Executive Summary

The TALUS-LEAM project, which involves modeling and analysis of future land-use change and the transportation infrastructure in the Traverse City region, was put in place to:

  • Meet the requirements of the Transportation and Community and System Preservation Pilot (TCSP) Program for the Traverse City region
  • Promote regional dialogue on land-use and planning
  • Create partnerships among governmental and non-governmental entities.

TALUS-LEAM uses the basic version of LEAM based on a limited set of drivers for which national data are readily available. Data required for populating and calibrating the model were fi rst compiled and cleaned up. Using these data, preliminary simulations of land-use change in the region were prepared and then critiqued by a group of local planners. This critique provided a sound basis for developing enhancements to the basic model that were then presented in two public workshops attended by over 80 people. These workshops were an opportunity to both inform the public about the work being carried out and also gather local knowledge about the region. Finally, as a demonstration of the ability to link land-use and transportation models, results from a LEAM simulation were processed into input fi les for Michigan Department of Transportation models for the Traverse City region.

TALUS-LEAM simulations of land-use change suggest that the region will tend to grow primarily towards the south and the west of Traverse City. There is also significant growth potential along the access routes into the region from the east and the south. If more growth occurs than is expected, then additional residential growth occurs in the western part of the region and additional commercial growth occurs in the eastern region. Review of these simulations in public workshops stimulated intense discussions on the future of the region and pointed to the need to more eff ectively capture the impact of the region's transportation corridors on land-use change. Thus, the TALUS-LEAM project has demonstrated the feasibility and value of modeling diff erent future consequences of the interactions among land-use, transportation, and other factors in the Traverse City region. The value is not in describing a single future that can be considered likely as much as describing a set of diff erent futures that is likely to contain within it conditions that will actually unfold in the future. With this set of futures, and the policy and investment decisions associated with each future, citizens and planners in the region can more meaningfully plan for the future of the region.

Introduction

Land-use change has arrived as an issue of national interest. According to the American Institute of Architects, a recent poll indicates that 'livable communities' is an important political issue for 78% of Americans. Communities are beginning to question the impacts that new development will have on their infrastructure, support or services. Patterns of changing land use have been blamed for increases in traffi c congestion and commute times, worsening air and water pollution, loss of farmland and open fi elds, forests and wetland losses, increased flooding, and property tax infl ation. But good solutions are diffi cult to fi nd; the relationships between this diverse set of problems and the policies that aff ect land use change are complex and diffi cult to ascertain. A poor understanding of these relationships and confl icting pressures from constituent groups often place municipal and regional planning entities in a diffi cult position. They must objectively assess de! velopment proposals while addressing constituent concerns, which may or may not be mutually exclusive.

The Traverse City region will not be immune to many of the positive and negative impacts associated with future landuse change. So, the Traverse City Transportation and Land Use Study (TC-TALUS) initiated the TALUS-LEAM project to understand the extent to which simulating diff erent future scenarios can help in deliberations about addressing the region's future. TALUS-LEAM uses the basic version of the Land-Use Evolution and impact Assessment Model (LEAM). LEAM is a collaborative computer-based decision support process designed to help local and regional planners and key stakeholders develop an understanding of land-use transformation issues by empirically defi ning the relationships between land-use change and the social, economic and ecological objectives of the community. LEAMbasic uses a limited set of drivers for which data are available nationally, and is eff ective in kicking off the process of integrating modeling in the regional planning process.

LEAM, developed at the University of Illinois with funding from the National Science Foundation, describes land-use changes across a landscape that result from the spatial and dynamic interaction among economic, ecological, and social systems in the region. In the LEAM approach, groups or individuals who have substantive knowledge relating to a particular system develop and test separate models of that system. These contextual sub-models are run simultaneously in each grid cell of raster based GIS maps linked to form the main framework of the dynamic spatial model. Inputs to the model utilize USGS national landcover data sets (at 30x30m resolution), census and economic data (readily available and transportable to multiple sites), along with variables relating to impact assessments sub-models (e.g. habitat, ecoregional inputs, water an energy inputs) to parameterize the model. LEAM produces simulations associated with diff erent policy and investment scenarios maps or movi! es that show the transformation of the subject landscape as a product of policy related inputs. These dynamic visual outputs are critical for testing policy scenarios and raising concerns regarding the impacts of development, environmental degradation, or confl icting land-use policies.

The TALUS-LEAM project has demonstrated the feasibility and value of modeling diff erent future consequences of the interaction between land-use, transportation, and other factors in the Traverse City region. The value is not in describing a single future that can be considered likely as much as describing a set of diff erent futures that is likely to contain within it conditions that will actually unfold in the future. With this set of futures, and the policy and investment decisions associated with each future, citizens and planners in the region can more meaningfully plan for the future of the region.

