross building area. The result is an increase in gross building area potential from 65,000 square feet to 97,435 square feet and an increase in shelter capacity from 12,428 square feet to 18,630 square feet per acre when the same floor quantity is considered. Given the same activity and revenue potential per sq. ft., this increase in gross building area represents an obvious increase in economic potential per buildable acre and per square foot of gross building area. Intensity increases from 0.752 to 1.397, however; and dominance increases from 1.044 to 1.997.

I don’t mean to imply that the intensity increase above is desirable. I am simply trying to illustrate the efficiency of evaluation that can be produced with a standard classification and measurement system for the Shelter Division of our Built Domain. At this point, we only recognize excessive intensity when we see it. Now that we can measure its presence, however, we may gain the knowledge needed to define the condition. If the previous intensities are considered too great, for instance, Table 4 can be produced to adjust these parameters with a few keystrokes.

TABLE 4

The open space value in cell F11 has been revised to 50% in Table 4. The parking specifications in cells A35 and A36 have been changed from Table 3 to equal those used in Tables 1 and 2. These changes reduce the 3 story gross building area to 53,719 sq. ft. in cell A46 of Table 4. The Planning Forecast Panel in Table 4 also shows that increasing the floor quantity to 10 in cell A53 cannot return gross building area potential to its Table 2 quantity of 65,000 sq. ft. when the unpaved open space percentage is increased from 39.5% to 50%. The trade-off involved should be obvious.

The intensity calculated in cell G53 for the 10 story building is less than that calculated for the 3 story building in Table 1 because 50% unpaved open space has been provided, but the intrusion and dominance calculated in cells H53 and T53 are much greater because of the increased floor quantity.

This example attempts to show the trade-offs involved when shelter capacity, activity, and intensity measurement become coordinated elements of design evaluation. The introduction of three-dimensional evaluation across all buildable acres of a city can make the shelter capacity evaluation associated with city design an essential contribution to city planning strategy, financial security, and leadership direction.

CITY DESIGN

Tables 1-4 addressed a 5.23 acre project with optional values entered in a single building design category template that included a design specification template, core module, planning forecast panel, and implications module. The tables illustrated the ability to forecast gross building area options that had shelter capacity, intensity, intrusion, and dominance implications. The text also emphasized that the ability to accurately and consistently predict gross building area options enabled predictions for many additional topics that were a function of these gross building area options, and the revenue potential of these options was emphasized.

The message is not limited to single project design however. The correlation of shelter capacity, intensity, activity, and location throughout a city will determine its social and economic stability. A two-dimensional land use plan supplemented with a zoning ordinance does not have the scope required.

The term for this city-wide three-dimensional effort to correlate shelter capacity, intensity, activity, and location within geographic limits defined to protect our quality and source of life is city design. A portion of its language has been illustrated by Tables 1-4. Smaller scale design efforts are referred to as urban design. The titles are not significant however. The common specification language in Tables 1-4 is the message, since it permits consistent measurement, evaluation, and leadership definition that can repeat success and avoid failure when research builds the specification knowledge required.

Tables 1-4 address one building design category. Six are used to shelter most activity on the planet. The correlation of these six building design categories and their specifications across all municipal land is city design. It produces the three-dimensional physical presence we have referred to as urban form, composition, texture, pattern, and so on; but these results have been arbitrary because specification knowledge has been an incomplete and uncorrelated contribution to a consistent leadership language. In my opinion, it has produced more sprawl and excessive intensity that design success and economic stability.

The design specification topics in Tables 1-4 represent a consistent vocabulary for the G1 Building Design Category. The five remaining categories use the same template format but expand on the topics involved. Together, these topics itemize the value decisions that lead physical design toward the visible results that symbolize the decisions made.

POSTSCRIPT

There are 17 gray cell decisions and 10 floor quantity choices in Tables 2-4. They have been mathematically correlated to produce the gross building area, shelter capacity, and intensity options presented. A change to one or more of these topic values will produce a new forecast. This should indicate the complexity of the design relationships involved and the integrated correlation required to provide informed leadership direction within a limited Built Domain that must learn to respect what is not property but its source of life.

Walter M. Hosack: January, 2024