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 88 of 350 step. This method is commonly used to correct potential noise (jitter and/or drift) on the time stamp delivered by the on board clock and inserted in the image data. It consists in an adjustment of the time stamp of each image line (thanks to root mean square method) computed over the overall imaging orbit. This processing option will be activated during commissioning phase to validate the above figures in-flight by GPP. 4.3.9.2.2 Band Co-Registration Constraints As described in section 3.5.2.2, the instrument focal plane staggered configuration induces an inter-band and inter detector parallax (also referred to as the B/H stereoscopic effect). Similarly to the radiometric corrections, fore and aft processing margins hereafter referred to as the “geometric processing margin” will be required to reconstruct the inter-band coregistration. Depending on the geometric processing performed, the fore and aft processing margins will be different: ○ As applied to one single detector processing, the processing margin will correspond to the maximum inter-band parallax equal to 14km along-track hence corresponding to about 2/3 rd of a scene. ○ If applied to all detectors at once for the entire MSI swath reconstruction across-track, the processing margin would correspond to the maximum inter-detector parallax equal to 46km along-track (maximised for band B9) hence corresponding to two MSI scenes. 4.3.9.2.3 Spatial Registration The stringent requirements of multi temporal registration (less than 0.3 pixels for 10m bands, cf. section 4.4.4.1) lead to improving the location accuracy though the refinement of the geometric model based on automatic registration with ground control points (GCPs) using an reference image. This geometric refinement process will correct perturbations which are not detected by the AOCS sensors (star trackers, GPS, gyros) by estimating the perturbations on the image itself and modelling polynomial corrections derived from the measured GCPs. To be optimised, this refinement shall be applied on the largest possible number of GCPs, ideally extracted from the complete imaging orbit. Expected perturbations of this correction possibly induced by refining the geometry using smaller image portions is reported in [RD-30]. In particular, it was concluded that spatial registration will be achieved with sufficient accuracy if applied on a continuous segment of image data of no less than 60km along-track over the full swath. In addition, it is anticipated that although spatially co-registered over the same image reference, the stitching of two images registered independently using different sets of GCPs could introduce visual discontinuities at the sewing boundary (at sub-pixel level). Whereas the geolocation error budgets of the spacecrafts theoretically allow for a polynomial based refinement model as currently specified, it is anticipated that potential thermo-elastic effects of the MSI could add local perturbations to the measurements which could in turn induce small discontinuities between the geometric models constrained independently. 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 89 of 350 To remove this effect it is recommended to introduce small image overlaps in the GCP extraction step such that GCPs located in the overlap portion will constrain both geometric models together hence minimising potential discontinuities after refinement. The sizing of the required overlaps is in the order of 25-50km, i.e. of one or two MSI scenes. 4.3.9.2.4 Resampling The spatial resolution of the MSI sensor measurements ranges from 60 meters down to 10 meters on-ground. To adapt the native geometry of the sensor acquisitions to a final image usable by Sentinel-2 product users, the MSI Level-1 algorithm features an orthorectification step together with a resampling step mapping the instrument pixels into the final geocoded space. The resampling step is performed for each spectral band using a resampling grid and an interpolation filter. This transformation, if not correctly applied, will impair the quality of the final image due to the aliasing effect induced by the geometric transformations performed in the discrete (non continuous) pixel space. To avoid this perturbation, driving recommendations for the choice of the interpolation filter and resampling grid spatial resolution relatively to the MSI native resolution are provided in [RD-30]. 4.3.9.2.5 Digital Elevation Model MSI Level-1C processing will require a fine spatial resolution Digital Elevation Model (DEM) of DTED1 class (resolution of 3 arcsec i.e. about 90 meters). Three DEM based on SRTM (Shuttle Radar Topographic Mission) data (http://edc.usgs.gov/products/elevation.html) are highlighted as appropriate candidates: o An SRTM-filtered DEM from JRC (http://srtm.csi.cgiar.org/); o An SRTM-filtered DEM from CNES; o ACE2 DEM from ESA which combines SRTM and radar altimetry data (http://tethys.eaprs.cse.dmu.ac.uk/ACE2/). SRTM DEM has an absolute horizontal accuracy (90% circular error) of 20 meters and an absolute vertical accuracy (90% linear error) of 16 meters. Considering the maximum view zenith angle of Sentinel-2 (10.26° at the edges of the swath), the vertical error of the DEM will translate in an absolute geolocation uncertainty of about 2.9m (90% linear error) which is not a dominant contribution within the overall absolute Sentinel-2 geolocation uncertainty budget. As being based on SRTM data, the first two DEMs do not cover the entire globe and only span between 60° North and 60° South latitudes (i.e. about 80% of all land areas). ACE2 DEM has been created by synergistically combining Satellite Radar Altimetry data with SRTM data within the region bounded by ±60 degrees latitude. Over the areas lying outside the SRTMs latitude limits, other sources have been used such as including GLOBE and the original ACE DEM, together with new matrices derived from reprocessing ERS-1 Geodetic Mission dataset with an enhanced retracking system, and the inclusion of data from other satellites. The quality of ACE2 DEM is slightly better than SRTM especially over steep mountainous regions. 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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4.6.3 OPERATIONAL TRANSFER BASELINE
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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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o preserving integrity of exchanged
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6 DETAILED OPERATIONS CONCEPTS GSC
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o Report generation frequency and c
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○ MSI L1A, L1B, L1C and TCI produ
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Some relevant use cases are present
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Two main mapping services have been
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