This report summarizes what the TALUS-LEAM project accomplished. After project objectives are enumerated, the next four sections summarize key accomplishments in project's four main tasks: modeling land-use change, reporting results, facilitating community involvement, and integrating with transportation modeling.

Objectives

The stated objectives of the TC-TALUS LEAM project were described as threefold:

A. To meet the requirements of the Traverse City regional TCSP Program: increase the knowledge base so as to improve the efficiency of the transportation system, reduce environmental impacts of transportation, reduce the need for costly infrastructure investments, ensure efficient access to jobs, services and center of trade, and examine development patterns which achieve these goals.

B. To create partnerships between governmental and non-governmental entities.

C. To promote regional dialogue on land-use and planning requires a combination of software and process technologies. The software component shall be capable of simulating land-use change in the region as a consequence of the interaction among a variety of drivers of change that operate at different scales, from a 30m x 30m parcel of land to the entire region. Drivers of change must be easily and separately reviewed (i.e. presented and manipulated in graphic form rather than as computer code), and must be modular so that individual drivers may be added, replaced, or removed as needed. Software must be capable of simultaneously estimating the social, economic, and environmental impacts of this land-use change. To ensure effective incorporation of the tool in the planning process, a 30- or 40-year simulation must be produced; this will likely involve implementations that run on clusters of computers. The results of a land-use simulation must be visualized i! n a number of dynamic and static, detailed and summary representations capable of being displayed in a Web browser. A Web-based interface that allows users to retrieve and interact with this data is required. The process component will prescribe procedures through which citizens of the region will engage with and be educated by land-use simulations. Through engagement it must be possible to document their insights about the causes and effects of land-use transformation. Through education it must be possible to narrow differences and build consensus about the future of the region.

The TC TALUS-LEAM project involved four separate but related tasks: land-use modeling, reporting model results, transportation modeling integration, community involvement.

TALUS LEAM Modeling

Data

Study Area

The Traverse City Regional LEAMbasic model incorporates input data from Grand Traverse, Leelanau, Benzie, Antrim and Kalkaska counties. A more detailed study area consists of the 9 townships in the TC-TALUS region plus Traverse City.

Data Collection

All data was collected at a 30m x 30m resolution. A presentation of this data was made to the TC TALUS Technical Committee for input and sign-off.

1. Basic Boundary & Feature Data ( Figure 1)

Figure 1 . The TALUS-LEAM Study Area

2. Land Cover Data ( Figure 2)

Figure 2 . TC Regional Land Cover Data

3. Road Network Data ( Figure 3)

Figure 3 . TC Road Networks

4. Non Developable Lands ( Figure 4)

Figure 4 . Non-Developable Lands

5. Historic Population Data ( Figure 5 and Figure 6)

Figure 5 . Historic Population Growth in the Study Area

Figure 6 . Changes in Housing by Census Tract

6. Projections of Population Growth ( Figure 7)

Figure 7 . Regional Demographic Information

7. Digital Elevation Data (Figure 8)

Figure 8 . Digital Elevation Map of the TALUS-LEAM study area.

8. Floodplain Data

Data Sign-off

A data sign-off process that consisted of: presentation, discussion, re-assessment, and revision was undertaken to insure that the data used in TC-TALUS LEAM was complete and accurate in the eyes of the TC-TALUS board. A statement that reflected this understanding was drafted and signed by TC TALUS and LEAMgroup.

TALUS LEAM Model Results

Preliminary TALUS-LEAM Model Results

Preliminary TALUS-LEAM model runs were completed and presented to TC TALUS in October 2004. These output were described as ”Rough-n-Ready” model runs, using available data with minimal verification. They were presented to initiate TALUS discussion and show progress toward a more detailed model. These are considered a useful first step to preliminary models that reveals possible data inconsistencies, inaccuracies.

Preliminary runs

Regional run. A preliminary look at the Talus region was completed in order to display the boundary areas and the breadth of the geography under consideration ( Figure 9).

Figure 9 . A preliminary LEAM run of the 3 county region.

Local run. A more detailed display of the Traverse City area. This was intended to show the depth of the work in progress and the ability of the model to display detailed geographies ( Figure 10).

Figure 10 . A more detailed display of the LEAM preliminary output near the Traverse City area.

These preliminary model runs were updated based on the feedback received. Following the October meetings a more detailed set of model runs were developed.

Final TALUS-LEAM Results

When planning for a region it is imperative to understand three important questions:

Over the next 25 years, changes in land use in the Traverse City area are inevitable. What kinds of changes might occur? Which of these are desirable and which are not desirable? What can we do to promote the desirable and limit the undesirable? These are questions that area residents must confront in order to minimize the possible negative effects of future changes.

