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Land Cover Small

rasterGeoTIFFEPSG:32633tinybundled

A categorical land-cover raster where 0 is NoData, not a class. Resampling or averaging categorical values silently invents classes that do not exist.

Pixels of landcover_small, a 16x16 raster, with NoData in magenta
1 band, 16x16 px, uint8. Rendered from the case's actual pixels, contrast-stretched for display; NoData is shown in magenta.
Property Value
Case ID landcover_small
Category raster
Format GeoTIFF
CRS EPSG:32633
Location Southern Italy / Sicily (synthetic, UTM 33N) — 15.00°E, 40.65°N → 15.00°E, 40.65°N
Test tier integration
Size class tiny
Storage class bundled
Redistributable yes
Loader rasterio
Status validated

Use this case

import pytest


@pytest.mark.geocase_case("landcover_small")
def test_landcover_small(geocase_case) -> None:
    data = geocase_case.load()
    assert data is not None

Use GeoCase in your tests

Install the complete set of vector, raster, and NetCDF dependencies:

pip install "geocase[all]"

View GeoCase on PyPI.

What this case checks

Confirm GeoCase preserves a categorical land-cover raster and its colormap. Every pixel is classified and the raster declares no NoData, because 0 doubling as both a class and a sentinel is a distinct risk that belongs in a case of its own rather than in a silent declaration here. That case is landcover_ambiguous_zero_small: the same scene with the ambiguity put back, so the pair isolates the collision (Plan 28, Plan 32).

Risk types covered

Expected behavior

Assertion Expected
expect_loadable yes
expect_crs yes
expected_epsg 32633
expected_band_count 1
expected_dtype uint8
expected_shape [16, 16]
expected_compression deflate
expected_band_names landcover
expected_colormap_present yes

Known answer

Computed from the actual bytes and gated against them. Grade your own output against these.

Quantity Value
NoData pixels 0
Bounds (case CRS) [500000.0, 4499840.0, 500160.0, 4500000.0]

Known consumer divergences

Disagreements already investigated on this case. If your reader reproduces one of these, it is catalogued — not a new finding.

titiler — titiler 0.24 / rio-tiler 8.x, GDAL 3.12.2

/preview.npy and /preview.tif return the dataset's colormap applied as RGB rather than the class codes, so the categorical values are unrecoverable from the response. Applies equally to landcover_ambiguous_zero_small.

Upstream: https://github.com/farzinashouri/geocase/blob/main/docs/plans/38-six-consumer-round-2-and-the-stac-adapter.md

Required capabilities

  • load
  • colormap-check

Files

Browse this case on GitHub

Source and license

  • Source: geocase-synthetic
  • License: MIT

Tags

categorical delivery:single-file geography:utm geotiff landcover product:landcover raster