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Planning Tools for Linking Rural Development and Transportation: A Case Study in Northeastern Mississippi

In This Article:

Guest post by Brian J. Morton, Senior Research Associate, Center for Urban and Regional Studies, University of North Carolina at Chapel Hill, (919) 962-8847, bjmorton[at]

Map of counties in Mississippi, including the study area of Mississippi Hills National Heritage Area, Four Case-Study Counties, Five Key Towns, and Tanglefoot Trail®
Mississippi Hills National Heritage Area, Four Case-Study Counties, Five Key Towns, and Tanglefoot Trail®

Union, Lee, Chickasaw, and Pontotoc counties, in the center of the Mississippi Hills National Heritage Area, were historically known for cotton and dairy production and furniture manufacture, but a very different future is unfolding, the result of years-long dedicated efforts to build both an automotive manufacturing cluster and heritage/active tourism. Toyota opened a Corolla assembly plant in 2011 near the village of Blue Springs, employing 2,000. Opened in 2013, the 43-mile Tanglefoot Trail® links Houston (Chickasaw County) to New Albany (Union County) with a rail trail.

The four counties face the challenge of sustaining the rural/small-town character on which heritage-based tourism depends while accommodating a booming, technologically-sophisticated industrial economy. We have developed a suite of analytical and communication tools that will help inform discussions of the benefits and costs of different rural development trajectories. Although developed for northeastern Mississippi, our tools apply techniques relevant to any small community or rural area that is engaged in economic development on a regional scale; performance-based transportation planning; active or heritage tourism; or sustainability or livability planning.

Great towns and regions deserve planning tools that inspire the imagination and provide information at fine and broad scales. Our tools address that need with: analyses of development capacity, bicycle-suitability assessments, streetscape renderings, and scenario assessments conducted with a regional land use – travel demand model. An in-depth report on our tools may be accessed here:

Build-Out Analyses:

Business As Usual and Downtown, Trail-Oriented Growth

Map showing Maximum Residential Density in Houston, MS Allowed by Existing Zoning
Maximum Residential Density in Houston, MS Allowed by Existing Zoning

What land use pattern might occur in the counties’ four largest towns—New Albany, Pontotoc, Houston, and Tupelo—if the maximum amount of development allowed by their zoning ordinances were to occur? How might an alternative development vision, one encouraging greater density in the town centers, change the locations of growth?

We conducted build-out analyses of each town using CommunityViz® to predict the business-as-usual development pattern and to compare it to downtown, trail-oriented growth. The business-as-usual build-out analyses used zoning maps to determine where, and how much, additional residential and commercial development could occur, subject to environmental constraints.

Downtown, trail-oriented growth dramatically differs from the business-as-usual scenario: compact mixed-use neighborhoods would develop within walking distance of downtown; more multifamily housing would be built; and new neighborhoods adjacent to the Tanglefoot Trail® trailheads (in the three trail towns) would also be built at a greater density than envisioned by current zoning. The following map illustrates the greater residential density (deeper shades of red) that would occur in and around Houston’s center with the downtown, trail-oriented growth scenario: as much as six units per acre, which is a substantial difference for that small town.

Streetscape Renderings

The prospect of increased density may understandably create anxiety over loss of community character. Renderings of hypothetical streetscapes are uniquely able to provide the qualitative information on which accurate evaluation of change in sense of place depends. The following pair of figures illustrates one possible modification to a streetscape that would be consistent with the downtown, trail-oriented growth scenario.

Washington Street, Houston, MS: Existing Streetscape, showing travel lanes and parking along commercial area with small businesses
Washington Street, Houston, MS: Existing Streetscape View
Artist's rendering of Washington Street, Houston, MS: Streetscape After Implementation of the Downtown, Trail-Oriented Growth Scenario
Washington Street, Houston: Streetscape After Implementing Downtown, Trail-Oriented Growth


Bicycle Suitability

Could the Tanglefoot Trail be the armature of a new transportation system facilitating active travel within the trail towns, playing the role of transformative infrastructure that stimulates construction of bicycle networks that could be used for daily travel needs?

A fine-scale assessment of the current suitability of the roadway network for bicycle travel should be the starting point of any investigation of the merits of investments in bicycle infrastructure. We rated the bicycle suitability of the roads that are most likely to serve as corridors connecting residential areas and important destinations. The degree of suitability reflects shoulder width, traffic volume, posted speed limit, road surface condition, and grade. The suitability ratings allowed us to identify the roads that are the best candidates for construction of bicycle lanes.

Land Use – Travel Demand Model and

Assessment of Broad-Scale Development Visions

The land use – travel demand model that we built brings a regional perspective to questions of economic development, transportation efficiency, and sustainability. The census block groups in Union, Lee, Chickasaw, and Pontotoc counties form the model’s core geography.

We predicted the travel behavior that could be induced by the direct and indirect growth caused by expansion of automobile manufacturing under two assumptions about the locations of population growth and of growth in the commercial establishments that provide the goods and services demanded by the new residents. In the Two Towns Scenario, the new households and commercial jobs are located in New Albany and Tupelo. In the Four Towns Scenario, the new households and commercial jobs are located in New Albany and Tupelo as well as Houston and Pontotoc. The Tanglefoot Trail is open in both scenarios, and the number of new households and their locations reflect the assumptions of the downtown, trail-oriented development vision.

One of the most important performance criteria for regional planning is transportation efficiency, which accounts for the distance someone travels to achieve a given daily activity schedule, and which directly correlates with fossil fuel consumption and vehicular emissions of air pollutants. An increase in vehicle-miles-traveled (VMT) per person indicates a decrease in transportation efficiency because travelers consume more resources (e.g., time and money) to pursue their daily routines, whereas a decrease in VMT per person indicates an increase in transportation efficiency. Decreasing VMT per person will typically decrease fuel consumption per person and vehicular emissions per person, although the latter decreases may not be proportional to the change in VMT per person.

Compared to the conditions in the year 2000, the Two Towns Scenario decreases daily, per person VMT by 0.74 miles/person. The Four Towns scenario result is a travel decrease of 0.19 miles/person. Both scenarios result in essentially the same amount of per-person travel.

The Four Towns Scenario is no less transportation-efficient than the Two Towns Scenario, and the Four Towns scenario provides geographically more inclusive support for heritage and active tourism because population and employment growth occur in all of the trail towns, not only in New Albany.


Prof. John Poros at Mississippi State University conducted the build-out analyses and bicycle suitability assessments and prepared the renderings. Joe Huegy at North Carolina State University helped immensely with building the land use-travel demand model. The Southeastern Transportation Research, Innovation, Development and Education Center funded our work.


Additional Resources


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