TALUS - LEAM seeks to engage the community in preparing for change by considering future land-use development patterns and the causes and consequences of these patterns. Area stakeholders and residents come together in open discussions. Through this process we expect to arrive at a collective sense of what local land-use policies and public investments will most benefit the Traverse City area in the future.

Historic land use change patterns

To get a sense of where we are now, we look at historic growth patterns from 1978 to 1998 along with a detailed look at land-use change from 1990 to 2000 ( Figure 11).

Figure 11 . Historic land use patterns in the TC study region

Baseline Scenario

A TALUS-LEAM baseline scenario ( Figure 12) was constructed to represent future land use projections in the TC study area using a business-as-usual approach to determining the likely number of new housing units that will be needed in the region by the year 2030 (Figure 13).

In the ‘baseline’ scenario, commercial/industrial growth is concentrated near the airport and to the west of Traverse City, with some sporadic commercial growth to the south. Residential growth continues to the south and west, with some hot spots to the southeast.

Figure 12 . TALUS-LEAM Baseline Scenario. Red are new commercial cell locations and yellow are new residential cell locations spatially allocated by the year 2030 using a business-as-usual population projection.

Figure 13 . TALUS-LEAM population projections.

 

Ultra Growth Scenario

A TALUS-LEAM ultra growth scenario ( Figure 14) was constructed to represent future land use projections in the TC study area using an ‘ultra-growth’ (250% higher than business-as-usual) approach to determining the likely number of new housing units that will be needed in the region by the year 2030. While such extreme growth is unrealistic, the results are useful for better visualizing the spatial distribution of potential growth. In the baseline model smaller effects are sometimes difficult to identify; Ultra growth scenarios aid in locating these areas of change.

Another form of visualization is the summary map. A summary map ( Figure 15, Figure 16) displays ‘when’ new cells will develop. Summary maps help TC residents to determine when events are likely to become a communal issue.

In this scenario, large amounts of Commercial/ Industrial growth are developing to the west and east of TC with smaller pockets to the north and a new commercial corridor developing to the south heading east. Residential growth continues to the south and west, with some pockets to the north and east. The southeast also continues to display pockets of development.

Figure 14 . TALUS-LEAM Ultra Growth Scenario. Red are new commercial cell locations and yellow are new residential cell locations spatially allocated by the year 2030 using an ‘ultra-growth’ population projection.

 

Figure 15 . TALUS-LEAM Ultra Growth Scenario Summary. Yellow cells are developments that happen ‘sooner’ in the allocation cycle (2000-2010). Green cells are developments that happen in the allocation cycle (2015-2020). And Blue cells are developments that happen ‘later’ in the allocation cycle (2025-2030).

Figure 16 . TALUS-LEAM Ultra Growth Scenario Summary Detail. Visually describes in more detail the previous ‘Ultra-Growth Summary Map”. Yellow cells are developments that happen ‘sooner’ in the allocation cycle (2000-2010). Green cells are developments that happen in the allocation cycle (2015-2020). And Blue cells are developments that happen ‘later’ in the allocation cycle (2025-2030).

Zoning Scenario

A TALUS-LEAM zoning scenario ( Figure 17) was constructed to represent future land use projections in the TC study area using existing township zoning maps as a guide and a baseline growth rate to determining the likely number of new housing units that will be needed in the region by the year 2030.

A comparison map that describes the differences between the ‘baseline’ and ‘zoning’ scenarios was constructed for residential and commercial uses ( Figure 18, Figure 19). These comparison maps instruct TC residents on the probable differences between scenarios.

Figure 17 . TALUS-LEAM Zoning Scenario. A TALUS-LEAM zoning scenario represents future land use projections in the TC study area using existing township zoning maps as a guide and a ‘baseline-growth’ number of new housing units that will be needed in the region by the year 2030.

Figure 18 . Residential Comparison Map. A comparison map that describes the differences between the ‘baseline’ and ‘zoning’ scenarios for residential growth. Yellow cells represent new growth that is common to the ‘baseline and ‘zoning’ scenarios. Brown cells are unique developments in the ‘zoning’ scenario. Blue cells are unique developments in the ‘baseline’ scenario.

Figure 19 . Commercial Comparison Map. A comparison map that describes the differences between the ‘baseline’ and ‘zoning’ scenarios for commercial growth. Yellow cells represent new growth that is common to the ‘baseline and ‘zoning’ scenarios. Brown cells are unique developments in the ‘zoning’ scenario. Blue cells are unique developments in the ‘baseline’ scenario.

Based on a review of the preliminary LEAM simulations some questions remain. How should we modify the drivers of land use change to better describe future land use in the TC region? What drivers should be added to the model? Should the current set of drivers be altered in some way to better describe the region?

