Datasets:

uffda-ag
/

usda-cdl-2025-30m-cog

Error code:   StreamingRowsError
Exception:    DecompressionBombError
Message:      Image size (22857960226 pixels) exceeds limit of 20000000000 pixels, could be decompression bomb DOS attack.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2365, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2284, in _apply_feature_types_on_example
                  decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2214, in decode_example
                  column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1517, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
                  image = PIL.Image.open(bytes_)
                          ^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3482, in open
                  im = _open_core(
                       ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3466, in _open_core
                  _decompression_bomb_check(im.size)
                File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3365, in _decompression_bomb_check
                  raise DecompressionBombError(msg)
              PIL.Image.DecompressionBombError: Image size (22857960226 pixels) exceeds limit of 20000000000 pixels, could be decompression bomb DOS attack.

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USDA NASS Cropland Data Layer 2025 — 30 m COG (EPSG:3857)

The 2025 USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), reprojected from the official national release and repackaged as a Cloud-Optimized GeoTIFF for streaming access via GDAL, rasterio, or Titiler.

Coverage: contiguous United States (CONUS). Nominal resolution: 30 m (EPSG:5070 source); ~38 m Web Mercator units / ~28–33 m ground resolution at CONUS latitudes after reprojection. Classes: all 256 CDL classes; original USDA NASS color table preserved. Published by: UFFDA — open US farmland intelligence.

License note. The cc0-1.0 tag reflects that this work carries no conditions on use. The underlying CDL is a US Government work under 17 U.S.C. § 105 (public domain by statute, not by UFFDA's dedication). UFFDA's reprojection and COG packaging add no copyrightable authorship. This is not an official USDA distribution — see the source links below.

Source & provenance

Source dataset: United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS), 2025 Cropland Data Layer. Released 2026-02-27. USDA-NASS, Washington, D.C. Available at: https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php

What UFFDA changed: Faithful nearest-neighbor reprojection of the USDA NASS 2025 CDL from EPSG:5070 (Albers Equal Area, 30 m) to EPSG:3857 (Web Mercator, ~38 m WM units / ~28–33 m ground resolution at CONUS latitudes); all 256 CDL classes and the original color table are preserved; individual pixel values at parcel-boundary cells may shift by ≤1 pixel due to grid-alignment differences between the two projections — inherent to nearest-neighbor reprojection, not a content error.

No pixel values were reclassified or altered.

Methodology: EPSG:5070 → 3857 via GDAL/rasterio (nearest-neighbor resampling), COG tiling via rio-cogeo, deflate compression, uint8 dtype, palette/color table preserved. Source GeoTIFF production lineage: USDA NASS ArcGIS Pro national CDL pipeline (dated 2026-03-24/25 in source metadata).

Disclaimer

Per USDA NASS: the CDL "is provided 'as is' and the USDA NASS does not warrant results you may obtain using the Cropland Data Layer" nor "any conclusions drawn from these data." 2025 CDL overall crop accuracy: 75.4% (kappa 0.712). UFFDA makes no additional warranty.

This is not an official USDA distribution. For the authoritative source and the most current release, see USDA CroplandCROS and CropScape.

Per USDA NASS: "no farmer reported data are derivable from the Cropland Data Layer." This dataset contains no personal information.

How to use

GDAL / command line

# Read metadata (no full download — COG range-request)
gdalinfo /vsicurl/https://huggingface.co/datasets/uffda-ag/usda-cdl-2025-30m-cog/resolve/main/2025_30m_cdls_cog_3857.tif

# Warp a small AOI to GeoTIFF
gdal_translate \
  /vsicurl/https://huggingface.co/datasets/uffda-ag/usda-cdl-2025-30m-cog/resolve/main/2025_30m_cdls_cog_3857.tif \
  my_aoi.tif \
  -projwin -9830000 5200000 -9750000 5140000

rasterio (Python)

import rasterio
from rasterio.windows import from_bounds

url = (
    "https://huggingface.co/datasets/uffda-ag/usda-cdl-2025-30m-cog"
    "/resolve/main/2025_30m_cdls_cog_3857.tif"
)

with rasterio.open(url) as src:
    # Read a small window (range request — no full download)
    window = from_bounds(-9830000, 5140000, -9750000, 5200000, src.transform)
    data = src.read(1, window=window)
    print(data.shape, src.crs)

Titiler (tile server)

https://titiler.opengeohub.org/cog/tiles/WebMercatorQuad/{z}/{x}/{y}
  ?url=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fuffda-ag%2Fusda-cdl-2025-30m-cog%2Fresolve%2Fmain%2F2025_30m_cdls_cog_3857.tif

Citation

@misc{uffda_cdl2025_cog,
  title        = {{USDA NASS Cropland Data Layer 2025 -- 30 m COG (EPSG:3857)}},
  author       = {{UFFDA}},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/uffda-ag/usda-cdl-2025-30m-cog},
  note         = {Reprojection of: United States Department of Agriculture,
                  National Agricultural Statistics Service (USDA-NASS),
                  2025 Cropland Data Layer. Released 2026-02-27. Washington, D.C.
                  Available at https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php}
}

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