After the necessary imagery is obtained, the process of digitizing and classifying features begins. This can be a time-consuming and labor-intensive task if performed manually. For example, it took civil engineers at Fehr & Peers six months to manually digitize only 750 of the 17,000 miles of sidewalks in San Bernardino County, California to ensure ADA compliance. Luckily, artificial intelligence (AI)-based mapping is revolutionizing how transportation planning organizations extract vector features from geospatial imagery. By working with Ecopia, Fehr & Peers was able to map the entire sidewalk system for San Bernardino County in just three months, plus digitize and classify 16 other distinct features of their multimodal transportation network.
2. Analyze transportation infrastructure with mapping data
With the newly collected data, transportation planners can conduct in-depth analysis of existing infrastructure to understand how it needs to be improved to support their specific goals. By mapping all of the transportation features in an AOI, planners can identify gaps in equity, ADA compliance issues, and safety concerns. For instance, many planning organizations overlay past crash data onto their transportation maps to identify what characteristics may be contributing to these traffic incidents, and develop solutions to mitigate these in the future. Similarly, planners may visualize pedestrian RoW features in communities that have expressed a need for more active transportation modes, and pinpoint gaps in sidewalk or bike networks that need to be addressed.
Ecopia helped the Southeast Michigan Council of Governments (SEMCOG) on one such analysis. Leveraging AI-based mapping data from Ecopia, SEMCOG was able to map 24,000 miles of sidewalks and 160,000 crosswalk features across their 5,000 square mile region. With this data, SEMCOG calculated that a quarter of their residents lacked adequate access to a sidewalk, and only a quarter of crosswalks were marked. These insights have enabled SEMCOG to develop actionable strategies to improve pedestrian RoW features and foster accessible and equitable active transportation modes.
3. Transportation planning public engagement
A critical step in any successful transportation planning project is engaging with the public to understand their needs and preferences. This can be achieved through a combination of online and in-person surveys, interviews with stakeholders from different government organizations, and public forums where community members can voice their opinions. By actively involving the public, transportation planners can gain valuable insights and ensure that the resulting plans reflect the community's aspirations.
For example, holding a public forum to learn about community preferences for pedestrian RoW features like bike lanes or walking trails can help narrow down where to start an active transportation planning project. Similarly, community members can provide helpful context about where it would be most helpful for different transportation modes to connect to each other. While data can reveal gaps in transportation networks and accessibility features, it’s important to also factor public opinion into your project plans to make sure resources are allocated where taxpayers need them most.
4. Transportation plan implementation
Using these actionable insights from geospatial data and public engagement, transportation planners can effectively implement their plans for creating more liveable communities. Having a comprehensive, accurate, and up-to-date record of all transportation features in an AOI helps planners implement transportation plans more efficiently, ensuring they are making the optimal infrastructure developments for their particular project goals. Data can additionally be used to communicate important project milestones with the public and get important feedback in real-time.
A digital source of truth for transportation networks can also help planners work towards multiple goals simultaneously. Many transportation planning initiatives have overlapping goals, so data can be leveraged by different stakeholders for a variety of projects. For example, planners tasked with developing active transportation networks may focus on expanding bike lanes throughout a community. The bike lane mapping data generated for this project can also be used by planners working on Vision Zero or other safety projects as they strive to make multimodal transportation infrastructure safer.