Case Study
In 2018, the mayor of Marshalltown, Iowa declared that transportation was the most critical issue facing the mid-size manufacturing town of roughly 27,000 residents. It had been over a decade since the city’s transit plan had been reviewed and updated, and a new plan was needed to take into account the changing and diverse population and to relocate services to better meet the needs of a modern workforce.
As seen in the figures above, over the last decade, more residents began commuting further from home to work, often because affordable and mid-range housing options were not available, pushing residents to live further from the city and their jobs. Over the same time, the percentage of residents identifying as Hispanic or Latino nearly doubled from 13% to 24%, and city officials anticipated that by the next census, schools in town would have more minority than Caucasian students. The mayor expected that each of these factors would drive ridership up. However, the Marshalltown Municipal Transit Authority (MMT) was experiencing declining public ridership each year, with a one-year drop of 11%; in 2016, MMT was also experiencing an increasing number of complaints that the public transit system was inconvenient and that it took too long to travel from one side of town to another for work, school and medical services.
To address the problem of declining and dissatisfied riders, Marshalltown worked together with ISU’s Cooperative Extension System (CES) and researchers from across campus to see how data science and the Community Learning through Data Driven Discovery (CLD3) process could help the City to improve its decision-making by accessing up-to-date information about City systems, infrastructure, population dynamics and social interaction. During the Data Discovery phase, a variety of data resources were uncovered:
- Community members identified and shared a variety of administrative data, including housing, existing bus routes and ridership data.
- ISU researchers identified over three dozen additional data sources to be collected (or parsed from PDF reports), imported, integrated, profiled and spatially and statistically analyzed.
- An ISU student rode all the bus routes in Marshalltown and recorded the routes and locations of each stop using a GPS-enabled smartphone and inventory form that allowed for photos and characteristics (benches, lighting, accessibility) of the stop to be recorded. This data was then overlaid with current bus routes to identify discrepancies between where the bus actually stopped and the published schedule.
- The sidewalk infrastructure and some street data were incomplete in the GIS provided by the city. To rectify this, the team digitized all sidewalks and any missing streets using OpenStreetMap (OSM).
"(This was) a big lesson in my view that you need to have the right people in the right positions to champion and support using data to make decisions."
The data collected in this inventory allowed the team to:
- Conduct spatial analysis of the accessibility (by sidewalk or street network) to the bus stops. Maps showing the portions of the city (service areas) that were within .25 and .5 mile distances were produced.
- These service areas were then overlaid on maps depicting the city’s social and economic distributions, largely from the Census, identifying the location within the community of populations most likely in need of public transit. These populations included minority, lower income, elderly, and housing units with no vehicle, among others. The produced maps clearly identified areas that would benefit from additional stops or routes in the northeast corner of town as well as around a senior living area in the northwest part of town.
- Data was shared with the mayor’s office and the city’s engineering firm as part of their review of bus stop accessibility. Newly digitized maps of city infrastructure were made publicly available via the OSM platform. Data dashboards were produced to inform the City Council of the bus stop and other non-transportation-related issues, suggesting that the benefits of this project will continue to grow as the city utilizes pilot data to inform other strategic decisions.
- Marshalltown’s transit administrator used the results of this study to support a plan for new bus stops that better meet the needs of residents, particularly those who face disadvantages.
Jessica Kinser, City Administrator for Marshalltown, reflected on working with the ISU team and the CLD3 process in an interview:
“I haven’t worked with any ISU research teams in the past, so I didn’t quite know what to expect. They were well versed in what data was available to them to help us get to a better understanding of the issue. They were patient and willing to help as we worked through struggles of what data we did or did not have on the City-side of things...The mapping definitely helped identify areas that were being underserved, and Kevin Pigors, our Transit Administrator, has been working to address those areas…(This was) a big lesson in my view that you need to have the right people in the right positions to champion and support using data to make decisions.”
At the conclusion of the CLD3 project, Kevin Pigors, Marshalltown Municipal Transit Administrator, and his team received the Federal Transit Authority Award of Excellence and the Iowa Transit Authority Award of Excellence for Highest Percentage Increase in Ridership Among Rural Transit Providers (11%, or 9,825 riders). Iowa State University Extension and Outreach was also recognized by the National Association of Community Development Extension Professionals as the 2020 regional winner and national runner-up for Innovation and Creativity in Outreach.
The project team included Christopher J. Seeger, Cass Dorius, Erin Mullenix, Bailey Hanson, Austin Dunn, Rakesh Shah, and Jonathan Sherwood.