SARLAND

SARLAND = SARLO-80 + Copernicus LCM-10 land cover (10 m), aligned to the SAR frame.

This dataset reuses the exact SAR samples from ONERA/SARLO-80 (complex UMBRA SAR crops at ~80 cm + SICD metadata + captions) and adds, for every sample, a 10 m land cover layer from the Copernicus Land Cover Map at 10m – Annual V1 (LCM-10) product, reprojected so that it is overlayable on the SAR crop using the optical→SAR transform derived from the SICD.

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Structure

WebDataset format, organized into chunks and shards:

train/
  chunk_000/
    shard-00000.tar
    shard-00001.tar
    ...
  chunk_001/
    ...

Each sample (shared key {id}, an 8-digit index) contains:

Member	Content
{id}.sar.npy	Complex SAR (SLC), identical to SARLO-80
{id}.sar.png	SAR amplitude (slant range), uint8
{id}.sicd.xml	SICD metadata (acquisition geometry)
{id}.meta.json	Metadata (crop, projection, captions, incidence angles…)
{id}.landcover.npy	New. (2, H, W) uint8 = [label, mask], aligned to the SAR frame
{id}.landcover.png	New. Colorized land cover, RGBA (alpha = validity mask)

• label: per-pixel LCM-10 class code (see legend), on the SAR crop pixel grid (~80 cm).
• mask: 1 = valid land cover pixel, 0 = invalid / outside footprint.
• The land cover is resampled onto the SAR grid via an affine warp (INTER_NEAREST), which keeps crisp class boundaries.

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Land cover: product and legend

Product: Copernicus CLMS — Land Cover Map at 10m – Annual V1 (LCM-10), 2020 base year. Sentinel Hub BYOC collection (CDSE) 828f6b20-8ffd-48f8-a1da-fefd271456db, band LCM10. 11 primary classes (FAO Land Cover Classification System):

Code	Class	RGB
10	Tree cover	(0, 100, 0)
20	Shrubland	(255, 187, 34)
30	Grassland	(255, 255, 76)
40	Cropland	(240, 150, 255)
50	Built-up	(250, 0, 0)
60	Bare / sparse vegetation	(180, 180, 180)
70	Snow and ice	(240, 240, 240)
80	Permanent water bodies	(0, 100, 200)
90	Herbaceous wetland	(0, 150, 160)
95	Mangroves	(0, 207, 117)
100	Moss and lichen	(250, 230, 160)

LCM-10 is in beta status on the CLMS side (final validation ongoing).

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Loading

import io, json
import numpy as np
from PIL import Image
from huggingface_hub import hf_hub_download
import webdataset as wds

local_tar = hf_hub_download(
    repo_id="SoleneDEBUYSERE/SARLAND",
    repo_type="dataset",
    filename="train/chunk_000/shard-00000.tar",
)

ds = wds.WebDataset(local_tar, shardshuffle=False)
sample = next(iter(ds))

sar_complex = np.load(io.BytesIO(sample["sar.npy"]), allow_pickle=False)
sar_amp     = np.asarray(Image.open(io.BytesIO(sample["sar.png"])).convert("L"))
meta        = json.loads(sample["meta.json"].decode("utf-8"))

# Land cover aligned to the SAR frame
lc = np.load(io.BytesIO(sample["landcover.npy"]), allow_pickle=False)  # (2, H, W)
label, mask = lc[0], lc[1]
lc_rgba = np.asarray(Image.open(io.BytesIO(sample["landcover.png"])).convert("RGBA"))

print("SAR amplitude:", sar_amp.shape)
print("Land cover   :", label.shape, "classes:", np.unique(label[mask > 0]))

SAR + land cover overlay

import numpy as np

amp = sar_amp.astype(np.float32)
p1, p99 = np.percentile(amp, [1, 99])
amp = np.clip((amp - p1) / (p99 - p1 + 1e-6), 0, 1)
base = np.stack([amp] * 3, axis=-1)

alpha = 0.45
valid = mask > 0
overlay = base.copy()
overlay[valid] = (1 - alpha) * base[valid] + alpha * (lc_rgba[..., :3][valid] / 255.0)

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Production

The dataset is generated by dataset_webformat_hf_SARLAND.py (+ landcover_lcm10.py): for each sample, the WGS84 corners of the SAR crop are computed from the SICD, the LCM-10 land cover is requested over the footprint via the Sentinel Hub Process API (CDSE), colorized, then warped into the SAR frame with a 3-point affine (optical→SAR). See the associated code repository.

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Licenses and attribution

Composite dataset — components have distinct licenses:

• Land cover (LCM-10): Copernicus Land Monitoring Service, implemented by the JRC and the EEA on behalf of the European Commission. CC BY 4.0, free of charge and usable for any purpose. Product: Land Cover 2020 (raster 10 m), global, annual – version 1. DOI: https://doi.org/10.2909/602507b2-96c7-47bb-b79d-7ba25e97d0a9
• SAR: imagettes derived from UMBRA data; refer to the UMBRA terms of use and to the source dataset ONERA/SARLO-80.

If you use this dataset, please cite the Copernicus/CLMS and UMBRA sources, as well as this dataset.