---
id: pystac-ext-datacube
version: "2.2.1"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# pystac-ext-datacube — Datacube extension for PySTAC

License: permissive · Maintenance: active · Downloads: 4.0M/mo

## What it is and what it does

pystac-ext-datacube is a plugin for PySTAC that adds support for the Datacube Extension specification (v2.2.0). It allows you to describe datasets organized as multi-dimensional arrays—such as satellite imagery or climate data—by attaching dimension metadata (types, extents, values, coordinate systems) to STAC catalog items. This is useful when your data has structure beyond simple geographic bounds: time series, spectral bands, or other array dimensions that need formal representation.

The package targets Python 3.10 and later and depends only on pystac-core. It's versioned to match the extension specification it implements, so version 2.2.1 targets the v2.2.0 Datacube Extension schema. Use it when building or consuming STAC catalogs that describe raster or array-based data with explicit dimensional organization.

Use it for:

- Catalog satellite imagery time series with explicit temporal and spectral dimensions in STAC
- Describe climate or weather model output as multi-dimensional datacubes with coordinate metadata
- Build searchable STAC collections for gridded geospatial data with dimension-aware filtering
- Extend existing PySTAC workflows to include datacube-specific metadata for array-based datasets

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Extends PySTAC to support the Datacube Extension specification, enabling representation of multi-dimensional datasets with dimension types, extents, values, and reference systems.

Yes, if you are building or consuming STAC catalogs that describe multi-dimensional raster or array data. The package is actively maintained, has no known vulnerabilities, and integrates cleanly into PySTAC workflows. Install only if your use case requires explicit datacube dimension metadata; pystac-core alone may suffice for simpler catalogs.

## Install

pip install pystac-ext-datacube
uv add pystac-ext-datacube
poetry add pystac-ext-datacube

## Installing pystac-ext-datacube

Before you install: Low friction: pure Python wheel with a single runtime dependency on pystac-core. Actively maintained with a recent release and no known vulnerabilities.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.

Quickstart:

pip install pystac-ext-datacube

from pystac_ext_datacube import DatacubeExtension
from pystac import Item

# Extend an existing STAC Item with datacube metadata
item = Item(...)
DatacubeExtension.add_to(item)

Requires Python 3.10 or later; pystac-core must be installed as a runtime dependency.

Verify before relying:

- Whether this extension is required for your use case or if pystac-core alone suffices
- Compatibility with specific PySTAC versions beyond the stated Python 3.10+ requirement

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 4.0M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

pystac datacube extension, stac multi-dimensional data, datacube metadata catalog, raster dataset organization, stac dimension specification, pystac extension plugin, multidimensional array metadata, stac-extension, geospatial-metadata, datacube

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