Caribbean Greenways & Trails (Southeast Blueprint Indicator)

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 ranging from improving human health, reducing traffic congestion and air and noise pollution, increasing property values, and generating new jobs and business revenue (ITRE 2018). The locations of greenways and trails are regularly updated through the open-source database OpenStreetMap. Input Data * [Southeast Blueprint 2023 subregions]: Caribbean * [Southeast Blueprint 2023 extent] * 2012 [NOAA Coastal Change Analysis Program (C-CAP) land cover files for the U.S. Virgin Islands] (St. Thomas, St. John, and St. Croix are provided as separate rasters), accessed 11-10-2022; learn more about [C-CAP high resolution land cover and change products] * 2010 [NOAA C-CAP land cover files for Puerto Rico], accessed 11-10-2022; learn more about [C-CAP high resolution land cover and change products] * [OpenStreetMap data “lines” layer, ]accessed 2-26-2023 A line from this dataset is considered a potential greenway/trail if the “highway” tag attribute is either bridleway, cycleway, footway, or path. In OpenStreetMap, a highway refers to “any road, route, way, or thoroughfare on land which connects one location to another and has been paved or otherwise improved to allow travel by some conveyance, including motorized vehicles, cyclists, pedestrians, horse riders, and others (but not trains)”. OpenStreetMap[®] is open data, licensed under the [Open Data Commons Open Database License] (ODbL) by the [OpenStreetMap Foundation] (OSMF). Additional credit to OSM contributors. Read more on [the OSM copyright page]. Mapping Steps The greenways and trails indicator score reflects both the natural condition and connected length of the greenway/trail. Natural condition 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 is calculated by averaging two measurements: local impervious and nearby impervious. Local impervious is defined as the percent impervious surface of the 30 m 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 a 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% * To create a percent impervious layer, start by converting the C-CAP land cover rasters for Puerto Rico (2 m resolution) and the U.S. Virgin Islands (separate downloads for St. Thomas, St. John, and St. Croix with 2.4 m resolution) from .img format to .tif using the Copy Raster function. * For each individual C-CAP layer, use the ArcPy Conditional function to make a binary raster assigning the impervious class a value of 100 (representing fully impervious) and all other classes a value of 0 (representing fully permeable). This mimics the data format of the 2019 National Land Cover Database (NLCD) used in the continental Southeast permeable surface indicator, which provides a continuous impervious surface value ranging from 0 to 100. Use focal statistics to calculate the percent of cells in a 30 m square that are identified as impervious in the C-CAP data, then reproject and resample the result to a 30 m resolution. * Use the Cell Statistics “MAX” function to combine the resulting four 30 m C-CAP impervious rasters. This creates an approximation of the percent developed impervious score from the 2019 NLCD. Connected length The connected length of the path is calculated using the entire extent of the potential greenways/trails dataset. A trail is considered connected to another trail if it is within 2 m of the other trail. Length thresholds are defined by typical lengths of three common recreational greenway activities: walking, running, and biking. The 40 km threshold for biking is 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 is set at 5 km (~3.1 mi) (Running USA 2017). The 1.9 km (1.2 mi) walking threshold is based on the average walking trip on a summer day (U.S. DOT 2002). * Using the statistics software R, download the OpenStreetMap data for Puerto Rico and the US Virgin Islands. * Select all lines from the OpenStreetMap data that have a highway tag of either footway, cycleway, bridleway, or path. These are all considered potential trails. * Removed all lines marked as private. * Identify lines from the potential trails that are tagged as sidewalks. Assign them a value of 1 in the indicator. Final scores If the potential greenway/trail was tagged as a sidewalk in the “other tags” field, it is given a value of 1 to separate sidewalks from what most people think of as a trail or greenway. If a pixel does not intersect a potential greenway/trail but is covered by the C-CAP landcover