What Are Workspaces?
Workspaces are based on technologies like S3 or Azure Blob Storage and provide an abstracted way to store and manage data. This feature gives users greater control over where results are saved and where data is loaded from.

How Does It Work?
Using Workspaces is straightforward and involves three steps:

1. Register or provision a workspace.
2. Export your results to the workspace.
3. Access previous results from workspaces using STAC.

For more details and the full documentation, visit: https://docs.openeo.cloud/workspaces/

This new functionality is designed to streamline collaboration and enable users to share processing results seamlessly with colleagues, collaborators, or the wider community through a simple, shareable URL.

Key Features of result sharing:

• Effortless Sharing: Generate a unique link to share your results.
• Interactive Visualization: Recipients can explore the shared data on an interactive map interface.
• In-Depth Insights: Access detailed metadata for comprehensive understanding of the data.
• Instant Downloads: Download the shared datasets with a single click.

This innovation makes it easier than ever to collaborate on Earth Observation projects, cutting-edge research, and complex data analysis. Whether you’re showcasing your latest processing workflows or enabling global cooperation, Result Sharing empowers you to make an impact with your work.

Experience the simplicity and power of sharing on the openEO Platform today. Visit openEO Platform to explore this new feature.

The Sen2Like processor was developed by ESA as part of the EU Copernicus program. It creates Sentinel-2 like harmonized (Level-2H) or fused (Level-2F) surface reflectances by harmonizing Sentinel-2 and Landsat 8/Landsat 9 to increase the temporal revisits. Based on the resulting L2F product, multiple indices can be computed, such as the NDVI and LAI. The fusion also involves the upscaling of Landsat 8/Landsat 9 data to Sentinel-2 resolution. With the new L2F data higher time-series resolution vegetation indices (such as NDVI, LAI, FAPAR, FCOVER) can be calculated.

OpenEO Platform users can now run the generation of high-temporal resolution vegetation indices through user-defined processes in the web editor.

Read more here: https://docs.openeo.cloud/usecases/crop-conditions/

OpenEO now supports the computation of Sentinel-2 Level-2F and Level-2H products. The harmonization/fusion process includes upscaling Landsat data to match the resolution of Sentinel-2 data. This enhancement opens up new possibilities for remote sensing applications. Learn more

Predict Forest Fractional Canopy Cover

OpenEO Platform can now predict Forest Fractional Canopy Cover using machine learning and high-resolution satellite imagery. This powerful feature allows users to analyze forest cover and monitor changes over time. Explore the details

Compute Maximum Flood Extents

OpenEO Platform users can now leverage the Global Flood Monitoring (GFM) service from EU’s Copernicus Emergency Management Service. Maximum flood extents for your area of interest can be easily computed using openEO Platform. For example, check out the flood-affected settlements in Pakistan here.

Stay tuned for more exciting updates from OpenEO Platform!

Furthermore, users now have the option to utilize adaptive thresholding functionality for enhanced vessel detection. This versatile approach can be extended to other datasets, offering valuable benefits to our users.

A big thanks to Sean Hoyal for the major contribution to the implementation!

Here we are looking back at a successful 2023 and all our accomplishments:

• continental scale crop mapping https://t.co/7Rb7sfxUDW
• world cereal data https://esa-worldcereal.org/en/about/worldcereal-products
• client side processing https://openeo.cloud/2023/09/01/client-side-processing/
• openEO processes dask repository https://github.com/Open-EO/openeo-processes-dask
• Sen2like integration https://sentinels.copernicus.eu/web/sentinel/sentinel-data-access/sentinel-products/copernicus-sentinel-2-msi-level-2h-and-level-2f-1
• training sessions and community repository https://github.com/Open-EO/openeo-community-examples
• marketplace launch https://openeo.vito.be/portal/catalogue

As we close the chapter on a remarkable 2023, we want to express our deepest gratitude to everyone who has been part of this journey. Your support and contributions have been instrumental in our success. We are excited about the future and look forward to continuing our work in the coming year. Here’s to more innovation, collaboration, and success in 2024! Thank you for being part of our story. Stay tuned for more updates and advancements from our team. Happy New Year!

