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SAR Dual-Pol Small

rasterGeoTIFFEPSG:32633tinybundled

A tiny two-band Sentinel-1 IW GRDH-like scene (VV, VH): uint16 detected-amplitude DNs (not dB, not calibrated backscatter), zero-valued border-noise columns, sentinel NoData 0. Generated by geocase.raster.presets, whose constants are machine-checked against a real S1A GRD annotation.

Pixels of sar_dualpol_small, a 16x16 raster, with NoData in magenta
2 bands, 16x16 px, uint16, sentinel NoData. Rendered from the case's actual pixels, contrast-stretched for display; NoData is shown in magenta.
Property Value
Case ID sar_dualpol_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("sar_dualpol_small")
def test_sar_dualpol_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 dual-pol VV/VH SAR scene, its band ordering, and band naming.

Risk types covered

Expected behavior

Assertion Expected
expect_loadable yes
expect_crs yes
expected_epsg 32633
expect_nodata yes
expected_band_count 2
expected_dtype uint16
expected_shape [16, 16]
expected_nodata_value 0
nodata_convention sentinel
expected_compression deflate
expected_band_names VV, VH

Known answer

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

Quantity Value
Mean over valid pixels 154.4151785714
Mean including NoData 135.11328125
NoData pixels 64
Bounds (case CRS) [500000.0, 4499840.0, 500160.0, 4500000.0]

Required capabilities

  • load
  • multiband-read
  • band-name-check

Files

Browse this case on GitHub

Source and license

  • Source: geocase-synthetic
  • License: MIT

Tags

delivery:single-file geography:utm geotiff product:sar raster sar