openEO · Project

One Standard API to Access Any Earth Observation Cloud Platform

environmentTestedTRL 5

Imagine every satellite data provider speaks a different language, so every time you want to switch providers you have to rewrite all your code from scratch. openEO built a universal translator — a single open-source interface that lets you run the same analysis on any Earth Observation cloud platform using Python, R, or JavaScript. Think of it like USB-C for satellite data: one plug, every device. It means you can compare providers, avoid vendor lock-in, and get to your answers faster without becoming an expert in each platform's quirks.

By the numbers

consortium partners

countries represented

industry partners including SMEs

total project deliverables

use cases implemented with Sentinel data

client API languages (Python, R, JavaScript)

API layers (core, driver, client)

40%

industry participation ratio

The business problem

What needed solving

Companies using satellite data for agriculture, insurance, urban planning, or environmental monitoring are stuck with proprietary cloud platforms. Switching providers means rewriting all processing code, comparing offerings is nearly impossible, and vendor lock-in drives up costs. There is no standard way to run the same Earth Observation analysis across different cloud back-ends.

The solution

What was built

The project built an open-source 3-layer API: a core API for finding, accessing, and processing large EO datasets; driver APIs connecting to industry-operated cloud back-ends; and client APIs in Python, R, and JavaScript. Deliverables include a core API prototype with proof of concept, a Python client implementation, and early prototype back-ends, totaling 26 deliverables.

Audience

Who needs this

AgTech companies processing satellite imagery for crop monitoringInsurance firms using satellite data for damage and risk assessmentEnvironmental consultancies performing land-use or climate change analysisGIS software vendors integrating multiple EO data sourcesGovernment agencies managing natural resources with satellite monitoring

Business applications

Who can put this to work

Precision Agriculture

SME

Target: AgTech companies and large farming cooperatives

If you are an AgTech company dealing with crop monitoring across large regions and struggling to switch between satellite data providers — this project developed a standardized API that lets you run the same vegetation index analysis on any cloud back-end. With support for Sentinel-1 and Sentinel-2 time series and 3 client languages (Python, R, JavaScript), your developers write the code once and deploy it against any provider.

Insurance & Risk Assessment

enterprise

Target: Property and crop insurance companies

If you are an insurance company dealing with natural disaster assessment or crop loss verification and currently locked into one satellite data vendor — openEO provides a single interface to query multiple Earth Observation cloud platforms. The 4 use cases demonstrated with Sentinel-1 and Sentinel-2 time series show how the same analysis can run across different providers, letting you cross-validate results and reduce dependency on any single vendor.

Environmental Consulting

any

Target: Environmental monitoring and compliance firms

If you are an environmental consultancy dealing with land-use change detection or pollution monitoring and spending weeks adapting code for each client's preferred data platform — openEO's 3-layer API architecture (core, driver, client) lets your team write analysis workflows once and deploy them on any supported cloud back-end. The open-source Python, R, and JavaScript clients mean your existing staff can start using it without learning proprietary tools.

Frequently asked

Quick answers

What does it cost to use openEO?

openEO is an open-source interface, so the software itself is free. Your costs would come from the cloud computing resources you consume on whichever back-end provider you connect to. Based on available project data, no specific pricing model was defined within the project scope.

Can this handle large-scale industrial satellite data processing?

The project was specifically designed to work with cloud-based processing engines handling large volumes of Earth Observation data, including Sentinel-1 and Sentinel-2 time series. The architecture connects to multiple European and worldwide industry-operated cloud back-ends through driver APIs, so it is built for scale rather than desktop use.

What is the IP and licensing situation?

openEO was implemented as an open source community project. This means you can use, modify, and integrate the API and client libraries without licensing fees. The open-source nature also means no single vendor controls the roadmap.

Which programming languages and platforms are supported?

The project delivered client APIs in 3 languages: Python, R, and JavaScript. The core API connects to multiple cloud back-ends through driver APIs, and the project tested against several European Earth Observation cloud platforms.

How mature is this technology for production use?

The project delivered a core API prototype, proof of concept Python client, and early prototype back-ends. Four use cases based on Sentinel-1 and Sentinel-2 time series were implemented to demonstrate capability. With 26 total deliverables completed by project end in 2020, the technology moved well beyond concept stage.

Does this work with existing Earth Observation infrastructure?

Yes, that is the core purpose. The driver API layer was specifically built to connect to back-ends operated by European and worldwide industry. The project evaluated the interface against a set of relevant Earth Observation cloud back-ends, confirming interoperability.

Is there ongoing support and development?

The project ended in November 2020, but it was designed as an open source community project with a public website at openeo.org. Based on available project data, the consortium of 10 partners across 7 countries included 4 industry partners who had commercial interest in continued development.

Consortium

Who built it

The openEO consortium brings together 10 partners from 7 countries (AT, BE, CH, DE, IT, NL, SI), with a healthy 40% industry ratio — 4 of the 10 partners are from industry, and 4 are SMEs. The mix of 3 universities and 3 research organizations alongside industry players means the project had both scientific depth and commercial grounding. Led by Technische Universität Wien in Austria, the consortium spans key European EO markets. The strong SME presence suggests practical, market-oriented development rather than purely academic output.

TECHNISCHE UNIVERSITAET WIENCoordinator · AT
UNIVERSITAET MUENSTERparticipant · DE
VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK N.V.participant · BE
SINERGISE LABORATORIJ ZA GEOGRAFSKEINFORMACIJSKE SISTEME DOOparticipant · SI
ACCADEMIA EUROPEA DI BOLZANOparticipant · IT
MUNDIALIS GMBH & CO KGparticipant · DE
WAGENINGEN UNIVERSITYparticipant · NL
EODC EARTH OBSERVATION DATA CENTREFOR WATER RESOURCES MONITORING GMBHparticipant · AT
JRC -JOINT RESEARCH CENTRE- EUROPEAN COMMISSIONparticipant · BE

How to reach the team

The project was coordinated by Technische Universität Wien (Austria). SciTransfer can facilitate an introduction to the research team.

Order a report on this consortium See TECHNISCHE UNIVERSITAET WIEN profile →

Next steps

Talk to the team behind this work.

Want to explore how openEO can eliminate vendor lock-in for your satellite data processing? Contact SciTransfer for a tailored briefing and introduction to the research team.

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