We showed how both platforms offer common interfaces via python to interact with different data sources and processing backends. We also explained how to use the openEO API and the Pangeo python packages to create and execute workflows for various use cases, such as land cover classification, vegetation index calculation, and time series analysis.

For more information find our jointly developed training materials online here: https://github.com/pangeo-data/pangeo-openeo-BiDS-2023

We are happy to welcome you at our joint platform training together with Pangeo at the upcoming BiDS – Big Data from Space conference in Vienna on Monday, November 6th. https://www.bigdatafromspace2023.org/

Pangeo & OpenEO tutorial

The tutorials are divided in 3 parts:

1. Introduction to the Pangeo ecosystem (09:00 – 10:30)
2. Introduction to the OpenEO platform (10:30 – 12:00)
3. Scaling Big Data Analysis with Pangeo and OpenEO: Unlocking the Power of Space Data (14:00 – 18:00)

You can find a detailed finalised agenda on OpenEO’s training session (part 2) here: https://pangeo-data.github.io/pangeo-openeo-BiDS-2023/part2/agenda_and_links.html

All three parts of our training sessions will take place in room 0.49. Here is a map of the venue:

https://earthmonitor.org/wp-content/uploads/2023/09/OEMC-GW-Program_LV_PDF-version-1.pdf

Day 1: Wednesday October 4, 2023

• “European platforms to support the EU Green Deal” by Benjamin Schumacher, Christian Briese
• “Reproducible and Reusable Remote Sensing Workflows” by Edzer Pebesma

Day 2: Thursday October 5, 2023

• “OpenEO in action. Learn how to get started with openEO via the Web Editor, Python and R.” by Peter Zellner, Michele Claus

BiDS – Big Data From Space 2023 – Vienna, AT

https://www.bigdatafromspace2023.org/programme

Monday, November 6, 2023

• Satellite Event: Unlocking the Power of Space Data with Pangeo & OpenEO

Tuesday – Thursday, November 7 – 9, 2023

• various presentations and demonstrations

Pangeo and openEO offer a training session that will guide you through the Pangeo (http://pangeo.io/) and openEO (https://openeo.org/) ecosystems for developing efficient Big Earth science data pipelines. Emphasis will be put on the complementarities of the two ecosystems with a goal to teach attendees how to fully exploit both frameworks to run complex data workflows. Attendees will learn about open, reproducible, and scalable Earth science. The workshop is designed to help anyone interested in starting their journey with Pangeo and OpenEO while avoiding common pitfalls.

All the Python packages used during this training are Open-source. Sample datasets used in the tutorial are EO datasets that are freely available to everyone and can also be used for real scientific analysis.
The Training material is open-source (CC-BY-4) too.
The workshop aims at empowering attendees to learn new skills and build confidence in using them in their work. The tutorial will have work along with hands-on exercises to check the understanding of attendees. Multiple opportunities to ask questions and discuss with the Pangeo and openEO communities will be offered.

Expected audience:

This workshop will assume prior knowledge of the Python programming language and basics of Xarray. We recommend learners with no prior knowledge of Python or Xarray to get familiar with them, for instance using Software Carpentry training material (https://swcarpentry.github.io/python-novice-gapminder/), Project Pythia (https://foundations.projectpythia.org/core/xarray.html), the xarray tutorial (https://tutorial.xarray.dev), or Pangeo Galaxy Training material (https://training.galaxyproject.org/training-material/topics/climate/tutorials/pangeo-notebook/tutorial.html).

Agenda:
9:00 Welcome (5 minutes)
9:05 Introduction and Motivation (15 minutes)

Part-1: Pangeo
9:20 Overview of the Pangeo ecosystem (20 minutes)
9:40 Understanding Xarray to avoid common pitfalls (30 minutes)
10:10 Interactive Visualization with Hvplot (20 minutes)
10:30 Break (30 minutes)