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Methodology

How CaveFinder ranks the terrain

CaveFinder reads public LiDAR elevation maps, finds the pits and sinks that look like cave entrances, and ranks them so you know where to walk first. This page explains how to read a scan, how accurate the ranking is, how spots are found, which elevation data it uses, and what it cannot do.

Reading a scan

Best first

Every scan lists its spots best first: the first spot is the one the model finds most cave-like in that scan. Start at the top and work down.

Under each spot is a one-line reason, including how many of the detection tests flagged it. No single clue decides the ranking. Depth, shape, how open the hollow is, and how many tests agree are weighed together.

A retention basin in a car park is a textbook depression, so spots on built land, water, cropland, bare ground, lawn or park, or sandstone and shale are ranked lower. The exception is a stream sink, because a swallet is exactly what a caver wants to see. A spot beside a road or track is flagged but not ranked lower: culverts and ditches are cave-shaped, and we would rather show you the fact than guess at a penalty.

Accuracy

How often the real cave makes the list

Top-10 35% of the time the real cave is among the ten highest-ranked spots.
Top-25 47% of the time it is in the top twenty-five.
Top-50 60% of the time it is in the top fifty.
within 50 m of the entrance · 2,691 known US caves in states the model never trained on · September 2026

Each test puts a known cave somewhere inside a search area of about one square kilometre and checks where it lands in the ranked list.

Why these caves. The model was tested only on known caves it had never seen, so the figures reflect ground that was new to it. Testing it on caves it learned from would make the numbers look better than a new user would see.

>What these numbers do not promise. They measure how often a known cave reaches the top of the list, not how many of the other spots are caves. CaveFinder ranks; it does not confirm. That still takes boots on the ground.

How spots are found

Several tests, one ranking

Each scan runs a set of detection tests over the elevation map. Each test looks at the ground a different way. A model trained on known caves then combines what the tests found into one ranking. Specific weights and thresholds are not published.

01
Closed basins
Fills the elevation map the way water would and flags every hollow that would hold a puddle, including a small inner pit at the bottom of a larger sink, which often marks the actual entrance.
02
Lower than the surroundings
Compares each point with the ground around it at several distances, and measures how enclosed it is. Catches hollows and overhung entrances that basin filling alone can miss.
03
Landform shape
Classifies the ground into standard landform types (ridge, slope, valley, hollow, pit). Pits and hollows are the cave-relevant ones.
04
Small-scale relief
Strips away the broad shape of the hillside to expose small features, a technique borrowed from archaeological LiDAR work that shows subtle entrances on gentle ground.
05
Shape and setting
Depth, width, roundness and slope of each spot, and how busy each test is in the area: a test that flags hundreds of spots counts for less than one that flags a few. Long ditches and drainage scars score lower than round, deep pits.
Elevation data

What goes in

Every elevation number CaveFinder uses comes from a public source. The app picks the best source for your scan area automatically, and you can override it.

  • United States: USGS 3D Elevation Program (3DEP): 1 m LiDAR where published, which covers most of the country; 10 m elsewhere.
  • Slovenia: ARSO national LiDAR, 1 m.
  • Canada: NRCan HRDEM, 1 m where surveyed.
  • France: IGN LiDAR HD, 1 m where flown.
  • New Zealand: LINZ LiDAR, 1 m where flown.
  • Everywhere else: global satellite elevation (Copernicus 30 m; ALOS 30 m and SRTM 90 m are alternatives you can pick).

Resolution matters. At 1 m a sinkhole a few metres across is clearly visible; at 30 m it can vanish inside a single pixel, so scans on global data find far less. The app shows which source a scan used and warns when only coarse data is available. Pro users can also upload their own elevation file.

Known caves

Known caves never change a score

The Known Caves (public data) map layer shows cave records that are already published publicly, credited on the Conservation page, never private cave surveys. It is an overlay only. It does not raise or lower any spot's score, so a spot that lands on a known cave was found from the terrain alone.

Spots from your own scans can be saved to your GPS. CaveFinder does not publish cave locations or share one user's scans with another.

Limits

What it cannot do

  • Doorways in cliffs and bluffs. The detectors look for pits and sinkholes. An entrance in a vertical face is not a depression and will not be found, which is why a famous cave can sit in a scan that reads low.
  • Openings smaller than the data. On 1 m elevation data a narrow crawl may occupy a pixel or two. Where only coarser data exists, less is visible and the app says so on the scan.
  • Very large or very deep shafts. Airborne scanning measures the ground surface, so a shaft the survey never saw into is not in the elevation data.
  • Anything underground. Everything here is inferred from the shape of the surface.
  • Confirming a cave. Even a top-ranked spot can be a filled sinkhole with no opening, an old quarry pit or a tree-fall hole. The list is a shortlist to walk, not a marker on a door.
  • Permission to go there. A spot on the map says nothing about who owns the land. Ask before you walk it.
Contact

Questions about methodology

Karst researchers, NSS members, and land managers with technical questions can reach the author at help@cavefinder.app. Reasonable methodology questions get a real reply, not a form letter.

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