Performing a Sidewalk Gap Analysis with Geospatial Data

What is a sidewalk gap analysis?

City planners and other transportation professionals perform sidewalk gap analysis to understand the connectivity of pedestrian infrastructure. A typical sidewalk gap analysis involves identifying places where sidewalk segments do not connect, abruptly stop, or simply do not exist. All of these scenarios are considered gaps in sidewalk connectivity and have implications for pedestrian mobility that planners must factor into their active transportation plans, walkability analytics, pedestrian right-of-way studies, and similar workflows.

Data needed to perform a sidewalk gap analysis

Geospatial data and geographic information systems (GIS) technology enable transportation planners to analyze sidewalk gaps digitally, eliminating the need to physically inspect all sidewalk infrastructure throughout their area of interest. However, for this to be possible, the following data must be available:

• Sidewalk vectors: Of course, the most important map data to have when performing a sidewalk gap analysis is a vector layer representing the sidewalk network itself. Vector data ensures that sidewalks are captured in planimetric-level detail for the most precise digital representation of real-world features, affording planners the ability to see and analyze sidewalk network segments accurately. Representing sidewalks in this way not only helps planners identify visible gaps, but also provides input for network analysis tools to automatically flag areas lacking connectivity.
• Road vectors: In addition to sidewalks, it can be helpful to have a vector layer representing road segments. When combined, road and sidewalk layers show where transportation infrastructure lacks a safe pedestrian route, highlighting areas where sidewalks can be built to increase walkability and connectivity. While road centerlines overlaid on imagery can provide some insight into sidewalk gaps, a full polygon feature layer representing roads is the most helpful for identifying where exactly sidewalks could exist.
• Crosswalk vectors: While not 100% needed for a sidewalk gap analysis, adding in a layer of crosswalk vectors can provide important supplemental information on walkability and pedestrian right-of-way. For example, visualizing crosswalks along with sidewalks and roads can show where pedestrian access continues across intersections - areas that might have otherwise been identified as gaps in sidewalk connectivity. Crosswalk data can also vary in detail, from simply identifying where crosswalks exist to including attribution related to visibility, type, and width, which can all add further context to a sidewalk gap analysis.
• Basemap imagery: Although vector layers are the most helpful for sidewalk gap analysis, it is also important to have high-resolution basemap imagery to overlay features on. Basemap imagery provides important context about the community being analyzed that cannot be gleaned from transportation features alone, and can be used to spot-check individual gaps when necessary. For instance, imagery may show that a pond exists between two sidewalk routes, providing an explanation for that particular gap in coverage while also indicating that building a pedestrian bridge may be the best solution to increase connectivity.

The importance of data quality for sidewalk gap analysis

When sourcing these datasets for a sidewalk gap analysis, it’s important to remember that data quality also plays an important role in the efficacy of the results. If any of the data layers used in the analysis do not truly reflect real-world sidewalk network conditions, the gap analysis cannot be used to confidently inform planning decisions. 

Keep an eye out for these three data quality metrics when assessing datasets to use in a sidewalk gap analysis:

• Completeness: Make sure all of your data layers are comprehensive, meaning there is no coverage missing across your area of interest. If you are not analyzing every sidewalk or road segment across your project area, you risk over- or under-identifying sidewalk gaps.
• Accuracy: Even if your data covers your entire area of interest, be sure to assess the geometric accuracy of features in relation to their real-world counterparts. A sidewalk vector feature that is represented even just a few feet away from its actual position on Earth’s surface can quickly impact results and derail an analysis.
• Freshness: One of the best ways to ensure data is complete and accurate is to source an up-to-date dataset. The world changes each day, with new construction and planning projects regularly impacting sidewalk infrastructure and connectivity. If data is stale, a sidewalk gap analysis could fail to factor in critical network features and produce incorrect results.

Sidewalk gap analysis methodologies

With the right data, there are a variety of ways to perform a sidewalk gap analysis. GIS programs and tools provide helpful resources for visualizing and analyzing sidewalk network connectivity, as well as for modeling infrastructure improvements based on the gap analysis findings. Thanks to these capabilities and the availability of geospatial data representing sidewalk and other relevant infrastructure, planners can analyze walkability and pedestrian right-of-way across large areas of interest without needing to physically inspect each sidewalk.

Within GIS, these are the most common ways to conduct a sidewalk gap analysis:

Manual sidewalk gap inspection

Once all relevant data layers are loaded into a GIS program planners can pan around the map of their area of interest and pinpoint where gaps in connectivity exist. These gaps can either be digitized as a new vector layer, or otherwise noted on the map itself.

Pros: Planners can leverage their professional expertise and human reasoning to identify where sidewalk gaps exist, and even append additional data related to possible reasons for the gap or the best solutions for closing it.

Cons: Manual map inspection is a labor-intensive process that can become quite costly when considering the time and resources required, especially over a large area of interest. If multiple planners are performing the sidewalk gap analysis, it is also important to consider any differences in professional interpretation that could result in inconsistencies, as individuals may interpret features differently.

While manual inspection is a valid option for GIS-based sidewalk gap analysis, it is best suited for small areas of interest or as a spot-checking method that supplements other methodologies.

