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rle-python

rle-python is the backend-agnostic core for IUCN Red List of Ecosystems (RLE) analysis. It provides the RLE data model (Ecosystems, AOOGrid, EOO), the assessment business logic, and local + cloud-file (gs://, s3:// via fsspec) data access. It has no Earth Engine dependency — Earth Engine support lives in the optional rle-python-gee distribution (import rle.gee).

Check your installed version with rle --version, and list the data-access backends registered in your environment with rle backends (see CLI & backends).

Everything imports under the shared rle namespace:

from rle.core import Ecosystems, make_aoo_grid, make_eoo

eco = Ecosystems.from_file("ecosystems.geojson", ecosystem_column="ECO_NAME")
print(make_aoo_grid(eco).compute().aoo_km2)   # Area of Occupancy (km²)
print(make_eoo(eco).compute().area_km2)       # Extent of Occurrence (km²)

What’s inside

Glossary

Red List of Ecosystems
The IUCN global standard (RLE) for assessing the risk of ecosystem collapse, organised around five criteria (A–E) and a set of threat categories. Often abbreviated RLE.
Ecosystem
A distribution dataset for one or more ecosystem types, loaded through the Ecosystems class from vector files, GeoParquet (local or cloud), in-memory GeoDataFrames, or Cloud Optimized GeoTIFFs.
EOO
Extent of Occurrence — the area of the convex hull enclosing all occurrences of an ecosystem, reported in km². Feeds RLE Criterion B1.
AOO
Area of Occupancy — the number of occupied cells on a standard 10×10 km grid (each cell covers 100 km²). Feeds RLE Criterion B2.
Functional Group
A level of the IUCN Global Ecosystem Typology (e.g. T1.1) that an ecosystem belongs to. Ecosystem codes such as T1.1.1 extend the functional group code.
Backend
A data-access implementation (e.g. local vector, GeoParquet, COG) advertised through the rle.backends entry-point group and discoverable via the registry.