GIS & AI Boost ADA Compliance in Cities: A Tech-Driven Accessibility Trend

Local governments are increasingly leveraging advanced technologies like Geographic Information Systems (GIS) and Artificial Intelligence (AI) to enhance the physical accessibility of their urban environments. While many municipalities are focused on meeting the 2026 federal mandate for digital accessibility, a parallel effort is underway to improve physical infrastructure, particularly sidewalks and curb ramps, for better compliance with the Americans with Disabilities Act (ADA) and an improved experience for all residents. Experts contend that richer data empowers better support for people with disabilities, enabling more informed investments in accessible infrastructure. This also supports the “curb cut effect,” a principle suggesting that making infrastructure accessible for individuals with disabilities ultimately benefits the broader population, including older adults, parents with strollers, and travelers with luggage.

In Lawrence, Kansas, the state’s sixth-largest city, officials are actively improving accessibility through GIS technology. Jessica Mortinger, transportation planning manager for the Lawrence-Douglas County Metropolitan Planning Organization, emphasizes that this initiative addresses a fundamental equity issue, as everyone is a pedestrian at some point. She notes that while at least 12 percent of the population experiences mobility issues, this rate significantly increases with age.

Under federal requirements, government entities employing more than 50 individuals must develop an ADA Transition Plan, a comprehensive roadmap for making facilities and infrastructure accessible. Evan Korynta, the city’s ADA compliance administrator, explains that Lawrence began its efforts in 2021 by utilizing lidar technology mounted on slow-moving vehicles to collect detailed information on its 6,500 ADA curb ramps. This provided crucial data on ramp slopes and conditions, highlighting areas ripe for improvement. The city has since embarked on a 20-year plan to achieve full accessibility, employing pedestrian demand and transportation disadvantaged models to prioritize improvements based on genuine need.

Mortinger highlights that this technical solution underpins a strategic and systematic improvement process. Using GIS tools, city staff can compile layers of data illustrating demand and ramp conditions, creating detailed maps that visualize priorities. This not only enhances public transparency but also facilitates more efficient investment decisions. Beyond improving the pedestrian experience, Korynta adds that leveraging technology for ADA compliance planning also safeguards cities from potential lawsuits. Mortinger further explains that the “storytelling” capabilities enabled by this data underscore the vital importance of the work, portraying how individuals are “fighting for justice in being able to access their community.” This narrative also appears to justify the significant investment; despite recent budgetary cuts elsewhere, the city commission approved the $100 million ADA transition plan in July 2024, with implementation now beginning. Mortinger acknowledges that “we still have work to do,” emphasizing that data-driven storytelling and the technology supporting it will be crucial for quantifying progress and fulfilling their responsibility as stewards of public funds.

Another jurisdiction making strides in this area is Douglas County, Nebraska, which collaborates closely with its largest city, Omaha, on GIS solutions. Both GIS and AI are playing pivotal roles in their curb management efforts. Approximately three years ago, Steve Cacioppo, the county GIS Department’s senior GIS analyst, began exploring deep learning and geospatial AI capabilities within their GIS platform. His goal was to develop a model that could extract features from aerial imagery to inventory the county’s more than 30,000 curb ramps.

While human identification of ADA curbs is straightforward, Cacioppo notes that training a deep learning model is an iterative process requiring continuous refinement. Early challenges included accurate identification when objects like shadows, trees, or vehicles obstructed the view. The model initially misidentified features such as car sunroofs or painted crosswalk rectangles as curbs, necessitating corrections. Although AI still requires human oversight and the model is not yet perfect, Cacioppo stresses the immense time savings; manual identification of all 30,000 curbs by a single employee was estimated to take over 1,000 hours. The data generated by this process is also shared with other municipalities in the county, supporting their own asset management and accessibility initiatives. Brett Kelly, an Omaha GIS technician, confirms that this data directly supports field work for the city’s ADA inspection staff, forming the foundation for compliance reporting, a significant leap from their previous “paper and pen” methods. Cacioppo foresees this AI application extending to other county inventory needs, such as identifying swimming pools or sewer locations, noting, “Maybe the AI finds something that they missed.” He highlights the accessibility of these tools, emphasizing that even without a programming background, he was able to develop the model, suggesting others can too.