Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services

By M. Drusch, U. D. Bello, S. Carlier, O. Colin, V. Fernandez, F. Gascon, B. Hoersch, C. Isola, P. Laberinti, P. Martimort and 5 more. 2012

4,222 citations recorded by the source corpus.

Subfields: Ecology, Media Technology, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/a36ae5728975a1850d9f18b80c5841ceda79b2cb

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Citations in the corpus

Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas (2016, background): “For instance, Sentinel-2 satellites will provide a global cover of continental surfaces every five days in 13 spectral bands from 10 to 60 m (Drusch et al., 2012).”
Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series (2017, background): “The availability Sentinel-2 imagery [3], with its unique characteristics (290 km swath, 10 to 60 m spatial resolution, 5-day revisit cycle with 2 satellites, 13 spectral bands) will enable the implementation of land cover map production systems for the delivery of up to date and accurate information”
The libRadtran software package for radiative transfer calculations (version 2.0.1) (2015, methodology): “– Remote sensing of surface properties; a model like libRadtran is particularly important to develop atmospheric correction methods (e.g. Drusch et al., 2012;60 Schulmann et al., 2015).”
Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band (2016, positive): “The freely-available Sentinel-2 Level-1C dataset is already a standard product of TOA reflectance [27].”
Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data (2020, methodology): “S2 bottom of atmosphere (BOA) reflectance images acquired between 30 June and 31 July 2018 were mosaiced using the bands B2, B3, B4, B5, B6, B7, B8, B8A, B11, and B12, measuring reflectance in the visible, near infra-red (NIR) and short wave infra-red (SWIR) spectrum (Drusch et al. 2012).”
Sentinel-2 Data for Land Cover/Use Mapping: A Review (2020, methodology): “Moreover, long-term (>5 years) land use/cover change monitoring by Sentinel-2 has the potential of strengthening existing policies by providing accurate and timely information [8,25].”
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (2015, background): “The forthcoming super-spectral ‘Copernicus’ Sentinel-2 (Drusch et al., 2012) and Sentinel-3 missions (Donlon et al., 2012), as well as the planned EnMAP (Stuffler et al., 2007), HyspIRI (Roberts et al., 2012), PRISMA (Labate et al., 2009) and ESA’s candidate FLEX (Kraft et al., 2012) imaging…”
Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. (2016, methodology): “This method would also be applicable to European Sentinel 2 sensor (Drusch et al., 2012).”
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion (2020, neutral): “The cloud removal algorithm developed in this work is applied on optical data from the Copernicus Sentinel-2 mission (Drusch et al., 2012).”
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data (2019, methodology): “These were in Level-1C processing format, which means that they underwent geometric and radiometric correction but were not atmospherically corrected (Drusch et al. 2012).”