Out-of-the-box methods for satellite imagery processing
Project description
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 usefrom="..."
andto="..."
instead ofdate=(...)
- 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 🙏
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