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The Polar Thematic Exploitation Platform (Polar TEP) provides a complete working environment where users can access algorithms and data remotely, obtain computing resources and tools that they might not otherwise have, and avoid the need to download and manage large volumes of data. This new approach removes the need to transfer large Earth Observation data sets around the world, while increasing the analytical power available to researchers and operational service providers.

Polar TEP Capabilities

Polar TEP make satellite data (Sentinels, Landsat, and other providers) easily accessible for browsing or analysis within the cloud or within the user’s own environment.

Polar TEP hosts a collection of algorithms that leverage different EO data sources. Users can develop their own applications in the Python language using Jupyter Notebooks.

Monitoring of the polar regions using machine learning is supported by the advance computing infrastructure of Polar TEP that hosts training data, algorithms, and results.

Headless execution or Conda environments are used to provide processing with minimal execution overhead and computing resources scaled to the current demand.

Polar TEP Latest Developments

Polar TEP provides tools to assist researchers in participating in all the facets of open and reproducible science, covering Input Data, Analysis, Collaboration, Results, and Dissemination.

Polar TEP provides support for educators to facilitate teaching. A custom environment for each course provides student and instructor accounts, special datasets, custom libraries, and a custom landing page.

Polar TEP works in collaboration with EOPORT to provide access to Sentinel 1 data in near-real-time (NRT) – within minutes of acquisition compared to the approximately three hours in our normal processing chain.

Polar TEP users can now access the CryoSat-2 CryoTEMPO-EOLIS point and gridded products in Jupyter Notebooks.
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Polar TEP Service offering

Machine Learning Environment

Polar TEP has implemented the MLFlow platform to support machine learning activities.

Processor Development Environment

Polar TEP provides two paths to support processor development. An Interactive Development Environment and a customized VM

Processor Execution Environment

Polar TEP provides a number of built-in processors, or users can develop their own and implement them in the Polar TEP Processor Execution Environment through the use of headless execution or Docker containers. 

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Algorithm Hosting Environment

Users can host their own applications on a VM within the Polar TEP environment.

Processor Integration Support Service

Integration of processors into the Polar TEP Execution Environment is documented and examples are provided.  Additional customized support is available.

Polar Data Management Support Service

The Polar TEP team includes world-class expertise on all aspects of the management and use of data.  They can provide advice to groups struggling with concepts and issues.

Example Applications

Polar Data Ecosystem

Polar TEP is an integral part of the wider polar data ecosystem.
A number of other polar data platforms are collaborating with Polar TEP.