A parks department evaluating a new trailhead usually weighs land availability, cost and access. Those factors arrive with numbers already attached. GIS handles a harder version of the same question well, and gets asked it far less often: what makes that trail usable for someone rebuilding a daily routine after treatment?
That’s a spatial problem. It just doesn’t get modeled as one very often.
The work involved is ordinary. Suitability modeling, service area analysis, proximity scoring, a slope screen off a DEM. Nothing exotic. What changes is the weighting scheme and which datasets get pulled into it.
Turning a Soft Criterion Into Weighted Layers
“Recovery-friendly” reads like a value statement. Inside a geodatabase it becomes something more boring and more usable, a weighted set of conditions that either exist at a location or don’t.
CDC’s parks and recreation guidance is a reasonable place to start on weighting. It reports that people living closer to a park, and feeling safer in it, are more likely to walk or bike there, and that less than half of the U.S. population lives within half a mile of a park. That page was last reviewed in January 2025, so the number is a standing planning baseline rather than a current-year count. Two mappable concepts fall out of it anyway: distance decay and coverage gaps.
The catch is what that half mile gets measured through. A straight-line buffer will happily report that a housing block sits 2,400 feet from a greenway while saying nothing about the four-lane arterial in between. Network distance along the actual walkable path is slower to compute and considerably more honest. CDC’s own guidance points park professionals toward mapping tools for this kind of assessment, so the spatial framing is already familiar in park planning.
The Layers That Earn Their Place
A workable model doesn’t need dozens of inputs. It needs the few that change the answer:
- Green space and canopy cover, from land cover rasters or NDVI
- Walkable route networks, with grade and crossing quality carried as attributes
- Transit stops and service frequency, since a park you can’t reach after 7pm isn’t really available
- Travel time to outpatient and primary care sites
- Traffic volume and noise surfaces
- Amenity clustering, meaning whether one location puts a trail, a field and a library inside the same short walk
Clustering is worth weighting on its own, though the evidence for how much weight is thinner than the intuition suggests. Several complementary amenities inside a short walk may support more repeat trips than a single destination does, and that’s a reasonable modeling assumption, not a settled finding. Run it as a sensitivity test before it drives a ranking.
Travel time to care is a separate input, and pairing it with recreation potential is a modeling choice rather than a validated composite. Recreation-potential models and healthcare-accessibility models are both established approaches, so building the two into one framework is technically feasible. Whether the combined score predicts anything useful is a question for the specific study area.
Slope Screening Runs Against the Trail Standards, Not Every Route Type
Accessibility gets written in policy language and then built in inches and percentages. The Access Board’s guidelines for outdoor developed areas set trail-specific criteria: a 36-inch minimum clear tread width, and a running slope of up to 5 percent for any length.
Steeper terrain gets handled in shorter segments, with resting intervals at the top and bottom of each. On trails, segments steeper than 5 percent and up to 8.33 percent are capped at 200 feet, segments above 8.33 percent and up to 10 percent at 30 feet, and segments above 10 percent and up to 12 percent at 10 feet. No more than 30 percent of a trail’s total length may exceed 8.33 percent, and running slope may never exceed 12 percent.
Those figures don’t travel to other route types. Under the cited ABA provisions, outdoor recreation access routes, which connect elements inside trailheads, picnic and camping facilities and viewing areas, allow only 50 feet in the 5 to 8.33 percent band and cap running slope at 10 percent. Establish the route type before applying any threshold, or the screen returns the wrong answer confidently.
These are ABA standards for covered federal facilities and federally funded or leased facilities, where applicable. State and local governments and private entities may have separate obligations under the ADA and applicable state or local requirements, so the ABA trail figures should not be treated as a universal ADA standard.
Thresholds are what GIS handles well. A DEM at adequate resolution can screen which candidate corridors appear capable of accommodating a 5 percent grade and which are likely to require substantial grading. Running that screen before anyone draws a plan set saves a difficult conversation later.
Cross slope is a different problem. The trail provisions hold cross slope to 2 percent on concrete, asphalt and board surfaces, with up to 5 percent allowed on other materials where drainage requires it. A DEM screens terrain-level slope, so compliance on a finished constructed surface generally needs site survey or design data. Some things still get measured on foot.
Where the Site Plan Meets the Programming
A well-sited park does nothing on its own. It gets used because something organizes people to use it, and that organizing activity is what turns a suitability score into actual trips.
One adjacent field is therapeutic recreation, which uses recreation and leisure activity to support health, functioning and quality of life. Treatment programs sometimes build that kind of activity into the daily schedule rather than leaving it to chance. The activity mix inside Conifer Park’s therapeutic recreation program runs to gardening, organized sports, creative sessions and hands-on activities designed to build interests that can be pursued in sobriety.
For planners the relevance is practical, if unproven at the scale most siting models work at. A facility that schedules outdoor group activities at recurring times may create predictable patterns of park use, and that demand assumption can be tested against observed counts before it feeds a weighting.
Perceived Safety Is the Layer That Maps Badly
Whether a place feels safe can shape whether a park gets used, and it’s the hardest factor on this list to represent spatially. Streetlight point data, sightline analysis and reported incident locations can provide useful proxies, and each captures a slice of it at best. None is a validated measure of perceived safety, and stacking all three into one composite invites more confidence than the inputs support.
Lighting is at least tractable. Fixture locations, a rough illuminance falloff, and you can see which segments of a loop trail go dark first. Incomplete, but still a map worth having.
What the Layers Won’t Tell You
Land cover says a parcel is green. It says nothing about whether the gate is locked, whether the path floods every spring, or whether people living nearby feel welcome walking into it. NDVI is a vegetation index, not a usability index, and treating it as one produces confident maps of places nobody goes.
So the model produces a shortlist. The shortlist gets walked. Then residents, clinicians and recreation staff argue with it, and that’s usually when the useful information turns up.
None of this waits on new technology. The inputs already exist, mostly free: parcel files, LiDAR-derived elevation, GTFS feeds, national land cover products. What’s missing more often is the habit of asking the question in spatial terms to begin with.