Algorithm-based sidewalk gap identification

GIS software often include tools that can help automate sidewalk gap identification. Using sidewalk, road, and other datasets as inputs, planners can program a GIS to highlight where feature gaps exist based on certain criteria. Sometimes these algorithms use logic determined by the planner to digitize all possible places for a sidewalk, producing a layer that can then be overlaid with existing sidewalks to highlight gaps. Another common algorithm-based approach uses proximity analysis to determine a gap length ratio across the sidewalk network, resulting in a connectivity score for each segment.

Pros: Automated sidewalk gap analysis tools drastically reduce the amount of time required to inspect an entire network, especially across large project areas. Planners can instead focus on interpreting results and developing plans to improve pedestrian walkability.

Cons: Algorithms do not always interpret geospatial data the same way a trained planning professional would, so results can vary in accuracy. These programming tools can also be complex to configure, often requiring some level of coding experience to operate. 

Across a large area of interest, it is usually best to leverage an automated sidewalk gap analysis tool. However, planners must be prepared to perform in-depth quality control on the results to ensure that they are consistent with the needs of the study.

Implications of sidewalk network connectivity

Planners conduct sidewalk gap analyses for many different reasons. Understanding sidewalk network connectivity informs active transportation plans, which provide opportunities for individuals to choose healthier transportation options such as walking that foster a greater sense of community livability. However, active transportation plans must include considerations for safety, accessibility, equity, and sustainability, all of which sidewalk gap analysis can provide critical insight for.

Pedestrian right-of-way & safety

Gaps in sidewalk networks present significant safety concerns for pedestrians. Where sidewalks do not exist, pedestrians are often forced to walk alongside busy roadways and risk involvement in a traffic incident. Similarly, sidewalk size, proximity to nearby roads, and the presence of marked crosswalks at intersections can impact awareness of pedestrian right-of-way, an important component of any active transportation plan.

Sidewalk accessibility & ADA compliance

For sidewalks to have their intended effect on a community, they must be accessible to all who would like to use them. Thanks to standards set by the Americans with Disabilities Act (ADA) and Public Right-of-Way Accessibility Guidelines (PROWAG), there are now recommended widths for sidewalks to accommodate all users, including those using wheelchairs and other mobility devices. Sidewalk gap analyses often include these ADA and PROWAG metrics to identify where gaps in accessibility exist, and can even consider similar guidelines related to curb height and crosswalk visibility.

Multimodal network connectivity & transportation equity

Active transportation plans are most effective when pedestrian routes are thoroughly connected to other modes of transportation. Multimodal networks, or networks that include connection points between different types of transportation methods, foster more equitable societies by giving individuals a variety of options to choose from depending on their specific needs and preferences. Sidewalk gap analysis enables planners to pinpoint areas where sidewalks are not connected to other modes, such as where a public transit stop cannot be safely accessed by pedestrians. Using sidewalk gap analysis to understand multimodal network connectivity is an important part of transportation equity analysis, which can help allocate resources to underserved areas lacking in pedestrian accessibility.

Sustainability & Net-Zero goals

Analyzing sidewalks is critical for many sustainability initiatives. Active transportation planning generally promotes more sustainable methods of travel, such as walking, running, or biking, which ultimately reduces a community’s carbon emissions and progresses Net-Zero goals. However, sidewalks are also impervious surfaces that cause higher levels of runoff in a stormwater event, which can lead to flooding. Sidewalk gap analyses help planners understand these sustainability implications in more detail to inform decision-making.

Sidewalk gap analysis example: understanding resident proximity to sidewalk networks

At Ecopia AI (Ecopia), we regularly work with departments of transportation (DOTs) and metropolitan planning organizations (MPOs) to provide the foundational data needed to perform a sidewalk gap analysis. For example, we recently produced a comprehensive sidewalk, crosswalk, and parking lot dataset for the Southeast Michigan Council of Governments (SEMCOG) to use in a sidewalk accessibility and proximity analysis. 

In just three weeks, Ecopia’s AI-based mapping systems extracted 24,000 miles of sidewalks with width attribution, 160,000 crosswalk polygons, and 4,000 parking lot polygons across SEMCOG’s 5,000 square mile area of interest. Using this data to conduct a sidewalk gap analysis and proximity study, SEMCOG was able to calculate that only 76% of the region’s population lives within 100 feet of a sidewalk, and only 23% of crosswalks were marked. These insights are used to inform SEMCOG’s infrastructure planning and improve the region’s walkability by making sidewalks and crosswalks more accessible and safe for pedestrians.

Learn more about Ecopia’s support of SEMCOG’s sidewalk gap analysis here.

High-precision geospatial data for sidewalk gap analysis

Ecopia’s AI-powered mapping engine efficiently extracts high-precision geospatial data from imagery at the scale needed to keep foundational data current with a dynamically changing world, but with the quality expected of a trained GIS or planning professional. Transportation planners no longer need to spend hours manually digitizing sidewalk and other relevant features from imagery, and can instead focus on performing sidewalk gap analysis that produce actionable insights to enhance community walkability and pedestrian right-of-way.

To learn more about how Ecopia can develop a comprehensive, accurate, and up-to-date geospatial database to fuel an authoritative sidewalk gap analysis, get in touch with our team.