Welcome to UKIS-pysat’s documentation!

The UKIS-pysat package provides generic classes and functions to query, access and process multi-spectral and SAR satellite images.


Download satellites data from different sources (currently Earth Explorer, SciHub, STAC), deal with and structure metadata.


Work with you local satellite data files and read information out of file names and metadata files. Currently, focusing on Sentinel-1.


Reading satellite data and performing simple, but cumbersome tasks. This is just a layer on top of rasterio for stuff we often need. It can very well be that using rasterio directly is often the better choice.


Here’s an example about some basic features:

from ukis_pysat.data import Source
from ukis_pysat.file import get_sentinel_scene_from_dir
from ukis_pysat.members import Datahub, Platform
from ukis_pysat.raster import Image

# connect to Copernicus Open Access Hub  and query metadata
src = Source(Datahub.Scihub)
meta = src.query_metadata(
    date=("20200101", "NOW"),
    aoi=(11.90, 51.46, 11.94, 51.50),
    cloud_cover=(0, 50),
for item in meta:  # item is now a PySTAC item
    uuid = item.properties["srcuuid"]

    # download geocoded quicklook and image
    src.download_quicklook(product_uuid=uuid, target_dir="/users/username/tmp")
    src.download_image(product_uuid=uuid, target_dir="/users/username/tmp")


# get sentinel scene from directory
with get_sentinel_scene_from_dir("/users/username/tmp") as (full_path, ident):
    with Image(full_path.join("pre_nrcs.tif")) as img:
        # scale the image array, having one band
        img.arr = img.arr * 0.3

Dimension order

The dimension order can be set upon initialization and you have to choose between first (bands, rows, columns), being raster shape needed for rasterio, or last (rows, columns, bands), being image shape used by most image processing libraries. Default is first. Compare with the documentation of rasterio. UKIS-pysat uses rasterio internally and the dimension order is always reshaped to first (bands, rows, columns) if the dimension order has been set as last. If the image was initialized with dimension order last, the result will be reshaped to last (rows, columns, bands) when calling img.arr.

Altering the array replaces all bands. If it is intended to alter a particular band, the remaining bands should be copied.

STAC API Item IO Concept

To enable reading from different types of file systems (similar to PySTAC), it is recommended that in the __init__.py of the client module, or at the beginning of the script using ukis_pysat.data, you overwrite the STACAPI_IO.read_item_method with function that read and write however you need. The following is an example for a on premise S3 environment:

from pystac import Item
from ukis_pysat.stacapi_io import STACAPI_IO

def on_premise_s3_url_method(feature, root_bucket="dem"):
   """the href is build like /collections/*collection_prefix*/items/*item_prefix*

   At some environments we will need to give back the href according to this method.
   item = Item.from_dict(feature)
   href = item.get_self_href()
   stripped_href = href.replace(r"collections/", "").replace(r"items/", "")

   return Item.from_file(f"s3://{root_bucket}{stripped_href}/{item.id}.json")

STACAPI_IO.read_item_method = on_premise_s3_url_method

Environment variables

To use ukis_pysat.data and to download from the respective Datahub you need to set the credentials as environment variables.

For EarthExplorer that’s:
For SciHub that’s:

Indices and tables