TALUS-LEAM Impacts

Once the simulations are run, it is important to recognize the impacts that the resulting changing land use patterns will have on the environmental, economic and social systems of the community. The assessment of probable impacts is important for understanding the ‘so what does it mean’ part of the simulation process. If things change in this way, what does it mean for society, the economy, and the environment in the region? Are we happy with that outcome? If not, what actions will be necessary to achieve results that are more satisfactory?

These ‘so-what’ impact assessments are important for comparing simulation outcomes and results. For example, TALUS-LEAM simulations show that with high regional growth, an additional 16,000 acres of residential land uses is associated with a 7,000 acre loss of forested land and a 7,000 acre loss of agricultural lands. In the TALUS-LEAM output, changes in land use acreages are preliminary impacts that can be quickly assessed. The following table ( Figure 20) and graph ( Figure 21) describes the land use change results from TALUS-LEAM.

Figure 20 . A table of projected land use changes at three intervals (2010, 2020, and 2030) based on TALUS-LEAM results.

Figure 21 . A graph describing the rapid growth of urban development in the TC area and the related loss in forested lands.

 

Because TALUS-LEAM output is derived annually, time-series information is easily acquired for analysis. In this simple example, the rate of growth is tracked by township (the top 5 are shown) in the TC region based on the TALUS-LEAM ‘baseline’ scenario ( Figure 22).

Figure 22 . The rate of growth in the top 5 townships in the TC region based on the TALUS-LEAM ‘baseline’ scenario.

 

Community Engagement

TALUS-LEAM scenarios were presented in a planning charrette to TC TALUS in December 04. This was intended to educate the committee on the public engagement process to be completed in February 05. Key questions regarding the preliminary runs that were to be explored at the public charrettes:

  • Why is the output wrong?
  • Are the underlying data flawed?
  • Do land-use drivers work differently in this region?
  • What makes this region unique in terms of land-use change?

Charrette Manual

A Charrette manual ( Figure 23 ) was produced to help educate TC TALUS committee members on how the charrette process works and how they might participate in the process at larger public forums. The manual describes the general objectives of the workshop: “In an effective LEAM workshop, local stakeholders identify key drivers of land-use change specific to the region in question, as well as scenarios (changing socio-economic trends, or specific public actions involving policy and investment choices) relevant to the region. More broadly, a LEAM workshop fosters dialog among participants.”

It also includes definitions: “Drivers are forces that cause land-use change to occur in certain areas and not others. “Scenarios are combinations of socio-economic trends and actions—such as a public policy or investment choice—that are of interest because they might result in very different future land-use patterns.” A step-by-step procedural description to help inform the local officials that were to participate in the charrette was also included in the manual (see appendix A).

 

Figure 23 . Charrette Manual. Appendix A

Press Release

A press release was developed and meetings with the press were completed as part of the planning charrette ( Figure 24).

 

Figure 24 . TALUS-LEAM press release.

Public Charrette

A typical LEAM charrette is a four-hour session that opens with an hour of introductory material. This is followed by two hour-long breakout sessions each followed by 20 minutes of synthesis. A 20-minute break is scheduled between the two breakout sessions.

A public charrette was held in February to solicit public input and inform the residents of the TC area about the study and its results. Two events, afternoon and evening, were held to provide easy access for resident participation.

TALUS–LEAM Report

A report characterizing TALUS-LEAM runs and output was produced and given to each participant at the two public charrettes. This documents details substantive issues about LEAM, what LEAM does, and how the process works. It also outlines and explains the results of the TALUS-LEAM output so that they can be clearly understood by a non-technical audience. This report document was distributed to attendees at public outreach sessions along with maps and visual images as part of the public charrettes ( Figure 25). (See appendix B)

Figure 25 . TC Charrette Report Handout. Appendix B

The report, along with a verbal and visual presentation provided the basis for discussion among charrette participants.

Public TALUS-LEAM Presentation

A verbal and visual presentation was constructed for the public charrettes ( Figure 26). The presentation describes the LEAM process and TC TALUS LEAM outcomes and as noted, provided the organization principals for the public meetings. It generally introduced LEAM and the LEAMgroup, how LEAM works, how TALUS-LEAM was developed, TALUS-LEAM outcomes, and outlined tasks for discussion – understanding what drives local change in the region, and what planning scenarios (investments and policies) they would like see analyzed (See Appendix C).

 

Figure 26 . The TALUS-LEAM public presentation. Appendix C

Charrette Results Report

Area stakeholders and residents came together during two workshop sessions conducted in the Garfield Township Building on February 24, 2005, for public review and critique of the TALUS-LEAM project. These workshops were expected to generate ideas about ways in which TALUS-LEAM could be tte r capture the mechanics of land use change in the region and to also delineate scenarios that might be explored using this tool. In essence, these workshops would direct future TALUS-LEAM exercises. The results of the TALUS-LEAM charrettes were described in a report tilted TALUS-LEAM Charrette outcomes ( Figure 27). (See Appendix D).