data, it is coded with a value of 0. Clip to the Caribbean Blueprint 2023 subregion. As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. Final indicator values Indicator values are assigned as follows: 6 = Mostly natural and connected for 5 to <40 km or partly natural and connected for ≥40 km 5 = Mostly natural and connected for 1.9 to <5 km, partly natural and connected for 5 to <40 km, or developed and connected for ≥40 km 4 = Mostly natural and connected for <1.9 km, partly natural and connected for 1.9 to <5 km, or developed and connected for 5 to <40 km 3 = Partly natural and connected for <1.9 km or developed and connected for 1.9 to <5 km 2 = Developed and connected for <1.9 km 1 = Sidewalk 0 = Not identified as a trail, sidewalk, or other path Known Issues * This indicator sometimes misclassifies sidewalks as greenways and trails because they are not tagged as a sidewalk in the OpenStreetMap data. * This indicator occasionally misclassifies driveways as “sidewalks and other paths” in places where they are not correctly tagged as private in OpenStreetMap. These typically appear as isolated pixels receiving a score of 1 on the indicator. * OpenStreetMap does not provide a complete inventory of greenways and trails in the U.S. Caribbean. Paths that are missing from the source data will be underprioritized in this indicator. For example, some trails are missing within National Wildlife Refuges. * This indicator includes trails and sidewalks from OpenStreetMap, which is a crowdsourced dataset. While members of the OpenStreetMap community often verify map features to check for accuracy and completeness, there is the potential for spatial errors (e.g., misrepresenting the path of a greenway) or incorrect tags (e.g., mislabeling a path as a footway that is actually a road for vehicles). However, using a crowdsourced dataset gives on-the-ground experts, Blueprint users, and community members the power to fix errors and add new greenways and trails to improve the accuracy and coverage of this indicator in the future. * This indicator sometimes underestimates greenway length when connections route under bridges or along abandoned dirt roads. Some of these issues have been fixed through active testing and improvement, but some likely remain. * Some greenways and trails continue along roadways that allow motorized vehicles, which are excluded from this indicator. As a result, certain trails may appear incomplete because the indicator only captures the sections dedicated for cyclists, pedestrians, and horseback riders. * 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. * This indicator doesn’t include Mona Island, even though there are important and popular trails, due to the lack of landcover data. Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email [hilary_morris@fws.gov]). Literature Cited American Planning Association. 2018. Recommendations for Future Enhancements to the Blueprint. [[https://secassoutheast.org/pdf/Recommendations-for-Future-Enhancements-to-the-Blueprint-FINAL.pdf]]. 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]]. National Oceanic and Atmospheric Administration, Office for Coastal Management. “C-CAP Land Cover Files for Puerto Rico and US Virgin Islands”. Coastal Change Analysis Program (C-CAP) High-Resolution Land Cover. Charleston, SC: NOAA Office for Coastal Management. Accessed November 2022. [[https://www.coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/]]. OpenStreetMap. Highways. Data extracted through Geofabrik downloads. Accessed February 26, 2023. [[https://wiki.openstreetmap.org/wiki/Highways]]. Running USA. 23 March 2017. U.S. Road Race Trends. Road race finisher total experiences slight year-over-year decline in 2016. [[https://web.archive.org/web/20170404232619/https://www.runningusa.org/2017-us-road-race-trends]]. U.S. Geological Survey (USGS). Published June 2021. National Land Cover Database (NLCD) 2019 Land Cover Conterminous United States. Sioux Falls, SD. [[https://doi.org/10.5066/P9KZCM54]]. U.S. Department of Transportation. National Highway Traffic Safety Administration and the Bureau of Transportation Statistics. 2002. National Survey of Pedestrian & Bicyclist Attitudes and Behaviors: Highlights Report. [[https://www.bts.gov/sites/bts.dot.gov/files/docs/browse-statistical-products-and-data/bts-publications/archive/203331/entire-1.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. 2018. 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. [[https://doi.org/10.1016/j.isprsjprs.2018.09.006]].