Protocol - Neighborhood Walking and Biking Environment

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MAPS-Mini is a 15-item neighborhood environment audit via GIS of a 0.25-mile walking or biking route from participant residences to the nearest nonresidential destination. The tool contains 3 items on street crossings, measured at every intersection on the route and 12 items on street segments, collected on every street block face on the route. Items were scored from 0-1 or 0-2. A total score summing all computed items for each participant represents the cumulative effect of microscale attributes of the built environment.

Specific Instructions

The Microscale Audit of Pedestrian Streetscapes (MAPS-Mini) can be completed by using one of two methods: route-level or segment-level data collection. A participant route will almost always start with a segment at the participant’s house. When there is no sidewalk on the participant’s side of the street, but there is one on the other side of the street, the route will start with a crossing. Segment-level data collection is completed block-by-block, and is an effective way to canvas an area. Each segment in the area is completed, as well as a crossing on one side (see example below), until the desired area is complete.

Full instructions can be found in the MAPS Data Collection and Scoring Manual:

Cain, K. L., Millstein, R. A., & Geremia, C. M. (2012). Microscale Audit of Pedestrian Streetscapes (MAPS): data collection & scoring manual. University California San Diego. Available for download at: https://drjimsallis.org/measure_maps.html#MAPSMINI

The MAPS-Mini should be administered by the study team. The questions can be completed using freely available map and street view tools, or by auditing in-person.

Please note there have been different kinds of implementation—some with remote online observers and some with Machine Learning to automate audits. When using this protocol, the user could search to identify if such data may be available for their geographic area of study.


MAPS Mini Survey – Segment Method  


Date                  Auditor ID#________

Route #                                    

Start Time: ________End Time: _______



Intersection of  ____________________&
Crossing from  N  S  E  W  to  N  S  E  W
1.  Is a pedestrian walk signal present?
 [ ] 0 No  
 [ ] 1 Yes
2.  Is there a ramp at the curb(s)?
 [ ] 0 No
 [ ] 1 Yes, at one curb only
 [ ] 2 Yes, at both pre-crossing and post-crossing curbs
 3. Is there a marked crosswalk?
 [ ] 0 No
 [ ] 1 Yes
Segment: *Count one (your) side of the street*
Street ______________Side  N  S  E  W
Starting Cross-street: ________________     
Ending Cross-street: ________________   
4.  Type:
 [ ] 0 Residential
 [ ] 1 Commercial
5.  How many public parks are present?
 [ ] 0
 [ ] 1
 [ ] 2 or more
6.  How many public transit stops are present?
 [ ] 0
 [ ] 1
 [ ] 2 or more
7.  Are there any benches or places to sit (include bus stop benches)?
 [ ] 0 No
 [ ] 1 Yes
8.  Are street lights installed?     
 [ ] 0 None  
 [ ] 1 Some
 [ ] 2 Ample  
9.  Are the buildings well maintained?
 [ ] 0 0-99%       
 [ ] 1 100%
10.  Is graffiti/tagging present (do not include murals)? 
 [ ] 1 No
 [ ] 0 Yes
11.  Is there a designated bike path?
 [ ] 0 No
 [ ] 1 Painted line
 [ ] 2 Physical barrier
12.  Is a sidewalk present? If no, skip to 12
 [ ] 0 No
 [ ] 1 Yes
13.  Are there poorly maintained sections of the sidewalk that constitute major trip hazards? (e.g. heaves, misalignment, cracks, overgrowth, incomplete sidewalk)
 [ ] 1 None
 [ ] 0 Any/no sidewalk present
14.  Is a buffer present?
 [ ] 0 No/no sidewalk present
 [ ] 1 Yes
15.  What percentage of the length of the sidewalk/walkway is covered by trees, awnings or other overhead coverage?
 [ ] 0 0-25% / no sidewalk
 [ ] 1 26-75%
 [ ] 2 76-100%
Score = Total Points____/21 = ____%
Scoring Instructions
Compute an overall score by summing all of the above items:
4 + 5 + 6 + 7 + 8 + 9 + S7 + 10 + 11 + 12 + 13 + 14 + 1 + 2 + 3
Compute the percent of total possible points:
See the MAPS-Mini data dictionary – segment method for detailed variable names and item-level coding. Scores from the individual items are averaged across street segments and crossings to compute participant-level scores. The total score is the sum of all computed items for each participant, expressed as a percent of total possible points, and indicates environmental support of active transport. A second scoring method is the “percentage of possible maximum score,” which is more easily interpretable and allows for comparison of scores across different versions.


