Python and Javascript Tools

Sentinel Hub Javascript Library

The Sentinelhub-js is an open source Javascript library for seamless integration of Sentinel Hub and other similar EO web services in web or node.js applications. Read our blog post on the library, and visit the Sentinelhub-js GitHub page for full documentation.

Sentinel Hub Python Package

The sentinelhub Python package allows users to make OGC (WMS and WCS) web requests to download and process satellite images within your Python scripts. It supports Sentinel-2 L1C and L2A, Sentinel-1, Landsat 8, MODIS and DEM data collections.

Check out python libraries for Sentinel Hub and read about it in the blog entry. For more information see documentation of Sentinel Hub Python packages as well.

Watch our OGC webinar for a quick introduction on how to run OGC requests in Python, where to find example notebooks, and a quick example OGC notebook on wildfire detection.

If you are interested in cloud detection, check out the Sentinel Hub Cloud Detector for Sentinel-2 images in Python, S2cloudless.

Jupyter Notebook

Check out Jupyter Notebooks examples and read about it in the blog entry.

eo-learn

Check out eo-learn, a free Sentinel Hub library, that brings Python and remote sensing closer together!

Eo-learn is a collection of open source Python packages that have been developed to seamlessly access and process spatio-temporal image sequences acquired by any satellite fleet in a timely and automatic manner. Read about it in this blog post entry and check out our live webinar on eo-learn basics to get started. Visit eo-learn documentation for more information.

eo-learn also supports machine learning! Read our blog posts on eo-learn below.

• Scale-up your eo-learn workflow using Batch Processing API - September 17, 2020
• S2cloudness or how we processed 130 Bn km² of cloud masks in less than a day - May 12, 2020
• Semi-supervised learning in satellite image classification - February 18, 2020
• Land Cover Classification with eo-learn: Part 3 - February 14, 2019
• Land Cover Classification with eo-learn: Part 2 - January 9, 2019
• Land Cover Classification with eo-learn: Part 1 - November 5, 2018
• On cloud detection with multi-temporal data - October 14, 2019
• Introducing eo-learn - July 31, 2018
• Sentinel Hub Cloud Detector — s2cloudless - January 22, 2018
• Improving Cloud Detection with Machine Learning - December 19, 2017
• Next mission — Automated detection of land changes - January 3, 2017

See also our machine learning section on Medium.