Upgrading the sentinelhub Python package
Whether you are a devoted user of Sentinel Hub, or someone interested in an easy way to automate accessing and processing of Sentinel-2 satellite images, there are exciting news for you.
The EO research team at Sinergise is happy to announce an upgrade release of the sentinelhub Python package. With this release, we have open-sourced many tools previously used internally only. The new version allows users to seamlessly make requests from Sentinel Hub OGC web services, download and process images within their Python scripts.
In order to request data from the OGC web services, you would need a Sentinel Hub account, and you can create a free trial account to access services for one month. An account is not needed to download the raw data from the AWS web service. You can then unleash the power within the package with a simple
$ pip install sentinelhub.
Some of the major features introduced in the new release are as follows:
- support for Sentinel-Hub’s OGC web services requests, namely Web Map Service (WMS) and Web Coverage Service (WCS), which adds to the existing support for downloading images from the Amazon Web Service (AWS) and converting products to .SAFE format;
- support for standard and custom multi-spectra layers, such as unprocessed bands (B01, B02, …, B08, B8A, …, B12), true color imagery, NDVI, or any other product which you can create with the Sentinel Hub Configuration Utility;
- support for multi-temporal requests, where all available images for the given location within the given time interval are returned;
- support for cloud coverage filtering;
- support for different Coordinate Reference System requests;
- support to read and write downloaded images to disk in the most common image and data formats.
Head to our GitHub source repository to find out all the functionalities of the package. You can read documentation on installation, dependencies, and on the implemented methods on our Read The Docs homepage.
An important part of the package are the examples, where Jupyter notebooks describe how to implement basic OGC requests, how to download data from AWS, or how to create time-lapses like the one below:
We will very soon dedicate a blog-post on the creation of time-lapses, along with code to generate them, so stay tuned to find out more.
Being an open-source project, your feedback and contributions are key to the continuous development and improvement of the package. Please report bugs, create issues, and merge requests to improve the functionality and usability of the package. If you needed any assistance, or just want to get in touch, do not hesitate to contact us. We are always happy to help.