Personnel and Training Required

Data collection training and certification involving 1 day of in-office training, and 2 days of field training. To be certified to rate independently, data collectors had to complete at least four route assessments with reliability
≥95% with the trainer.

Equipment Needs

GIS software including tax assessor and ESRI parcel layers; computer with access to the Internet for Google Maps, basic web searches for location name/address; Network Analyst software for identifying the shortest route from a participant’s home to the nearest eligible destination.

Requirement CategoryRequired
Major equipment No
Specialized training Yes
Specialized requirements for biospecimen collection No
Average time of greater than 15 minutes in an unaffected individual No
Mode of Administration

GIS-based Analysis


Not applicable


Not applicable

Selection Rationale

MAPS-Mini is validated in multiple populations and settings, and for in-person and automated audits. It is low burden to participants.



caDSR Common Data Elements (CDE) Walking and Biking Infrastructure 12114278 CDE Browser
Derived Variables


Process and Review

Not applicable

Protocol Name from Source

Microscale Audit of Pedestrian Streetscapes (MAPS-Mini)


Cain, K. L., Gavand, K. A., Conway, T. L., Geremia, C. M., Millstein, R. A., Frank, L. D., Saelens, B. E., Adams, M. A., Glanz, K., King, A. C., & Sallis, J. F. (2017). Developing and validating an abbreviated version of the Microscale Audit for Pedestrian Streetscapes (MAPS-Abbreviated). Journal of Transport & Health, 5, 84–96. https://doi.org/ 101016/j.jth.2017.05.004

Sallis, J. F., Cain, K. L., Conway, T. L., Gavand, K. A., Millstein, R. A., Geremia, C. M., Frank, L. D., Saelens, B. E., Glanz, K., & King, A. C. (2015). Is your neighborhood designed to support physical activity? a brief streetscape audit tool. Preventing Chronic Disease, 12, E141. https://doi.org/10.5888/pcd12.150098

General References

Fox, E. H., Chapman, J. E., Moland, A. M., Alfonsin, N. E., Frank, L. D., Sallis, J. F., Conway, T. L., Cain, K. L., Geremia, C., Cerin, E., Vanwolleghem, G., Van Dyck, D., Queralt, A., Molina-García, J., Hino, A., Lopes, A., Salmon, J., Timperio, A., & Kershaw, S. E. (2021). International evaluation of the Microscale Audit of Pedestrian Streetscapes (MAPS) Global instrument: comparative assessment between local and remote online observers. International Journal of Behavioral Nutrition and Physical Activity, 18(1), 84. https://doi.org/10.1186/s12966-021-01146-3

Koo, B. W., Guhathakurta, S., & Botchwey, N. (2022). Development and validation of automated microscale walkability audit method. Health & Place, 73, 102733. https://doi.org/10.1016/j.healthplace.2021.102733

Protocol ID


Export Variables
Variable Name Variable IDVariable DescriptiondbGaP Mapping
Structural Social Determinants of Health
Measure Name

Neighborhood Walking and Biking Environment

Release Date

December 14, 2022


Neighborhood Walking and Biking Environment encompasses the quality of the walking and biking environment and conditions, including safety, comfort, and convenience, near an individual’s neighborhood.


Walkability has been associated with increased walking behavior and physical activity, and is a protective factor for chronic diseases, such as obesity and diabetes, and depression. It has been found to have associations with cognitive functioning.


neighborhood walking and biking environment, Walking, walking behavior, obesity, diabetes, depression, cognitive functioning, physical activity, neighborhood, environment, built environment, automated audit, pedestrian audit, microscale, remote data collection, neighborhood built environment

Measure Protocols
Protocol ID Protocol Name
291001 Neighborhood Walking and Biking Environment

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