openEO platform provides intuitive programming libraries to process a wide variety of earth observation datasets. This large-scale data access and processing is performed on multiple infrastructures, which all support the openEO API. This allows use cases from explorative research to large-scale production of EO-derived maps and information. 

Enabling simplicity

Implementing large EO processing workflows commonly requires engineers and scientists to invest a major part of their effort in data management: maintaining file-based data collections, running pre-processing pipelines...

Providing transparency

Many scientific programming libraries offer manifold functionality to users in their own development environment or within cloud-based analytical environments.

Pixel to continental scalability

Traditional file-based systems greatly limit the flexibility and efficiency to exploit the EO data repositories. openEO Platform provides users with full flexibility for accessing and manipulating data.

Community & Federation

Researchers often work in siloed environments - too little code is reused and the wheels are too often reinvented. openEO platform fosters an inspirational development environment that.

Clients

openEO Platform can be used in a wide variety of programming languages and environments:

JupyterLab

For interactive prototyping, programming and visualization, our JupyterLab instance is well-suited to run Python-based workflows in an IDE-like environment. Required libraries and useful tools are installed out of the box, so that users can get started with little overhead. It’s the most convenient way for Python programmers to interact with openEO Platform.

openEO Platform Editor

The Editor is an interactive and visual user interface in the Browser. It gives easy access to all functionalities without requiring programming experience. Users can get an overview of available data sets and processes or monitor the status of their processing workflows. A block-based workflow editor helps beginners without programming experience to run their use cases.

JavaScript

Primarily for use in browser-environments, but also includes support for NodeJS and TypeScript

Get started arw
Python

Development in all Python environments, including advanced support for Jupyter

Get started arw
R Language

R Language support with nice integration into RStudio and RMarkdown

Get started arw


Note: The R client is not officially supported, but should support most functionality.

Use Cases

openEO platform is constantly evolving with new features that become available to users. New features result from a set of ten initial use cases that each bring new openEO process to provide the required analytical functionality. The following use cases have already been implemented:

Service Offering

openEO platform aims at covering the needs of real-world EO users and experts. Therefore, we invite you to join the development and evolution process! Play around with the platform using the free trial or apply for Network of Resources Sponsoring for running larger use cases. We'd love to hear your feedback and get to know the features and capabilities that you need! The following offers are available right now:

Free Trial

free


You want to try and "play" with the Platform. You don't have a specific use case in mind and want to see how it works.


Valid for: 30 days

Register

Network of Resources Sponsoring

free


You want to use openEO Platform for longer running projects or get specific support from our development team for your workflows. Limited funding (5,000 EUR) for non-ESA projects.


Valid as per sponsoring request

Apply

Commercial

paid


If you are not eligible for NoR sponsoring, projects can pruchase our services via the Network of Resources.


Valid as per Purchase

Apply

It is possible to apply for Network of Resources Sponsoring after your free trial period if you find openEO Platform useful for a newly developed idea.

Processing capabilities

openEO Platform offers processing capabilities for a wide variety for Earth Observation workflows (e.g., Optical, SAR). All data is exposed as data cube to the user so that the complexity of file handling and data loading is abstracted away and users can immediately start with implementing their processing workflows.