Figure 27 . TALUS-LEAM Charrette Outcomes. See Appendix D

Identifying drivers of land use change

During each brainstorming session, participants were divided into smaller groups of eight or nine each. Every participant was asked to consider questions such as: “What are the drivers of land use change in the region?” “What causes growth?” “What causes development?” Each group was assigned to document the results of this initial brainstorming exercise.

After an hour of group discussion, list-making and driver selection, one spokesperson reported the results to the entire group of workshop participants. The non-prioritized, complete listing of all land use driving forces generated by the smaller groups is available in the report.

Following the group presentations, each participant was asked to cast his/her allotment of ten “votes” for what s/he considered to be the most important driving forces of land use change in the Traverse City region. By making marks next to the listed drivers on the summary sheets, participants were instructed to not vote more than once on any single driver. A total of 267 votes were cast, and the results were grouped into the following categories:

• Ecological Drivers

• Economic Drivers

• Political Drivers

• Social Drivers

• Structural Drivers

• Transportation Drivers

 

Identifying scenarios of land use change

New groups were formed for the second breakout session, and participants were asked to consider some of the alternative futures they would like to see realized in the region. The discussion focused on the following questions: “What will happen?”; “What could happen?”; and “What would you like to see happen?” Aft e r brainstorming each group ranked their results and reported the most important scenarios to the collective workshop.

Prioritizing the scenarios of land use change. Similar to the “Drivers” session, each participant was given votes (i.e., dots) for voting on the scenarios considered most important among those presented to the entire group. The same five broad categories used to group the driver results are the basis for grouping the scenarios. Considering each item serves as a potential scenario for LEAM development (and even minor variations of a policy/action may need further exploration), consolidation of these items was done with caution. A total of 216 votes were tallied, and selected transportation, regional planning, and development rights & restrictions, and village centers as the most important scenarios to consider.

• Ecological Scenarios

• Economic Scenarios

• Political Scenarios

• Social Scenarios

• Structural Scenarios

• Transportation Scenarios

The public charrettes sought to incorporate a wide variety of opinions from a diverse group of stakeholders about the future of the Traverse City region. The information gathered from the workshop, and analyzed in the report, can serve as the basis for refining and informing the TALUS LEAM project. The TALUS LEAM project, through an iterative process, aims to encourage dialogue in the region by informing residents, stakeholders and government officials of potential land use futures.

The results of this basic version of TALUS - LEAM may serve as one-resource local officials will use to guide future land use changes. Planning and policy choices should reflect the desires of the diverse group of stakeholders involved, as highlighted by the outcomes of the project.

 

Transportation Modeling Integration

Identifying the implications of potential land use change on regional transportation systems is an important component of this work. Toward that end, TALUS-LEAM output data was prepared in a proof-of-concept effort to inform (provide input) to the TC-TALUS regional transportation (TRANSCAD) model.

TALUS-LEAM: Coupling Simulations of
Land-Use Change with Traffic Models

Introduction

Alternative patterns of future land-use change, as simulated using TALUS-LEAM, help stakeholders in the Traverse City region grapple with different and competing public policy and public investment choices. If these alternative future land-use patterns can be translated into socio-economic characteristics of parts of the region, then stakeholders have a better handle on what the future holds beyond just land consumption. In particular, such socio-economic characteristics can serve as inputs into traffic models that then explicate the impact of land-use change on traffic.

TALUS-LEAM locates new residential and commercial development at a fine spatial resolution (30x30 meters). This resolution makes it possible to aggregate and account for future development in any portion of the Traverse City region. These sub-regions may be defined by political boundaries such as townships, and the boundaries of facility planning areas such as water and sewer districts. Future development can also be aggregated by Traffic Analysis Zone (TAZ) as used by the Michigan Department of Transportation (MDOT) in its traffic model. The results of this aggregation can be directly entered into MDOT’s transportation model built using TRANSCAD software.

This report provides details of how TALUS-LEAM results are translated into socio-economic characteristics of TAZs. We present the method used, the results obtained, and conclude with discussion of the implication of these results.

Method

As inputs, the MDOT traffic model requires information about population, households, employment (retail and non-retail), and automobile ownership for each TAZ. To generate this information for a given TALUS-LEAM simulation, the first step is to compute the amount of new residential and commercial land in each TAZ. This can be computed for any year in the future, but in this specific case the year 2025 was chosen to match MDOT’s target year for traffic modeling. The amount of new land is computed through a simple GIS operation that overlays TAZ boundaries on TALUS-LEAM results and counts the number of 30x30 meter cells that change land-use designation to residential or commercial in each TAZ. This analysis and its results are illustrated in Figure 28 and Figure 29. As can be seen from these figures, some TAZs do not have any new commercial development, any new residential development, or any development at all.

