How GIS and Lidar Equitably Prioritize Sidewalk Repairs in Lawrence, Kansas

The City of Lawrence, Kansas, is improving the walkability of their city, especially in the downtown areas where pedestrian foot traffic is high. For that same reason, these areas may have cracks, overgrown vegetation, or no sidewalk at all that impede pedestrian access to local amenities, businesses, and resources. Sidewalk repairs take time and are costly, and just like other cities Lawrence needs to prioritize where efforts in their Sidewalk Improvement Program occur. The city quickly realized to improve walkability they needed to identify where they were going to begin repairs using GIS. To equitably drive their infrastructure investments, the Lawrence - Douglas County Metropolitan  Transportation Planning Manager Jessica Mortinger and her team are solving the walkability issue of their city by making real-time, data backed decisions to support their cause and increase transparency on why certain areas in the city are prioritized for sidewalk repairs. 

The Sidewalk Improvement Program assists property owners in meeting their legal requirements (Kansas Statute and City Code) by helping identify and repair these hazards, as well as providing technical and financial assistance (where applicable). However, the costs of these repairs ultimately fall on the property owners.

Darren Haag, Asset and Innovation Manager, helped turn the Sidewalk Improvement Program into a more data driven process. Before, the city would inform homeowners of sidewalks that needed repair where they saw fit and that is why the city incorporated GIS as an essential business function if the city hoped to continue their initiatives for fixing the sidewalks in the most equitable and transparent manner. Darren’s GIS expertise allowed him to make a sidewalk network model that helps the city make the informed decisions on which sidewalks to prioritize, ensuring that the residents were being selected through data and not at random. 

“The city understood the demographic characteristics of the surrounding area and how residents may not use automobiles as a source of transportation,” said Haag. “However, the challenge of identifying problem areas in the sidewalk infrastructure through data analysis would revolutionize how the city would go about prioritizing their efforts.” 

A GIS-based network analysis built upon an existing sidewalk network to help demonstrate the sidewalk connections throughout the city was the first step. In Esri’s ArcGIS Pro, Darren identified routes that take the shortest path between identified origins and destinations.  This analysis uses custom route prioritization based on path type and other attributes.  For example, taking a path with an existing sidewalk is prioritized over a path without or crossing a street with a crosswalk is prioritized over crossing a street without a crosswalk. Destinations include: Schools K-12, Park entry points, public attractions, public transit stops, public government institution, hospitals, daycares, universities, and business and each are weighted differently. Previously, they wouldn’t have been able to weight these destinations and then quickly visualize where their prioritized efforts needed to take place. The routes are aggregated to identify sidewalk segments with the highest volume of trips or potential pedestrian demand. 

In addition, Darren narrowed down the areas in the sidewalk network using a transportation disadvantaged populations layer, which reflects additional priority to provide an improved means for multimodal trips. This layer adds more context to the area and elevates equity by including households with a person who has a disability, minorities, single parent households, zero vehicle households, and other disadvantaged characteristics. It is the overlap with the sidewalk network model and the transportation disadvantaged population where Darren and Jessica can select prioritization over other areas and hand this information off to city council and other community leaders to make the most informed decision.

Once they were able to identify the priority corridors, terrestrial lidar data forecasted the current conditions of the sidewalk to locate where exactly the hazards are faster. Lidar is a remote sensing method that creates 3D models and maps of objects and environments, in this case providing niche insights such as the slope of the sidewalks and its condition. The lidar data was crucial in determining where to send field contractors to inspect the vulnerabilities in the sidewalk network. This saved the field contractors’ time in their efforts of marking each data point into GIS, reducing the overall cost of labor.

The field contractors logged the sidewalk hazards using ArcGIS Survey123, a dynamic form and survey builder for data collection efforts, to pinpoint the exact location of the hazards, collect additional sidewalk condition data, and measures the area of the hazard to determine project cost. This information is then fed into a web map in real-time where Jessica and team can visualize the scope of the project and all the collected data. After inspections, the web map was then made available for the public to view. 

Mortinger was thrilled to know that with the help of GIS, the city of Lawrence could make the most informed decision possible to meet the needs of the people she serves. Although the automation streamlines the processes of getting the sidewalks fixed, the human element of the decision making was still an important measure when evaluating the success of the project overall. “There are human factors that we also have to consider in our decision making that we may not know just based on the model, but the model gives a neutral approach to making equitable decisions in our community” said Mortinger. “These same tools can be used for other investment decisions, which will be a constant evolution of the workflow.”

The GIS-based methodology behind the sidewalk network analysis can also be attributed to the city’s wider scale ADA Transition Plan initiative. Darren and his team are also using a similar workflow to keep track of the ADA compliant curb ramp throughout the city. Improving walkability for all residents is the goal, but accessibility is another key driver to attain a multi-modal network for all residents.