A Python package for simple STAC queries
GitHub: https://github.com/cloudsen12/easystac
Documentation: https://easystac.readthedocs.io/
PyPI: https://pypi.org/project/easystac/
Conda-forge: https://anaconda.org/conda-forge/easystac
SpatioTemporal Asset Catalogs (STAC) provide a standardized format that describes geospatial information. Multiple platforms are using this standard to provide clients several datasets. Platforms such as Planetary Computer, Radiant ML Hub and Google Earth Engine use this standard, however, only Google Earth Engine provides a fully easy API that is transparent for clients.
easystac
is a Python package that provides users of STAC objects as well as clients from Planetary Computer and Radiant ML Hub
with an easy API that is transparent for them, implementing Google Earth Engine-like methods
and classes to query, explore and convert STAC assets to xarray
objects.
Some of the easystac
features are listed here:
- Simple authentication for Planetary Computer and Radiant ML Hub.
- Access to STAC collections from Planetary Computer and Radiant ML Hub.
- Earth Engine-like classes such as ImageCollection, including filtering methods.
- Compatibility with xarray.
Check the simple usage of easystac
here:
import easystac as es
from geojson import Point
geom = Point([-76.3,3.4])
E84_S2_L2A = (es.ImageCollection('sentinel-s2-l2a-cogs')
.fromSTAC('https://earth-search.aws.element84.com/v0')
.filterBounds(geom)
.filterDate("2021-01-01","2022-01-01")
.getInfo(resolution = 10,assets = ["B02","B03","B04"]))
In the case of specialized STAC objects, we have created special modules for Planetary Computer:
import easystac.planetary as pc
from geojson import Point
pc.Authenticate()
pc.Initialize()
geom = Point([-76.1,4.3])
S2 = (pc.ImageCollection("sentinel-2-l2a")
.filterBounds(geom)
.filterDate("2020-01-01","2021-01-01")
.getInfo(resolution = 10))
This principle applies also for Radiant ML Hub.
import easystac.radiant as rd
rd.Authenticate()
rd.Initialize()
S1floods = (rd.ImageCollection("sen12floods_s1_source")
.filterDate("2019-01-01","2019-01-05")
.getInfo(epsg = 4326,resolution = 0.0001))
Install the latest version from PyPI:
pip install easystac
Upgrade easystac
by running:
pip install -U easystac
Install the latest version from conda-forge:
conda install -c conda-forge easystac
Install the latest dev version from GitHub by running:
pip install git+https://github.com/cloudsen12/easystac
The project is licensed under the MIT license.