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 272 of 350 6.8.3.5 Archived Data Retention & Clean-up This scenario accounts for the autonomous archived data retention and clean-up operations. The AI function according to the defined archive rules configuration, autonomously performs the required clean-up operations, data circulation operations (e.g. data circulation to other centres), etc. The data retention policy is part of the archive rules configuration. Accordingly it is possible to define the archive time period (i.e. according to data ageing) for each data-type managed. The following steps are identified for this operation scenario: 1) The AI function verifies autonomously for new applicable archive data retention / cleanup rules; 2) The AI function triggers the matching rules. The clean-up activities remove the appropriate PDIs and all or part of the associated metadata. One use case of this operation scenario is the L1A product data items archive during a limited time period (e.g. archive such products for two weeks for expert evaluation). 6.8.3.6 Data-Driven Archive-to-Archive Data Circulation This scenario accounts for the autonomous archive-to-archive data circulation operations. The AI function autonomously makes available to the PDGS/DC function the new archived data required for data circulation operations according to the configuration. Finally it is the DC function that performs in last instance the delivery of the data to the configured interfaces. Some use cases are presented according to this operation scenario: L0 production generated and archived in a given ground-station can be circulated to another processing centre to continue with the level 1 processing activities; The archived MSI production in a centre with the LTDP role will be systematically circulated to the PDGS long term archive service. 6.8.3.7 On-Demand Archive-to-Archive Data Circulation This scenario describes the operator-driven archive-to-archive data circulation activities performed punctually according to different motivations (e.g. specific data mirroring into other archives, a bulk of data circulation to support specific calibration campaigns, etc). The AI function will offer to the operator an HMI for the selection of the archived data for the circulation activities. As explained in the previous scenario, the AI function relies on the PDGS/DC function to perform the data circulation operations (i.e. electronic or media data circulation). The following steps are identified for this operation scenario: 1) The operator selects via the AI function HMI the archived product data items to be retrieved; 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 273 of 350 2) The AI function retrieves the selected product data items and places them in the datacirculation out-tray; 3) The DC function autonomously circulates the data to the interfaces. 6.8.3.8 Bulk Archived-Data / Inventoried-Metadata Export This scenario accounts for the operator-driven selected archived data or/and inventoried metadata export. Accordingly the operator based on the AI function HMI defines the selection of the data / metadata to be exported (typically can be a defined time-window, product-type, etc.) and triggers the action. The main use cases envisaged for this operation scenario are: Bulk metadata export of one archive centre to feed the DAX function in case of contingency; Bulk archived data export to be ingested into a different AI function instance; 6.8.3.9 Maintenance This scenario accounts for some operator-driven and other autonomous maintenance and special operations activities to ensure the correct behaviour of the function and ensure the required performances (for archival, retrieval, query, etc). The following actions can be performed as part of this operations scenario: Data relocation operations. When some storage HW needs replacement (e.g. due to a disk failure), the operator triggers for the data relocation activities to the new HW; Storage capacity enhancements. The operator adds and configures new HW elements to improve AI function storage capabilities; Inventory metadata index recreation. Performed autonomously to improve the AI function query and retrieval performances through metadata query parameters; Data backup activities. Backup activities include capabilities to dump/export relevant data to other functions (i.e. PDGS/DAX function that mirrors the AI inventory content); Data restore activities on contingency or on mirror archive centres; 6.9 Data-Access Index (DAX) Operations 6.9.1 PRINCIPLES 6.9.1.1 Centralised Data Index In opposition to the PDGS archives that can be deployed in several centres, the Data-Access Index function (DAX) is a centralised function and concentrates the reference to all the products availability thorough the different archives instances. Therefore the index acts as 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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GSC Sentinel-2 PDGS OCD - Emits - ESA

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