offline land/sea lookup (a Trifold library)

Mode

Points: classify many lon/lat points. Route: classify a polyline and see which land/sea stretches it crosses.

Route (polyline)

Pick an example, or hit Draw on map and click to drop points; click Finish (or the button again) to classify.

Your own points / route

Open CSV / GeoJSON…

CSV: lon,lat[,name] per line (or a header naming lat/lon columns in either order). GeoJSON: a FeatureCollection of Points (Points mode) or a LineString (Route mode). Files stay on your machine.

OSM coastal refinement exact OSM polygon test wherever the coastline crosses a cell (downloads once)

Off: coastal answers use the bundled land-area fraction. On: near-exact coastline. Watch how the counts, confidence and lookup rate change.

Debug layers source coastline (NE, follows the refinement setting)

Click anywhere on the map to see the level-10 triangle and its classification.

JavaScript (browser or Node)

import { LandCheck } from "./landcheck.mjs";

// Node: bundled file · browser: fetch the 182 KB dataset
const lc = await LandCheck.fromFile();              // Node
const lc = await LandCheck.fromUrl("landsea_L10.tfls"); // browser

lc.isLand(24.7536, 59.437);   // true  (lon, lat)
lc.check(-0.1276, 51.5072);
// { land: true, kind: 'land', confidence: 1,
//   landFraction: 1, cell: 'TFA95BM', refined: false }

// a whole route: land/sea segments with distances
lc.checkPolyline([[24.75,59.44],[18.07,59.33]]).segments;
// [{land:true,kind:'land',...,distanceKm,fraction}, ...]

Python (stdlib only)

from landcheck import LandCheck

lc = LandCheck()                       # bundled data
lc.is_land(24.7536, 59.4370)           # True
lc.check(-0.1276, 51.5072)
# LandResult(land=True, kind='land', confidence=1.0,
#   land_fraction=1.0, cell='TFA95BM', refined=False)

# vectorised: ~2.8 µs/point with numpy
lc.is_land_batch(lons, lats)

# a whole route: land/sea segments with distances
lc.check_polyline([(24.75, 59.44), (18.07, 59.33)]).segments

Canonical index

Any Trifold cell at level ≤ 10 maps to addr64 >> 39, a 25-bit integer where a level-l cell covers exactly 4^10−l consecutive indices. The whole classification becomes run-length intervals.

TFLS format · 182 KB

153,884 runs as varint(gap), varint(len·2|coastal) + a 4-bit land fraction per coastal cell, zlib-compressed. Level-agnostic: the same tooling serves an L8 (~30 KB) or L12 (~3 MB) variant.

Lookup path

Pure-float point location (no dependencies, bit-identical to the SDK) descends 10 subdivision levels, then one binary search over the run starts. ~0.8 µs in Node, ~13 µs in pure Python, ~2.8 µs batched with numpy.

OSM refinement · TFLR

OSM simplified land polygons clipped to every cell crossed by either source coastline, quantized to a cell-local 16-bit grid (~0.1 m), with zigzag-varint rings and the even-odd rule. The OSM polygon test can override Natural Earth land, sea or fraction answers in those cells.

Batch · 100,000 points per call

Singular · one point per call

Trifold base

38,016 samples/s

Trifold + OSM refinement

37,231