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Text · dataset · 2020

Sentinel-2 Surface Reflectance Analysis Ready Data 2016-Q3

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Description

Data for 2016-Q3 This dataset is the Sentinel-2 Surface Reflectance Analysis Ready Data (ARD) archive for Switzerland, generated sen2cor 2.5 (step.esa.int/main/third-party-plugins-2/sen2cor/). Detailed description about the Sentinel-2 A & B missions can be found in the CEOS Earth Observation Handbook: database.eohandbook.com/database/missionsummary.aspx?missionID=552 database.eohandbook.com/database/missionsummary.aspx?missionID=553 Sentinel-2 (S2) is a constellation of two sun-synchronous satellites operated by ESA respectively from 2015 to 2022 (Sentinel-2A) and 2017-2024 (Sentinel-2B).

Switzerland is covered by twelve Sentinel-2 scenes (ID: 31TGM, 31TGN, 32TLR, 32TLS, 32TLT, 32TMR, 32TMS, 32TMT, 32TNS, 32TNT, 32TPS, 32TPT). This corresponds to a spatial extent of latitude 45.0 to 47.9N, longitude 5.5 to 11.8E. Data are downloaded as L1C products corresponding to 100x100km2 geometrically corrected Top Of the Atmosphere (TOA) tiles.It supports land monitoring related services, including generation of generic land cover maps, risk mapping and fast images for disaster relief, generation of leaf coverage leaf chlorophyll content and leaf water content42,43.

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Both satellites carry the MultiSpectral Instrument (MSI). Sentinel-2 processed to level 2A with Sen2Cor comes with a scene classification (similar to the pixel_qa band provided by USGS for Landsat data) with 12 classes as described at: earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm. It helps identifying pixels that are saturated or defective as well as cloud and cloud shadows that may affect the quality of the images.

In addition, ESA provides a monthly status of the quality of Sentinel-2 data through Data Quality Reports (DQR). These reports document geometric and radiometric performances against initial sensor specifications together with observed anomalies and issues. DQR are available at: sentinels.copernicus.eu/web/sentinel/data-product-quality-reports.

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Inferred from text
Image 65% · Satellite remote sensing 65%
Provenance · 1 source records, 8 field assertions
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Yaretaoai:unige.ch:yareta:f0e571f0-03d7-46a0-b861-bfa926ff01f44 h agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:earth-environmentalmapping · yareta unige chconnector:yareta_unige_ch@1.0.0
concepts[modality].local:modality:imageenrichment · yareta unige chkeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:remote-sensingenrichment · yareta unige chkeyword-concept-rules@1.0.0title+description (65%)
descriptionsource · yareta unige chconnector:yareta_unige_ch@1.0.0/metadata/dc/description
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titlesource · yareta unige chconnector:yareta_unige_ch@1.0.0/metadata/dc/title