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Using the STAC API

Data Explorer exposes its catalogue through the STAC API 1.1.0 (SpatioTemporal Asset Catalog). The API can search, filter and retrieve imagery metadata without using the web interface.

Main endpoint

https://explorer.piksel.big.go.id/stac

Why STAC​

STAC is an open standard for cataloguing geospatial assets. It offers:

  • A common interface. The same STAC clients can connect to Piksel and other catalogues such as Microsoft Planetary Computer, Earth Search and USGS Landsat.
  • Flexible filtering. CQL2 queries can filter by area, time, cloud cover and other fields exposed by the catalogue.
  • Broad tool support. STAC is supported by pystac-client, stackstac, odc-stac, QGIS and other geospatial tools.

Endpoint Structure​

EndpointPurpose
/stacRoot catalogue with links to the available collections
/stac/collectionsLists the available collections
/stac/collections/{product}Metadata for one collection
/stac/searchSearches for items across collections using filters
/stac/queryablesFields available for filtering

Example: Search with pystac-client​

Install pystac-client to access the STAC API from Python.

pip install pystac-client
from pystac_client import Client

catalog = Client.open("https://explorer.piksel.big.go.id/stac")

search = catalog.search(
    collections=["ls9_c2l2_sr"],
    bbox=[119.5, -9.5, 121.5, -8.0],
    datetime="2022-08-01/2022-08-31",
    limit=100,
)

for item in search.items():
    print(item.id, item.properties["datetime"])

This example searches for Landsat 9 Surface Reflectance imagery over East Nusa Tenggara in August 2022.

Advanced Filtering with CQL2​

Piksel's STAC API supports CQL2 (Common Query Language) for filters that cannot be expressed with the basic search parameters.

search = catalog.search(
    collections=["s2_l2a"],
    bbox=[95.0, -11.0, 141.0, 6.0],
    filter_lang="cql2-json",
    filter={
        "op": "and",
        "args": [
            {"op": "<=", "args": [{"property": "eo:cloud_cover"}, 20]},
            {"op": ">=", "args": [{"property": "datetime"}, "2024-01-01T00:00:00Z"]},
        ],
    },
)

This example searches for Sentinel-2 imagery across Indonesia with cloud cover of 20% or less from January 2024 onwards.

Open /stac/queryables to see the fields available for filtering.

Retrieve Asset Locations​

Each STAC item contains assets with locations for files such as Cloud-Optimised GeoTIFFs. The URI scheme and access method depend on the product and its storage location.

item = next(search.items())
red_band_url = item.assets["red"].href
print(red_band_url)

Libraries such as rioxarray, rasterio and odc-stac can use these asset locations when the relevant storage access is configured.

Pagination​

For large result sets, the pystac-client iterator handles pagination automatically:

for item in search.items():
    process(item)

Use limit to set the page size and max_items to cap the total number of items returned.

Further reading