Figure 28 . TALUS TAZ Boundaries and Future Development as projected by TALUS-LEAM.

Deriving socio-economic characteristics from the amount of new residential and commercial land in a TAZ is a more complicated process. The amount of new residential land provides a basis for estimating the number of new households. Based on the total households (existing and new) in a TAZ, population and automobile ownership can be estimated. The amount of new industrial and commercial land provides the basis for estimating new jobs.

In the future, one acre of residential land is likely to be associated with different numbers of households in different Traverse City region TAZs because that variation exists at present. In the year 2000, for instance, TAZs in the upper quartile of the range contained over 7 households per acre, while those in the lowest quartile contained less than 3 households per acre. These ratios are likely to vary similarly across the region in the future and we can expect that new households in a TAZ will consume land at a similar, though not identical, rate as they did in the year 2000. In TAZs with no residential land in 2000, households are assumed to consume the same amount of land as households in the 25th percentile of values in 2000.

 

Figure 29 . Sample Future Land Consumption

The number of new households in each TAZ, combined with the number of households that were present in the year 2000, gives us the total number of households in the year 2025. This number then serves as the basis for estimating other TAZ characteristics such as population and automobile ownership. Population is estimated by multiplying the total number of households by the average number of people per household. Again, the average number of people per household varies across the region and is also likely to vary across time. Furthermore, in each TAZ, this number is likely to decline at a decreasing rate over time, as it has been doing across the mid-west. (A different scenario may involve a different rate of decrease, perhaps no decrease at all.) In TAZs with no households in 2000, households are assumed to have the same average number of people as households in the 25th percentile of values in 2000. With declining numbers of people in each household, TAZs that see no incr! ease in households will see smaller populations. Some TAZs with growth may also see smaller populations because the growth in households is not large enough to offset the decrease in household size.

Automobile ownership—the number of households owning 0, 1, 2, and 3 cars, and the average number of cars per household—is also estimated based on the total number of households. Here, the proportion of households in each of these categories in a TAZ is assumed to remain the same over time. (Other scenarios worth playing out involve increased and decreased automobile ownership.) By applying these proportions to the total number of households, we arrive at the number of TAZ households in each category. Using these numbers, we compute the total number of automobiles in the TAZ and, by dividing the number of automobiles by the number of households, the average number of automobiles per household.

As mentioned earlier, the amount of new industrial and commercial land provides the basis for estimating new jobs. As with the number of households, the number of jobs associated with one acre of commercial and industrial land also varies across TAZs. That kind of difference is also likely to continue in the future, but the number of jobs per acre is expected to decline over time because of factors such as increasing worker productivity. Since the number of jobs in the region is not projected, we assume that the ratio of jobs to population remains constant. Just as with population, TAZs with no new industrial and commercial development have fewer jobs in 2025 than they did in 2000. Even TAZs with growth may see fewer jobs because the amount of new industrial and commercial land is not large enough to offset the decrease in jobs per acre.

The approach outlined above captures some of the complex nature of regional growth. In a region, growth is not likely to be simply distributed evenly across space nor is it likely to be distributed on the basis of current share of the region’s total population or employment. The relationship between socio-economic characteristics and the amount of land varies across the region. So, we identify the nature of the relationship in each TAZ, make assumptions about how it might change in the future, and then compute socio-economic characteristics for that TAZ before aggregating these values for the region. Thus, regional estimates closely reflect local conditions.

Results

The socio-economic characteristics of TAZs in the Traverse City region were estimated for each of three TALUS-LEAM scenarios. The first scenario assumes that the region will grow as projected by the US Census, that no public policy constraints are placed on development, and that other factors driving land-use change will play out as they have in the past; this is the Baseline scenario. The second scenario assumes a higher rate of growth than in the Baseline scenario, but other aspects of the Baseline scenario remain unchanged; this is the High-growth scenario. The third scenario assumes the same rate of growth as the High-growth scenario but also imposes current zoning restrictions on land-use change; this Zoning scenario allows us to understand the consequences of current zoning restrictions through comparisons with the High-growth scenario.

Baseline Scenario

If land-use change occurs as shown in the baseline scenario, then the region’s net population is slated to be slightly fewer than 104,000 in the year 2025, along with slightly less than 50,000 households. This represents a net regional increase of just over 30,000 people and 20,000 households more than in the year 2000. The rate of increase in households is greater than the rate of increase in population because of declining household size mentioned earlier. The net increases described above mask some interesting changes at a smaller scale. Over the half the TAZs will see some loss in population totaling just over 5,500 fewer people. In TAZs with population increases, these increases total more than 35,600 people. This total implies that the amount of land needed to accommodate growth is actually more than would be suggested by the net population increase. Thus, the region will be consuming more land per capita in the year 2025 than at present.

