GSC Sentinel-2 PDGS OCD - Emits - ESA

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GSC Sentinel-2 PDGS OCD Issue 1 Revision 2 (draft) - 25.07.2010 GMES-GSEG-EOPG-TN-09-0008 page 270 of 350 3) The operator sets up the AI function according to the configuration received. Some use cases are presented according to this operation scenario: A new collaborative archive centre with is incorporated to the PDGS federation. Thus the data retention policy map for that centre and others is updated according to the overall PDGS objectives; A change on the data retention policies decided by the POM (e.g. The POM may decide to increase data retention time of transient stored products, for instance the level 1a products or on the contrary limit it according to defined mission objectives. 6.8.3.2 Data Archive & Inventory This scenario accounts for the autonomous data archiving activities performed by the AI function according to configuration. The AI function works in a data-driven manner fed by different PDGS functions; for instance the DPC and DC functions feed the archive with new data resulting of the processing and data circulation activities respectively. The AI function performs all the archiving and inventory activities automatically unattended based on new inputs. Theses are the main operations performed during the archival of new data: 1) The AI function autonomously detects the new data to be archived in the in-tray(s); 2) The AI function autonomously archives and inventories the new data according to the configured archive rules; 3) The relevant metadata of new archived data is extracted and inventoried accordingly. The archive and inventory operations integrity must be ensured preventing for any data loss due to errors, missing disk space, etc; 4) The AI function autonomously notifies and updates the PDGS/DAX function with the configured metadata of the new archived data; 5) The AI function autonomously reports on the performed operations (archival, removal, extraction, inventory, etc) to the PDGS/MPA function (through the MCC function). Some use cases are presented according to this operation scenario: New MSI production (e.g. level-0 production) generated by the DPC function is archived; Received X-Band HKTM data is archived (i.e. S2HKTM products); Auxiliary products (e.g. POD products) received via DC function are archived for later usage; 6.8.3.3 Discovery of Archived Data This scenario accounts for the AI function autonomous archived data discovery capabilities offered to other PDGS functions (i.e. DPC and DAG functions) to provide a view on the archived PDIs. The data discovery operations are performed locally to the AI function inventory according to the defined query interface. ESA UNCLASSIFIED – For Official Use © ESA The copyright of this document is the property of ESA. It is supplied in confidence and shall not be reproduced, copied or communicated to any third party without written permission from ESA.
GSC Sentinel-2 PDGS OCD Issue 1 Revision 2 (draft) - 25.07.2010 GMES-GSEG-EOPG-TN-09-0008 page 271 of 350 This scenario is always initiated by the other PDGS functions when searching for archived product data items based on some inventoried data (e.g. data-type, time segments, etc). The query interface relies on the inventory metadata associated to every product data item archived. Accordingly the AI function supports queries based on the inventoried metadata. The following steps are identified for this operation scenario: 1) A PDGS function generates a query and passes it to the AI function; 2) The AI function processes the query request, thus it checks syntax & semantics with respect to the defined interface. Once the request has been validated, the AI function based on the metadata inventoried, looks for the matching PDIs; 3) The AI function generates the query result (i.e. the list of product data items matching the request) and provide it to the originator request according to defined query interface. Some use cases are presented according to this operation scenario: The DPC function queries on the required PDIs for a given processing job. By the query result, the DPC function knows whether the required data for such processing job is available; The DAG function queries to the AI inventory for some product data items availability according to the user requests. 6.8.3.4 Archived Data Retrieval This scenario accounts for the autonomous data retrieval activities as requested by other PDGS functions. The following steps are identified for this operation scenario: 1) The DPC function requests for required input data for a given processing job according to the data retrieval interface; 2) The AI function processes the retrieval request, validates by checking syntax & semantics; 3) The AI function leaves the PDIs on the defined out-tray. The main use cases are presented according to this operation scenario: The DPC function relies on the AI function for the management and high performance data retrieval operations needed for the subsequent processing activities. In this scenario, due to the required archival/retrieval operations performance, the DPC and the AI function interact locally through a specific dedicated interface; The DAG function requests for the archived product data items needed to build a userproduct. The DAG function can interact remotely with the AI function due to lower data retrieval timeliness constraints with respect to the processing activities. ESA UNCLASSIFIED – For Official Use © ESA The copyright of this document is the property of ESA. It is supplied in confidence and shall not be reproduced, copied or communicated to any third party without written permission from ESA.
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[RD-33] Sentinel-2 MSI - Level 2A A
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LES LGS Land Equipped Sites Local G
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3.5.2 MULTI-SPECTRAL INSTRUMENT CHA
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Table 4-5 Radiometric image quality
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Product- Type On-Line retention Off
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Product- Type Identifier S2MSI0 S2M
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5 PDGS DESIGN GSC Sentinel-2 PDGS O
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○ Effective processing resources
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Two main mapping services have been
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The requirement on the cloud covera
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