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stactools-usda-cdl

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A stactools package for USDA Cropland Data Layer (CDL) product.

The USDA Cropland Data Layer (CDL) is a crop-specific land cover data layer. The data is provided at 30 m resolution over the Contiguous United States (CONUS) from 2008 to Present. The USDA CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, the ISRO ResourceSat-2 LISS-3, and the ESA SENTINEL-2 sensors collected during the current growing season.

This package can generate STAC files from TIFF files that link to the Cloud-Optimized GeoTiff (COG) files.

Item types

There are three primary item types in this dataset:

  • cropland: Yearly crop-cover classification dataset, optionally with a confidence product.
  • cultivated: A boolean raster describing whether a given pixel was "cultivated" in the target year.
  • frequency: A set of four rasters that describe how often four main crop types were planted in the past fourteen years.

Examples

There is an example collection at examples/collection.json.

Tiling

While this stactools package can create items for the original, CONUS-wide GeoTIFFS, it also supports tiling the data into more manageable sized Cloud-Optimized GeoTIFFs. To tile a GeoTIFF:

stac usda-cdl tile --size 500 tests/data-files/2021_30m_cdls.tif tiles

If you have a bunch of hrefs to existing tiles, you can use stac.create_items_from_tiles to intelligantly partition those hrefs by product type and tile:

from stactools.usda_cdl import stac
from pathlib import Path
hrefs = list(Path("tests/data-files/tiles").glob("*.tif"))
items = stac.create_items_from_tiles(hrefs)

Installation

pip install stactools-usda-cdl

Command-line Usage

Use stac usda-cdl --help to see all subcommands and options.

Collection

Create a collection:

stac usda-cdl create-collection collection.json

Item

Create an item:

stac usda-cdl create-item /path/to/source/file.tif item.json

Get information about all options for item creation:

stac usda-cdl create-item --help

Contributing

We use pre-commit to check any changes. To set up your development environment:

pip install -e .
pip install -r requirements-dev.txt
pre-commit install

To check all files:

pre-commit run --all-files

To run the tests:

pytest -vv

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USDA Cropland Data Layer

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