The net number of jobs in the region in the year 2025 is expected to be just less than 33,000; this is a combination of about 7,000 retail and 26,000 non-retail jobs. This number represents a net regional increase of just under 9,500 jobs when compared to jobs in the year 2000. A large number of TAZs (around 65%) are expected to have fewer jobs than in 2000; a total of about 4,500 fewer jobs. This is the result of changes such as increasing productivity and not because of loss of employers. On the other hand, in TAZs with more jobs than in 2000, there are slightly fewer than 14,000 new jobs. Again, in 2025, the region will be consuming more land per job than in the year 2000.

In this scenario, slightly fewer than 92,000 automobiles are expected in the region in the year 2025. This is up from around 51,000 in the year 2000. On a per-capita basis, this represents a significant increase. In the year 2000, there were about 0.7 automobiles per person; in the 2025, the ratio is expected to be close 0.9 automobiles per person. On a per-household basis, however, the difference is much less. In the year 2000, there were about 1.74 automobiles per household on average; in 2025, this average is 1.84 automobiles per household. The large increase in cars is, therefore, the result of the large increase in households that was described earlier. Nonetheless, the increase in cars represents a significant load on the region’s road infrastructure.

The following table summarizes these changes:

These changes are distributed differentially across space. In this scenario, the population in the year 2025 is located mostly in a ring of TAZs that lie immediately outside an inner core of TAZs (in Traverse City and the Peninsula) that have fewer people. (See Figure 30). In terms of change between 2000 and 2025, some of the inner core TAZs actually lose population while the outer ring sees big increases. (See Figure 31). Increase in employment over the same time period is also concentrated but in a tighter ring of TAZs. Several TAZs see no change in employment; several in the core and two in the periphery (one in the east, the other in the west) lose jobs. (See Figure 32). There are not as clearly defined patterns in the increase in automobile by TAZ. In general, most TAZs see an increase in automobile ownership, although a few see a decrease. (See Figure 33).

Figure 30 . Baseline Scenario 2025 population projections by TAZ.

Figure 31 . Baseline Scenario 2000 - 2025 changes in population by TAZ.

Figure 32 . Baseline Scenario 2000 - 2025 changes in employment by TAZ.

Figure 33 . Baseline Scenario 2000 - 2025 changes in automobile ownership by TAZ.

High-Growth Scenario

The high-growth scenario plays out the consequences of larger growth than projected by the US Bureau of the Census. Since the region is currently already exceeding previous Census projections, this scenario deserves attention. In broad quantitative terms, this scenario has the region in the year 2025 exhibiting the kind of changes found in the Baseline scenario: the number of households increases at a faster rate than the population; some TAZs see reduced population numbers, some TAZs see reduced jobs; the number of automobiles in the region increases at a rate greater than the population increase but roughly consistent with the increase in households; the net increase in population and jobs masks the actual increase, which is greater than the net increase. The table below summarizes some of these changes.

Despite the larger amount of growth in this scenario, the spatial patterns are also fairly similar to those exhibited in the Baseline scenario. These patterns are shown in Figures 34, 35, 36, and 37. In terms of population change, most of the inner TAZs are not affected by the extra growth, but TAZs on the periphery that saw little change or small loss of population see growth or no change. In terms of employment, most of the extra growth it appears will occur in some eastern TAZs where there are fewer jobs lost in a few TAZs and more jobs gained in a few TAZs. The extra automobiles produced by the extra growth are also mostly in the east, though there are some TAZs west of Traverse City that also see growth and less dramatic reductions.

Figure 34 . High Growth Scenario 2025 population projections by TAZ.

Figure 35 . High Growth Scenario 2000 - 2025 changes in population by TAZ.

Figure 36 . High Growth Scenario 2000 - 2025 changes in employment by TAZ.

Figure 37 . High Growth Scenario 2000 - 2025 changes in automobile ownership by TAZ.

Zoning Scenario

This scenario simulates land-use change as constrained by zoning controls currently in place. The net growth in population, households, jobs, and automobiles are few percentage points more than in the High-growth scenario but not all of this difference can be attributed to total positive increase in TAZs. Interestingly, as a result of where the growth has been directed, the total negative change in TAZs is smaller than in the High-Growth scenario and that enhances the difference between the two scenarios. Here too, the broad quantitative characteristics are not different from the other two scenarios.


