This cultural resource indicator measures both the natural condition and connected length of greenways and trails to characterize the quality of the recreational experience. Natural condition is based on the amount of impervious surface surrounding the path. Connected length captures how far a person can go without leaving a dedicated path, based on common distances for walking, running, and biking.
Reason for Selection
This indicator captures the recreational value and opportunities to connect with nature provided by greenways and trails. Greenways and trails provide many well-established social and economic benefits (ITRE 2018).
Monitoring ApproachLocations of greenways and trails are regularly updated through the open source database OpenStreetMap. Data on condition are updated every 5 years through the National Land Cover Database (NLCD).
– OpenStreetMap data “roads” layer (accessed 11/21/2019): A line from this dataset is considered a potential greenway/trail if the value in the “fclass” attribute is either bridleway, cycleway, footway, or path.
– 2016 National Land Cover Database 2016 (NLCD): Percent developed imperviousness
The greenways and trails indicator score reflects both the natural condition and connected length of the greenway/trail.
Natural condition is based on the amount of impervious surface surrounding the greenway/trail. Since perceptions of a greenway’s “naturalness” are influenced both by the immediate surroundings adjacent to the path, and the greater viewshed, natural condition was calculated by averaging two measurements: local impervious and nearby impervious. Local impervious is defined as the percent impervious surface of the 30 meter pixel that intersects the trail. Nearby impervious is defined as the average impervious surface within a 300 m radius circle surrounding the path (note: along that 300 m stretch of trail, we only count the impervious surface within a 45 m buffer on either side of the trail, since pixels nearer the trail have a bigger impact on the greenway/trail experience). The natural classes are defined as follows:
3 = Mostly natural: average of local and nearby impervious is <=1%
2 = Partly natural: average of local and nearby impervious is >1 and <10%
1 = Developed: average of local and nearby impervious is >=10%
The connected length of the path is calculated using the entire extent of the potential greenways/trails dataset. Length thresholds were defined by typical lengths of three common recreational greenway activities: walking, running, and biking. The 40 km threshold for biking was based on the standard triathlon biking segment of 40 km (~25 mi). Because a 5K is the most common road race distance, the running threshold was set at 5 km (~3.1 mi) (Running USA 2017). The 1.9 km (1.2 mi) walking threshold was based on the average walking trip on a summer day (U.S. DOT 2002).
As a final step, if the potential greenway/trail did not have a value in the “name” field, it was considered a sidewalk and given a value of 1 to separate sidewalks from what most people think of as a trail or greenway. If a pixel did not intersect a potential greenway/trail, it was coded with a value of 0.
Final indicator values
Indicator values were assigned as follows:
7 = Mostly natural and connected for >40 km (high)
6 = Mostly natural and connected for 5-40 km or partly natural and connected for >40 km
5 = Mostly natural and connected for 5-1.9 km, partly natural and connected for 5-40 km, or developed and >40 km
4 = Mostly natural and connected for <1.9 km, partly natural and connected for 1.9-5 km, or developed and connected for 5-40 km
3 = Partly natural and connected for <1.9 km or developed and connected for 1.9-5 km
2 = Developed and connected for <1.9 km
1 = Sidewalk or other path (low)
0 = Not a greenway, trail, sidewalk, or other path
– Greenway length is sometimes underestimated when connections route under bridges or along abandoned dirt roads. Most of these issues have been fixed through active testing and improvement, but some may remain.
– Greenway segments that are not named in OpenStreetMap are scored too low. The name attribute is currently used to separate greenways and trails from sidewalks. Most of these issues have been fixed through active testing and improvement, but some may remain.
– Sidewalks that are not greenways and trails, but are named in OpenStreetMap, may be mistakenly included as greenways and trails. The name attribute is currently used to separate greenways and trails from sidewalks. Most of these issues have been fixed through active testing and improvement, but some may remain.
– When calculating nearby impervious for one greenway, if there’s another greenway within 300 m, impervious surface from the different but overlapping greenway buffer area is also used to compute natural condition. This is an unintended issue with the analysis methods. Investigation into potential fixes is ongoing.
– The indicator doesn’t currently include areas where future greenways are planned.
Disclaimer: Comparing with Older Indicator Versions
There are numerous problems with using South Atlantic indicators for change analysis. Please consult Blueprint staff if you would like to do this (email firstname.lastname@example.org).
American Planning Association. 2018. Recommendations for Future Enhancements to the Blueprint. http://www.southatlanticlcc.org/wp-content/uploads/2018/08/Recommendations-for-Future-Enhancements-to-the-Blueprint-FINAL.pdf.
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Institute for Transportation Research and Education (ITRE) & Alta Planning and Design. February 2018. Evaluating the Economic Impact of Shared Use Paths in North Carolina: 2015-2017 Final Report. https://itre.ncsu.edu/wp-content/uploads/2018/03/NCDOT-2015-44_SUP-Project_Final-Report_optimized.pdf
Running USA. 23 March 2017. U.S. Road Race Trends. Road race finisher total experiences slight year-over-year decline in 2016. https://www.runningusa.org/2017-us-road-race-trends
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Xian, G., Homer, C., Dewitz, J., Fry, J., Hossain, N., and Wickham, J., 2011. The change of impervious surface area between 2001 and 2006 in the conterminous United States. Photogrammetric Engineering and Remote Sensing, Vol. 77(8): 758-762.http://www.mrlc.gov/downloadfile2.php?file=Preferred_NLCD11_Impervious_Surface_Citation.pdf
Yang, Limin, Jin, Suming, Danielson, Patrick, Homer, Collin G., Gass, L., Bender, S.M., Case, Adam, Costello, C., Dewitz, Jon A., Fry, Joyce A., Funk, M., Granneman, Brian J., Liknes, G.C., Rigge, Matthew B., Xian, George, A new generation of the United States National Land Cover Database—Requirements, research priorities, design, and implementation strategies: ISPRS Journal of Photogrammetry and Remote Sensing, v. 146, p. 108–123, at https://doi.org/10.1016/j.isprsjprs.2018.09.006.
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Potential Metadata Source