What is STAC? ¶

According to the official specification, “Spatio-Temporal Asset Catalog (STAC) specification is a common language for describing and cataloging spatio-temporal assets” to facilitate indexing and discovery. The specification comprises four components:

1. STAC Item - A single spatio-temporal asset as a GeoJSON feature with datetime and links
2. STAC Catalog - JSON file organizing STAC Items through linked structure
3. STAC Collection - Extended catalog with metadata including extents, licensing, and keywords
4. STAC API - RESTful endpoint enabling searchable access to items

Why use STAC? ¶

STAC addresses challenges with large-scale, multi-source spatio-temporal datasets. While filename-based organization works for small datasets, larger collections from varied sources present inconsistencies in naming formats and properties. STAC standardization enables straightforward comparison across these datasets.

STAC Tools ¶

Multiple tools support STAC workflows. Kartoza developed the STAC API Browser for QGIS. This article focuses on PySTAC, “a library for working with STAC in Python 3.”

Installing PySTAC ¶

Core installation:

pip install pystac

With optional components:

pip install pystac[validation] pystac[orjson]

Reading a STAC Catalog ¶

Example code demonstrates loading catalog metadata:

from pystac import Catalog, get_stac_version

root_catalog = Catalog.from_file('./example-catalog/catalog.json')
print(f"ID: {root_catalog.id}")
print(f"Title: {root_catalog.title or 'N/A'}")
print(f"Description: {root_catalog.description or 'N/A'}")

Output:

• ID: landsat-stac-collection-catalog
• Title: STAC for Landsat data
• Description: STAC for Landsat data

Crawling STAC Collections ¶

List collections within a catalog using get_collections():

collections = list(root_catalog.get_collections())
collection = root_catalog.get_child("landsat-8-l1")

Crawling STAC Items ¶

Recursively retrieve all items using get_all_items():

items = list(root_catalog.get_all_items())

Modifying or Writing to STAC ¶

Update items and persist changes locally:

item_to_update = root_catalog.get_item("LC80140332018166LGN00", recursive=True)
item_to_update.common_metadata.instruments = ["LANDSAT"]
new_catalog.normalize_and_save(tmp_dir)

Wrap-Up ¶

STAC enables efficient browsing of large spatio-temporal datasets. Multiple tools exist for creation, modification, reading, and visualization across platforms.