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Data processing

Searching, automation,
chain processing


Our cloud infrastructure provides users with innovative methods to efficiently process and distribute data in a matter of seconds.

Thanks to the Data Explorer tool, users can order and process the data automatically using API or manually with GUI.

Depending on users experience and needs 4 complementary processing modes available to all registered users may be used

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Processing on the Virtual Machine

Users run a local processing chain on a dedicated VM instance (or a VM cluster using a tool like Kubernetes or Docker) interacting with the archive via local access interfaces (S3, NFS) or OGC interfaces (WCS/WMS/WMTS).

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Processing in the shared code development environment

Jupyter - users run their code interactively accessing the archive using preinstalled libraries (EOlearn, GDAL) or directly.

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Processing of data using external applications

Users of EO data processing software, eg. GIS, can access earth observation data using OGC interfaces (WCS/WMS/WMTS) by using data processing capabilities of the SentineHub to do data processing on the fly.

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Cluster computing

PGaaS - Product Generation as a Service - users run tasks in a serverless environment, triggering the next processing steps via an API operating on the archive using local access interfaces (S3, NFS) or OGC interfaces (WCS/WMS/WMTS). Our processing is container-based, so we are able to process up to several hundred thousand products for the customer in a very short time. Thanks to the cluster computing, users can improve their workflow.

Currently, a number of processors are available to automatically generate Analysis-Ready Data from Sentinel-1 (terrain-corrected backscatter, interferometric coherence) and Sentinel-2 (surface reflectance with sen2cor). Additional processors can be installed, delivered by the user in the form of a docker image. The use of the dockerized application allows for server-less data processing with its own workflow rules.

Sample automated processing can be found on CREODIAS S2scenes.

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