Sky kit

Out-of-the-box satellite imagery processing.

Adding fun to satellites coolness 😎

Warning: This is still a work in progress. Please do not use in production, yet.

Seriously, what is it? 🧐

Sky kit is an ensemble of methods to ease satellite imagery processing to developers and data scientists. Working with any satellite providers, should be as easy as:

from skykit.providers import ProviderName

Install 🚀

As with any python package, pip is your friend:

pip install skykit

Usage 🎡

Quick Start

The following code download tiles of Sentinel-1 satellite that includes Paris (France), from 01/03/2019 to 08/03/2019:

from datetime import date
from skykit.providers import Sentinel

sat = Sentinel(username="xxx", password="yyy")
# Add source="Sentinel-2" if you want to query Sentine-2
# Not specifying a source will default to Sentinel-1

tiles = sat.query(
    coordinates=(2.349014, 48.864716), # Paris (FR) coordinates
    dates=(date(2019,3,1), date(2019,3,8))
    )

len(tiles) # returns 12

sat.download(tiles) # Tiles will be grouped in a .zip file

In the previous example, the tiles variable will include meta information of every tile returned from Sentinel-1 query.

Todo 🔭

• Add Landsat provider
• Create Tile class to create a uniform use of tiles, no matter which provider
• Ease working with tiles meta data
• Allow querying using a polygon
• Allow querying using an address
• Use friendly dates (like text: "26/03/2019"), of use from="..." and to="..." instead of date=(...)
• Allow working on specific bands. Something like:

tile = tiles[0]
image = tile.get('b04') # or tile.b04() ???

• What about tests? Seriously! <-- ⚠ URGENT

This list is not exhaustive.

Contribution 💪

Please suggest contributions using Github's Pull Requests.

License 🤮

Read the LICENSE.txt file.

Thanks 🙏