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How Camprtron Sources and Ranks Camping

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Camprtron ranks dispersed (free) and developed (reservable) camping across all 50 states. Every rating traces back to a named public dataset, joined and analyzed with a PostGIS spatial pipeline. Most of that data is public-domain government data. One source, OpenStreetMap, is community-mapped, and the list below says what it supplies. Nothing is invented. Where a data source is thin or missing, we say so on this page rather than fill the gap with a guess.

Data sources

Camprtron draws from these public datasets:

  • USFS Motor Vehicle Use Maps (MVUM): road access classification and seasonal travel windows for National Forest System roads. This is the backbone of every access-type rating, and the source of the seasonal closure windows.
  • USFS Enterprise Data Warehouse: National Forest System trails and the Forest Service recreation-site layer that marks designated dispersed sites.
  • Recreation Information Database (RIDB): developed campground locations, facility attributes, and reservation status from recreation.gov.
  • Protected Areas Database of the United States (PAD-US): public-land ownership and managing agency, used to confirm where dispersed camping is permitted. Where a BLM surface-management layer is more detailed, that layer is used instead.
  • Wilderness Connect: designated Wilderness boundaries, used to keep drive-in dispersed corridors out of Wilderness.
  • NHDPlus High Resolution: rivers, streams, and water bodies, used for water-proximity scoring.
  • National Hydrography Dataset (NHD): the same water layers where NHDPlus High Resolution is not published (Alaska).
  • USGS Geographic Names Information System (GNIS): named summits, used for peak-proximity scoring.
  • USGS The National Map: campground and trailhead points that fill gaps in the other sources.
  • US Census TIGERweb: full-detail state boundaries, used to decide which state each site is in.
  • State agency data: state park campgrounds, state forest roads, state trail inventories, and fishing-water classifications, where a state publishes them.
  • OpenStreetMap: community-mapped camp sites on public land, public campgrounds the government sources miss, mountain-bike trails, and the towns and highways used for privacy scoring. This is the one community-mapped source; the app labels a dispersed site that comes from community mapping.

Curious how much of each dataset we actually serve? Our data coverage page breaks down the exact campground, state-park, and dispersed-site counts loaded for every supported state.

You can also take the data with you. The dataset download page publishes the public field set as CSV or JSON under a Creative Commons Attribution licence, free for any use including commercial, provided you credit Camprtron.

The spatial pipeline

Source layers are loaded into PostGIS and reprojected to a projected coordinate system chosen for each region, so distances are measured in meters on the ground rather than degrees on a globe: NAD83 / Conus Albers (EPSG:5070) for the 48 contiguous states, NAD83 / Alaska Albers (EPSG:3338) for Alaska, and NAD83 / UTM zone 4N (EPSG:26904) for Hawaii. Every candidate site is then enriched with nearest-neighbor distances to peaks, perennial water, trails, and roads. All measurements are stored in canonical units (meters, feet, and minutes) and converted only at display time, so a unit mix-up cannot silently corrupt a score.

The scoring model

Each site receives a composite score from 0 to 1, computed from seven weighted criteria:

  • Peak proximity: distance to named summits
  • Water proximity: distance to perennial water
  • Privacy: isolation from roads and neighboring sites
  • Fishing: access to fishable water
  • Hiking: trail access
  • Mountain biking: access to bike-legal trails
  • Drive time: estimated travel time from your trip origin

Dispersed and developed camping are ranked as two separate lists, because they answer different questions and should not be forced to compete on the same axis. When a criterion does not apply to a search, its weight is redistributed proportionally across the remaining criteria, so a missing factor never shows up as a misleading zero.

A small number of hard gates run before ranking. A water-required search drops sites with no perennial water within range, and the range gate drops sites outside the minimum and maximum distance or drive time you set. Access type is never a gate. We rank a rough road lower for a passenger car, but we never hide it.

Drive time

Drive time is an estimate, not a turn-by-turn route. Camprtron builds it from three parts: a fixed allowance to get out of the origin area, a highway leg whose distance is inflated for the terrain of the destination region, and a slower access leg on the final roads to the site. The estimate costs nothing to compute and gives the same answer every time. Every result is labeled as estimated, so no result is presented as a precise routed time.

Access type and rig suitability

Every site carries an access-type label derived from MVUM road classification: passenger car, high clearance, or 4×4 capable. When you tell the app about your vehicle, Camprtron turns its clearance, drivetrain, and tires into a capability tier, compares that tier against each site’s access type, and returns a suitability verdict. That verdict is computed fresh for every search. It is always a warning and never a filter, so you stay in control of what you are willing to drive. This page and the public site show only the access-type label; rig-specific verdicts live in the app.

Coordinate precision and what stays private

Public-facing coordinates on this site are rounded to roughly 1 km precision (two decimal places). That is enough to show which area a site sits in for search and discovery, while exact campsite coordinates, trip-specific ranks, rig verdicts, and live availability remain inside the app. This split is deliberate. General location is a discovery detail; a precise pin is a trip-planning detail.

Known limitations

Honest data means naming its edges:

  • Seasonal closures are derived, not live. No statewide live closure feed exists for National Forest roads, so closure windows are inferred from MVUM seasonal road designations. Always confirm current conditions with the managing ranger district before a trip.
  • Fishing uses a water proxy. Where no state fishing-water layer is integrated, or where it is sparse, fishing scores fall back to nearest perennial water, which favors sites near streams and lakes generally rather than confirmed stocked fisheries.
  • Some signals are still being built out. Per-site elevation bands, cell-coverage estimates, and full site descriptions are in progress and are simply omitted rather than approximated when a backing source is not yet integrated.

Freshness

Reference layers are refreshed from their source feeds through an ETL pipeline that reloads RIDB, MVUM, hydrography, and land-status data, then recomputes derived signals such as access tiers and seasonal windows. The “last updated” date at the top of this page reflects the most recent methodology revision.