Here too, the spatial patterns in population, households, employment, and automobile ownership are similar to the other scenarios but with notable changes. Spatial patterns are displayed in Figures 38. 39, and 40. In terms of population, applying current zoning controls appears to shift population closer to Traverse City (though not in the city) and also to some TAZs in the west. Change in employment in TAZs is more strikingly different between the two scenarios. In the High-Growth scenario, growth is mostly in a ring of TAZs around Traverse City while in the Zoning scenario growth seems in a string of TAZs running south of the city. Changes in automobile ownership exhibit more local differences. In the east of the region, automobile ownership is greater in the south as a result of zoning; in the west, automobile ownership only changes in a few northern TAZs.

Figure 38 . Zoning Scenario 2025 population projections by TAZ.

Figure 39 . Zoning Scenario 2000 - 2025 changes in employment by TAZ.

Figure 40 . Scenario 2000 - 2025 changes in automobile ownership by TAZ.

Discussion

Comparisons between scenarios are also instructive. In particular, the differences between the Baseline scenario and projections for TAZs made by MDOT show the impact of using land-use change as a basis for estimating future socio-economic characteristics in TAZs. Differences between the High-Growth and Zoning scenarios demonstrate the impact of current zoning controls. In Figure 41, which shows the future population in TAZs as estimated by MDOT, one sees that the change is more or less evenly distributed around the region. When compared with the Baseline scenario (see Figure 42), we see that MDOT population estimates are higher in the east of the region and in the Peninsula (shades of purple), while TALUS-LEAM estimates are higher in the west of the region and closer to Traverse City (shades of brown). In comparing the High-Growth and Zoning scenarios (Figure 43), we see that current zoning controls promote population growth in TAZs closer to Traverse City and in the Pe! ninsula, as seen in changes in the share of the regional population (direct comparisons between the two scenarios are not appropriate because total growth is different). On the other hand, zoning controls reduce the share of regional growth found in western TAZs.

Figure 41 . MDOT projected future population by TAZ.

Figure 42 . TALUS-LEAM Baseline Scenario vs MDOT. Population projection differences by TAZ

Figure 43 . High Growth Scenario vs Zoning Scenario. Population projection differences by TAZ

Transportation Integration Conclusions

TALUS-LEAM simulations of future land-use change show a fairly dramatic socio-economic restructuring of the region. Likewise, the above analysis also demonstrates how this approach can explicate the consequences of public policy choices such as zoning controls. The data generated through this analysis serve as inputs into models that estimate impacts of socio-economic change on traffic on the region’s road network. A more sophisticated use of TALUS-LEAM simulations would involve a two-way coupling between these simulations and traffic models, as changes in the region’s traffic patterns in turn alter future land-use patterns.

 

Conclusions

TALUS-LEAM simulations of future land-use change show a fairly dramatic socio-economic restructuring of the region. Likewise, the above analysis also demonstrates how this approach can explicate the consequences of public policy choices such as zoning controls. The data generated through this analysis serve as inputs into models that estimate impacts of socio-economic change on traffic on the region’s road network. A more sophisticated use of TALUS-LEAM simulations would involve a two-way coupling between these simulations and traffic models, as changes in the region’s traffic patterns in turn alter future land-use patterns.

Over the next 25 years, changes in land use in the Traverse City area are inevitable. What kinds of changes might occur? Which of these are desirable and which are not desirable? What can we do to promote the desirable and limit the undesirable? These are questions that area residents must confront in order to minimize the possible negative effects of future changes.

TALUS-LEAM has already begun to engage the community in preparing for change by considering future land-use development patterns and the causes and consequences of these patterns. Area stakeholders and residents have come together in open discussions. Through this process we have begun to arrive at a collective sense of what local land-use policies and public investments will most benefit the Traverse City area in the future.

This phase of the TALUS-LEAM project has come to an end with successes in each of the objectives that were identified before the project began. We see it is possible to effectively simulate and communicate different land-use futures for the region. These sets of futures provide a good foundation for community engagement with TC-TALUS on questions about the region’s futures as was demonstrated in public charrettes. TALUS-LEAM results can be post-processed as inputs into TC-TALUS transportation modeling efforts.

The differences between TALUS-LEAM and MDOT futures described above suggest that the value in simulations is not in describing a single future that can be considered likely as much as describing a set of different futures that is likely to contain within it conditions that will actually unfold in the future. With this set of futures, and the policy and investment decisions associated with each future, citizens and planners in the region can more meaningfully plan for the future of the region. A next phase must build on these successes.

Some clear directions for next steps emerged from this preliminary effort. Public charrettes incorporated a wide variety of opinions about the future of the Traverse City region from a diverse group of stakeholders. The information gathered from the charrette can provide a sound basis for refining and informing TALUS-LEAM. The potential for tighter coupling with the transportation modeling discussed earlier must be investigated further.


Townships:
AcmeGreen Lake
BlairLong Lake
East BayPeninsula
ElmwoodTraverse City
GarfieldWhite Water

(all in Grand Traverse County, expect Elmwood in Leelanau)